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MmAUTiLUS

Supplement 2

(Issued with Volume 108)

Molecular Techniques and

Molluscan Phylogeny

Proceedings of a Symposium held at the

Eleventh International Malacological Congress

Siena, Italy

31 August-5 September, 1992

Edited by

M. G. Harasewych

Department of Invertebrate Zoology

National Museum of Natural History

Smithsonian Institution

Washington, DC 20560 USA

and

Simon Tillier

Laboratoire de Malacologie

Muséum national d’Histoire naturelle

55, rue Buffon

F-75005 Paris, FRANCE

1994

ISSN 0028-1344

Available from:

THE NAUTILUS

P.O. Box 7279

Silver Spring, MD 20907 USA

per > aan

Supplement 2

(Issued with Volume 108)

August 11, 1994

ISSN 0028-1344

CONTENTS

MOLECULAR TECHNIQUES AND MOLLUSCAN PHYLOGENY

PREUACE, 5 ooh ss Saale SO a ey Ce ee MS ea RO eee a ne Fie Fa an ma 1

PLENARY LECTURE

George M. Davis Molecular Genetics and Taxonomic Discrimination....................... 3

D. J. Colgan The Evolutionary Consequences of Restrictions on Gene

W. F. Ponder low-E xamplesmnomprly drobiidesnailsia aes nen ne een eee 25

Kenneth C. Emberton Allozyme Cladistics in Malacology: Why and How?..................... 44

S. Laura Adamkewicz Use of Random Amplified Polymorphic DNA (RAPD)

M. G. Harasewych Markers to Assess Relationships Among Beach Clams of the

(CemUSOD ONC ciara asap eas ree a a aay, Pel GUE a A At tsb dl

Jeffrey L. Boore Mitochondrial Genomes and the Phylogeny of Mollusks.................. 61

Wesley M. Brown

Jonathan Terrett The Mitochondrial Genome of Cepaea nemoralis

Sue Miles (Gastropoda: Stylommatophora): Gene Order, Base

Richard H. Thomas Composition and Heteroplammy .................... ee ee 79

Douglas I. Cook The Highly Variable and Highly Mutable Mitochondrial

Eleftherios Zouros DNA Molecule of the Deep Sea Scallop Placopecten

MEP CULOTULCUS POT tater AE oa. oh oc 85

Elaine Rumbak

David G. Reid

Richard H. Thomas

Birgitta Winnepenninckx

Thierry Backeljau

Rupert De Wachter

Gary Rosenberg

George M. Davis

Gerald S. Kuncio

M. G. Harasewych

Simon Tillier

Monique Masselot

Jean Guerdoux

Annie Tillier

Jonathan B. Geller

Dennis A. Powers

Maria Lazaridou-

Dimitriadou

Y. Karakousis

A. Staikou

Thierry Backeljau

Karin Breugelmans

Herwig Leirs

Teresa Rodriguez

Dimitri Sherbakov

Tatyana Sitnikova

Jean-Marie Timmermans

Jackie L. Van Goethem

Erik Verheyen

Reconstruction of Phylogeny of 11 Species of Littorina

(Gastropoda: Littorinidae) using Mitochondrial DNA

Sequence Daltaw \.o WA 5 Bene ee ee ee re

Small Ribosomal Subunit RNA and the Phylogeny of the

Moolltsea:c- ier cto sen een EN eh ae nec a pee ld oe oe TR

Preliminary Ribosomal RNA Phylogeny of Gastropod and

UnionoideantBivalve NMollusksiey eee ie naennnnne

Monophyly of Major Gastropod Taxa Tested from Partial

28S rRNA Sequences, with Emphasis on Euthyneura and

Hot-Vent Limpets Peltospiroidea.............................

Site-Directed Mutagenesis with the Polymerase Chain

Reaction for Identification of Sibling Species of Mytilus..........

PRESENTED AS A POSTER

Morphological and Genetic Variation in Greek Populations

of the Edible Snail Helix aspersa Miller, 1774

(Gastropoda: Pulmonata): A Preliminary Survey ................

PRESENTED AS A POSTER

Application of Isoelectric Focusing in Molluscan

Systeinaties’\: steer eters ohne sew ce ae metas hore ete Rene ree

THE NAUTILUS, Supplement 2:1-2, 1994

Preface

Page 1

With its tremendous diversity and excellent fossil rec-

ord extending from the earliest Cambrian to the present,

the phylum Mollusca presents extraordinary opportu-

nities and challenges to students of all aspects of evolu-

tionary biology. The confluence of new techniques of

data acquisition (among them scanning and transmission

electron microscopy and nucleic acid sequencing) and

data analysis (most notably cladistic methodology) has

prompted many advances in studies of molluscan phy-

logeny at all levels over the past decade. Yet despite the

use of varied data sets and techniques, many of the most

basic questions at the highest taxonomic ranks remain

unresolved. While mollusks, particularly Cepaea, Ceri-

on, and Partula, have played important roles in the stud-

ies of population genetics and speciation, the phylum

remains underrepresented in studies at higher taxonomic

levels. Happily, this situation is changing, and increased

research in molecular malacology is evidenced by the

appearance of the “Mollusc Molecular News’ and bul-

letin board on the internet.

The papers comprising this volume were presented at

the Symposium on Molecular Techniques and Molluscan

Phylogeny that was convened during the Eleventh In-

ternational Malacological Congress, held in Siena, Italy,

in August-September of 1992. This collection of works

contains the majority of the papers and posters presented

during this Symposium, and represents a overview of

contemporary research in this rapidly growing area of

systematic malacology. Although a symposium on a sim-

ilar topic was held during the American Malacological

Union meetings in 1987, the results presented at that

time were judged by the participants to be too prelim-

inary to warrant publication. We are heartened that the

majority of the contributors to the present symposium

felt that their work was sufficiently advanced to be pub-

lished.

We thank Prof. Folco Giusti for the invitation to or-

ganize this symposium, and for his assistance in coping

with the many attendant details. We extend our appre-

ciation to all participants in the Symposium, and rec-

ognize the special efforts that several colleagues have

made to attend these meetings. The contributions of the

numerous co-authors, many of whom were not present

at the Symposium but nevertheless contributed to its

success, are gratefully acknowledged.

In the Plenary Lecture, which opened the Congress

and set the stage for the Symposium, George Davis set

forth his views on the utility of molecular genetics for

molluscan systematics. Presenting case studies primarily

from his own work, he documented the value of molec-

ular data as well as the potential pitfalls in incautious

interpretation of molecular data.

The organization of the Symposium into three sessions,

each covering a broad topic, is reflected in the arrange-

ment of papers in this volume. The first group of papers

documents the use of population genetics techniques for

studies of speciation or phylogenetic inference. Colgan

and Ponder present a sophisticated analysis of the varied

effects of restrictions on gene flow on speciation using

allozyme data. Emberton reviews and compares methods

for constructing phylogenies using allozyme data, while

Adamkewicz and Harasewych explore the utility of RAPD

techniques, recently developed for differentiating pop-

ulations and strains, for the inference of phylogenetic

relationships among closely related species.

The second group of papers focuses on the mitochon-

drial genome and explores the utility of mitochondrial

DNA (mtDNA) for investigating a broad range of genetic

relationships. Boore and Brown review the varying and

contradictory hypotheses regarding the relationships of

the phylum Mollusca and its classes, and advocate the

use of the arrangement of genes (gene order) of the

mitochondrial genome as phylogenetic characters. Ter-

rett and colleagues present new data on the gene order

of Cepaea nemoralis and compare it with those of other

metazoans. At the other extreme, Cook and Zouros an-

alyze inheritance patterns of variations in the size of the

mitochondrial genome among sibling scallops, and con-

clude that because of its rapid turnover, such size vari-

ation does not provide information useful for taxonomic

studies. In the last paper of this group, Rumbak and

colleagues use the sequence of a portion of the gene for

the small ribosomal RNA to study the relationships of 13

species of littorinids.

The third group contains papers on the use of ribo-

somal sequence data to resolve phylogenetic relationships

among mollusks. Winnepeninckx and associates present

the complete sequence and structure of the 18S rRNA

of Onchidella celtica, a pulmonate snail, and compare

it to 25 other known metazoan sequences to assess the

monophyly and relationships of three molluscan classes

as well as the relationships of Mollusca among the Meta-

zoa. Preliminary analyses of sequences derived from the

D6 loop of the 28S rRNA of 43 gastropod and bivalve

species reported by Rosenberg and collaborators reveal

variation in the rates of sequence divergence but do not

refute morphology-based phylogenies. A group led by

S. Tillier present the most broadly represented sequence-

Page 2

based phylogeny of Gastropoda to date. Geller and Pow-

ers use site-directed mutagenesis to descriminate be-

tween sibling species of Mytilus based on a single base

difference in a region of their 16S ribosomal gene.

Two additional papers, originally presented as posters,

are included. One (Lazaridou-Dimitriadou and col-

leagues) reports on allozyme variation in Greek popu-

lations of Helix aspersa, the other (Backeljau and nu-

merous collaborators) reviews the use of isoelectric

focusing in molluscan systematics.

Initial attempts to investigate the origins and early

evolution of the Mollusca by the use of molecular data

have met with only limited success, and in the process

have questioned some of the most basic precepts of mor-

THE NAUTILUS, Supplement 2

phology-based classification. Perhaps most notable of these

is the growing body of evidence from both nuclear and

mitochondrial genomes that places Bivalvia as the out-

group to a clade containing the Gastropoda and Poly-

placophora. Clearly, the addition of taxa, especially from

presently unrepresented molluscan classes, would be of

great value.

The growing body of molecular data, together with

increasingly sophisticated and better reasoned methods

of analysis, portend great advances in our understanding

of molluscan evolution in the coming years.

M. G. Harasewych

Simon Tillier

THE NAUTILUS, Supplement 2:3-23, 1994

Page 3

Molecular Genetics and Taxonomic Discrimination

George M. Davis

Pilsbry Chair of Malacology

The Academy of Natural Sciences

1900 Benjamin Franklin Parkway

Philadelphia, PA 19108, USA

a a a

PROLOGUE

The following paper is based on the Plenary address I gave

before the 11th UNITAS Congress, the International Congress

of Malacologists, held in Siena, Italy 28 August-7 September

1992. The address is dedicated to Professor Foleo Giusti, a

friend, colleague, and scholar dedicated to excellence in sys-

tematics who, with G. Manganelli (1992), wrote concerning the

discrimination of species:

“The good systematist is not one without doubts or the one

who always succeeds in defining a phenomenon or recognizing

a ‘species’. It is rather the one who studies the phenomenon

trying to understand it in all its facets and who is not above

admitting that its exact nature escapes him ...Let us stress

again that only a little humility and a little consciousness are

required. ”

INTRODUCTION

If we could call back to the present some of the early

fathers of morphology-based malacology, for example

Cuvier, Bouvier, Troschel, Stimpson, Pelseneer, Thiele,

Johansson, and Pilsbry to name a few, and bring them

up to speed on the vast accumulation of literature since

their time, they would readily understand and be en-

thusiastic about the modern day potential for sophisti-

cation in taxonomic discrimination. They would say that

it is about the recognition of, and the definition of species,

genera, and higher taxa. They would be in agreement,

and I with them, that the fundamental basis for taxo-

nomic discrimination was then, and is today, the com-

parative anatomical data set.

Unfortunately, over the past several decades, detailed

comparative anatomy has been the most under-used tool

in molluscan systematics. However, given the recent ac-

ceptance of cladistic methodologies (in malacology, only

in the past 6 to 7 years), one sees a return to comparative

anatomy. The hunt for unique anatomical characters and

character-states in order to nest taxa in sets based on

synapomorphies, is gaining increased respectability.

Growing awareness that there is a need for well defined

qualitative anatomical characters and their states, which

serve to demonstrate differences among taxa in order to

construct hypotheses of evolved relationships (phyloge-

nies), should stimulate modern anatomical work on all

groups of mollusks.

Molecular techniques have long been used as an aid

for discriminating among taxa. However, as with cla-

distic tools, malacologists have lagged far behind micro-

biologists, mammalogists, and herpetologists in applying

them. The use of immunology in systematics is over four

decades old; the use of allozymes, three decades. The

now-generation is scrambling to sequence RNA and DNA

aided by PCR and cloning.

The use of allozymes in molluscan systematics is now

well established and will not be supplanted by genomic

techniques for years to come. The quantities of useful

information that can be gained through allozyme elec-

trophoresis are enormous and can be obtained at rela-

tively little cost compared to the considerable expenses

involved in pursuing sequence work. Allozymes are es-

pecially useful in comparing closely related genera, spe-

cies within a genus, and sorting out species-level prob-

lems. Allozyme electrophoresis is an ideal tool for

population genetics as applied to delineating species.

DNA-RNA sequencing is in its infancy, literally explod-

ing in dimensions of use, problems, and surprises. Given

600 million years of spectacular molluscan evolution, one

can be sure that molluscan DNA from more than 100,000

living species from seven classes will yield numerous

surprises and cause researchers to have many a migraine

headache.

A major concern with molecular data is the analysis

of data. It is generally agreed today that there is as yet

no truly satisfactory way to analyze such data to ade-

quately portray relationships (exhaustively reviewed by

Buth, 1984 for allozymes and by Swofford & Olsen, 1990

for sequence data). There is a dichotomy of approach:

cladistic and phenetic. In a phenetic mode, the usual

approach is a UPGMA treatment of distance data based

either on allele frequencies (allozymes) or sequence dif-

ferences. A phenogram is the standard presentation. Cla-

distic analysis requires a unit character. With allozymes,

using the locus as a character seems to be the best at

present, with different allele combinations scored as char-

acter-states. With sequence data, the unit character sug-

Page 4

gested is the gene. Further, genes must be calibrated for

the taxa studied relative to rates of evolution if credible

phylogenies are to be structured. Phylogenetic hypoth-

eses are based on cladograms derived from computer

programs such as PAUP (Swofford, 1983) or HENNIG-

86 (Farris, 1988) that use parsimony criteria to obtain

the shortest possible tree. However, there is a universal

call by those involved in the evolution of bacteria, viruses,

and protists as well as other groups of taxa for research

to provide better modes of analyses of molecular data to

make better trees (Davis, 1994).

One rarely sees both phenetic and cladistic analyses

together in the same paper, especially when the database

is an anatomical one. I strongly urge that both be used

and the results examined for congruence. In the phenetic

mode, combining principal component analysis (PCA)

and multidimensional scaling (MDS) with ordination di-

agrams usually yields considerably better results than

simply using similarity or distance coefficients to do a

UPGMA structured phenogram. The benefits are:

1) As one moves from the initial phenogram to PCA

to MDS, a tree of relationships between each taxon (spe-

cies, individual, etc.) such as a Prim Network, usually

becomes shorter and the cophenetic correlation with the

original matrix increases indicating that the result better

portrays relationships among the taxa (phenetic parsi-

mony, Davis et al., 1994a).

2) Ordination diagrams of individuals or species or

genera in 1 X 2, 1 X 8, 2 X 8 dimensional space with

taxa connected by a Prim Network provides a consid-

erably improved understanding of taxon interrelation-

ships both as to scale of divergence and direction of

divergence of the taxa. Ordination of taxa in n-dimen-

sional space removes the constraints of the one dimen-

sional phenogram.

3) The PCA allows one to assess character correlations

that are the basis for the distribution of taxa along each

dimension of n-dimensional space. The utility of these

multivariate techniques will be highlighted later in this

paper.

It has been a decade and a half since I reviewed ex-

perimental methods in molluscan taxonomy (Davis,

1979b). While it was possible then to review nearly the

entire literature pertaining to molluscan molecular sys-

tematics from amino acid work, through immunology

and protein electrophoresis, it would be counter-pro-

ductive to attempt to do so now. Instead, I will give my

views on the utility of molecular genetics today for mol-

luscan systematics. In outline form below are presented

the topics I will discuss as to the prominent uses of mo-

lecular genetics:

I: To uncover cryptic species.

II: For population genetics:

A: To detect and study hybridization.

B: To examine special selective pressures.

C: To study breeding structure.

III: To study patterns of evolution:

A: Speciation.

B: Phylogeny.

THE NAUTILUS, Supplement 2

IV: To uncover unique aspects in the evolutionary

process.

In presenting case studies, primarily from my own

experiences with these issues, there are several key and

central issues to focus on and always keep in mind:

1: There is no universal molecular clock, and taxa

therefore must be calibrated relative to genetic distance.

Different clades may have evolved at different rates.

2: Genetic distances do not define species or higher

taxa.

3: Species concepts are important relative to inter-

preting genetic distance data.

4: Definitions of taxa and discrimination among taxa

fundamentally require anatomical ground-plan data in-

cluding developmental and cytological data, not genetic

distances.

5: When morphological data yield few characters and

character-states that enable discrimination among taxa,

the need for molecular genetic data increases.

CLOCKS AND CALIBRATION

It is not the purpose of this paper to exhaustively review

all that has been written on this topic. It is useful to

abstract five key points derived from the reviews of Tem-

pleton (1980, 1981), Barton (1989), Harrison (1991) and

the diverse publications of Gillespie (1984, 1986a,b; 1987)

that focus on the issues of molecular clocks. 1) Rates of

molecular evolution are more variable than expectations

based on a simple Poisson mutation process. 2) Protein

- DNA evolution rates are not consistent with neutral

theory. 3) Molecular evolution is rate-variable and epi-

sodic, and, in the view of some, best explained by in-

voking natural selection ( Nevo & Beiles, 1988; Skibinski

& Ward, 1982; Murray et al. 1991). 4) Any attempt to

apply a molecular clock to comparisons of even closely

related species is hazardous. 5) There is no simple pattern

between mode of speciation and genetic distance.

With due respect, one must consider the serious ar-

guments of those supporting neutral mutation theory

(refer to numerous papers by Nei and Kimura reviewed

in Nei & Graur,1984) employing statistical tests of data

derived from allozymic data providing heterozygosity or

gene diversity where effective population size and mu-

tation rates are known. But there is so much more in-

volved in considering rates of evolution; one example is

provided. Consider the rapid duplication and loss of genes

coding for the alpha chains of hemoglobin where dif-

ferences in rate are apparently associated with differ-

ences in lengths of non-coding regions (Zimmer et dl.,

1980). They consider that adaptive evolution may de-

pend more on the type of genetic variability than on

various point mutations that affect protein structure.

That there is no universal clock, and that different

clades may evolve at different rates based on molecular

genetic data is clearly demonstrated in Figure 1, where

regressions 1, 3, and 6 pertain to different groups of

teleost fish ( from Hillis & Moritz,1990 based on data

from Avise & Aquardo, 1982). For further elucidation

G. M. Davis, 1994

18 1

—> 12

(5)

ke}

(5)

(7)

C1) 6

= 3

0 7

0 0.5 1.0

Nei’s genetic distance D

Figure 1. Regressions of changes of Nei’s genetic distance D

through time for different clades. Clades 1,3,6 are for different

teleost fishes. Redrawn from Hillis and Moritz (1990).

on this topic, refer to Hillis and Moritz (1990) for similar

plots for DNA, RNA, etc. To provide an example, a

statistical analysis of DNA sequences from artiodactyls,

rodents and primates show that there is no global mo-

lecular clock in mammals. Rates of nucleotide substitu-

tions in rodents are approximately four to eight times

higher than in higher primates( Li et al., 1987) Regres-

sions for different molluscan clades are similar to those

shown in Figure 1, as demonstrated below.

Genetic Distances, Their Utility and Calibration:

Different measures of genetic distance have different

utilities. When referring to genetic distance based on

allozyme “alleles”, one must state whose formula was

used. The traditional D is that of Nei (1972) although

the Nei (1978) modification is now widely used; it rep-

resents the accumulated number of codon substitutions

per locus since time of divergence; it is a squared distance

that rises with time. There is no upper limit, constraints

being only the number of loci used and alleles found. It

is non-metric. One of the beauties of this measure is that

as taxa diverge more and more, the difference is not

squeezed between 0 and 100%. Yes, there are genetic

interpretation and statistical problems with values ex-

ceeding 1.0, but aside from the problems of metricity,

the cause for the rise above 1.0 is clear from the data.

Sewell Wright (1978) considered Arc distance (Cavalli-

Page 5

ARC-D

Se ooo oo oe ie a

NEI'S-D

Figure 2. A comparison of Nei’s D with Arc distance based on

data from my various papers. As Arc distance becomes com-

pacted, Nei’s D continues to rise. As Nei’s D is compacted at

lower values, Arc distance gives a better approximation of dif-

ferentiation among closely related taxa.

Sforza & Edwards, 1967) to be the best as it is a metric

distance where the “coordinates in the hyperspace are

the square root of the allele frequencies, a procedure

that locates all populations on the surface of a hyper

sphere with respect to a locus”. Best or not in the pure

mathematical sense, both distances have their use. A plot

of Nei vs. Arc D values is given in Figure 2 based on a

variety of data I have published or accumulated. It is

clear that Nei’s D values are compacted at the lower

values (to the left) where closely related populations are

compared. In this situation, Arc D gives a better under-

standing of differentiation. At the other end of the plot,

with the greater divergence of distantly related taxa, the

Arc D values become compacted and less informative

while Nei’s D values continue to rise thus providing a

better understanding of divergence even though the val-

ues do not rise linearly and are not metric. Nei’s D can

be used to calibrate within-group variance, and gaps

between nested sets of taxa that represent different tax-

onomic levels. Nei’s D can be used for multidimensional

scaling and with a Prim network to obtain a three di-

mensional visual sculpture of relationships, patterns of

divergence, and gaps between sets of taxa as long as one

understands the constraints and limitations due to the

non-metricity of the measure. When publishing results,

I advocate providing both Nei’s and Arc distances. Cer-

tainly the Nei’s D is needed because of the vast literature

now built up using this measure. It has become a uni-

versal standard for comparison.

Beware of those who grind-run gels-publish without

studying the patterns and processes of morphological

diversification, life history diversification and ecological

diversification throughout the clade of concern and in

sister clades. There is so much more involved in under-

standing species differentiation then examining a genetic

distance and extrapolating taxonomic rank. This is well

understood in vertebrate literature; see the review of

Avise and Aquardo (1982). However, I have heard it

Page 6

THE NAUTILUS, Supplement 2

Table 1. Calibrating clades for Nei’s D: selected examples. Mean + standard deviation.

Population level

Hydrobiidae (Davis et al., 1989)

6 populations

Truncatellidae (Rosenberg, 1989)

4 populations

2 populations

Pomatiopsidae (Woodruff et al., 1988)

7 populations

Planorbidae (Mulvey et al., 1988)

6 populations

Planorbidae (Bandoni et al., 1990)

12 populations

Unionidae (Davis et al., 1981)

5 populations

11 populations

Hydrobia truncata

Truncatella pulchella

Anodonta cataracta

Elliptio complanata

Truncatella caribaeensis

Oncomelania hupensis quadrasi

Biomphalaria glabrata

Biomphalaria pfeifferi

0.008 + 0.005

0.029 + 0.020

0.067

0.039 + 0.038

0.103 + 0.068

0.053 + 0.066

0.034 + 0.038

0.065 + 0.039

Species: differences among species of a genus

Truncatellidae (Rosenberg, 1989)

5 species Truncatella

Succineidae (Hoagland & Davis, 1987)

2 species Novisuccinea

2 species Oxyloma

Unionidae

7 species (Davis, 1981) Elliptio

3 species (Davis, 1983) Uniomerus

3 species (Kat, 1983a) Anodonata

6 species (Kat, 1983b) Lampsilis

Sphaeriidae (Hornbach, 1980)

4 species Sphaerium

2.226 + 0.862

0.004

0.269

0.210 + 0.017

0.308 + 0.165

0.457 + 0.073

0.609 + 0.478

0.568 + 0.310

Genera: differences among genera of the same tribe

Unionidae (Davis, 1981; Davis et al., 1981)

Amblemini

Pleurobemini

4 genera

3 genera

0.651 + 0.275

0.243 + 0.086

Subfamilies: differences among subfamilies of Unionidae

(Davis, 1981; Davis et al., 1981)

3 subfamilies

remarked by some malacologists newly come to the use

of allozymes that the average Nei genetic distance(D)

among populations of a species is < 0.09( or some such

value), or that D = 0.20 or 0.30 indicates a species

difference, especially if the populations involved are sep-

arated by considerable distance (widely allopatric).

Woodruff et al. (1988) have done this while applying an

evolutionary species concept (e.g. Wiley, 1981) [or one

could equally use a phylogenetic species concept (for a

review, see Cracraft, 1989)] to argue that populations

with a D of 0.60 are distinct species as they have their

own evolutionary history and can be diagnosed on unique

qualitative characters (e.g. unique alleles). Are they cor-

rect? No, not on this evidence alone. There are cases of

perfectly good species with D < 0.06 (Sene & Carson,

1977; Kirkpatrick & Selander, 1979; Davis et al., 1981)

and cases with populations with a large D value not being

1.903 + 0.186

considered different species. Consider the complexity of

assessing taxonomic meaning of D for mole rats of the

superspecies complex of Spalax ehrenbergi, in Israel,

where members differ by a D of 0.039 compared with

a D of 0.234 between the two superspecies S. leucodon

and S. ehrenbergi, indicating the recency of divergence

in the later and considerable age of divergence from the

former (Nevo, 1991). These issues will be revisited in this

paper.

Nei’s D is used to calibrate clades because one can

compare among taxa from populations to subfamilies or

families for the very reason that there is no upper limit

for Nei’s D. In this context, refer to Table 1. At the

population level, it is instructive to know that allopatric

populations of Hydrobia truncata (Hydrobiidae), spread

out along the coast of North America from New England

to Maryland have a mean D of 0.008 while in species of

G. M. Davis, 1994

a sister family (Truncatellidae), populations of the same

species distributed from Florida through the West Indies

differ by a mean D of 0.029 or more, i.e. four times as

much difference as in the former case. But, in the pul-

monate Planorbidae, widely allopatric populations of

Biomphalaria glabrata differ by a mean D of 0.103 (Mul-

vey et al., 1988)! Studies of 12 populations of Biom-

phalaria pfeifferi widely distributed throughout Kenya

revealed that two pairwise comparisons had Nei’s D >

0.240 (Bandoni et al., 1992) while the average D was

0.053.

Genetic distances can point out anomalies, but do not

explain them. Three uses in Table 1 illustrate: 1) the D

among five species of “Truncatella” is 2.226, consider-

ably more than between three subfamilies of Unionidae

(1.903). The data suggest that more than one genus is

involved. Is this correct? One needs to go back to the

detailed comparative anatomy to look for marked changes

in groundplan among species groups. Rosenberg (per-

sonal communication) showed me that his anatomical

data would indeed justify different generic rank given

the types of differences that do occur among the taxa he

studied relative to the types of differences that justify

generic discrimination among taxa of sister rissoacean

families (Hydrobiidae, Pomatiopsidae, etc.). He awaits

data for more species before naming genera. 2). In the

pulmonate family Succineidae, in one instance perfectly

distinct species differ by a D of 0.004, while in another

the difference is 0.269. The former should be populations

according to some who follow a D formula to assign

taxonomic rank, while the latter data do suggest different

species. I will revisit this case later. 3) In the freshwater

bivalve Elliptio, the difference among species is low,

0.210 while in another clade (different tribe) the differ-

ence among Lampsilis species is three times greater, i.e.

0.609.

At higher taxonomic levels, it is clear that differences

seen among subfamilies of Unionidae that go back at

least to the Cretaceous accumulated slowly while much

more recently evolved “genera” of Truncatellidae ( given

the ages of the West Indian islands for these terrestrial

taxa) differentiated genetically at a considerably greater

rate.

THE UTILITY OF MOLECULAR GENETICS

I: CRYPTIC SPECIES AND CONVERGENCE

The following example abstracted from Davis (1983)

serves four purposes: 1) It demonstrates the power of

molecular genetics to uncover cryptic species. 2) It clear-

ly demonstrates nature’s perversity in obscuring genetic

diversity under the cover of convergent morphologies.

3) It shows that when too few morphological character-

states serve to distinguish generic groupings of species,

molecular genetic data may be decisive. 4) It underscores

the fact that shells provide the least valuable data for

elucidating relationships among higher taxa (genera,

tribes, etc.).

Page 7

The North American freshwater clam genus Uniom-

erus was long considered to have only one species, U.

tetralasmus (Johnson, 1970). The genus is barely dis-

cernible from Elliptio. The shells of both genera are

highly convergent for most species (differing only in beak

sculpture that is mostly eroded away at an early stage

of growth), and the only anatomical discriminant found

thus far involves the complexity, or lack of it, in the

branching of the branchial papillae.

William Heard and I collected what appeared to be

a single population of Uniomerus from an area of some

100m? in a stream of the panhandle of Florida. Electro-

phoretic results ( 14 loci, 24 alleles) revealed two inter-

mixed but distinctly different species (the shells were

numbered, thus allowing separation of shells based on

results of unique alleles). After the fact, I could separate

the species on the basis of shell for about half of the

shells. I subsequently obtained a population of Uniom-

erus from Georgia with a distinctive shell phenotype and

did a three-way electrophoretic comparison. To my con-

siderable surprise, the greatest D in the three pairwise

comparisons was 0.498 (from the two Floridian taxa), a

value greater than between any of the 13 pairwise com-

parisons for species of non-lanceolate Elliptio (greatest

D of 0.446; Davis et al., 1981; Davis, 1984). Three species

of Uniomerus were involved, not one! Parallelisms in

shell characters disguised the two sympatric Floridian

species. The myth that ecologically induced variation in

shell size and other shell characters was generally con-

siderable within unionid species, and thus there was only

one species of Uniomerus, was exploded.

The question arose: Could one clearly demonstrate the

relative value of shell data, morphological data, and mo-

lecular genetics data for discriminating evolved rela-

tionships among species of Unionidae? To answer this

question, I compared the following taxa: The three spe-

cies of Uniomerus, Elliptio complanata, Fusconaia fla-

va, Lampsilis teres, Quadrula quadrula, Quincuncina

infucata. These taxa were classified by Davis and Fuller

(1981) into three tribes on the basis of comparative im-

munology and anatomy as follows: Pleurobemini: Ellip-

tio, Fusconaia, Uniomerus; Amblemini: Quadrula,

Quincuncina,; Lampsilini: Lampsilis. Too few anatom-

ical characters have been found to allow a definitive

cladistic analysis for unionid genera. Davis and Fuller

(1981) found eight, of which two were shell characters.

The larger clades (tribe, subfamily levels) are readily

separated, but not the differences among some genera

such as Uniomerus vs. Elliptio. Thus, anatomical data

are limited.

I compared the above taxa using shell morphometric

data and molecular genetics. I used the same multivariate

procedures with both data sets, ie. multidimensional

scaling (MDS) with ordination of taxa on the first two

principal components. The taxa were then connected

with a Prim network. In the morphometric analysis, 39

characters were scored and treated by Principal Com-

ponent Analysis to assess character correlations prior to

MDS. Results are shown in Figures 3 and 4. Results based

Page 8

THE NAUTILUS, Supplement 2

foe

Figure 3. Ordination of unionid taxa on first two principal components following multidimensional scaling and use of Prim network;

based on shell morphometric data. The shapes approximate the shapes of the taxa. Three taxa could not be discriminated (EC,U1,U2).

EC, Elliptio complanata; FF,Fusconaia flava; LT, Lampsilis teres; QI, Quincuncina infucata, QQ, Quadrula quadrula; U1,2,3,

Uniomerus species 1,2,3. Adapted from Davis (1983).

on shell data indicate relationships based on correlates

of shell shape, not those based on anatomy and immu-

nology. One cannot separate individuals of Elliptio com-

planata and two species of Uniomerus. The data based

on allozymes (Figure 4) reflect the tribal relationships

based on anatomy and immunology. Clearly there are

shell shape convergences (Figure 3). In Figure 4, Fus-

conaia flava and Elliptio complanata group close to-

gether in the same computer calculated set (D = 0.208)

with a D less than that between the latter species and

Uniomerus species 1 (D = 0.303), in spite of the fact

that the shape of Fusconaia is the same as that of Quad-

rula and distinctly different from the shape of Elliptio

and Uniomerus. Lampsilis is genetically highly diver-

gent from the other taxa as it should be, based on anatomy

and immunology. The advantages of using MDS and the

Prim network are clear. One can see the pattern of di-

vergence of species of Uniomerus from species of Ellip-

tio. One can see the direction of divergence of species

from each other. It is readily observed that the greatest

G. M. Davis, 1994

Page 9

EC ete

QQ!

Figure 4. Same taxa and ordination techniques as in Figure 3 but using genetic distances from allozyme electrophoresis. All taxa

are clearly separated. Fusconaia and Quadrula are not closely allied as in Figure 3. Fusconaia is closely allied genetically to Elliptio

(contrast Figure 3). There is greater distance between U2 and U8 than there is between Elliptio and Fusconaia! Adapted from

Davis (1983).

distance between two species of Uniomerus exceeds the

distance between two genera, i.e. Elliptio complanata

and Fusconaia flava; however, the direction of diver-

gence of Fusconaia is away from Uniomerus relative to

Elliptio.

Take Away Messages

Several points can be made:

1) There is a cryptic radiation of species of Uniomerus

hidden by parallel evolution of shell shape and by con-

chological variation that was previously interpreted as

ecophenotypic or random variation.

2) It is predicted that other species of Uniomerus will

be found. Consider the type species, U. tetralasmus from

Texas that has a shell phenotype different from the phe-

notypes of the three species discussed here. From the

evidence thus far, populations of Uniomerus with dif-

ferent shell phenotypes have a high probability of being

different species.

3) Shells that look similar may belong to genera of

diverging clades. Shell data provide the least valuable

data for taxonomic discrimination above the species lev-

el, and especially above the generic level.

4) When the anatomical database is weak, one must

rely more on molecular databases.

5) Genetic distances must be calibrated within and

between clades in order to understand the magnitude of

distance values that indicate specific status. Gaps be-

tween species groups and the direction of taxon diver-

gence are clarified using multidimensional scaling and

ordination with a network.

II; POPULATION GENETICS

Hybridization

The following example demonstrates the use of molec-

ular genetics to uncover hybridization. Bianchi et al.

(1994) electrophoretically examined the allozymes of two

North American freshwater gastropod pleurocerid spe-

cies, Elimia virginica, an eastern slope species, and E.

Page 10

livescens, an interior basin species. These two species are

readily distinguished by differences in shell sculpture.

What drew our attention was the presence of both species

in the Erie Canal, which connects the interior basin Lake

Erie to the Hudson River, an eastern slope drainage

system. The canal was built in 1825. Near the center of

the canal at Mudlock, Strayer noted a blurring of shell

phenotypes and asked the question: Could hybridization

be occurring?

The electrophoretic study yielded data from 22 loci

involving 39 alleles. Nei’s genetic distance in the two

species comparison was 0.332; Arc distance was 0.577,

values indicative of species differences for North Amer-

ican Pleuroceridae (again,calibration) as evidenced by

the work of Dillon (1984,1988), Dillon and Davis (1980),

and Chambers (1978, 1980). We divided snails from the

Mudlock location into two groups: one most resembling

the E. livescens shell phenotype, with some shells ap-

pearing to be pure E. livescens, the other most resem-

bling the E. virginica type with some shells appearing

to be pure E. virginica. There were 11 polymorphic loci,

of which nine were diagnostic. A sampling of results is

given in Table 2. It is clear that hybridization and in-

trogression have occurred. There are no F, generation

snails involved as there is fixation for alternative alleles

at the LAP locus. However, evidence for introgression

was found at seven (78%) of the diagnostic loci.

In our study and those referenced above, mean het-

erozygosities are very low for populations and species

(0.002-0.03 most common). Thus, the situation along the

Erie Canal stands out prominently with H values of 0.035,

0.044. As is characteristic of hybrid zones, polymorphism

increases, there is an increase in rare alleles, and hetero-

zygote deficiency is frequently found (Hewitt, 1988; also

note the presence of new electromorphs called hybri-

zymes by Woodruff, 1989). Vainola and Huilsom (1991)

effectively described the occurrence of a hybrid zone for

populations of Mytilus, but their diagnostic loci were

not as distinct as those in our study.

Special Selective Pressures

In a study of populations of marine marshland snails,

Hydrobia truncata, from North America, New England

to Maryland, there were no significant anatomical dif-

ferences except for size (Davis et al. 1988; 1989). Elec-

trophoretic studies involved 80 loci, 49 alleles. There

were 18 invariant loci. One population in a salt pond

(Flax Pond) on Long Island, New York was of particular

interest. This pond was 185 years old. The population

differed from the others by Nei’s D of 0.12 + 0.01 while

the other populations differed among themselves by a D

of 0.07 + 0.01. This difference is due, in part, to eight

unique alleles. The F; statistic shows population differ-

entiation due to the unique genetics of the Flax Pond

population; there are no significant regional differ-

ence(Fs; = 0.004). The Flax Pond population is different

from the other populations for two additional reasons: 1)

the snails are of gigantic size; 2) the snails are excep-

THE NAUTILUS, Supplement 2

Table 2. Sampling of allele frequencies from the pleurocerid

hybridization study.

virginica __ livescens virginica _ livescens

Locus control hybrid-mix hybrid-mix control

AAT-1

100 1.00 0.097 0.711 —

97 — 0.903 0.289 1.00

GPI

100 1.00 0.016 0.974 =

— 0.984 0.025 1.00

NADD

100 1.00 0.210 0.763 =

105 — 0.790 0.237 1.00

LAP

100 1.00 — 1.00 —

97 — 1.00 — 1.00

tionally heavily parasitized. The extreme parasite burden

causes the gigantism (Davis et al., 1988). The density of

snails is also very high, some 25,000/m?. The most plau-

sible explanation for the maintenance of unique alleles

in a population of only 185 generations is density de-

pendent selection where any mutation yielding a unique

allele yields some benefit to a population extraordinarily

stressed by parasitism (an idea attributable to Haldane).

Breeding Structure

Allozyme electrophoretic studies play a central role in

the modern study of genetic structure of populations and

especially breeding structure. The topic has been re-

viewed as it relates to mollusks (Selander & Ochman,

1983). An example of such a study is provided by

McCracken and Selander (1980), in which they studied

the breeding systems of 14 species of three families of

terrestrial slugs in the eastern United States. They dem-

onstrated that for six species, the normal breeding system

was either facultative or obligatory self-fertilization. One

of the species had three monogenic strains. One of the

most studied self-fertilizing species is the land snail Rum-

inia decollata with more than 30 monogenic or very

weakly polymorphic strains (Selander & Kaufman, 1978).

Take Away Message

Allozyme electrophoresis is, and will continue to be, an

essential tool for studying population structure, patterns

of reproduction, and uncovering different effects of se-

lective pressures.

III: PATTERNS OF EVOLUTION

A: Speciation

Species Definitions: One cannot speak of discriminating

among species and engage in describing new species

without committing to a species concept and being pre-

G. M. Davis, 1994

pared to defend the concept. This commitment is es-

pecially important if one is to apply molecular data in

justifying species status. This is not the place, nor is there

enough time in this presentation to argue at length all

pertinent aspects for defending a particular concept. I

will be brief.

There are essentially five concepts worth arguing about

of which I accept the fourth in the list. These are exten-

sively reviewed by Templeton (1989). (1) The Biological

Species Concept defended by Mayr (1963) has also been

called the isolation species concept (Patterson, 1985;

Templeton, 1989). It isnot acceptable as it stands because

the emphasis is on isolating mechanisms. As most of us

know from experience, the problem is not one of distin-

guishing species that occur in sympatry, but those that

are allopatric, e.g. in Korea vs. Japan. Intrinsic isolating

mechanisms are irrelevant as isolating barriers during

allopatric speciation. This is not to reject the relevance

of isolating mechanisms when they occur and are part

of the process of speciation, such as an instantaneous

cytological event within a population that causes repro-

ductive isolation. However, the process of speciation in

allopatry has nothing to do with “isolating barriers”.

Because Mayr associated polytypic species with con-

venience in pigeon-holing taxa, various authors have re-

jected both the biological species concept and the pol-

ytypic species concept (e.g. Cracraft, 1989). However,

these are two separate issues. There is value in under-

standing isolating mechanisms where they do apply dur-

ing the process of speciation; and I agree with Templeton

(1989) that polytypic taxa are relevant as a concept in

theory and practice. It is a straw-man issue to dismiss

both concepts just because some thought to use polytypic

taxa as an excuse to reduce the number of names one

would have to deal with. The polytypic species issue will

be revisited later.

Gareth Nelson (1989) rejects the biological species con-

cept because it assumes that species are the basic units

of evolution. Since he rejects the idea that species are

the basic units of evolution, he rejects the concept of

species! While I can agree that species are not the basic

units of evolution, I still can accept the reality of species.

Populations are the fundamental units of evolution in as

much that mutations or new gene combinations in in-

dividuals of a population are basic to the process of spe-

ciation, and excepting clonal and/or selfing individuals,

population structure is necessary for the spread of new

genes.

I reject both the evolutionary (model 2) and phylo-

genetic (model 3) species concepts for the same reasons.

Wiley’s (1981) evolutionary species concept involves “a

lineage which maintains its integrity from other such

lineages and has its own evolutionary tendencies and

historical fate”. It requires parental system of ancestry

and descent. It requires large disjunctions in allopatry

where one or more unique diagnostic qualitative char-

acters are needed. The phylogenetic species concept of

Rosen (1978) and Cracraft (1989) is the same but the

analysis must be done by cladistic methods. “A phylo-

Page 11]

genetic species is an irreducible (basal) cluster of organ-

isms, diagnosably distinct from other such clusters, and

within which there is a parental pattern of ancestry and

descent”. As Nelson and Platnick (1981) stated earlier,

“species are simply the smallest detected samples of self

perpetuating organisms that have unique sets of char-

acters’. At this point one should note that all species

concepts discussed here involve taxa that are monophy-

letic, ie. there is a parental pattern of ancestry and de-

scent; even the biological species concept.

The problems with the above concepts (models 2 and

3) are that they provide no guidance as to what characters

are important for defining species. By their criteria, two

allopatric populations that differ in an electrophoretic

study of allozymes, by two or three alleles unique to each

population, should be called different species. Hardly!

While both concepts admit to cohesion, i.e. the integrity

of a morphological database, they do not allow for vari-

ance, or how much variance can be associated with a

species. They deal only with the concept of cohesion, not

with the mechanisms responsible for cohesion. Ignorance

of population genetics as it relates to expression of mul-

tiple alleles at a single locus would easily lead to splitting

populations into discrete species when they really should

be considered one species.

I prefer the cohesion species of Templeton (1989)

(model 4) that includes the recognition concept (model

5) of Patterson (1985). According to Patterson, a species

is a population of biparental organisms sharing a common

fertilization system. This is the “flip side” of the biological

species concept of Mayr.

For Templeton, speciation is the evolution of cohesive

mechanisms. A species is a group of populations of a

monophyletic lineage. There is phenotypic-reproductive

cohesion. These populations share the same fundamen-

tal niche, i.e. the populations are interchangeable =

demographic exchangeability. Natural selection pro-

motes cohesion both through favoring reproductive co-

hesion, genetic relatedness and affecting the limits of

demographic exchangeability. The concept integrates

population genetics and ecology with the standard stud-

ies of morphology. The concept can be applied to all

organisms from outbreeders to syngameons or partho-

genetic organisms.

Using this concept requires more work and more data,

but who ever said that understanding the process of spe-

ciation was simple and uncomplicated? The process of

distinguishing species is not simply akin to picking up

marbles and assigning names to them on the basis of size,

surface patterns, and colors. With the cohesion concept,

two populations, one in Japan and the other in Korea,

might have their own evolutionary fates ahead of them,

yet still belong to the same species.

Patterns of Speciation: The relative ease of discrimi-

nating among species very much depends on the pattern

of speciation one encounters. There are two major modes

that I have encountered again and again: adaptive ra-

diation and morphostatic radiation. Osborn (1918) first

Page 12

used the term adaptive radiation: “ Adaptive radiation

is, descriptively, this extreme diversification of a group

[ e.g. mammalian, reptilian] as it evolves in all the dif-

ferent directions permitted by its own potentialities and

the environments it encounters.” For Stanley (1979),

adaptive radiation is the rapid progression of new taxa

from a single ancestral group. If one takes Stanley’s def-

inition, one might be dealing with the concept that Os-

born had in mind, where there is a considerable diver-

sification in morphological ground plans, or one might

be involved with a morphostatic radiation as defined by

Davis (1992).

Benton (1988) very well captured the essence of the

Osborn concept. The “key phases of an adaptive radia-

tion such as that of the placental mammals 65 million

years ago... involves (1), “an initial phase of rapid

diversification from a single ancestor... (2) the estab-

lishment of a diversity of new body plans in this early

phase... (3) early extinctions amongst the initial ele-

ments of the radiation. . .(4) a final phase of stabilization

of the lineages. ...’ It is important to assess the time

scale of an adaptive radiation. The mammalian radiation

exploded between 65 to 55 million years ago. All the

orders from bats to whales were established in this 10

million year period. There is also a taxon scale to consider.

There has been extraordinary morphological diversifi-

cation within the freshwater gastropod family Poma-

tiopsidae, but especially in the subfamily Triculinae that

is wholly southeast Asian and southern Chinese. In rel-

atively short time, some 12 million years to the present,

these small snails have diversified into three tribes and

over 23 genera (Davis,1992). The rapid diversification

probably took place in the first few million years (Davis

et al., 1984). There is a splendid adaptive radiation that

centers in the Mekong River (Davis, 1979) that involves

some ten of the 23+ genera. There is also a large mor-

phostatic radiation in southern China.

I use the term morphostatic radiation to include those

monophyletic taxa that have indeed radiated, but in al-

lopatry and where there are little or no discernible niche

differences. Likewise there is comparatively little mor-

phological differentiation compared to what one sees in

an adaptive radiation where morphology may vary in a

number of dimensions that reflect adaptations to differ-

ent environments. I use the term to replace Gitten-

berger’s (1991) “non-adaptive radiation” that is:

“.. non-adaptive radiation should denote evolutionary

diversification from a single clade, not accompanied by

relevant niche diversification. . the various species re-

sulting from the process would,in principle, not be able

to be sympatric.” As it is reasonable to consider that all

species in nature are adapted to their environments, the

term non-adaptive seems unsuitable. Further, one can

discern between adaptive radiations sensu Osborn, where

morphological adaptations to differing environments are

considerable, and morphostatic radiations as defined

above. Gittenberger maintains that there are numerous

intermediate situations between the two types I describe,

and that the concepts of higher taxa and genera are too

THE NAUTILUS, Supplement 2

Table 3. Scoring genera and the radiation of species of each

genus for qualitative morphological and ecological differences

involving eight characters that includes ecology. See text for

details. Ay = coefficient of radiation diversity.

Adaptive radiation: Triculinae

Huben- Lacun- Pachy- Julli-

dickia opsis drobia enia

Shell 5) 10 10 10

Radula 5 5 0 0

Mantle cavity 0 5 0

Head 0 5 0 0

Female reprod. system 5 5 5 5

Male reprod. system 5 0 0 5

Nervous system 0 0 0 0

Ecology 5 10 10 5

Sum scores = 25 40 25 25

Ay = 8.68

Morphostatic radiation: Triculinae

Neotric- Gamma- Wucon-

Tricula ula tricula chona

Shell 0 0 0 5)

Radula 0 0 0

Mantle cavity 0 0 0 0

Head 0 0 0 0

Female reprod. system 5) i) 5 5

Male reprod. system 0 0 0 0

Nervous system 0 0 0 0

Ecology 0 0 0 0

Sum scores = bY i) 5 10

ill defined. I reject these notions. There are sufficient

quantitative and cladistic procedures to clearly define

taxa except in certain instances of morphostatic radiation

where the mosaic of few characters confounds under-

standing the limits of species in allopatry.

In a morphostatic radiation one may be able to discern

among species or subspecies because of shell sculptural

differences such as seen in Albinaria of Gittenberger’s

(1991) example. There may be a mosaic of quantitative

differences that separate species. But these are, in such

radiations, usually small differences. To make the point,

I compare four genera of the Triculinae adaptive radi-

ation with four genera of the Triculinae morphostatic

radiation in Table 8. Each genus is scored for qualitative

differences in morphology and ecology compared with

other genera, where the species occupy different ecolo-

gies. There are eight characteristics scored. A genus is

scored 5 when it clearly differs from other genera in a

change in ground plan; species in the genus are scored

5 when they diverge in a character. For example, La-

cunopsis differs from other genera in ecology (5) and

the species have radiated into different niches (5); ecol-

ogy thus scores 10. In the same genus the radula differs

from others in the tribe but the radula is the same in all

of the species, therefore it scores 5 for radula. In a mor-

phostatic radiation one cannot tell the shells of Neotricula

G. M. Davis, 1994

from those of Tricula; shells score 0 as the species do not

radiate with different shell shapes or sculpture; etc.

To quantify the differences between the types of ra-

diation, I use a coefficient of adaptive differentiation, Ag,

that is calculated using the formula:

It is a standardized sum of mean squared differences

where n = number of characters scored; $,S5. . .S, =in-

dividual score for a character for generic species group

1, etc.; N = number of generic species groups. From the

example given in Table 3, there is 4.5 times the amount

of diversification morphologically and ecologically in the

adaptive radiation of triculine taxa compared to the mor-

phostatic radiation of triculines.

I have digressed considerably on species definitions

and patterns of speciation because it becomes clear that

discriminating among species in an adaptive radiation,

and where several congeneric species may be located in

a habitat, may be a relatively easy task. The difficulties

reside with allopatric taxa of a morphostatic radiation

where molecular genetics may be extremely useful or

may confound the issue. The situation I presented above

for the three species of Uniomerus is an example of

usefulness of molecular genetics. I will present two ex-

amples where the interpretation of molecular genetics

must be made in light of all other data.

Oncomelania hupensis polytypic species: Oncomelania

is a member of the Pomatiopsidae: Pomatiopsinae, with

what I currently consider to be two species: Oncomelania

hupensis and O. minima. This genus is a member of a

morphostatic radiation. The latter species occurs in Ja-

pan; the former has subspecies distributed in China (1),

Taiwan (2), Japan (1), Sulawesi (1), and the Philippines

(1). The systematics of this genus was reviewed by Davis

(1980,1981). Briefly, O. hupensis was considered to be a

polytypic species because: (1) the anatomy, except for

differences in size, was identical for all allopatric pop-

ulations; (2) the main shell differences were the occur-

rence of ribs on some populations in southern China;

however ribbing is controlled by a single gene and this

gene has been manipulated by hybridization experi-

ments; (3) the populations can be hybridized with no loss

of viability of F, or subsequent generations; (4) as anyone

who has simultaneously raised these snails in culture will

attest to, there is ecological exchangeability between pop-

ulations. There are indeed small differences in suscep-

tibility to different allopatric populations of Schistosoma

japonicum; in size; in degree of shell varix formation;

and the degree of gland formation about the medial

aspects of the eyes.

Recently, Woodruff et al. (1988) did an electropho-

retic allozymic study of several populations of Onco-

Page 13

melania hupensis quadrasi from the Philippines and

compared them with O. h. hupensis from China. The

Nei’s D among the Philippine populations averaged 0.036

(greatest value = 0.134); The Chinese and Philippine

populations differed by a mean of 0.62 + 0.04. They

concluded that the Chinese and Philippine snails be-

longed to different species because of the large genetic

distance. They justified this conclusion by (1) invoking

the evolutionary species concept; (2) they reject the bi-

ological species concept with its emphasis on reproduc-

tive isolation and consider polytypic species to be an

essential element of the biological species concept; (3)

they argue that subspecies is a category of convenience,

a way of pigeon-holing taxa and reducing the number

of names one has to deal with; (4) they argue that the

use of subspecies causes confusion by underestimating

the number of independently evolving lineages.

I disagree! The polytypic species concept with its sub-

species is indeed useful; it certainly does not have to be

married to the biological species concept. Also, the rec-

ognition of subspecies does not reduce the number of

names used nor does it imply that the allopatric popu-

lations involved are not independent evolving lineages.

The use of subspecies serves a very useful purpose and

is not used as a matter of convenience. Further, the

Oncomelania hupensis polytypic species complex does

meet the major criteria of the evolutionary species con-

cept: reproductive recognition and genetic integrity.

Large genetic distances by themselves do not serve to

define species. For example, Johnson et al. (1984) found

that a population of Cepaea nemoralis introduced from

Europe to Lexington, Virginia (southern U.S.A.) differed

from a population from Florence, Italy by Nei’s D of

0.631; a population from Santa Croce near Pavia, Italy

compared with the Florence population differed by D

of 0.391. This species is well known for geographic vari-

ation for both shell polymorphism and allozymes. The

species is well studied throughout its range. To quote

Johnson et al. (1984), “The decoupling of genetic di-

vergence from speciation emphasizes the limitations of

viewing the process of speciation solely in genetic terms.”

In questioning the origin of the Lexington population,

Stine (1989) used restriction enzyme analysis of mito-

chondrial DNA to demonstrate it to be more closely

related to populations from England rather than from

Italy (Nei’s D of 0.409).

What Woodruff et al. (1988) are doing is ignoring the

great genetic cohesion that unites the subspecies of On-

comelania hupensis, a cohesion that is associated with

demographic exchangeability. One powerful example of

this genetic cohesiveness is the invariability of the re-

productive systems. There is indeed cohesion in repro-

ductive recognition. While I certainly agree that the

ability to hybridize is not a criterion for merging per-

fectly good species (examples of syngameons are nu-

merous), it is instructive that the large Nei’s D does not

interfere with the hybridization of these subspecies with

no loss of viability in the offspring or through successive

generations. There is indeed genetic cohesiveness. Be-

Page 14

ROGERS’ D

.90 .80 .70 .60 .50

1.7 1.6 1.5 1.4 1.3

THE NAUTILUS, Supplement 2

-OVALIS

.CHIT

.MINN.-A

. MINN.-B

74 FA C4 CS

Belen (CS

SP.aiG

SP.- B

. SP-A

nnn nan

OXYLOMA

.40 .30 -20

- OVALIS

. CHIT

. MINN.-A

. MINN.-B

Behe (S

/ SPB

2 SAS [D)

Dn NnNnNHnDn 222 2

6 SPAS /A\

1.2 1.1 1.0 0.0

UPGMA- MORPHOLOGICAL DISTANCE

Figure 5. A comparison of phenograms comparing some of the succineid taxa studied by Hoagland and Davis (1987). Allozymic

electrophoretic results are compared with morphological results. Modified from Hoagland and Davis (1987). Sp. D was not studied

electrophoretically. S= Succinea; N=Novisuccinea. See text for details.

yond the cohesiveness of the reproductive organs, there

is the cohesiveness in all the other details of anatomy,

reproductive habit, responses to environmental manip-

ulation. The usefulness of the subspecies designation in

this example is to bring attention to the great cohesion

throughout this complex and understand what this im-

plies for many aspects of the biology of the species through

time. It would be useful if Woodruff et al. would examine

the disruption of cohesion (i.e. morphological diversifi-

cation) in sister taxa to Oncomelania that are likewise

considered part of a morphostatic radiation, i.e. species

of Tricula or Neotricula. One finds numerous characters

of use to distinguish among species. Examples of these

are most frequently found in slight modifications of the

reproductive systems; e.g. penis with papilla in one spe-

cies, without papilla in another; penis with pronounced

ejaculatory duct in one species, without ejaculatory duct

in another; penis mounted center on the head vs. right

of center; seminal receptacle arising at position “a” in

one species, or in position “b” in another. Also,the shell

G. M. Davis, 1994 Page 15

A O.HUPENSIS

N.LILU

G.CHINENSIS

G.SONGI

—— SS

-80 32 -64 -56 -48 -40 32 24 16 .08 -00

B O.HUPENSIS

N.LIL

G.CHINENSIS

G.SONGI

—S

1.00 -90 -80 70 -60 -50 -40 30 -20 -10 -00

Cc O.HUPENSIS

N.LILW

G.CHINENSIS

G.SONGI

1.00 -90 -80 70 -60 50

-40 -30 20 -10 -00

Figure 6. Phenogram based on UPGMA treatment of genetic distances. A. Nei’s D; B. Wright's modified Rogers’ D; €. Arc D. O.

= Oncomelania, N.= Neotricula; G.= Gammatricula. Adapted from Davis et al. (1994b).

may have an internal tooth on the columella vs. no tooth;

and so on. These small differences are the types found

in a morphostatic radiation in contrast to major ground-

plan changes found in an adaptive radiation. The contrast

with polytypic Oncomelania hupensis is striking. To

achieve full species status, some occurrence must cause

disruption of the cohesion seen. This is evidenced in

Oncomelania minima of Japan where the shell shape

departs from that seen in Oncomelania hupensis; there

Oncomelania

hupensis

Neotricula

lilii

Gammatricula

songi

Gammatricula

chinensis

Figure 7. Cladogram based on a Hennig86 treatment of the

same allozyme data used in Figure 6, but scoring each locus

as a character.

are several shifts in the morphologies of the reproductive

systems (Davis, 1969), character-state changes similar to

those seen in the sister subfamily Triculinae. The point

is that one must know what occurs in sister taxa relative

to the taxon under study; what are the patterns of char-

acter change relative to recognition of species.

Unfortunately, the use of subspecies in malacology is

generally farcical! No wonder the term subspecies is little

respected when subspecific status is awarded to popu-

lations that differ by so slight a character-state as an extra

bump or node or rib in one population that is not seen

in another. Numerous subspecies have been based on

conchology alone where the basic definition of a species

has not been worked out, let alone any understanding of

what the extra bump means. However, while most mal-

acological subspecies currently named in the literature

have no biological validity, there are indeed substanti-

ated cases of polytypic species, and Oncomelania hu-

pensis is one of them.

The land snail genus Succinea: In this example, com-

parative anatomy, ecology, and molecular genetics were

used to assess species status. As will be shown, molecular

genetic data were useful in some cases, not useful in

other cases. The question was, what was the true identity

Page 16

2 G

2 i .

= 2 2

> = x= ()

= = o Zs)

(2) = o o

10(1) 7(0)

1-6(1)

ea)

SYNAPOMORPHIES

PLESIOMORPHIES

Figure 8. Cladogram based on morphological data for the same

taxa shown in Figures 6, 7.

of a rare and endangered species, Succinea chittenan-

goensis Pilsbry, and how could it be distinguished from

other sympatric species on or at the Chittenango Falls

in upper New York State in the northeastern USA? The

study included topotypical S. ovalis and populations of

Succinea from Pennsylvania and Minnesota. The out-

groups for the electrophoretic study were Oxyloma re-

Gammatricula

chinensis

hilii

Gammatricula

songi

Neotricula

THE NAUTILUS, Supplement 2

tusa Lea, and O. decampi gouldi Pilsbry of Chittenango

Falls. Through electrophoresis and shell morphometrics,

another species was found at the falls in addition to S.

ovalis and S. chittenangoensis, a species with a shell

shape similar to S. putris (Linnaeus) of Europe. In the

anatomical studies, 51 characters were scored using bi-

nary coding. In the allozyme studies, 31 loci involving

87 alleles were found. The data of both sets were ana-

lyzed using multivariate analysis yielding UPGMA de-

rived phenograms as shown in Figure 5 [modified and

simplified from Hoagland & Davis (1987)]. The findings

were: (1) Genetic and morphological data support the

conclusion that three genera are involved; Succinea,

Novisuccinea, and Oxyloma. (2) Oxyloma is more closely

related to Succinea than it is to Novisuccinea. (8) N.

ovalis and N. chittenangoensis at the falls cannot be

distinguished electrophoretically while they are clearly

distinct in terms of anatomy and ecology (as well as on

shell differences). They are distinct species. (4) The two

populations of Novisuccinea from Minnesota are clearly

not N. ovalis. They are not morphologically distinct yet

they have diverged genetically (Nei’s D = 0.104). Fur-

ther studies would be necessary to assess whether or not

they are specifically distinct. (5) In the remainder of the

comparisons results based on morphology paralleled those

based on molecular genetics.

Why are the falls Novisuccinea species morphologi-

cally divergent yet not electrophoretically so? The prob-

able answer is that the area was glaciated until 10 to 12

thousand years ago. With retreat of the glaciers and the

uncovering of the falls, N. chittenangoensis evolved from

an ancestor of regional N. ovalis by colonizing the falls

with concomitant shifts in morphology in adapting to

new ecological space. There has not been enough time

to diverge in terms of allozymes.

Oncomelania

hupensis

r = 0.84

Figure 9. Prim network based on multivariate analysis of morphological data. The taxa are those treated in Figures 6-8.

G. M. Davis, 1994

B: Phylogeny

Molecular genetics are certainly useful in assessing phy-

logeny. I will provide an example that builds on the

morphostatic radiations given above involving the Po-

matiopsidae: Pomatiopsinae and Triculinae (Davis et al.,

1994b). The questions asked were: Are the Pomatiopsinae

and Triculinae monophyletic? Is Oncomelania closely

related genetically to the more generalized triculine taxa

that are part of the morphostatic radiation? What genetic

distances might one expect between genera of the Tri-

culinae? Is a cladogram based on genetic data congruent

with a cladogram based on anatomy? Are these clado-

grams congruent with biogeographical data?

The electrophoretic analysis involved 28 loci and 78

alleles. The morphological analysis involved 17 charac-

ters. Phenograms based on UPGMA treatment of three

genetic distances are given in Figure 6. A cladogram

based on using each enzyme locus as a character and

applying Hennig86 version 1.5 (Farris, 1989) is given in

Figure 7. Oncomelania is the outgroup; there was no

differential weighting or polarities assigned. Only one

tree resulted, with a consistency index of 0.62. The clado-

gram based on the morphological data is given in Figure

8. The phenograms and the two cladograms are congru-

ent. The cladograms are congruent with biogeography

and the hypothesis on the direction of evolution from

northern Burma-western Yunnan, China with dispersion

and divergence down evolving river systems (Davis, 1980,

1992). These congruencies give confidence about the

phylogenetic results published earlier based solely on

comparative anatomy (e.g. Davis & Kang, 1990; Davis,

1992)

The question about monophyly is also answered. There

is no great divergence of Oncomelania from the triculine

taxa. The question was justified for the following reason.

In the Pomatiopsinae, the spermathecal duct runs from

the bursa copulatrix to the anterior end of the mantle

cavity. In the Triculinae the spermathecal duct runs from

the bursa to the pericardium or to the posterior end of

the mantle cavity. Are the spermathecal ducts homolo-

gous? It has been a hypothesis that the spermathecal duct

in the Triculinae derived from the primitive gonoperi-

cardial duct that connects the oviduct to the pericardium

in some rissoacean taxa. However, in the Pomatiopsinae

there is a vestigial gonopericardial duct and the sper-

mathecal duct! Two families might be involved.

The average Nei’s D between Oncomelania and the

triculine taxa is 1.29 + 0.41. This is not a large distance

considering what one might expect of different families.

It is especially not large when one calibrates the system.

The distance between two of the triculine taxa is 1.26,

a D value greater than between Oncomelania and Gam-

matricula songi where D = 1.00. In describing G. songi,

Davis et al.(1994) stated that the anatomical innovations

found in this species warranted generic status, but that

a new genus would not be named until more species of

Gammatricula were found and studied. As shown in

Figure 9, G. songi and G. chinensis diverge equally from

Page 17

Neotricula along the Prim Network. Considering there

to be three triculine genera involved, the average Nei’s

D among them is 0.890 with a range of 0.689 to 1.236.

Thus, Oncomelania seems more to be a genus closely

allied within a triculine generic grouping rather than a

member of a different subfamily. Once again the point

is made: Measures of genetic distance do not serve to

define taxon levels! The subfamilies Pomatiopsinae and

Triculinae are firmly based on qualitative anatomical

data that in either a phylogenetic/ cladistic or multi-

variate analysis support those diverging sets of genera at

a hierarchical level deserving subfamilial status. The ge-

netic data do serve to confirm close genetic relationship,

not a highly disjunct pattern indicating polyphyly.

Take Away Message

Discriminating taxa at the species level is most difficult

when one is dealing with allopatric populations of a mor-

phostatic radiation. There are indeed different processes

of speciation. Speciation may proceed uncoupled from

genetic differentiation seen in structural genes such as

demonstrated using allozymes. Considerable genetic dis-

tances do not necessarily mean that the overall genetic

cohesiveness among populations is disrupted to the extent

that species status is attained. Rapid morphological change

in adapting to new environmental space may outpace

molecular genetic change. In examining a large radiation

spread over great distances, one would expect that in

perhaps 70% or more of the species, morphological and

molecular genetic change would diverge in parallel. Un-

tangling species-level problems can be a most challenging

task as pointed out by Giusti and Manganelli (1992; see

Prologue). For those engaged in this task, one needs as

much data as one can obtain, certainly building on a

firm platform of detailed comparative anatomy. Ecolog-

ical data are essential. Molecular data are always useful,

but do not add to the solution of a problem in a rote

formulated way. Above all, molecular data must be cal-

ibrated for the radiation under study.

Concerning phylogeny: Molecular genetic tools are es-

sential to test phylogenies based on comparative anato-

my. Together, both data sets provide insight into the rate

of evolution. Together, both data sets serve to test hy-

potheses about biogeography.

IV: UNCOVERING UNIQUE ASPECTS IN EVOLUTIONARY

PROCESS

It has been known for a long time now that different

molecular data sets may yield different results. Also, one

set of tools is better suited for assessing relationships at

one taxonomic level, while other tools are better suited

for a different taxonomic level. For example, restriction

enzyme analysis of mitochondrial DNA is most suited

for determining relationships at the population level, or

among closely related species. Allozymes are superb for

studies of population genetics and to assess relationships

Page 18

THE NAUTILUS, Supplement 2

QUADRULA, MEGALONAIAS, UNIOMERUS

ANODONTA, LAMPSILIS, OBLIQUARIA

ELLIPTIO, AMBLEMA, FUSCONAIA,

PLECTOMERUS, UNIO

GONIDEA

CUMBERLANDIA MONODONTA

MARGARITIFERA MARGARITIFERA

MARGARITIFERA FALCATA

Figure 10. Phenogram following UPGMA treatment of distance coefficients based on LrRNA sequence differences among species

of freshwater clams of the family Unionidae (for further details, see Rosenberg et al., 1994).

among species, monophyletic genera and tribes to sub-

families. Immunology has been used with success from

the species to family level. However, as discussed above,

there is no universal molecular clock. Different data sets

may yield different results. For example, Murray et al.

(1991), as part of a series of excellent studies of evolution

and speciation within the Pacific islands land snail Par-

tula, compared the results of morphological investiga-

tions, protein electrophoresis, and mtDNA and defended

the following: “...the different data sets evolve inde-

pendently and at variable rates. This mosaic pattern of

evolution can only occur if natural selection plays a role

in the genetic differentiation of Partula”’.

We are now in a new age, one of sequencing. Cloning

genes and nucleic acid sequence analysis began to ex-

plode in the decade of the 80's. Exciting developments

were made possible with DNA amplification by the poly-

merase chain reaction (PCR) where a DNA segment of

some 6000 base pairs may be amplified starting with as

little as a single gene copy (reviewed by Landergren et

al., 1988). As with the emergence of any new technology,

one should expect some surprises. Paradigms based on

studies of mammals may be shattered when studying

mollusks that have evolved over 600 million years with

amazing diversification of anatomical groundplans,

physiologies, and genetics. I present one such surprise

encountered when studying large-ribosomal-RNA se-

quences of a series of freshwater clams (Unionidae) as

part of a larger study that included land snails and the

prosobranch Oncomelania (Emberton et al., 1990).

The taxa studied are listed in Table 4 in the classifi-

cation scheme of Davis and Fuller (1981). We examined

some 150 base sequences that included the highly con-

served 5’ end and the D-6 divergent domain plus flank-

ing regions. We scored 26 differences among taxa and

subjected these to a simple standard UPGMA treatment

with the resulting phenogram shown in Figure 10. I wish

to make only a few remarks about these results; a more

detailed treatment of these sequence data in relationship

to sequence data from diverse mollusks is presented later

in this issue (Rosenberg et al., 1994).

Morphological, immunological, and allozyme data

support the concept that there are three equal and di-

vergent clades (Figures 11, 12, adapted from Davis &

Fuller,1981; Davis et al., 1981). I would prefer to call

them subfamilies, while others have split off the group

of Margaritifera as a separate family. I point out, how-

ever, that given the weight of evidence, the group of

Anodonta is equally divergent from other non-Margar-

itifera unionids and thus should be accorded equal rank

either at the family level or subfamily level.

While there is congruence of the morphologi-

cal,allozymic, and immunological data, the LrRNA se-

Table 4. Unionid species used to study LrRNA sequences

classified in the scheme of Davis and Fuller (1981) based on

immunological and morphological data.

Margaritiferinae

Cumberlandia monodonta

Margaritifera margaritifera

Margaritifera falcata

Anodontinae

Anodonta cataracta

Anodonta imbecilis

Anodonta grandis

Ambleminae

Gonideini

Gonidea angulata

Pleurobemini [should be Unionini]

Elliptio complanata

Pleurobema cordatum

Fusconaia cerina

Unio pictorum

Uniomerus “tetralasmus”

Amblemini

Amblema plicata

Quadrula quadrula

Quadrula cylindrica

Megalonaias boykiniana

Plectomerus dombeyianus

Lampsilini

Lampsilis claibornensis

Lampsilis teres

Obliquaria reflexa

G. M. Davis, 1994

Page 19

GONIDEINI

= ce)

AMBLEMINAE

MARGARITIFERINAE

ANODONTINAE

Figure 11. Ordination diagram following multidimensional scaling using immunological distances from freshwater clams of the

family Unionidae. Computer-derived sets and subsets are enclosed in the dashed lines. As with the allozymic data-set (Fig.10),

there are three discrete clusters: Margaritiferinae, Anodontinae, and Ambleminae( Amblemini,Lampsilini, Unionini, Gonideini).

Adapted from Davis and Fuller (1981).

quence data offer some surprises! As seen in Figure 10,

(1) Anodonta cannot be distinguished from Lampsilini

genera Lampsilis and Obliquaria. (2) One cannot distin-

guish among species or genera in the groupings of An-

odonta etc., Elliptio etc., and Quadrula etc., yet there

are distinct differences between the two species of Mar-

garitifera. (3) Cumberlandia monodonta, is widely sep-

arated from the species of Margaritifera. The differences

among the Maragitiferinae taxa and with other unionids

involve sequence changes at 25 positions, while the dif-

ference between the Anodonta group of genera and the

Quadrula group of genera involves only one difference.

The point to be made here is that Anodonta seems firmly

nested with other genera of the tribes Unionini ,Amble-

mini, and Lampsilini while on all other data, both mor-

phological and molecular (immunological and allozym-

ic), Anodonta is highly divergent from genera of those

tribes (Figures 11,12). The three Margaritiferinae taxa

Page 20

ANODONTA

-1.0

MARGARITIFERA

THE NAUTILUS, Supplement 2

0.2 = EUSCONAIA

J (0 . \

\ - \

2 ; /ELLIPTIO

-0.9

Figure 12. Ordination diagram following multidimensional scaling using allozymic electrophoretic data from freshwater clams of

the family Unionidae. Computer-derived sets and subsets are enclosed in dashed lines. A Prim network is used to connect taxa.

Note the direction of divergence of Anodonta away from Margaritifera, apecommately equidistant from the set of the Ambleminae

( Lampsilis, Fusconaia, Elliptio). Adapted from Davis et al. (1981).

show considerable divergence among themselves, with

considerable changes in the variable and 3’ flanking re-

gion, not seen in the other unionids. This is indeed a

surprise. One interpretation that warrants further testing,

is that the Margaritiferinae diverged from all other

unionids at an early date and uniquely departed from

other unionids in this pattern of sequence changes. An-

odonta, while maintaining the rather conservative se-

quence structure, diverged from the non-Margaritiferi-

nae clade, also at an early date, and rapidly diversified

morphologically with concomitant immunological and

allozymic changes.

Take Away Message

It is clear that a single measure of genetic distance cannot

be used to discriminate among taxa. Speciation indeed

G. M. Davis, 1994

progresses by different patterns and processes. Speciation

may proceed unhinged from genetics (as evidenced by

current molecular techniques); some allopatric popula-

tions may retain great cohesion in breeding system, mor-

phology and demographic exchangeability (all geneti-

cally controlled) yet accumulate considerable structural

gene changes that, by themselves, do not justify giving

the populations species rank. Generally, morphological

and genetic data diverge in parallel. Two points are

especially clear: (1) a species concept is necessary that

does not go to the absurdity that one or two qualitative

differences among allopatric populations justifies species

status, especially on the basis that the separated popu-

lations, being thus isolated, have their own unique tra-

jectory in time and space; (2) one needs all the possible

data one can obtain to sort out some species problems,

starting with detailed anatomical data and ecological

observations.

Indeed, the new generation of molecular tools are

yielding surprises. Sequence data join the other tools in

providing powerful insights into patterns and processes

of evolution. However, as mountains of data accumulate,

it will become increasingly clear that all the problems

with other molecular data sets will become evident with

sequence data: convergences, sequences of one molecule

( e.g. LrRNA) being uninformative for some groupings

of taxa, while showing wild divergences for other taxa,

etc. These problems will settle down with the sequencing

of whole genes and using genes as characters in phylo-

genetic analysis. We are a long way from this, as yet,

costly and time consuming task. Increased automation

of procedures will ease the task.

CONCLUSION

Clearly nature is both capricious and pernicious in how

she spins off species and promotes patterns and processes

of evolution. It certainly appears this way to a seasoned

systematist. The work of discriminating among taxa is

clearly complex and multidimensional. There are no rote

rules to apply such as stating that species status is achieved

when Nei’s D equals some artificial value. What is splen-

did today are the variety of tools that can be applied to

solving taxonomic problems. The battery of new molec-

ular tools are especially appreciated and provide the basis

for much rigor in testing hypotheses about taxonomic

relationships. I have discussed in this lecture the utility

of molecular tools for uncovering cryptic species, for

studying population genetics, and for studying patterns

of speciation and phylogeny.

I hope that I have made clear the point that the fun-

damental basis of taxonomic discrimination is based on

detailed comparative anatomy and cytology. Genetic dis-

tances, by themselves, do not serve to define species or

higher taxa. There is no universal molecular clock! Fur-

ther, morphological, allozymic, MtDNA, and DNA se-

quences may diverge at different rates within the same

taxon. Taxa within a clade must be calibrated relative

to genetic distance. In studying a situation involving the

Page 21

species-level, it is useful to know if one is involved with

an adaptive radiation or a morphostatic radiation; it is

useful to know the characters and character-state changes

that serve to distinguish species and genera in sister taxa.

To add to the want list, a systematist would like to de-

termine the ecological correlates of morphology, the time

of taxonomic divergence, and the direction of evolution.

Such data require knowing a group on a global basis.

Timing and direction may come from paleontological

evidence or from geological events. And still, as Giusti

and Manganelli (1992) stated so well, a good systematist

“..is not above admitting that its exact nature [what is or

has occurred] escapes him. . .”. Understanding a complex

situation in speciation may take years of study.

ACKNOWLEDGMENTS

This presentation, and much of the work presented here

was supported by an NIH grant AI 11873 TMP. The

graphics were prepared by Susan Trammell. I am in-

debted to Gary Rosenberg for reading and making useful

criticisms of this manuscript.

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7 = ‘t inieinl,

Mey ees

THE NAUTILUS, Supplement 2:25-43, 1994

Page 25

The Evolutionary Consequences of Restrictions on Gene Flow:

Examples from Hydrobiid Snails

D. J. Colgan

W. F. Ponder

The Australian Museum

P.O. Box A285

Sydney South, Australia 2000

ABSTRACT

The evolutionary consequences of restrictions on gene flow are

discussed in relation to the population genetic structure and

speciation of four Australian hydrobiid snail faunas. The stud-

ied faunas comprise: (1) the brackish water genus Tatea; (2)

species of Fluvidona in freshwater streams at Wilsons Prom-

ontory; (3) species of Fonscochlea and Trochidrobia in artesian

springs near Lake Eyre in South Australia; and (4) species of

an undescribed genus at Dalhousie Springs in northern South

Australia, another arid zone artesian spring complex. Gene flow

in these hydrobiids is very variable. It is high in Tatea, relatively

high at Dalhousie Springs and extremely low in Wilsons Prom-

ontory and the Lake Eyre springs. Levels in the latter two

faunas are similar despite a great disparity in geographic area.

In these four faunas, the detail of gene flow patterns is complex,

emphasising the dependence of population structure on the

interaction of current and historical factors. This is illustrated

by speciation patterns, the numbers of species and their dis-

tributions usually correlating well with observed levels of gene

flow. However, there are examples, among species groups with

comparable, but very low gene flow, in which some taxa have

undergone speciation yet others have not.

The data were analysed using F-statistics and the private

allele frequency approaches. Whilst the qualitative conclusions

from the two approaches were generally similar, the exceptions

usually indicated (on biogeographic grounds), that the F-sta-

tistics approach is the more reliable estimator of gene flow. The

private alleles approach is dependent on a coincidence of the

scale of sampling with the biological scale of population sub-

division. Intensive sampling schemes, as utilised in our studies,

tend to find even rare alleles in more than one population even

though they may be quite restricted in geographical distribu-

tion. An analytical method for treating conditional allelic fre-

quencies would not be as sensitive to this problem as the private

alleles approach.

Key words: Gene flow, snails, freshwater, isozymes, Hydro-

biidae, evolution, population structure.

INTRODUCTION

The evolutionary fate of populations is largely deter-

mined by two sets of factors. The first may be charac-

terised as “coping factors’ —those determining the sur-

vival of a population. This set includes external pressures,

such as predation, parasitism and disease, extremes of,

or changes in, climate, competition from other species

or resource diminution. It also includes endogenous prop-

erties such as the amount of local inbreeding or the ca-

pacity of the breeding system to engender genetic re-

combination. The second set may be characterised as

“isolating factors’ —those factors which affect the evo-

lutionary history of a population relative to other, orig-

inally con-specific, populations. In general, this history

depends on how effective gene flow is in overcoming

differentiation inevitably arising from genetic drift or

responses to local selection. Conversely, speciation pro-

cesses are contingent on an “evolutionarily sufficient”

restriction of gene flow between populations that have

successfully accommodated the first set of factors. These

two sets of factors are, however, also inter-related. For

instance, it may be only through the introduction of a

novel gene from another area that a population is enabled

to withstand a climatic change.

Many studies have shown that speciation is directly

related to reductions in gene flow (reviewed by Grant,

1980; Porter, 1990). It is difficult, however, if not im-

possible, to predict what restrictions on gene flow over

what period of time constitute evolutionarily significant

barriers. The importance of the evolutionary conse-

quences of restriction on gene flow is such that its esti-

mation remains a goal of many experimental studies (e.g.

Skibinski et al., 1983; Waples, 1987; Johnson et al., 1988;

Mitton et al., 1989; Arter, 1990; Porter, 1990; Preziosi

& Fairbairn, 1992). There is also continuing interest in

the development of mathematical models for the analysis

of gene flow (e.g. Slatkin, 1985a; Barton & Slatkin, 1986;

Slatkin & Barton, 1989) and/or the the genetical sub-

division of species (Cavalli-Sforza & Feldman, 1990).

We have been investigating the hydrobiid gastropod

faunas of a variety of habitats to characterise their tax-

onomic and population genetic structure. We were par-

ticularly interested in how biological and environmental

differences between these faunas are reflected in the

Page 26

degree of genetic divergence and the amount of genetic

exchange between populations, and in the evolutionary

consequences of those differences. A priori, factors such

as the biological ability to disperse, the geographic scale

of the system, weather patterns, topography and the ac-

cessibility and suitability of the habitat for potential bi-

ological dispersal agents might all be expected to play a

part in determining levels of gene flow.

Gene Flow

In this paper we define gene flow as the genetically-

effective transmission of alleles between extant discrete

populations and between various parts of the range with-

in species in which population boundaries cannot be dis-

cerned or do not occur. We do not regard re-colonization

after local extinction as an example of gene flow (agree-

ing with Endler, 1973; Grant, 1980;—but contrast Slatkin

1985b). Re-colonization, or original colonization simply

increases the number of populations of a species, other

processes being required for phylogenetic consequences.

Generally, continued gene exchange will homogenize

original and derived populations. Significant differenti-

ation requires persistent marked reductions in gene flow.

Any estimate of gene flow made on the basis of allelic

frequencies confounds factors operating during two dis-

tinct phases of the differentiation process. Firstly, the

establishment of a population implies a sampling process

which may cause differences in frequency arrays (Carson

& Templeton, 1984; Wool, 1987). Secondly, the differ-

ences reflect subsequent patterns of gene flow and dif-

ferential selection as well as any current trends. In the

discussion below, we usually make the assumption that

the comparisons between estimates of gene flow in dif-

ferent biological situations reflect differences in only one

of these two confounded factors in any given case. This

may not always be an accurate description of biological

reality. High allelic frequency differences may result

from a divergent initial founder effect or from a sub-

sequent reduction in gene flow, differential selection or

any combination of these three factors. Direct methods

of estimating gene flow, requiring observation of the

mating success and/or fertility of known immigrant in-

dividuals, largely overcome these problems. The labour

and practical difficulies involved in making such esti-

mates is such, however, that indirect methods are usually

pursued (Slatkin, 1985b; Johnson et al., 1988).

The Measurement of Gene Flow

Both methods of estimating gene flow which are used

here measure the parameter Nm, where N is the (effec-

tive) size of each sub-population and m is the probability

that a gamete in the offspring generation is an immigrant

to the sub-population where it occurs. Three principal

models of population structure have been developed as

mathematical abstractions to provide a theoretical

framework for measuring Nm:

THE NAUTILUS, Supplement 2

(A) The Island model (Wright, 1931), in which each

of an infinite number of discrete sub-populations

receives migrants at random from other sub-pop-

ulations. The geographic distance between pop-

ulations does not affect the rate of gene flow be-

tween them.

The Stepping Stone model (Kimura & Weiss, 1964),

in which gene flow occurs between a population

and its immediate neighbours in one or two di-

mensional geographic arrays. Gene flow does not

occur directly between two populations which are

not immediate neighbours.

Models in which the population is considered to

be continuously distributed in one or two dimen-

sions, with the degree of genetic differentiation

of individuals separated by a given distance de-

termined by the levels of gene flow.

The accuracy of these models’ approximation to pop-

ulation structure will vary. If the studied species has high

vagility, the requirement of the Island model that each

sub-population exchanges migrants with all others will

be a more accurate approximation than if the vagility is

low. Conversely, the Stepping Stone model’s restriction

on migration between populations which are not near

neighbours is more likely to be accurate if the studied

species has low vagility.

F-Statistics

The overall inbreeding coefficient can be partitioned into

components reflecting non-random breeding (F\,) and

the effects of between sub-population differentiation (F<)

(Wright, 1951). Under the infinite island model of pop-

ulation subdivision, if the migration rate is small, then

(Wright, 1951):

Fer = (1 + 4Nmy?

A variety, indeed almost a plethora, of alternative meth-

ods for the calculation of quantities very similar or iden-

tical to Fg; have been suggested (Wright, 1951, 1978;

Nei, 1973; Nei & Chesser, 1983; Cockerham, 1969; Weir

& Cockerham, 1984). Many of these were developed in

response to complications of the original two-allele per

locus situation studied by Wright. It can be shown that

these are usually encompassed by natural extensions of

Wright’s approach. Others attempt to take account of

relaxation of the simplifying assumptions (negligible se-

lection, mutation, etc.) made in Wright's analyses. The

various methods have been widely reviewed (e.g. Chak-

raborty & Leimar, 1987; Weir, 1990) and the differences

between them shown, generally, to be of second-order

significance. Moreover, both analytical (Slatkin, 1985b)

and simulation (Slatkin & Barton, 1989) studies tend to

emphasise the qualitative similarities between F; vari-

ables defined under either the Island or Stepping Stone

Models. Where estimates of gene flow given below are

based on Fez, this will be indicated by Nm(F¢,).

D. J. Colgan and W. F. Ponder, 1994

Conditional Allelic Frequencies

There are two main methods of analysing gene flow using

the approaches of Slatkin (1981, 1985a). The first requires

that the “occupancy rate’ for an allele be determined.

This is the number of sub-populations in which the allele

is found, divided by the total number of sub-populations.

The conditional average frequency of the allele is the

average of its frequencies in those sub-populations where

it actually occurs. Levels of gene flow between sub-pop-

ulations are visualised by graphing the conditional av-

erage frequency of each allele against occupancy rate.

Such representations can be useful in comparison of the

levels of gene flow in different taxa (e.g. Govindaraju,

1989) but, in the absence of an analytical theory, can be

used to provide numerical estimates only by making

analogies with the results of computer simulations (John-

son et al., 1988). In the second method, attention is re-

stricted to “private alleles”, i.e. those found in only one

sub-population. Slatkin’s simulations (1985a) found that,

in both Island and Stepping Stone Models, the conditional

average frequency of private alleles (p(1)) is approxi-

mately linearly related to the migration rate by the ex-

pression:

logio(P(1)) = alogi(Nm) + b

where a and b take values dependent on the number of

individuals sampled from each sub-population. One

claimed advantage of this approach is that its estimates

of migration rates are theoretically only slightly depen-

dent on mutation or the many types of selection which

might operate (Barton & Slatkin, 1986; Slatkin & Barton,

1989). Estimates of gene flow based on the frequency of

private alleles given below are designated as Nm(p(1)).

The Family Hydrobiidae

Small prosobranch snails of the world-wide family Hy-

drobiidae are the most diverse freshwater gastropods,

with nearly 400 generic names currently in use (Kabat

& Hershler, 1993). Commonly, in Australia, freshwater

Hydrobiidae occupy small streams or springs. The pop-

ulations in these isolated or semi-isolated habitats show

varying degrees of differentiation because of an apparent

inability to disperse readily. A low level of dispersal may

be possible, for example by birds or even flying insects

(Rees, 1965; Boeters, 1979, 1982).

Other genera inhabit brackish or estuarine waters. Ge-

netic data have been used to test hypotheses based on

morphological criteria in such taxa (Lassen, 1979; Davis

et al., 1988, 1989; Ponder & Clark, 1988; Ponder et al.,

1991). They tend to have large geographic ranges, partly

because some have a planktonic marine larval phase, but

also because they live in tidal marshland habitats where

they are potentially readily transported by birds.

In the remainder of this paper, we will concentrate

on-our recent investigations of three freshwater hydro-

biid radiations at Wilsons Promontory, in the Lake Eyre

supergroup of the South Australian Mound Springs and

Page 27

in the Dalhousie Springs complex at the north of South

Australia. For comparative purposes, we will often refer

to our studies of the brackish water (usually estuarine)

genus Tatea (Ponder et al., 1991). The fauna of the Lake

Eyre spring supergroup has been formally described

(Ponder et al., 1989) and that of Dalhousie Springs has

been briefly reported on with respect to shell morphology

(Ponder, 1989). The Wilsons Promontory study will be

described in detail in a forthcoming publication (Ponder

et al., 1994).

MATERIALS AND METHODS

Summary information regarding collecting sites, etc. can

be found in Appendix 2. More detail is provided for

Tatea in Ponder et al. (1991), the Wilsons Promontory

Fluvidona in Ponder et al. (1994), the Lake Eyre springs

in Ponder et al. (1989) and on Dalhousie Springs in

Zeidler and Ponder (1989). Genotypic data are available

from the senior author. Data for Tatea and Fluvidona

on allozymic frequencies, observed heterozygosities and

the various environmental parameters which were mea-

sured are given in Ponder et al. (1991, 1994). Similar

data for the other faunas will be presented separately

for each system.

Standard methods for cellulose acetate electrophoresis

were used (Hebert & Beaton, 1989, Ponder et al., 1991).

Individual snails were homogenized with 10-30 ul (mean

20 ul) of buffer, providing enough sample for up to 12

gels. Because of their small size, it was not possible to

examine each snail for all enzymes. Where more than

one locus is shown below as encoding the same enzyme,

each was designated numerically in order of decreasing

mobility. Allozymes identified for each locus are desig-

nated in the same way. The enzymes scored for each

species, or species grouping, together with abbreviations

used, Enzyme Commission Numbers, and number of

presumptive loci are listed in Appendix 1. There were

some differences between taxa in the number of loci that

were electrophoretically interpretable. These are speci-

fied in Appendix 1. The computer packages BIOSYS-1

(Swofford & Selander, 1981), NTSYS (Rohlf, 1990) and

PHYLIP, version 3-4 (Felsenstein, 1989) were used to

assist analysis.

All taxonomic groupings treated here were initially

analysed without assuming any hierarchical structure of

the populations. F,;, conditional allozymic frequencies

and private allelic frequencies were calculated. Popu-

lations were then clustered in hierarchies, as described

below and as detailed in Appendix 2. Components of

overall genetic differentiation were obtained for this clus-

tering using the WRIGHT78 step of BIOSYS. Allozymic

frequencies in taxonomic units at each intermediate level

of the clustering were calculated after pooling the data

from the sub-units included in the same group. The pooled

data were used to estimate Fs; values and conditional

(and private) allelic frequencies for units at this inter-

mediate level. This approach has a statistical tendency

to reduce the variance in gene frequencies (and hence

Page 28

Figure 1. Map of Wilsons Promontory showing major drainages

and the distribution of Fluvidona species. The area covered is

shown by the dot at the head of the arrow on the inset map of

Australia. The other inset shows a detail of Whisky Creek.

Locations of straight-sided snails are shown by O, the MPI 3

convex by Ml, MPI 4 by @ and MPI 5 by Q. Drainages: (1)

Darby River; (2) Whisky Creek; (3) Squeaky Creek; (4) Tidal

River; (5) Titania Creek; (6) Growler Creek; (7) Frasers Creek;

(8) Roaring Meg; (9) Picnic Creek; (10) First Bridge Creek;

(11) Freshwater Creek; (12) Blackfish Creek; and (13) China-

mans Creek.

increase the estimate of Nm) to a degree dependent on

levels of variation between samples pooled into the same

unit. If the variation is merely a sampling artefact then

the procedure will increase accuracy of Nm estimation.

But if the variation is due to biological subdivision of the

populations, then the estimate should be regarded more

as an upper limit on the degree of gene flow. A priori,

it is not possible to decide which of these two alternatives

is correct as we do not know what constitutes an effec-

tively panmictic unit in these hydrobiids. A second effect

of the pooling procedure is that alleles which are found

in more than one population and hence not “private” in

the original subdivision, may be regarded as private at

higher clustering levels if they are there restricted to

only one unit. Again, this reflects the uncertainty about

the biological structure of the population. Pooling data

may not always resolve this uncertainty but patterns in

such analyses will usually be informative about popu-

lation structure to at least some extent.

The sample sizes used in the studies varied from locus

to locus and from population to population. The average

sample per locus is shown in Appendix 2. When Nm was

estimated from the conditional frequencies of private

alleles, the parameter values for a sample size of 25 were

taken from Barton and Slatkin (1986). Alternative pa-

THE NAUTILUS, Supplement 2

Kilometres

Figure 2. Map of the Lake Eyre mound springs showing the

distribution of Fonscochlea and Trochidrobia species. The area

covered is indicated on the inset of Australia. The site of a

spring group is indicated by an “x”. Presence of a species in

the group is indicated by @ for F. accepta, © for F. aquatica,

@ for F. zeidleri, a for F. billakalina, W for F. variabilis, @

for T. punicea, © for T. minuta and O for T. smithi. The

spring groups are: (1) Freeling; (2) Outside; (3) Twelve Mile;

(4) Strangways; (5) Billakalina; (6) Beresford /Warburton; (7)

Coward/Jersey /Elisabeth/Kewson; (8) Blanche Cup; (9) Her-

mit Hill; (10) Davenport; and (11) Welcome.

rameter values did not, however, significantly affect nu-

merical estimates of gene flow.

THE STUDY AREAS

Wilsons Promontory

Wilsons Promontory (Figure 1), the southern-most part

of the Australian mainland (39°S, 146°28’W), consists of

granite hills up to 754 m with many permanent streams

and rivers fed by high rainfall (>1000 mm per year).

Its geological and climatological setting are summarised

by Wallis (1988) and Schmidt and Thornton (1992). The

hydrobiid fauna (genus Fluvidona) of the Promontory

comprises two endemic morphologically-recognisable

species, the shells of one with straighter whorl! outlines

and one with more convex whorls. The latter morpho-

species is divisible into three genetic species by very

nearly fixed sympatric differences in the MPI phenotype,

referred to as the MPI 3, MPI 4 and MPI5 genetic species.

For hierarchical analyses of population structure, sites

were grouped within streams, streams within catchments

and catchments within species, providing two interme-

diate levels (streams, catchments) in an analysis. Popu-

lations in which hybrids were seen were ignored in the

D. J. Colgan and W. F. Ponder, 1994

analyses examining gene flow within genetic species (see

Appendix 2).

South Australian Mound Springs

The springs, fed from the Great Artesian Basin of Aus-

tralia, are of considerable limnological and conservation

significance to the very arid area in which they occur

(Ponder, 1986; Harris, 1993). The springs generally lie

on the fringes of the Basin, where the aquifers abut

impervious rock or lie near the surface. The Lake Eyre

Supergroup, the most extensive group of springs associ-

ated with the Great Artesian Basin, extends about 400

km between Marree and Oodnadatta and provides vir-

tually the only permanent water in the area. The area

with springs is only rarely more than 20 km wide, so

that the supergroup conforms quite well to a one di-

mensional, discontinuous model. The geological history

of these springs is not well known. Estimates of the ages

of some large (extinct) mounds range from late Miocene

to Recent. These are probably at least Pleistocene (Wopf-

ner & Twidale, 1976; Williams & Holmes, 1978; Thomp-

son & Barnett, 1985) but the springs have probably been

in the area much longer. The taxa presently inhabiting

the springs may be relicts of more widespread forms

from a generally wetter period in the Neogene or may

represent faunas associated with these artesian springs

through much of the Tertiary.

The predominant drainage pattern in the Lake Eyre

basin is at right angles to the line of springs. Hence the

transport of snails between spring groups by floods would

be unlikely—although such transport could occur within

spring groups. Spring nomenclature and grouping used

in this paper follows Ponder et al. (1989). The hydrobiid

fauna consists of two endemic genera, Fonscochlea (five

species) and Trochidrobia (four species) (Ponder et al.,

1989)

For hierarchical analyses, springs were compared

within spring groups. The groups were then collected

into “clusters” (see Figure 2, Appendix 2), the Southern

cluster comprising springs between Welcome Springs and

Hermit Hill, the Middle cluster comprising springs be-

tween the Blanche Cup complex and Strangways and

the Northern comprising Outside, Twelve Mile and

Freeling Springs. If species were found in more than one

of these clusters, a second intermediate level was in-

cluded in the hierarchy. This could not, however, be

done for all species, Fonscochlea accepta, for instance

being found only in the Southern cluster. The Southern

cluster was divided into three groups: (1) Welcome

Springs; (2) Davenport Springs; and (3) the Hermit Hill

springs. The Middle cluster was divided into five groups:

(1) Blanche Cup springs, (2) the group consisting of Cow-

ard, Kewson, Elizabeth and Jersey springs, (3) Billakal-

ina; (4) Beresford and Warburton Springs; and (5) Strang-

ways Springs. The Northern cluster was divided into two

groups: (1) Twelve Mile and Outside springs; and (2)

Freeling Springs.

Page 29

Kilometres

Figure 3. Map of the Dalhousie Springs showing the distri-

bution of the globular (4), pupiform (@) and Fluvidona-like

snails (%). Spring groups are identified by letters near dashed

boundaries.

Dalhousie Springs

This complex is another large group of arid zone springs

in northern South Australia associated with the Great

Artesian Basin (Figure 3). Aspects of its geology and

biology are surveyed in a number of papers in Zeidler

and Ponder (1989). The many springs in the complex

occupy an area of about 70 km?. They range in size from

small nascent or senescent seeps, to actively flowing and,

at the upper end of the size scale, to outlets (of about

140 L/sec) which feed pools of 50 m or more in width

with outflow channels supporting wetland vegetation for

up to 15 km (Smith, 1989). Their combined discharge

accounts for 90-95% of the total produced by all South

Australian artesian springs (Smith, 1989), and 41% of the

overall output from Great Artesian Basin springs (Ha-

bermehl, 1982). They are well separated from springs of

the Lake Eyre supergroup, the northernmost population

of species from that region (F. zeidleri) being 140 km

away. These springs are likely to be early Pleistocene in

age (Krieg, 1989). Minor local overflow due to rare heavy

rain may facilitate interspring transport. Major flooding

is unlikely (Kotwicki, 1989).

Spring nomenclature and groupings used in this paper

follow Zeidler and Ponder (1989), except as specified

below. Eight main groups of springs, designated A to H

are recognised (Figure 3, Appendix 2). C is divided into

four sub-groups, and D into two. Herein, group H will

be treated as comprising two groups, because H3 is well

separated from H1. We have also split E into two sub-

groups containing, respectively, (1) E5 and El and (2)

Page 30 THE NAUTILUS, Supplement 2

Table 1. Estimates of Nm derived from the average frequency of private alleles or from the average F,, at various clustering

levels. The overall estimates assume no population hierarchy. The next two columns are estimates from data pooling within the

first intermediate hierarchical level and the final two columns are for pooling within the second hierarchical level (where applicable).

The upper figure in each cell is the observed value of the variable. The lower figure is the value of Nm calculated from the

observation.

Level 1 pooling Level 2 pooling

Overall

Species For pi)

Fluvidona (straight-sided) 0.130 0.444

0.776 0.3138

Fluvidona (convex) MPI 3 0.086 0.535

0.872 0.217

MPI 4 0.075 0.681

1.104 0.117

MPI 5 0.161 0.240

0.295 0.791

Fonscochlea accepta 0.116 0.207

0.525 0.958

F. aquatica 0.110 0.781

0.570 0.070

F. zeidleri 0.360 0.728

0.074 0.093

F. variabilis 0.196 0.792

0.211 0.066

F. billakalina 0.044 0.263

2.769 0.700

Trochidrobia punicea 0.143 0.600

0.363 0.167

T. smithi 0.426 0.730

0.055 0.092

T. minuta 0.086 0.375

0.872 0.417

Dalhousie (globular) 0.159 0.321

0.302 0.529

Dalhousie (pupiform) 0.180 0.413

0.244 0.355

Dalhousie (Fluvidona-like) 0.296 0.670

0.104 0.123

E2, E7 and E8. Generally, for hierarchical analyses,

springs were clustered into sub-groups, sub-groups into

groups and groups into the species. Three hydrobiid spe-

cies were recognised in our genetic studies. The globular

and pupiform species belong to an undescribed endemic

genus, the third species (also endemic) being tentatively

included in the widespread genus Fluvidona. Separate

analyses were performed for each species.

RESULTS

The levels of gene flow in the four Fluvidona taxa from

Wilsons Promontory are extremely low as shown by the

overall F-statistics in Table 1. The smallest F,; value is

for the convex MPI 5 genetic species. At 0.240, this is,

F sr p(1) F sr p(1)

0.120 0.375 0.108 0.348

0.491 0.417 0.589 0.468

0.110 0.523

0.570 0.228

0.199 0.628 0.081 0.462

0.205 0.148 0.967 0.291

0.091 0.282 0.073 0.254

0.791 0.637 1.157 0.734

0.028 0.110

6.036 2.023

0.128 0.756 0.149 0.412

0.439 0.081 0.338 0.357

0.289 0.750 0.155 0.625

0.108 0.083 0.316 0.150

0.300 0.783 0.173 0.688

0.101 0.069 0.261 0.113

0.226 0.300

0.165 0.583

0.098 0.580 0.160 0.470

0.696 0.175 0.299 0.282

0.265 0.584 0.224 0.346

0.125 0.178 0.167 0.472

0.244 0.429

0.144 0.381

0.038 0.105 0.028 0.082

3.565 2.131 6.036 2.799

0.015 0.296 0.014 0.228

17.706 0.595 19.942 0.846

0.300 0.492

0.101 0.258

however, near the higher end of the range previously

found for gastropods over comparable geographic scales

(Gould & Woodruff, 1986, 1990; Johnson et al., 1988).

The overall Fs; values for the straight-sided Fluvidona

species and the convex MPI 3 and MPI 4 genetic species

are very high. The levels of migration suggested by these

values range down to 0.117 for the MPI 4 genetic species,

implying that the fraction of a deme which is replaced

by immigrants each generation (m = 0.117/N) is very

small. The estimates of Nm(F,,) values based on the

pooling of data from individual samples may be com-

plicated by the likelihood that the pooled data do not

represent single populations. The trends in the estimates

are, however, very similar to those based on single pop-

ulations. Those for the MPI 4 genetic species are higher

than those for other Fluvidona taxa, but still suggest that

D. J. Colgan and W. F. Ponder, 1994

Page 31

Table 2. Variance components in the hierarchical F-statistic analyses. The Fy figures indicate that variance ascribable to variation

in the specified X variable (e.g., population) within the specified Y variable (e.g., spring group). Where two intermediate levels are

used for a species in the hierarchy, all six cells are filled. Where one level is used only three cells are filled. The top figure in each

cell is the calculated Fy, value and the bottom, the percentage of the total variance comprised by this.

X variable: Population Population

Y variable: Level 1 Level 2

Species

Fluvidona (straight-sided) 0.226 0.434

13 27

Fluvidona (convex) MPI 3 0.005 0.374

0 7

MPI 4 0.152 0.539

6 20

MPI 5 0.052 0.190

6 20

Fonscochlea accepta 0.122

F. aquatica 0.217 0.744

7 23

F. zeidleri 0.346 0.677

12 23

F. variabilis 0.382 0.599

1 19

F. billakalina 0.101

Trochidrobia punicea 0.118 0.262

6 13

T. smithi 0.745

T. minuta 0.059

Dalhousie (globular) 0.288 0.303

33 35

Dalhousie (pupiform) 0.304 0.363

24 28

Dalhousie (Fluvidona-like) 0.538

Variance components

Population Level 1 Level 1 Level 2

Total Level 2 Total Total

0.426 0.269 0.257 0.015

26 17 16 ]

0.570 0.371 0.567 0.312

26 7 26 14

0.679 0.456 0.622 0.305

25 16 23 ll

0.255 0.145 0.214 0.081

Qi 15 23 9

0.173 0.058

49 16

0.771 0.673 0.707 0.105

24 21 22, 3

0.718 0.506 0.568 0.127

24 We 19 4

0.781 0.352 0.646 0.454

24 11 20 14

0.220 0.1383

48 29

0.574 0.164 0.518 0.423

28 8 25 21

0.719 0.100

46 6

0.358 0.318

49 43

0.284 0.021 — 0.006 —0.027

33 2 =Il =8)

0.384 0.085 0.115 0.032

30 U 9 2

0.656 0.049

53 4

Nm is less than one. Values for MPI 4 are all higher than

for the individual sample estimation, marginally so for

the pooling of samples within tributaries and notably for

the pooling into catchment based units. Even so, the data

suggest that a catchment receives less than one migrant

from another catchment in every three generations.

Restrictions on gene flow are also suggested by analyses

of the conditional frequency of private allozymes. Es-

timates of migration rates based on these data are much

greater than those based on Fe; and differ in the relative

rates ascribed to the different taxa. The latter situation

is particularly notable in MPI 4 which apparently has

the highest rate of inter-population migration among all

four species, whereas its Nm(F¢,) is the lowest.

The components of variance due to differentiation be-

tween taxonomic units at different hierarchical levels are

presented in Table 2. Although comparison of these val-

ues is complicated by varying proportions of the popu-

lations being pooled at each level, some trends can be

observed. Particularly striking is the concordance be-

tween the three MPI genetic species, where in each case

almost half of the variation is explained by differences

between tributaries or between catchments. This con-

trasts with the straight-sided Fluvidona where only one

third of the variability is explained by such differences.

We have investigated gene flow in eight of the nine

Lake Eyre mound springs hydrobiids, Trochidrobia in-

flata being found in only two of our sample sites. As can

be seen in Figure 2 and Appendix 2, the distributions of

these species vary markedly in size. Fonscochlea accepta

is restricted to the Southern cluster of springs, F. billak-

alina to the central cluster and T. minuta to the northern.

The range of the other species extends into more than

one spring cluster, with F. zeidleri and F. variabilis being

found in all three clusters. The apparent levels of gene

flow between the populations of the species reflect this

variability in range. F. accepta has high gene flow, with

Nm(F.,) between spring groups being more than two.

Conversely, gene flow in F. aquatica, the snail which is

an ecological replacement for F. accepta in the central

Page 32

THE NAUTILUS, Supplement 2

Table 3. Estimates of F,,; or Gs; in gastropods. Measures using Gs; (Nei, 1973) are indicated by an asterisk. Geographic scale is

the distance between the extremes of the sampled range. References are: (1) Johnson and Black (1984a,b); (2) Brown (1991); (3)

Mitton et al. (1989); (4) Campton et al. (1992); (5) Grant and Utter (1988); (6) Day (1990); (7) Chambers (1980); (8) Jarne and

Delay (1990); (9) Mulvey et al. (1988); (10) Bandoni et al. (1990); (11) Johnson et al. (1988); (12) Gould and Woodruff (1986); and

(13) McCracken and Brussard (1980).

Species and reference No. of loci

Marine species

(1) Siphonaria jeanae 4

(2) Haliotis rubra 12

(3) Strombus gigas 7

(4) Strombus gigas 4

(5) Nucella lamellosa 2

(6) Nucella lapillus 8

Freshwater species

(7) Goniobasis (2 species) 14

(8) Lymnaea peregra 6

(9) Biomphalaria glabrata 13

(10) Biomphalaria pfeifferi W

Terrestrial species

(11) Partula taeniata 17

P. suturalis 16

(12) Cerion (New Providence) 8

(18) Triodopsis albolabris 2

and northern clusters, is quite low, Nm being 25 times

less between spring groups. In these large aquatic Fon-

scochlea, approximately the same relative levels of gene

flow are indicated by the estimates derived from con-

ditional allelic frequencies. Using Fs, for estimation, a

similar pattern is shown in comparisons of the smaller

aquatic species F. billakalina and F. variabilis, with gene

flow between spring groups in the former being nine

times the level in the latter. In Trochidrobia, gene flow

inferred from Fy statistics between spring groups in T.

minuta is twice as high as it is in the other two species

of the genus. In these latter two sets of comparisons,

however, the estimates derived from conditional allelic

frequencies do not show the same pattern as the F.;

estimates. F. billakalina has a similar Nm(F,) to F. var-

iabilis and the value for T. punicea is almost five times

as great as that for T. minuta.

The components of variation due to different hierar-

chical levels are strikingly similar in the aquatic F. aqua-

tica and the amphibious F. zeidleri. There is some dis-

agreement as to the level of Nm(Fs;) between spring

clusters for these species, but otherwise estimates of inter-

population migration in these species are remarkably

concordant. The concordance is significantly less for

Nm(p(1)). The components of variation are also similar

in two other species (F. variabilis and T. punicea) from

the Lake Eyre mound springs. Interestingly, the pattern

No. of samples Scale (km) Fg, mean

1 10 0.002

28 2,500 0.004

18 5,000 0.022

21 5,000 0.076

4 500 0.011*

14 5,000 0.023*

12 0.1 0.021

30 1,000 0.286

6 0.5 0.015

10 10 0.092

15 20 0.195

12 1,000 0.408

4 50 0.018

6 1,000 0.805

12 500 0.589

22 20 0.279

23 20 0.168

36 30 0.143

i 500 0.255

of variation of this pair differs from that of the two large

aquatic Fonscochlea, showing much greater between-

spring divergence.

Estimated Nm(F¢,) between populations at Dalhousie

Springs is in the higher reaches of the ranges observed

in these studies, in both the pupiform and globular spe-

cies. This trend is even more marked for inter-group

migration as assayed at higher hierarchical levels. Inter-

spring subgroup migration is higher in the globular snails

than in any other level-one pooling, and the estimate for

the pupiform snails is exceeded only by F. accepta and

F. billakalina. The calculated migration rates betwen

spring groups are higher for both the globular and pup-

iform Dalhousie radiations than for any other taxon in

our studies. As expected, the proportion of variation ex-

plained by differences at the lower hierarchical levels is

very high in comparison to our other studies. Indeed,

virtually all of the variation in the globular snails is due

to differentiation of populations within spring-subgroups,

within spring groups, or within the overall spring com-

plex (and not of spring-subgroups within groups, etc.).

The levels of gene flow estimated from Nm/(p(1)) for the

two higher hierarchical levels are extremely high in the

context of the present results. To the extent that these

estimates are credible, they reinforce the suggestion that

gene flow is high in the Dalhousie Springs complex, at

least as compared to the other study sites.

D. J. Colgan and W. F. Ponder, 1994

DISCUSSION

Our hydrobiid studies emphasise the dependence of pop-

ulation structure on a wide range of interacting biological

and environmental factors which must be considered in

historical terms. The three hydrobiid faunas we have

treated extensively in this paper, and the previously stud-

ied Tatea (Ponder et al., 1991) differ (either certainly

or probably) in such biological characteristics as size,

thermal and salinity tolerances and desiccation resis-

tance. These various hydrobiids also occupy different

types of habitat. Tatea occupies essentially continuous

habitat. Wilsons Promontory Fluvidona and the Dal-

housie Springs snails have habitats which are discontin-

uous, with relatively small distances between suitable

areas. The Lake Eyre fauna is in discontinuous, widely

separated habitat.

Before discussing our results in detail, some prelimi-

nary comparisons may be made to reinforce that gene

flows actually do differ between the faunas. The Wilsons

Promontory radiation occupies a much smaller geo-

graphic area than the Lake Eyre fauna, with the excep-

tion of Fonscochlea accepta. The markedly higher levels

of gene flow in F. accepta might suggest that the un-

derlying processes are more efficient in this taxon. Con-

versely, such relativity emphasises the very restricted

levels of gene flow in the Wilsons Promontory snails. This

is also suggested by comparisons of these Fluvidona spe-

cies with the Lake Eyre F. aquatica, F. variabilis and F.

zeidleri. The MPI 4 and MPI 3 genetic species do have

a slightly higher Nm(F,,;) than the Fonscochlea species

but this is a minor difference when the disparity between

their ranges is considered. These Fonscochlea species

each have linear extents well over an order of magnitude

larger than the MPI 3 and MPI 4 Fluvidona (over 200km

as opposed to less than 20km).

Population Structure in Quasi-Continuous Aquatic

Habitats

Although the vagaries of ocean currents may reduce gene

flow to or from a particular area (Todd et al., 1988;

Mitton et al., 1989), marine snails with planktonic (and

especially planktotrophic) larvae have wide natural dis-

tributions in which variation between local populations

is only a minor fraction of overall genetic diversity (Table

3). This pattern is found in Nassarius. obsoletus (Gooch

et al., 1972), Littorina littorea (Berger, 1973; Janson,

1987), Siphonaria jeanae (Johnson & Black, 1984a,

1984b), the species with planktotrophic larvae among

the Crepidula studied by Hoagland (1984), Strombus

gigas (Mitton et al., 1989; Campton et al., 1992) and

Haliotis rubra (Brown, 1991) which has a lecithotrophic

larva. Species distributions in these marine gastropods

tend to be either widely separated, often in conjunction

with geographic barriers to gene flow, or to be broadly

sympatric (e.g. Littorina - Berger, 1973; Janson, 1987;

Crepidula - Hoagland, 1984) presumably reflecting past

allopatric speciation and subsequent dispersal into sym-

Page 33

patry. The latter pattern was observed in our studies of

Tatea (Ponder et al., 1991). This genus, predominantly

estuarine with an assumed free-swimming larval stage,

has a very wide distribution, being found throughout

temperate Australia. Its two species T. rufilabris and T.

huonensis are sympatric over virtually all of this range.

There are exceptions to these patterns of speciation in

some groups with specialised feeding patterns which have

high species densities (Vermeij, 1987).

Groups with direct larval development or brooding

should have reduced gene flow, greater differentiation

and, conceivably, higher likelihood of speciation. The

first two predictions have been borne out in studies of

Littorina saxatilis (Snyder & Gooch, 1973; Janson, 1987)

and Nucella lamellosa (Grant & Utter, 1988). That a

short planktonic phase increases rates of speciation is less

certain. Littorina saxatilis does have a number of closely-

related sibling species (Janson, 1987; Johannesson, 1988;

Sundberg et al., 1990) and N. lamellosa may represent

a species complex (Grant & Utter, 1988). However, N.

lamellosa, as presently recognised, has one of the largest

geographic ranges of North Pacific gastropods.

Population Structure in Discontinuous Aquatic

Habitats

There have been major investigations of gene flow and

the genetic structure of two groups of the freshwater

gastropods in the caenogastropod genus Goniobasis.

Chambers (1978, 1980) investigated species from Florida

and Dillon and Davis (Dillon & Davis, 1980; Dillon, 1984)

those from the border regions of Virginia-North Caro-

lina. Three main results are relevant. (1) There is a high

degree of genetic divergence between populations within

the same drainage system indicating low levels of gene

flow. (2) There are larger differences between drainage

systems, reflecting an even smaller likelihood of inter-

drainage gene flow. (3) Identified taxa tend to remain

allopatric or parapatric, with geographically-restricted

ranges, suggesting that dispersal after speciation is lim-

ited. Dillon (1988) provides direct information on rates

of gene flow in transplanted G. proxima populations.

These are about 15-20 m upstream and 5-10 m down-

stream (per year), the discrepancy in movement rates

being caused by the behavioural tendency of freshwater

(Dillon, 1988) (and even riparian—Arter, 1990) snails to

crawl upstream in compensation for down current drift.

The findings for Goniobasis are not true of all fresh-

water snails, as shown by studies of genetic variation in

basommatophoran pulmonates. Dispersal in these snails

is often assisted by self-fertilisation (Mimpfoundi & Greer,

1989; Bandoni et al., 1990) and species distributions are

generally wide-ranging. Measurement of gene flow is

often hampered because of extremely low levels of ge-

netic variation (Mimpfoundi & Greer, 1989; Jarne &

Delay, 1991). Where flow can be assessed, as in Biom-

phalaria straminea (Woodruff et al., 1985), B. came-

runensis (Mimpfoundi & Greer, 1990), B. pfeifferi (Ban-

doni et al., 1990) or Bulinus cernicus (Rollinson et al.,

Page 34

1990), evidence of substantial population differentiation

is usually found, albeit at a geographic scale much larger

than in Goniobasis. Genetic variation in Biomphalaria

glabrata from the Caribbean is, however, primarily due

to inter-island differentiation (78%), with only 2% being

due to intra-island differences (Mulvey et al., 1988).

Each of the three main observations on Goniobasis is

applicable to the Wilsons Promontory Fluvidona but they

are less accurate descriptions of the two artesian spring

faunas, indicating that they are not generally character-

istic of freshwater dioecious gastropods. At Dalhousie

Srings, levels of inter-spring and inter-spring group dif-

ferentiation are not high and the globular and pupiform

species are sympatric over a substantial range. There are

instances in the Lake Eyre fauna where sister-species

remain essentially allopatric (e.g. F. accepta and F. aqua-

tica), but these are the exceptions.

Habitat Stability and Area Effects in Wilsons

Promontory

Habitat on Wilsons Promontory has probably been re-

duced during periods of aridity. The Fluvidona popu-

lation structure may still be showing distortions caused

by recent aridity-induced interruptions of migration,

particularly in the more upland MPI 3 and MPI 4 genetic

species. Modelling suggests that the re-attainment of

structural equilibrium following disruption is of the order

of hundreds of generations rather than thousands (or

more) for both the Fs; (Crow & Aoki, 1984) and p(1)

(Slatkin & Barton, 1989) approaches. The re-attainment

can, of course, only begin after the disruption is halted.

In the MPI 4 genetic species there are several geographic

groupings broadly definable by catchment. Gene flow

between these is low, with Nm(Fs,) values of 0.148 for

populations pooled within tributaries and 0.291 within

catchments. Following a period of aridity, increased lev-

els of migration in wetter times may overcome incipient

genetic divergence, unless the period were so prolonged

that the isolates undergo speciation. Such considerations

reinforce the importance of modelling the impact of non-

equilibrium population structures on measures such as

Fey (e.g. Whitlock (1992). They also suggest comparison

with “area effects’ and their various evolutionary con-

sequences.

Area effects were initially recognised by their distinc-

tive phenotypic frequency arrays sharply clinally de-

marcated from neighbouring areas (Cain & Currey, 1963)

and were subsequently observed for allozymic frequen-

cies (Ochman et al., 1983; Johnson et al., 1984). Area

effects have been correlated with the rapid expansion of

relict populations (Cameron & Dillon, 1984; Ochman et

al., 1983; Johnson et al., 1984). They were initially pre-

sumed to be stable characteristics of essentially contin-

uous populations, leading White (1978) to entertain the

possibility that they might be involved in parapatric spe-

ciation. This is doubtful for Cepaea, at least, given that

the genus contains only four species (Gould & Woodruff,

1990). Conversely, Clarke and Murray (1969) considered

THE NAUTILUS, Supplement 2

parapatric speciation associated with area effects was a

likely cause of distribution patterns in local isolates and

semispecies of the seven species of Partula. Although this

remains a possible hypothesis (Murray & Clarke, 1980)

confirmation has been hindered by the finding that, de-

spite substantial intra-specific variability, electrophoretic

divergence between reproductively-isolated taxa is low

(Johnson, 1977; Johnson et al., 1986a). One critical ques-

tion regarding population differentiation can, however,

be addressed using electrophoretic data. The studies of

Johnson et al. (1986b) on allozymic variation suggest that,

rather than deriving from multiple invasions, the fauna

on Moorea evolved as an endemic radiation.

Partula is a recent invader of the Society Islands, prob-

ably arriving no more than 2.5 million years ago (Johnson

et al., 1986b). This contrasts with the apparent antiquity

of C. nemoralis which can be distinguished from its sister

C. hortensis in fossil beds at least 10 million years old

(Lamotte, 1951). It is not surprising, then, that the causes

of area effects, and their phylogenetic consequences,

should differ between the two genera. The Wilsons Prom-

ontory Fluvidona exhibit a mixture of characteristics.

The fauna is speciose, at least for such a small area, of

probable ancient origin and subject to range expansion

and contraction. In contrast to Cepaea, these changes

have encouraged speciation. In contrast to Partula, this

has probably been allopatric.

Speciation and Gene Flow in Lake Eyre and Dalhousie

Springs

It is very difficult to predict what amount of gene flow

would permit speciation because of the interdependence

of biological and current and historical abiotic factors.

This can be illustrated by a number of examples. Firstly,

the Dalhousie Springs globular and pupiform snails are

distinct species, as judged by nearly-fixed differences in

wide sympatry. They are very closely related to each

other and have no known close relatives. In situ diver-

gence would be paradoxical if the current high levels of

gene flow within these species reflect those applying his-

torically. Comparisons of F. zeidleri with the allopatric

pair of sister species F. accepta and F. aquatica gives a

second example of this type. As judged by Fg, values,

gene flow levels in F. zeidleri and F. aquatica are cur-

rently almost identical and very low. Why should the

evolutionary fate of the ancestor of F. accepta and F.

aquatica differ from that of F. zeidleri? Spatial or tem-

poral local factors must have had a significant cladoge-

netic impact in this case.

The evolution of new species in Partula apparently

reflects the successive west to east appearance of new

land masses in the archipelago-wide basis, with no species

being found on more than one island (Johnson et al.,

1986a). We expected a contrasting pattern in the Lake

Eyre hydrobiids, owing to the potential confounding of

geographic proximity with sporadic spring appearance.

This was not observed, however, with almost all major

genetic groups being definable by an appropriate north-

D. J. Colgan and W. F. Ponder, 1994

south division. Only in F. zeidleri and F. billakalina are

there populations which are more closely related to dis-

tant areas than to their neighbours. This suggests that

springs are colonised from relatively local sources as they

arise, minimising the role of long-distance gene flow

caused by factors such as bird transport.

Gene Flow Estimation by Fs, or p(1)

Two recent studies have suggested that the private alleles

model (Slatkin, 1985a) is not as useful an estimator of

gene flow as Fs; (Waples, 1987; Johnson et al., 1988).

Johnson et al. (1988) compared the two approaches by

relating them to direct estimates of gene flow in Partula.

The private allele approach tended to give a higher es-

timate of interpopulation migration than did the F-sta-

tistics approach, which gave values nearer to the direct

estimates. This is not always the case in our investigations;

Nm<(p(1)) is higher than Nm(F7) in eight of fifteen com-

parisons using the overall data, eleven (of fifteen) at the

first level hierarchical pooling, and eight (of ten) at the

second hierarchical pooling. Waples’ (1987) arguments

against the general utility of the private alleles approach

rest on the inconsistency of its estimates of gene flow

with known larval dispersal patterns in ten species of

shore fishes. In the hydrobiid data, too, there are notable

inconsistencies in the estimates. For instance, Nm(p(1))

for the population by population migration rate in the

MPI 4 genetic species is the highest of the four Wilsons

Promontory Fluvidona, yet in all but one other estimate,

including both pooled Nm(p(1)) comparisons and all

Nm(Fz), this species has the lowest estimated gene flow.

The private alleles approach also gives divergent esti-

mates of gene flow in F. aquatica and F. zeidleri while

the estimates for these species from the Fs; approach are

highly concordant.

There are several possible reasons why the private

alleles model may not reflect population structure as ac-

curately as the Fs; approach. Firstly, the average fre-

quency of private alleles (p(1)) may be determined from

too few observations (Waples, 1987; Johnson et al., 1988).

The number of private alleles in our observations mainly

exceeds the figure of 20, sufficient to obviate sample-size

effects (Slatkin, 1985a). This is so for all three calculations

(population by population and both poolings) for the

Wilsons Promontory MPI 4 genetic species, F. zeidleri,

F. aquatica, F. variabilis and T. punicea. Sample size

problems can also arise if there are too few populations

and this may apply to our analyses in which data were

variously pooled. Particularly, the very high estimates of

Nm(p(1)) in Dalhousie Springs data pooled into less than

eight samples may be due to such effects although Slatkin

(1985a) considered five populations sufficient to provide

a good estimate.

The present data suggest that estimation problems may

also be caused where there are too many samples. There

are numerous instances in all three present studies of

alleles which are found in only a small geographic range.

Such a range, be it the length of a tributary or a small

Page 35

spring group, may represent the true neighbourhood size

for the population. Too intensive sampling might obscure

this, inflating the estimate of Nm. The impact of such

effects on p(1) indicates that for this approach to be

successful, there must be a fortuitous match between the

scale of sampling, the biological scale of effective pop-

ulation boundaries and inter-population migration. Anal-

ysis of gene flow using the conditional frequency of all

alleles would not be affected to anything like the same

extent by the intensity of sampling. Consequently we

suggest that an analytic model allowing information from

all alleles to provide a numerical estimate of Nm would

be more useful than current approaches.

Waples (1987) mentions some other difficulties with

the private alleles approach, including the non-linearity

of the estimator when Nm > 10 or Nm < 0.1 and the

possibility that uniform selection may bias the estimates

if Nm < 1] (Slatkin, 1985a). Estimation of gene flow based

on Fs; may also be biased by the failure of the assumption

that selection is negligible (Wright, 1951; Waples, 1987;

Johnson et al., 1988; Porter, 1990). To date, however,

we have not detected significant selective differentials in

our studies of hydrobiids.

Despite the apparently poorer performance of the pri-

vate alleles estimates compared to the use of F-statistics,

they are easy to compute and should be included in

investigations of gene flow for comparative purposes.

More weight should be given to Fs; values when grossly

divergent estimates of migration rates are obtained from

the two approaches. Yet such divergences should also be

taken as a signal that there has been significant distur-

bance in the evolutionarily recent past - or that sampling

does not match the scale of population structure.

ACKNOWLEDGMENTS

We thank Gerard Clark, Peter Eggler and Themo Terzis

for performing the electrophoresis and collection assis-

tance, and Janet Waterhouse, David MacIntosh, Jimmy

and Hazel Ronay, Des Beechey and Roger De Keyzer

for collection assistance. Alison Miller prepared the fig-

ures. We thank Professor M. Johnson, and two anony-

mous reviewers for attentive reading and criticism of the

manuscript. This work was largely supported by grants

from the Australian Research Council and the NPWS

Endangered Species Program.

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Page 39

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Page 40

Appendix 2. Hierarchical sample structure analysed for var-

ious hydrobiid species. The highest hierarchical levels are writ-

ten flush to the left margin of each column. Lower levels are

successively indented. Spring groups and watersheds are iden-

tified in figures 1 to 3. The average number of specimens scored

for each locus is given after the sample designations.

Wilsons Promontory Fluvidona Hierarchy: Catchment-Stream-

Site. ‘MAIN’ indicates the principal stream of the catchment,

‘ONE’, ‘TWO’, etc., the tributaries. Sites within catchments

are numbered, approximately, clockwise.

Straight-sided

WHISKY CREEK

LOWER

WCl 12.64

8.36

12.09

8.27

11.41

SQUEAKY CREEK

MAIN

SC2

FRASER CREEK

MAIN

FC1

GROWLER CREEK

MAIN

GC10

Convex MP13

GROWLER CREEK

MAIN

GCl12

FIVE

GC13

FRASER CREEK

MAIN

FC3

ROARING MEG

MAIN

RM1

RM3

ONE

RM2

TWO

RM4

FIRST BRIDGE CREEK

MAIN

FBI

PICNIC CREEK

MAIN

PCl

7.09

7.99

7.27

7.00

7.04

8.54

5.27

13.64

7.04

7.32

Appendix 2. Continued.

FRESHWATER CREEK

TWO

FW3

WATERLOO BAY

MAIN

WBI

WB2

Convex MP14

WHISKY CREEK

MAIN

TIDAL RIVER

ONE

TR4

TRS

THREE

TR7

TR8

FOUR

TRO

FIVE

TRI

TRIO

TWO

TR2

SIX

TR6

GROWLER CREEK

MAIN

GC21

ONE

GC16

TWO

GC6

THREE

GC4

GC5

BLACKFISH CREEK

ONE

BC4

TWO

BC6

THREE

BC8

THE NAUTILUS, Supplement 2

6.41

7.09

16.09

13.55

12.95

12.99

13.95

13.90

27.95

38.45

8.63

8.36

7.63

8.00

8.09

8.81

8.63

8.36

11.41

8.96

7.93

7.82

7.91

5.91

7.45

D. J. Colgan and W. F. Ponder, 1994 Page 41

Appendix 2. Continued. Appendix 2. Continued.

SQUEAKY CREEK DAVENPORT SPRINGS

MAIN DS4 13.92

SC2 7.36 DS5 10.38

D :

ONE S6 13.62

SC3 7.36 eet. HILL

15.42

Convex MPI5 HH8 10.38

CHINAMANS CREEK HH9 15.38

MAIN HH10 10.46

CCl ; 15.72 HH11 10.46

DARBY RIVER Hd ee

MAIN F. aquatica

DR2 14.50 MIDDEE

ONE ei hs 9.70

DR3 13.96 BC15 9.85

TWO BC16 9.85

DR4 14.64 COWARD/KEWSON

WHISKY CREEK CS19 9.81

MAIN ES20 9.15

ES21 O70

WCl 12.55 ey 7.54

WC2 10.00

Wwc4 11.64 JS28 9.73

WC5 11.64 E29 oo

TIDAL RIVER BERESFORD SPRINGS

MAIN BS22 9.69

TRI 10.72 STRANGWAYS SPRINGS

GROWLER CREEK ae ae

MAIN :

GC25 3.34 NORTE

IDE SPRIN

FRESHWATER CREEK OUPre.S i

OS25 8.85

MAIN TM26 9.00

FW 7.0

: FREELING SPRINGS

FRASER CREEK FR31 10.73

MAIN FR32 9.73

MNI a8 F. billakalina

ONE BILLK

FC1 7.09 BK18 7.92

SQUEAKY CREEK STRANGWAYS

MAIN SS24 8.00

SCl 14.28 $S30 9.13

Lake Eyre Hydrobiidae Hierarchy: Region-Spring group-Site. F. variabilis

Samples are identified by spring group initials and a number SOUTH

indicating south-north order in the entire Lake Eyre collec- WELCOME SPRINGS

tions. WS2 9.80

F. accepta DAVENPORT SPRINGS

WELCOME SPRINGS DS6 8.60

WS1 15.38

WS? 10.38 MIDDLE

WS3 15.38 BLANCHE CUP

BC13 9.70

BC14 10.44

BC15 10.20

BC16 7.92

Page 42

Appendix 2. Continued.

COWARD/KEWSON

CSA 7.92 DS4 9.00

CS19 8.00 DS5 8.92

ES20 8.56 DS6 8.00

ES21 10.08

KH97 8.44 HERMIT HILL

JS28 10.20 HH7 8.00

JE29 7.80 HH8 8.00

HH10 7.96

BERESFORD SPRINGS HH12 aD

BS22 8.32

WA23 8.20 OEE

BLANCHE CUP

NOU BC13 8.00

OUTSIDE SPRINGS BCI5 AOS

Soe ae COWARD/KEWSON

/ CS19 7.38

FREELING SPRINGS S20 788

FR31 7.79 ES21 7.92

FR382 7.96 KH27 7.88

F. zeidleri ae oe

SOUTH es

HERMIT SPRINGS T. smithi

HH8 3.50 MIDDLE

so BLANCHE OU a

BLANCHE CUP r

BC14 10.25 BK18 16.89

COWARD/KEWSON BERESFORD SPRINGS

CS17 10.25 BS22 10.22

CS19 8.75 STRANGWAYS SPRINGS

ES20 10.21 Seay 13.27

ES21 9.96 SS30 9.22

KH27 7.88

JS28 10.17 NORTH

JE29 8.33 OUTSIDE SPRINGS

BILLAKALINA OS25 15.33

BERESFORD SPRINGS IP, antineie

BS22 iorae OUTSIDE SPRINGS

WA23 10.25 OS25 8.44

STRANGWAYS SPRINGS FREELING SPRINGS

$S24 10.09 FR31 13.61

NORTH FR32 11.56

OUTSIDE SPRINGS Dalhousie Springs Hydrobiidae Hierarchy: Spring group-Sub-

TM26 8.88 group-Site. Samples marked with a “p” are from the pool of

large springs and those with “o” from the outflow.

FREELING SPRINGS @lawalan

FR32 8.79 obular

5 A ONE Al 6.64

T. punicea A3 8.57

SOUTH A8 19.57

WELCOME SPRINGS B ONE Bl 11.48

WS! 8.00 C A Calp 49.50

WS3 9.46 Calo 37.07

Calo 28.39

Calo 33.54

CaQ 32.25

THE NAUTILUS, Supplement 2

Appendix 2. Continued.

DAVENPORT SPRINGS

D. J. Colgan and W. F. Ponder, 1994 Page 43

Appendix 2. Continued. Appendix 2. Continued.

B Cb2 6.93 D A Dal 6.00

Cb2a 5.93 Da2 17.64

Cb2b 6.29 Da3 11.75

c Cel 6.07 B Dbl 6.00

Cc3 6.50 Db2 9.79

D Cdlp 7.40 Db4 5.96

Cdlp 7.00 E A E5 23.21

Cdlo 4.32 B El 19.85

Cdlo 7.00 E2 9.21

Cd2 14.25 ETa 18.07

Cd8 Sl E8 21.93

Pupiform F ONE Fl 20.04

A ONE Al 18.89 F2 17.89

AQ 21.29 G ONE Ga2 26.07

AS 6.11 Ga8 33.14

A6 17.82 Ga4 15.00

A8 34.11 Ga6a 6.39

B ONE Bl 8.86 Ga6b 14.07

B2 9.79 H ONE Hl 6.96

Cc A Ca2 29.79 TWO H3 17.75

Ca3 26.29 Fluvidona-like

oe ie © Cdil 4.16

ala

Ca7b 30.71 . oe oe

Ca8 17.79

Cal2 30.18 F F9 4.16

Cal3 28.25 G Gal 4.16

B Cb4 8.21 Ga2o 4.16

Cb5o 6.00 Ga6 4.16

Cb5p 17.86

C Cel 6.43

Cc4 16.43

Cc8 8.32

D Cdlp 6.96

Cd3 5.61

Cd5 5.43

Cd9 6.36

THE NAUTILUS, Supplement 2:44-50, 1994

Page 44

Allozyme Cladistics in Malacology: Why and How?

Kenneth C. Emberton

Department of Malacology

Academy of Natural Sciences of

Philadelphia

1900 Benjamin Franklin Parkway

Philadelphia, PA 19103-1195, USA

ABSTRACT

A hypothetical but plausible data set is introduced for which

Mickevich and Mitter’s (1981, 1983) qualitative-coding, min-

imum-turnover cladistic (= discrete parsimony) method ac-

curately reconstructs phylogeny, whether rare alleles are de-

tected or not, but for which both the UPGMA distance method

and a hand-calculated application of Swofford and Berlocher’s

(1987) frequency-parsimony method give incorrect phyloge-

nies. Mickevich and Mitter’s (1981, 1983) method is outlined

and demonstrated. When applying this method to 20 polygyrid

genera using Hennig86 (Farris, 1988), two problems arose and

were circumvented. First, allelic combinations occurred in

complexly interrelated sets (interim solution: treat such sets as

single character-states); and second, alternative character-state

trees existed for each locus (solution: binary-code each alter-

native, then weight by the reciprocal of the number of alter-

natives). Cladistic analysis of the polygyrid-genera allozyme

data (Emberton, 1994) ordered yielded the same topology as,

but higher resolution than, when run unordered.

Key words: allozymes, phylogenetics, cladistics, discrete par-

simony, distance methods, frequency-parsimony, ordered vs.

unordered data, Gastropoda Polygyridae.

INTRODUCTION

Allozyme data remain among the easiest and cheapest

to obtain for molecular systematics (Richardson et al.,

1986; Hillis & Moritz, 1990). Despite the current revo-

lution in nucleic-acid sequencing (see other papers in

this volume), allozymes may continue to play a major

role in molluscan systematics in many laboratories

throughout the world, for many years to come.

Of the two discrete ways to use allozyme data for

systematics (Sarich, 1977), population genetics has dom-

inated in molluscan studies (Berger, 1983; Cain, 1983;

Johnson et al., 1988; Hillis, 1989; Woodruff, 1989; Wood-

ruff & Solem, 1990) while phylogenetic reconstruction

has been less common. This paper deals only with phy-

logenetic reconstruction.

There are three main approaches to phylogenetic re-

construction using allozymes (Buth, 1984; Swofford &

Berlocher, 1987): distance methods (Sneath & Sokal, 1978;

Farris, 1972), cladistics (= discrete parsimony = phy-

logenetic but not taxonomic aspects of cladistics) (Hen-

nig, 1966; Wiley, 1981; Brooks & McLennan, 1991; Har-

vey & Pagel, 1991), and frequency-parsimony (Swofford

& Berlocher, 1987). Of these, distance methods have been

by far the most commonly used in molluscan systematics

(e.g. Davis et al., 1981; Johnson et al., 1986; Emberton,

1988), whereas cladistics has been relatively uncommon

(Emberton, 1988, 1991; Hoeh, 1990) and frequency-par-

simony remains untried. Which of these three is the most

appropriate application of allozyme data to phylogenetic

reconstruction? What is the best method? Does this meth-

od hold up even when rare alleles are undetected? Is this

method practical? What are its pitfalls, and how can

they be avoided?

The purpose of this paper is to begin to address these

questions by (1) introducing a hypothetical case of allo-

zyme evolution for which only a cladistic method, and

neither UPGMA (a distance method) nor frequency-par-

simony (as understood and hand-calculated by the pres-

ent author), accurately reconstructs phylogeny, both with

and without detection of rare alleles; (2) explaining and

demonstrating Mickevich & Mitter’s (1981, 1983) qual-

itative-coding, minimum-turnover cladistic method; and

(3) documenting how this method was applied, using

Hennig86 programs (Farris, 1988), to a complex mala-

cological data set (Emberton, 1994).

MATERIALS AND METHODS

The hypothetical phylogeny (Figure 1) consists of an

outgroup (out) and three taxa (A, B, and C) with the tree

topology: out(A(B,C)). The devised allozyme data from

this phylogeny (Figure 1) consist of three loci (locus 1,

locus 2 and locus 3), each of which has three alleles (a,

b, and c). In all three loci the designated course of evo-

lution was from allele a to allele b, passing through the

intermediate stage of heterozygosity ab.

In locus 1, the outgroup is fixed for a, taxon A is

heterozygous for ab, and taxon B is fixed for b; taxon C

has evolved further to acquire a third allele (c), for which

it is heterozygous (bc). Locus 2 in this hypothetical case

K. C. Emberton, 1994

Page 45

Allele Frequencies

a |1.00 0.05 - -

Locus 1 b = 0.95 1.00 0.05

c = = = 0.95

a |1.00 0.05 - -

Locus 2 b - 0.95 0.05 1.00

c - = 0.95 =

a {1.00 0.05 - 0.95

Locus 3 b — 0.05 1.00 0.05

c - 0.90 - -

Figure 1. Hypothetical phylogeny and allozyme frequencies

for three loci frequencies for three loci. See text for explanation.

is identical to locus 1, except that allele c is acquired by

taxon B rather than by taxon C. Locus 8 differs in that

allele c is acquired only by taxon A, and taxon C partially

reverts to allele a. The frequencies of alleles are shown

in Figure 1, and range from 0.05 to 1.00.

For a representative distance-method analysis of this

hypothetical phylogeny and allozyme-evolution pattern,

unweighted pair group, mathematical averaging

(UPGMA) was used (Sneath & Sokal, 1973). This method

can be applied to any genetic-distance matrix; the index

of genetic distance chosen here was that of Prevosti (see

Wright, 1978) because of its simplicity of calculation, its

UPGMA from Frequency Cladistics:

Prevosti Dist. Parsimony Min. Turnover

out C A B out A B Cc out A B Cc

kaa] [iss

Locus 1

out B A G out A B Cc out A B Cc

fie hes

Locus 2

out C A B out C A B out A B (e

jel

Locus 3 US

out B A c out C A B out A B

Loci 1+2+3

Figure 2. Performance tests of three different methods of phy-

logenetic inference, analysing the hypothetical data set in Fig-

ure 1. See text for details.

UPGMA from Frequency Cladistics:

Prevosti Dist. Parsimony Min. Turnover

out A B c out A B Cc out A B Cc

[ea

Locus 1

out B A Cc out A B Cc out A B Cc

Lo LJ

Locus 2

out C A B is © A B out A B Cc

[ EA LI

Locus 3 ] L

out C A B out A B Cc

(three LJ

Loci 1+2+3 equal al-

ternatives)

Figure 3. Same as Figure 2, but after deleting allelic occur-

rences at frequencies of 0.05.

meeting of the triangle-equality criterion, and its simi-

larity in performance to the preferred—both theoreti-

cally and empirically—Cavalli-Sforza and Edwards arc

and arc-chord indices (see Wright, 1978). It must be

emphasized that UPGMA, although commonly used, is

well known to be highly prone to inaccuracies when

evolutionary rates differ among lineages. A fuller and

fairer test of distance methods—beyond the scope of this

paper—would have to include neighbor joining and oth-

er methods that do not assume constancy of evolution in

all lineages.

Application of frequency-parsimony attempted to fol-

low Swofford and Berlocher (1987), analyzing the data

by hand rather than using the FREQPARS program of

Swofford (1988). According to the present author's un-

derstanding, the frequency-parsimony method (Swof-

ford & Berlocher, 1987) finds a set of hypothetical an-

cestors that minimizes the total amount of change in all

alleleic frequencies; there may be more than one set of

hypothetical ancestors—in such cases, hypothetical an-

cestors were chosen as identical to extant taxa whenever

possible.

Cladistic (= discrete-parsimony) analysis treated the

locus as character, allelic combinations as character-states,

and heterozygotes as evolutionarily intermediate be-

tween homozygotes for the same alleles (qualitative cod-

ing, minimum turnover model of Mickevich & Mitter,

1981, 1983; see below). This is a favored method of

cladistic treatment of allozyme data (Buth, 1984), but a

fuller evaluation would also have to consider transmodal

theories as outlined by Mickevich and Weller (1990).

Each of these three methods of phylogeny reconstruc-

tion was applied four times: to locus 1, to locus 2, to locus

3, and to all three loci combined. The entire analysis was

then repeated under the assumption that rare alleles were

Page 46

out A B Cc

a [2-00 0.05 - S

Locus 1 b | = 0.95 1.00 0.05

(oe = = = 0.95

a |1.00 0.05 - -

Locus 2 b = 0.95 0.05 1.00

@ 2 0.95 -

a ab b b

a --> ab --> b

Loci 1, 2 ab --> b

out A

a --> ab

Figure 4. Application of cladistic steps 1-5 (see text) to Figure

1’s loci 1 and 2. See text for explanation.

undetected, i.e. after deleting all allelic occurrences of

frequency 0.05. All computations were by hand.

To explain and demonstrate Mickevich and Mitter’s

(1981, 1983) qualitative-coding, minimum-turnover cla-

distic method, the method was broken down into easy-

to-follow steps, with a worked-through example using

the hypothetical data set (Figure 1).

This method was applied, using Hennig86 programs

(Farris, 1988), to a data set from 20 genera of polygyrid

land snails (Gastropoda: Pulmonata: Stylommatophora),

as part of a broad-based phylogenetic analysis that also

incorporated behavior and reproductive anatomy (Em-

berton, 1994). The data consisted of eight cladistically

informative loci whose allelic variation was classified into

29 character states. Hennig86 programs were used be-

cause Platnick’s (1989) empirical tests found them su-

perior to any other programs then available in finding

the most parsimonious cladograms from real data sets.

Current PAUP programs, however, may perform more

accurately than in the past, and they would probably be

more flexible in dealing with the polygyrid data set (see

below).

RESULTS

Figure 2 shows results of the three methods applied to

the data of Figure 1. UPGMA gave the incorrect phy-

logeny for each of the three loci, as well as for combined

loci. Frequency-parsimony (as interpreted by the present

author) gave the correct phylogeny for loci 1 and 2, but

the incorrect phylogeny both for locus 8 and for all three

loci combined. The cladistic method, on the other hand,

always gave the correct phylogeny, although with in-

complete resolution for locus 3, in which taxa A, B, and

C appear in a trichotomy.

Deleting rare alleles gave similar results, but with less

resolution overall (Figure 3). Thus UPGMA produced

THE NAUTILUS, Supplement 2

out A B (eo

a |1.00 0.05 - 0.95

Locus 3 b - 0.05 1.00 0.05

Cc > 0.90 = =

a ab b ab

a --> ab --> b

out A B Cc

= |

a --> ab

Locus 3

Figure 5. Application of cladistic steps 1-5 (see text) to Figure

1’s locus 3. See text for explanation.

the incorrect phylogeny for all three loci, and gave three

equal alternative phylogenies for the combined loci. Fre-

quency parsimony (as interpreted by the present author)

was correct for locus 2, but gave incorrect results for loci

1 and 3 and for combined loci. The cladistic method

gave topologies that were incorrect for locus 1, correct

and resolved for locust 2, and correct but incompletely

resolved (with a trichotomy for taxa A, B, and C) for

both locus 3 and for the combined loci. Thus the cladistic

method was the only one of the three to accurately re-

construct phylogeny from the hypothetical data set,

whether rare alleles were detected or not.

The qualitative coding, minimum turnover model

(Mickevich & Mitter, 1981, 1983; Buth, 1984) can be

outlined in six steps:

1. Treat each locus as a character.

2. Delete alleles found in only one taxon (autapo-

morphies) (although it is not clear whether Mick-

evich and Mitter are strong advocates of this par-

ticular practice).

3. Treat each allelic combination as a character state,

ignoring frequencies (qualitative coding).

4, Order character states into character-state trees that

minimize the total number of allelic changes (min-

imum-turnover model).

5. Root character-state trees by outgroup comparison.

6. Combine all character-state trees using the prin-

ciple of parsimony (a computer program is usually

required).

out A B |

Ll 3b --> 3ab (reversal)

= lab --> 1b

Loci 1+2+3 mm 2ab --> 2b

3ab --> 3b

mm ila --> lab

mm 2a --> 2ab

3a --> 3ab

Figure 6. Application of cladistic step 6 (see text) to character-

state trees of Figures 4 and 5. See text for explanation.

K. C. Emberton, 1994

MPI 100/100

3 100/102

99/100

99/99

4 99/102 a

MPI 102/104 a MPI 101/101

2 4

\ 4

MPI 102/102

jal

Figure 7. Detected allelic character states in the MPI locus

among 20 genera of polygyrid snails, with hypothesized char-

acter-state assignments and transformations (from Emberton,

in review).

These steps are demonstrated for the hypothetical phy-

logeny in Figures 4-6. Figure 4 shows loci 1 and 2, each

of which yields the same cladogram, and each of which

is treated separately (step 1). Since allele c occurs in only

one taxon, it is deleted as a phylogenetically uninform-

ative autapomorphy (step 2). This leaves three allelic

combinations (a, b, and ab), each of which is treated as

a single character state, regardless of allelic frequencies

(step 3). Thus taxa B and C are scored equally for char-

acter-state b, even though this allele occurs at frequency

1.00 in taxon B and at frequency 0.05 in taxon C (Figure

4). Ordering these three character states by the mini-

mum-turnover model (step 4) results in the order b <-

> ab <-> a. This order is more parsimonious regarding

allelic changes (i.e., turnover) than either alternative (i.e.,

b <-> a <-> abora <-> b <-> ab). Rooting this

ordered character-state tree (a linear transformation se-

ries in this case) is done by outgroup comparison (step

5). The outgroup has character state a, which is therefore

hypothesized as plesiomorphic. The rooted character-

state tree, therefore, is a -> ab —> b for both locus 1

and locus 2. Each of these two loci has the same single-

locus cladogram shown at the bottom of Figure 4.

Cladistic treatment of hypothetical locus 3 is similar

and is outlined in Figure 5. The locus is treated inde-

pendently (step 1); the autapomorphy for allele c in taxa

A is deleted (step 2); the character states are defined as

allelic combinations a, b, and ab (step 3), which are

ordered and rooted in the tree a -> ab —> b (steps 8

and 4). The resulting single-locus cladogram (bottom of

Figure 5) also puts taxa A, B, and C in a monophyletic

clade defined by the synapomorphic transition a —> ab.

This cladogram differs from those for loci 1 and 2 (Figure

4), however, in that it gives no further resolution: the

transition ab -> b shows up only as an autapomorphy

of taxon B.

Step 6 consists of combining the single-locus character-

state trees or cladograms (Figures 4 and 5) in the most

parsimonious way (i.e., involving the least amount of

overall turnover among character states within their re-

spective loci). This results in the cladogram of Figure 6,

Page 47

which is a perfectly accurate reconstruction of the orig-

inal hypothetical phylogeny (Figure 1).

The preceding example was simple enough to be per-

formed by hand. For complex data sets, the program

Hennig86 (Farris, 1988) has been recommended (Plat-

nick, 1989). For encoding branching character-state trees

for Hennig86 analysis, binary coding is needed. The pres-

ent author finds it useful to think of binary coding as a

method of encoding not by character state but by trans-

formation (between two character states). To encode the

hypothetical data, each transformation is numbered as

follows:

Transformation

Locus Transformation Number

] a— ab 0

1 ab > b 1

2 a — ab 2

2 ab > b 3

8 a — ab 4

3 ab > b 5

The following taxon-by-transformation matrix, then,

is submitted to Hennig86. Each taxon is scored for the

occurrence (1) or non-occurrence (0) of each transfor-

mation in the lineage that produced that taxon.

Transformation

ie OC hla oe 2y es

out 0 0 0 0 0 0

A ] 0 ] 0) 1 0

B 1 1 1 1 1 1

C 1 Il ] a a 0

Given this matrix, Hennig86 produces the correct clado-

gram shown in Figure 6.

Applying this six-step method of allozyme cladistics

to 20 polygyrid genera (Emberton, 1994) resulted in

problems in steps 4 and 6. In step 4 (ordering allelic

combinations into character-state trees), there was often

a problem of a confusingly large number of allelic com-

binations, many of which occurred in complexly inter-

related sets. For example, the mannose phosphate isom-

erase locus (MPI) yielded five alleles (99, 100, 101, 102,

and 104, referring to their relative positions in mm on

the electrophoretic gels). These alleles occurred in eight

allelic combinations, which are shown in Figure 7. Or-

dering these eight combinations as individual character

states would produce extreme complexity and, given the

distributions of these combinations among taxa (Ember-

ton, 1994), would yield apparently little additional phy-

logenetic information.

The ultimate solution to this problem seems to require

writing a computer program to perform the minimum-

turnover algorithm, regardless of the number of allelic

combinations. An interim procedure, however, is to treat

such interrelated sets as single character states. For the

MPI example, this groups five interrelated allelic com-

binations as a single character state (Figure 7: character

state .3). For other examples, see Emberton (1994).

Page 48

77 78 86 87

17.1 —17.2 —> 17.3 17.1 —>17.3 —>17.2

79) oe

17.4 17.4

80 81 89 90

17.1 —>—17.2 —> 17.3 17.1 —>17.3 —> 17.2

a2 A 91 &

17.4 17.4

83 84 92 93

17.1 —> 17.2 —> 17.3 17.1 —> 17.3 —> 17.2

a5 A 94

17.4 17.4

Weights for Transitions 77-94 = 1/6

Figure 8. Alternative character-state trees derived from Figure

7. Numbering of character states and transformations as in

Emberton (in review).

Another problem that arose in applying step 6 (com-

bining all character-state trees using parsimony) was that

of alternative character-state trees. For example, in the

MPI locus (Figure 7), state .3 has an equal probability

(according to the minimum-turnover model: step 5) of

being derived from states .1 or .2, but not from state .4.

Likewise, state .4 has an equal probability of derivation

from any of the three other states. To encode all these

possible transformations would unduly weight infor-

mation-poor loci over information-rich loci.

A solution devised by Emberton (1994) is to use all

transformations in all alternative character-state trees,

but to weight them by the reciprocal of the number of

alternatives. For example, the multiple arrows among

MPI character states .1, .2, .3, and .4 (Figure 7) result

in six alternative character-state trees that are shown in

Figure 8. Each of these trees was encoded for Hennig86

analysis (using the transformation-coding method de-

scribed above, producing transformations numbers 77-

94 as used in the complete analysis of polygyrid genera:

Emberton, 1994). Before analysis, however, transfor-

mations 77-94 were all assigned a relative weight of 1/

6 (using the ccode command of Hennig86). Transfor-

mations in other characters received other weights, de-

pending on each character’s total number of alternative

character-state trees.

Another point needs to be made respecting step 4

(ordering allelic combinations into character-state trees).

Although ordering of character states is considered by

many cladists to be a central tenet of phylogenetic sys-

tematics (Hennig, 1966; Brooks & McLennan, 1991; Har-

vey & Pagel, 1991; Wilkinson, 1992), Hauser & Presch

(1991; Presch, 1992) and others maintain that, at the

very least, ordered data should also be analyzed unor-

dered to determine the robustness of the cladogram to

hypotheses of character-state order. This procedure ap-

plied to the polygyrid-genera allozyme data set (Em-

berton, 1994), yielded the comparison shown in Figure

9. The cladogram for ordered allozyme data has the same

THE NAUTILUS, Supplement 2

out WN XTVC OAFESYGDRPIMK

TT LTE

Allozymes unordered

out WNXTVC OAFESYGDRPIMK

{Ls TLL

Figure 9. Cladograms from allozyme data on 20 polygyrid

genera (from Emberton, in review).

Allozymes ordered

topology as that for unordered data, but with greater

resolution (an increase from four nodes to eight nodes).

DISCUSSION

The present author’s obvious preference for discrete-

parsimony analysis of allozyme data (= allozyme cla-

distics) is mildly supported by the evaluation outlined in

Figs. 1-3, which demonstrates a hypothetical case in

which cladistics successfully reconstructs the true phy-

logeny—even when rare alleles are undetected—while both

UPGMA and frequency parsimony (as interpreted and

hand-calculated by the present author) fail. Further eval-

uations using both hypothetical and real data, and using

other distance and parsimony methods, are needed to

test these results, but it seems clear at least that the

distance method of UPGMA bases phylogenetic infer-

ence on both plesiomorphic and apomorphic characters,

including autapomorphies. On first principles, therefore,

UPGMA (and, in the present author’s incompletely in-

formed opinion, other distance methods) should not be

used to reconstruct phylogeny (Harvey & Pagel, 1991;

Brooks & McLennan, 1991). Although it is true that

UPGMA and cladistics results often are congruent, such

cases only demonstrate relatively constant rates of allo-

zyme evolution within the limitations of the data set,

and do nothing to make the phylogenetic inference itself

more robust.

Frequency parsimony (Swofford & Berlocher, 1987)

depends heavily on frequencies, which can vary widely

within a taxon (e.g. Emberton, 1993), and furthermore

requires an algorithm that is very difficult to program

and costly in computer time to run. A preliminary pro-

gram is available (FREQPARS: Swofford, 1988; not used

for the present paper), but can handle only very small

data sets and often does not produce the most parsi-

monious solution(s) (Swofford, 1988; D. Lindberg, per-

sonal communication, 1992).

The practice of allozyme cladistics, as outlined above

and demonstrated in Figs. 4-6, seems logical, objective,

and empirically validated (Mickevich & Mitter, 1981,

1983; Buth, 1984). For polygyrid land-snail genera, it

yielded a phylogenetic hypothesis that was generally both

K. C. Emberton, 1994

Page 49

consistent with and complementary to a hypothesis based

on an independent anatomical data set (Emberton, 1994,

unpublished).

Polymorphisms-both in allozyme and in morpholog-

ical data— may at first seem a hindrance to cladistics. As

Mickevich and Mitter’s (1981, 1983) method points out,

however, polymorphisms can offer important clues to

character evolution, and hence to taxon evolution. Or-

dering of character states within characters may some-

times lead to error, however, so it is important to analyze

data both ordered and unordered (Hauser & Presch, 1991;

Wilkinson, 1992; Hauser, 1992). Ordering does enhance

phylogenetic resolution without changing topology among

polygyrid genera (Figure 9; Emberton, 1994), but does

not among Truncatella snail species (G. Rosenberg, per-

sonal communication) and apparently does not among

taxa in several non-molluscan data sets (Hauser & Presch,

1991). Clearly, each new data set must be evaluated in

its own right.

ACKNOWLEDGMENTS

Supported in part by N.S.F. grant BSR-87—-00198 to the

author and N.I.H. grant TMPI11373 to G. M. Davis. I

also thank Gary Rosenberg for helpful discussion, M.G.

Harasewych for inviting my participation in this sym-

posium, and Harasewych and two anonymous reviewers

for useful comments on a previous draft.

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THE NAUTILUS, Supplement 2

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THE NAUTILUS, Supplement 2:51-60, 1994

Page 51

Use of Random Amplified Polymorphic DNA (RAPD) Markers to

Assess Relationships Among Beach Clams of the Genus Donax

S. Laura Adamkewicz

Department of Biology

George Mason University

Fairfax, VA 22030, USA

M. G. Harasewych

Department of Invertebrate Zoology

National Museum of Natural History

Smithsonian Institution

Washington, DC 20560, USA

ABSTRACT

The polymerase chain reaction was used to amplify genomic

DNA from nine populations of donacid clams representing six

taxa occurring in three sympatric pairs. The randomly ampli-

fied polymorphic DNA (RAPD) markers produced by this tech-

nique successfully distinguished among all taxa. Each taxon

possessed a unique subset of markers and one member of each

sympatric pair differed from the other by several markers. The

taxa also separated clearly into two groups, one North American

and the other Caribbean. Use of RAPD markers as characters

in a cladistic analysis produced well resolved phylogenetic trees

of high consistency.

Key words: RAPD, PCR, phylogeny, biogeography, Donax.

INTRODUCTION

Comparisons of closely related species are often infor-

mative with regard to the functional biology of their

shared characters, while comparisons of sympatric con-

geners can provide insights to the selective forces and

adaptive complexes that are important in speciation

(Larson, 1989). Western Atlantic species of beach clams

in the genus Donax are particularly appropriate candi-

dates for such comparative studies. Six species or sub-

species have been described from the coastal waters of

the eastern United States, and nearly as many have been

reported from the Caribbean (Morrison, 1971). All of

these species are highly polymorphic for shell colors and

patterns, and one (Donax variabilis Say, 1822) serves as

a classic example of a hyper-variable species (Moment,

1962). Both in the western Atlantic and world-wide, Don-

ax often occur as sympatric species pairs or triplets (Ab-

bott, 1974; Ansell, 1983; Morrison, 1971) that partition

their shared habitat. The selective forces that promote

the rise and maintenance of hyper-variable polymor-

phisms are poorly understood (Allen, 1988; Owen &

Whitely, 1988) and may be clarified by comparative

studies. Furthermore, the interaction of habitat parti-

tioning and hyper-variability has been studied only in

the snail genus Cepaea (Clarke, 1960). Our long-term

goal is to investigate these questions in Donax. However,

the sympatric co-occurrences of two or more similar and

often highly polymorphic species have placed the sys-

tematic status of some of these taxa in dispute.

Morrison (1971) recognized six taxa along the Atlantic

and Gulf coasts of the United States: 1) Donax fossor

Say, 1822, which ranges from New York to North Car-

olina; 2) Donax variabilis variabilis Say, 1822 (as Donax

roemeri protracta Conrad, 1849!), which occurs from

Virginia southward along both coasts of Florida and west-

ward along the Gulf coast to Mississippi; 3) Donax par-

vulus Philippi, 1849, with a range that extends from

North Carolina to the eastern coast of Florida; 4) Donax

dorotheae Morrison, 1971, which occurs along the Gulf

coast from Florida to Louisiana; 5) Donax variabilis roe-

meri Philippi, 1849 (as Donax roemeri roemeri Philippi,

1849), which ranges from the Mississippi delta westward

along the coasts of Texas and Mexico; and 6) Donax

texasianus Philippi, 1847 with the same range as D.

variabilis roemeri. Only in the northern-most part of its

American range is Donax represented by a single species,

D. fossor. Elsewhere, species of Donax generally occur

as sympatric pairs. In the Caribbean and along the coast

of northern South America, the genus is represented by

Donax denticulatus denticulatus Linné, 1758, D. den-

ticulatus stephaniae Petuch, 1992, D. striatus Linne,

1767, and D. vellicatus Reeve, 1855, with two or three

species occurring together. Donax denticulatus is the

type species of the subgenus Chion Scopoli, 1777 (Gray,

1847).

Where species of Donax co-occur, they subdivide the

habitat in much the same way. As described by Morrison

(1971), Donax parvulus, D. dorotheae, and D. texasianus

all occupy the same habitat and are allopatric, replacing

one another along the coast, each co-occurring with Don-

ax variabilis. In every case, D. variabilis is larger, occurs

1 See Boss (1970) and Melville (1976) for details on the no-

menclature of this taxon.

Page 52

higher in the inter-tidal zone, and migrates more actively

with the tides. The other three species are much smaller,

occur at the bottom of the inter-tidal zone and spend

much of the year sub-tidally. During at least some parts

of the year, these species occur with D. variabilis and

both can be collected in the same handful of sand. This

co-occurrence, combined with morphological similarity,

has placed the status and rank of several taxa in dispute.

Abbott (1974) considered D. parvulus to be an offshore

ecological form of D. variabilis. Loesch (1957) reviewed

the names of donacid taxa reported from the Texas coast

and stated that morphological intergrades had been re-

ported between D. texasianus and what may have been

D. dorotheae near Louisiana and between D. texasianus

and D. variabilis roemeri along the Texas coast. Chanley

(1969) suggested that D. fossor represents a [temporary,

seasonal] summer extension of the range of D. variabilis.

In the Caribbean, D. vellicatus, like several of the

American taxa, remains primarily sub-tidal. Donax den-

ticulatus and D. striatus partition their habitat somewhat

differently, but the division is still based on the tendency

to migrate with the tide, as well as a preferred position

in the inter-tidal zone. Wade (1967, 1968) has observed

that, although D. denticulatus and D. striatus did some-

times occur together, D. denticulatus migrated actively

throughout the tidal cycle while D. striatus maintained

a constant position higher in the inter-tidal zone.

Historically, separations of donacid species and sub-

species have been based exclusively on shell morphology

(primarily on size, inflation [obesity], and degree of stri-

ation), which is subject to environmentally induced vari-

ation. Molecular data are often suitable for resolving

taxonomic questions of this nature where the cause of

morphological differences cannot be ascribed to either

genetic or environmental differences. The restriction of

a molecular character, either an allele in an allozyme

system or a DNA marker, to one member of a sympatric

species pair is taken as evidence of the absence of inter-

breeding between the two taxa. While molecular evi-

dence cannot confirm genetic isolation when two pop-

ulations are allopatric, it can at a minimum demonstrate

genetic divergence. A previous attempt to differentiate

between sympatric populations of D. parvulus and D.

variabilis using allozyme data yielded ambiguous results

(Nelson et al., 1993). While allele frequencies differed

between the two groups, no alleles unique to either taxon

were found. Because the allozyme data could not distin-

guish the two taxa, additional molecular markers were

sought.

The use of randomly amplified polymorphic DNA

(RAPD) markers to differentiate between closely related

individuals, populations and species was introduced in

1990 by Williams et al. and by Welsh and McClelland.

In essence, segments of genomic DNA are amplified by

the polymerase chain reaction (PCR) using a single very

short primer (9 to 11 nucleotides) whose sequence might

occur multiple times within the genome. The RAPD

amplification of genomic DNA produces a set of frag-

ments of various molecular weights, their number and

THE NAUTILUS, Supplement 2

size depending upon the number of times the primer

sequence occurs in the genome, as well as the distances

between pairs of primer sites. The RAPD technique has

already been shown to produce genetic markers for Men-

delian segregational analysis (Klein-Lankhorst et all,

1991), genetic markers to distinguish among individuals

within one population (Smith et al., 1992), genetic mark-

ers that identify cultivars within a species (Hu & Quiros,

1991), and genetic markers that discriminate among spe-

cies within a genus (Kambhampati et al., 1992).

As a necessary prelude to the long-term goal of in-

vestigating morphological polymorphisms and ecological

niche-partitioning in Donax, the present study seeks to

resolve the systematic status of several western Atlantic

donacid taxa and to discern their phylogenetic relation-

ships. Failure of the allozyme data to resolve these taxa

definitively has led us to investigate the utility of ran-

domly amplified polymorphic DNA (RAPD) markers to

distinguish between populations, subspecies and species

in the genus Donax, as well as to determine the rela-

tionships of these populations and taxa using cladistic

methodology.

MATERIALS AND METHODS

1. COLLECTION OF SPECIMENS

Donax were collected at the six locations shown on the

map in Figure 7. These collections included samples from

nine populations, representing six taxa, which are listed

in Table 1 and are further identified as follows. 1) Donax

variabilis variabilis (DVF) and 2) Donax parvula (DPF)

were collected in the spring of 1990 at Indiatlantic Beach,

on the Atlantic coast of Florida. 3) Donax variabilis roe-

meri (DVR) and 4) Donax texasianus (DTT) were col-

lected at Corpus Christi, on the Gulf coast of Texas, in

spring of 1990. 5) Donax variabilis variabilis (DVG) were

collected in 1992 at Alligator Point on the Gulf coast of

Florida. Collections were made in Jamaica in both May

and November of 1991 for 6) Donax denticulatus (DDM)

from Port Maria, a town on the northern coast of the

island, along the town’s seawall 7) Donax denticulatus

(DDN) from Negril, a town on the western side of the

island, at the Cosmos Beach Club 8) Donax denticulatus

(DDB) and 9) Donax striatus (DSB) from Black River,

a town on the southern coast of the island, at the Bridge

House Inn.

Donax were collected by sieving sand from the inter-

tidal zone of a beach. The animals were placed in plastic

bags and kept cool until they could be identified to spe-

cies, then frozen at —20° C and shipped to George Mason

University. Thereafter, clams were maintained at —60°

C until DNA was extracted. Attempts to collect Donax

fossor and D. dorotheae at their respective type localities

were unsuccessful, and these taxa are not included in the

present study. Shells of the samples used in this study

are deposited in the collections of the National Museum

of Natural History, Smithsonian Institution. Catalogue

numbers for voucher lots are listed in table 1.

S. L. Adamkewicz and M. G. Harasewych, 1994

Page 53

Table 1. Sources of the nine populations of Donax used in this study. Collecting sites are those shown on the map in figure 7.

Sample

designation Taxon

DVF Donax variabilis variabilis

DVG Donax variabilis variabilis

DVR Donax variabilis roemeri

DPF Donax parvulus

DTT Donax texasianus

DDM Donax denticulatus

DDN Donax denticulatus

DDB Donax denticulatus

DSB ' Donax striatus

2. EXTRACTION OF DNA

To avoid contamination from food organisms, only mus-

cle dissected from the foot of each clam was used to

extract DNA. Approximately 30 mg of tissue was treated

according to a protocol derived from that of Reeb and

Avise (1990). Tissue was macerated in a 1.7 ml micro-

centrifuge tube containing 400 ul TE buffer (10 mM

Tris, 1 mM EDTA, pH 7.6) for about 30 seconds with a

pestle driven by an electric drill. After adding 25 ul of

10% sodium dodecyl sulfate (SDS), the extract was in-

cubated at 65° C for 30 to 60 minutes. Next, 70 ul of 8M

potassium acetate was added, the mixture shaken, and

chilled on ice for 60 minutes. After the extract was cen-

trifuged at 14,000 x g for 10 minutes, the supernatant

was transferred to a clean tube and the pellet discarded.

The supernatant was chilled at —20° C for 2 minutes,

spun again for 10 minutes, and again transferred to a

clean tube. Next, 400 ul of chloroform and 400 ul of tris-

saturated phenol were added, the tube shaken, and cen-

trifuged for 5 minutes at 14,000 x g. The upper, aqueous

layer was transferred to a clean tube, 400 ul of chloroform

added, the tube shaken, and centrifuged for 5 minutes.

The upper, aqueous layer was again decanted to a clean

tube, treated with chloroform, and centrifuged. After

the upper layer was transferred to yet another clean tube,

Iml of cold 95% ethanol was added and mixed by gently

inverting the tube. The sample was kept at —20°C for

two minutes and centrifuged again for 10 minutes. The

supernatant was discarded and the pellet was washed

with 1 ml of 80% ethanol. After another centrifugation

for 5 minutes at 14,000 x g, the ethanol was discarded

and the pellet was dried in an incubator at 38° C for

about 30 minutes. The cleaned DNA pellet was dissolved

in 300 ul of TE buffer and kept at —20° C until needed.

This procedure yielded DNA at concentrations rang-

ing from 5 to 35 wg/ml. If initial PCR amplification

failed, the DNA was further purified with “GeneClean

II” (BIO 101 Inc., P.O. Box 2284, La Jolla, CA 92038)

after which it amplified satisfactorily.

3. PCR AMPLIFICATION OF DNA

The amplification protocol of Bowditch et al. (1993) was

used in this study. “Amplitaq’” DNA polymerase, sup-

USNM catalogue

Collecting site number

Atlantic coast of Florida 869538

Gulf coast of Florida 869539

Gulf coast of Texas 869540

Atlantic coast of Florida 869541

Gulf coast of Texas 869542

Port Maria, Jamaica 869543

Negril, Jamaica 869544

Black River, Jamaica 869545

Black River, Jamaica 869546

plied by Perkin-Elmer/Cetus at an activity of 8 units

per ul, was used at a concentration of 0.5 units per sample

(0.06 ul). The four nucleotide triphosphates were sup-

plied by Pharmacia as 100mM stocks and mixed to make

a single stock 0.25 mM for each dNTP. A special RAPD

buffer was prepared according to the recipe: 100mM

Tris, 5|00mM KCI, 19mM MgCl,, and 10 mg/ml bovine

serum albumin (not acetylated). Primers came from two

sources: 20 (designated OP-E) were from Operon Tech-

nologies Kit E and 40 (designated LMS-P) were provided

by the Laboratory for Molecular Systematics, National

Museum of Natural History, Smithsonian Institution,

where they had been synthesized.

Between 5 and 15ng of DNA from an individual clam

and 50ng of a single, short primer (10mer in all cases)

were combined in 25 ul of a reaction mixture comprised

of: 18 yl sterile distilled water, 2.5 ul] RAPD buffer, 2.5

ul deoxynucleotide mix, 1 ul primer, and 1 ul target

DNA. The reaction mix was topped with mineral oil and

placed in a Perkin-Elmer 4800 Thermocycler for 45 cy-

cles of a RAPD amplification profile as follows: dissoci-

ation of DNA for 1 minute at 94°C, annealing of primer

for 1 minute at 36°C, polymerization of DNA for 2 min-

utes at 72°C. The amplification products were loaded

onto a 1.4% agarose gel, electrophoresed in TBE buffer

(89mM Tris, 89mM Boric Acid, 2mM EDTA) and vi-

sualized with ethidium bromide. Each primer produced

a characteristic set of amplification products with sizes

ranging from 0.3 to 3.0 kilobases, which appeared as

bright bands on the agarose gels (Figure 1). Rather than

measuring distances from the origin, approximate sizes

were determined by comparison to fragments of known

size in a mixture of lambda DNA cut with HindIII and

$X174 cut with HaelII. To confirm that two bands were

identical, samples were run in adjacent lanes of a gel.

Throughout this paper, these products are referred to

interchangeably as “amplification products,’ “DNA

fragments,” or “RAPD markers.”

4. SELECTION OF PRIMERS AND MARKERS

Sixty primers were screened on a panel of 24 individuals

comprised of three clams from each of the sample pop-

ulations except D. striatus (DBS). Each primer was used

Page 54

DVF DVR DVG DTT DPF DDM DDNDSB

S-1 -

bee ere eho.

Figure 1. RAPD amplifications generated by primer OP-E18.

The horizontal bars over the gel join the three individuals from

each population that were run on each gel. Sample designations

above the bars refer to taxa and populations listed in table 1.

The letter M identifies lanes containing molecular weight stan-

dards (lambda DNA cut with HindIII + #X174 cut with HaelII).

Standard bands and sizes in kilobases are depicted to the right

of the gel.

at least twice to amplify each screening DNA. A primer

was judged to be suitable for use in this study if it met

the criteria of: 1) amplification, that is, the production

of clearly resolved DNA fragments, 2) reproducibility,

with at least one DNA fragment appearing consistently

and reproducibly in repeated assays of the same indi-

viduals, and 3) commonality, or the presence of at least

one DNA fragment in two or more populations (but not

necessarily two or more taxa). Primers that met these

requirements were not common. Approximately one

fourth of the primers tested failed to meet criterion 1,

with most of the remainder failing criterion 3. Criterion

2, reproducibility, was not a serious problem. For all of

the markers chosen, amplification of DNA from the same

individual produced the same results whether the am-

plification was repeated in separate PCR experiments or

replicated within the same PCR experiment. Identical

results were produced when amplifications were repeat-

ed using a Coy thermocycler, in which temperature

changes much more slowly than in a Perkin-Elmer ma-

chine.

THE NAUTILUS, Supplement 2

The initial screening procedure identified five primers

that produced a total of 17 RAPD markers that were

informative for the purposes of this study. These primers

and markers are described in Table 2 and representative

results are shown in Figure 1. Of the two primers from

the Laboratory for Molecular Systematics, primer LMS-

PO1 is the same as primer AP8g of Williams et al. (1990)

while primer LMS-P56 was designed and synthesized at

LMS. A total of nine individuals from each population

were assayed at least twice with each of the five primers.

Samples with similar markers were run side-by-side in

the replicate assay in order to facilitate direct compar-

isons.

5. PHYLOGENETIC ANALYSIS:

Data were analyzed and trees produced using Hennig86

version 1.5 software (Farris, 1988). The implicit enu-

meration (ie;) algorithm was used in each series of anal-

yses to insure that all shortest, equally parsimonious trees

were found.

Each RAPD marker was treated as a separate character

regardless of which primer was used to generate it or

which other bands from the same or other primers co-

occurred with it. In an initial analysis (Analysis 1), the

17 markers listed in Table 4 were scored as either absent

(0) or present (1) for each population, and a hypothetical

outgroup, scored as lacking all 17 RAPD markers (all

characters = 0), was used (for data matrix, see Appendix

1). In subsequent analyses, the markers were scored as

absent (0), polymorphic (1), i.e. present in some but not

all members of the population, or fixed (2), i.e. present

in all members of the population. In Analysis 2, this data

set was run unordered, using the same hypothetical out-

group as in Analysis 1 (data matrix in Appendix 2). A

third series of analyses used the same data matrix but,

instead of the hypothetical outgroup, each of the basal

taxa from Analysis 2 (DSB, DDN) was used in turn as

the outgroup. The arrangement of character states on

the resulting trees were examined using the Dos Equis

(xx) and xsteps tree diagnostic commands.

Table 2. DNA primers used in this study. For each primer the table shows: the sequence; the average number of DNA amplification

products detected in an individual, with the range of averages among the nine groups following in parentheses; and the sizes of

those DNA amplification products used as markers. Primers designated OP-E are from Operon Technologies Kit E and primers

designated LMS-P were provided by the Laboratory for Molecular Systematics. Those fragments followed by an asterisk (*) are

characteristic of the Caribbean taxa, while those followed by an ampersand (&) are characteristic of the Carolinian taxa. Note that,

for any given primer, the smaller fragments are always characteristic of the Carolinian taxa.

Average number of RAPD

Primer Sequence

OP-E07 5’-AGATGCAGCC

OP-E16 5'-GGTGACTGTG

OP-E18 5'-GGACTGCAGA

LMS-PO1 5’-TGGTCAGTGA

LMS-P56 5'/-AGATCTGCAG

DNA fragments

per clam (range)

Size (kb) of

useful RAPD markers

3.8 (3.14.3) 0.6 1.5

3.4 (2.6-4.3) 0.3& 0.5& 0.6% 0.9 1.1

3.0 (1.6-4.2) 0.5& 0.6* 0.9

2.8 (2.0-3.2) 0.5& 1.0* 1.2*

3.0 (2.2-3.6) 0.3& 0.6& 1.1* 1.2*

S. L. Adamkewicz and M. G. Harasewych, 1994

Page 55

Table 3. Distribution of RAPD DNA markers in May and November samples of Donax denticulatus from Port Maria, Jamaica.

As in tables 2 and 4, the RAPD marker identification designates the primer that produced the marker, the approximate size of

each marker in kilobases, and our identifying marker number. Each entry in the matrix shows the number of individuals in which

the RAPD marker was detected over the number of individuals tested (e.g., 3/9). Because Primer OP-E07 was not used with the

May sample, data from this sample were not included in table 4, which serves as the data matrix for phylogenetic analysis.

OP OP OP LMS

Primer: E16 E16 E18 PO]

Marker size

(kb): 0.9 Li 0.9 12

Marker

number: i 9 10 12

May 9/9 . 9/9 9/9 0/9

November 9/9 9/9 9/9 1/9

RESULTS

1. STABILITY OF RAPD MARKERS OVER TIME

To assess the stability of the RAPD markers used in this

study, two different samples of Donax denticulatus from

Port Maria, Jamaica, were examined, one taken in May

and the other in November of 1991. These two samples

produced identical RAPD markers with only slight dif-

ferences in frequencies between the two collections (Ta-

ble 3). The only marker not present in both samples,

marker 12 (LMS-P01/1.2kb), was the rarest, appearing

in only 3 of a total of 21 individuals assayed.

2. DISTRIBUTION OF RAPD MARKERS AMONG

POPULATIONS

Table 4 summarizes the distribution of the 17 RAPD

markers among the nine assayed populations, but does

not contain data from the May sample of Donax den-

ticulatus from Port Maria. Because the presence of two

species in the sample from Black River was not discoy-

ered until after the laboratory work was completed, these

two populations have reduced sample sizes (3 D. den-

ticulatus, 6 D. striatus).

Of the 17 RAPD markers assayed, two (markers 8 and

9), each produced by a different primer, were present

at varying frequencies in all nine populations. All three

samples of D. variabilis (DVF, DVG, DVR), including

the subspecies D. variabilis roemeri, had the same 11

markers appearing in at least one member of each pop-

ulation. Of these 11 markers, two appeared in no other

taxon. Similarly, all three populations of D. denticulatus

(DDM, DDN, DDB) shared a set of 11 markers, three

of which appeared in no other taxon. Twelve of the 17

RAPD markers were not shared between D. variabilis

(DVF, DVG,DVR) and D. denticulatus (DDM, DDN,

DDB). The three remaining taxa, each represented by a

single population, showed clear affinities with either D.

variabilis or D. denticulatus. The absence of unique

markers in these taxa was an artifact of the criteria for

primer selection (i.e.- that bands occur in at least two

sample populations). Nevertheless, Donax parvulus (DPF)

was distinguished from its sympatric congener D. var-

iabilis variabilis (DVF) by the absence of RAPD markers

LMS LMS OP OP LMS

P56 P56 E16 E18 PO1

il. 1.2 0.6 0.6 1.0

13 14 15 16 17

4/8 8/8 9/9 9/9 9/9

6/6 5/8 8/9 9/9 8/9

1 and 2, while D. texasianus (DTT) differed from its

sympatric congener D. variabilis roemeri (DVR) in lack-

ing markers 1, 2, 3, and 7. Marker 2, which was fixed in

all populations of Donax variabilis and present in no

other taxon, appears to be a diagnostic marker for this

species. The Caribbean species D. striatus (DSB) differed

from D. denticulatus (DDB) in lacking 5 RAPD markers

(10, 11, 15, 16, 17), of which two (10, 16) were fixed in

D. denticulatus. Marker 16, which occurred in all in-

dividuals of D. denticulatus tested, was unique to this

species and may be used as a diagnostic marker for this

species.

Although diagnostic markers were not identified for

some taxa, the absence of multiple RAPD markers in

one member of each sympatric pair (including markers

fixed in the other member of the sympatric pair) is taken

as evidence that these pairs do not exchange genetic

material. An empirical observation is that when primers

produced RAPD markers characteristic of both Carolin-

ian and Caribbean taxa, markers that distinguished Car-

olinian taxa were invariably shorter than markers that

were diagnostic of Caribbean taxa (Table 2). The sig-

nificance of this observation is not yet clear.

3. PHYLOGENETIC ANALYSES

An initial cladistic analysis (Analysis 1), scoring each of

the 17 RAPD markers as absent or present (regardless of

frequency) in each sample population and using a hy-

pothetical outgroup in which all characters were scored

as absent, produced a single most parsimonious tree

(length = 20, ci = 85, ri = 91) that resolved all species

level taxa but left populations and/or subspecies unre-

solved (Figure 2). Fourteen of the 17 character trans-

formations plotted unambiguously onto this tree (Figure

2). Each of the remaining three characters (markers 7,

10, 11) could either have been present in the common

ancestor of all the taxa in this study and subsequently

lost in a single taxon (Figure 2), or have arisen twice

independently (Figure 3). An analysis of character po-

larity using the out-group comparison method (Watrous

& Wheeler, 1981) indicated that the presence of markers

7, 10, and 11 is plesiomorphic, as they occur in both the

in-group and the out-group, while their loss, in each case

Page 56 THE NAUTILUS, Supplement 2

restricted to a functional in-group, is apomorphic (Fig

Saor DD od ”),

= 2 Ll tl Ss

A second analysis, scoring the RAPD markers as absent

(0), polymorphic (1) or fixed (2), and employing the same

hypothetical outgroup, produced four equally parsimo-

nious trees (length = 32, ci = 90, ri = 92) when the data

were run unordered. One tree, supported by all markers

except 8, 10, and 11, matched the topology of the tree

in Figure 8, except that all sample populations were

resolved. In the other three trees, which differed only in

the resolution of D. denticulatus populations and which

were supported by all markers except 7, 8, and 13, Donax

striatus emerged as the sister group to all remaining taxa.

The nelsen consensus tree (length = 34, ci = 85, ri = 87)

of these four trees is shown in Figure 4. Twelve of the

17 character transformations plotted uniquely onto the

consensus tree, while markers (7, 8, 10, 11, 18) could be

interpreted as evolving in several equally parsimonious

scenarios. Analyses of character polarity using the out-

group comparison method (Watrous & Wheeler, 1981)

ea nom liees ou suggest that marker 7 was fixed in the Donax ancestor,

SSS became polymorphic in the North American clade, and

eventually lost in Donax texasianus, while marker 11,

which was polymorphic in the Donax ancestor, was lost

in Donax striatus, but became fixed in Florida popula-

tions of Donax variabilis. The remaining markers could

not be mapped onto the consensus tree (Figure 4) without

reversals (markers 8, 13) or convergences (marker 10).

Only marker 8 was incompatible with all of the initial

trees.

When the data were reanalyzed using Donax striatus

as the outgroup, one most parsimonious tree (length =

28, ci =96, ri = 97), resulted (Figure 5). Likewise, when

the Black River population of Donax denticulatus, served

; = = = = = = = = as the outgroup, a single, equally parsimonious tree (length

= 28, ci =96, ri = 97), was produced (Figure 6).

All analyses that employed an intermediate character

S8e2,|2Seeeo lid state produced identical tree topologies for the Carolin-

atari eprom 2S ian samples but differed in the resolution and/or rela-

tionships of the Caribbean taxa and populations.

LMS

P56

6/6

5/9

3/3

4/6

LMS

POL

1.2

1/9

1/3

6/6

0.6

E18

0.9

9/9

2/9

9/9

3/3

E07

9/9

6/9

9/9

2/9

7/9

2/3

5/6

E16

0.9

0.5

DISCUSSION

RAPD markers observed in the nine samples, represent-

ing six species or subspecies of Donax, showed a high

degree of polymorphism both within and among taxa.

Nevertheless, the polymorphisms did not obscure rela-

tionships among the samples and the presence of these

markers was stable over time. The distribution of these

RAPD markers supports previously disputed distinctions

between members of the following three sympatric pairs

of species: Donax parvulus and D. variabilis variabilis,

D. texasianus and D. variabilis roemeri, and D. denti-

culatus and D. striatus, as well as between the similar

but allopatric pair D. parvulus and D. texasianus.

Among the earlier applications of RAPD methodology,

the technique was used to distinguish between individ-

uals, strains, cultivars, populations and species (e.g. Hu

& Quiros, 1991, Kambhampati et al. 1992). The char-

E16

0.5

9/9

7/9

9/9

0.3

8/9

9/9

6/9

5/9

E18

9/9

the marker in kilobases and a sequential number to identify the marker. Each entry in the matrix shows the number of individuals in which the RAPD marker was detected

E16

]

2/9

1/9

4/8

over the number of individuals tested (e.g., 3/9). In a few cases, the number of individuals tested was less than nine, either because fewer DNA samples were available (DDB,

DSB) or because we were unable to score an individual for a particular marker (markers 1, 13, 14). When no individuals produced a marker, the entry is marked “—” rather

than 0/n. Data are grouped to emphasize affinities among sample populations, rather than by primer.

Size (kb):

Number

Table 4. Distribution of the RAPD DNA markers among sample populations. For each RAPD marker, the band designation identifies the primer, the approximate size of

DVF

DVG

DVR

DPF

DTT

DDM

DDN

DDB!

DSB?

LMS OP OP L]

P56 = C«éEIG~—=é«CECLL'

1.2 0.6 0.6

14 15 16

5/8 8/9 9/9

6/9 8/9 9/9

1/3 2/3 3/3

6/6

1 Only 3 individuals available for testing.

2 Only 6 individuals available for testing

DDM

DDN

DDB

DVR

DVG

DVF

15,14

7,8,9,10,11

Page 57

= Za xe ow

Qa a a > > >

Q a a Q a a

Cl=85

Rl= 91

LENGTH= 20

Figures 2-3. Phylogenetic tree resulting from analysis 1, in which all RAPD markers listed in table 4 were scored as absent or

present in each sample population, regardless of frequency (data matrix in appendix 1). 2. Character transformations plotted onto

tree. Markers 7, 10 and 11 are plotted as having arisen once and been subsequently lost in a single taxon. 3. Markers 7, 10 and 11

are plotted as having arisen twice independently.

acterization of diagnostic markers that would identify

Donax species was beyond the scope of this study, and

our criteria for primer selection precluded the recogni-

tion of markers unique to taxa represented by single

samples. Even with this screening bias, fixed, species

specific RAPD markers were discovered for Donax var-

iabilis s.l. and for D. denticulatus, the two species in this

study that were represented by multiple samples.

Kambhampatiet al. (1992) successfully applied RAPD

methodology to identify mosquito species and were able

to cluster individuals of the same species correctly by

applying phenetic algorithms (UPGMA) to markers gen-

erated by two primers. Although the resulting pheno-

gram did not reflect the ancestral relationships of the

mosquito species, these authors did not rule out the utility

of RAPD data for phylogeny reconstruction but sug-

gested that a greater number of primers (>20) should

be tested to find lineage-specific markers. Our results

confirm their conjecture. A survey of 60 primers was

necessary to select the 5 primers and 17 markers that we

Figure 4. Nelson Consensus Tree of four equally parsimonious

trees produced when all RAPD markers listed in table 4 were

scored as absent, polymorphic, or fixed (data matrix in appendix

2) and all characters were run unordered. Character transfor-

mations are plotted onto the tree. Where alternative, equally

parsimonious character transformations were possible, prefer-

Oo LL

> >

Q Q

s faa) Zz ag 3 2

aq 2 © Oo.

(an) 4 2

17 1] 13 1 Ie A :

a ! SS; 1

2 2

7 0

10 1

3 1

13 2 Sh ?

jaa) 15 1

ip) 16 2

Q 17 2

4 2

5 1

; 0 i "1 of °

th ; OF 3

0 14

=) Cl=85

O 7 2 Ri = 87

aL 2 LENGTH = 34

10 2

ence was given to the ordered, but not polarized, transformation

series (0 <-> 1 <-> 2) and to reversals (loss of marker) over

convergent origins of a marker.

Page 58

O Le

> >

a) a)

THE NAUTILUS, Supplement 2

DVG

DVF

Cl = 96

Rl = 97

LENGTH = 28

Figure 5. Most parsimonious tree produced when all RAPD

markers listed in table 4 were scored as absent, polymorphic,

or fixed, and all characters were run unordered. Based upon

results of the previous analysis (Figure 4), Donax striatus was

selected as the outgroup.

used to construct phylogenies. As RAPD markers have

previously been shown to segregate in a Mendelian man-

ner, behaving as dominant alleles (Williams et al., 1990),

we treated the individual markers as homologous char-

acters suitable for cladistic analyses. Although the anal-

yses were run unordered, when character transforma-

tions could be plotted onto the resulting tree in several

equally parsimonious ways, preference was given to the

ordered, but not polarized, transformation series (0 <-

> 1 <-> 2) because this series reflects the manner in

which alleles enter, are distributed within, and leave

populations. Preference was also given to reversal (loss

of a marker) over convergent evolution of a marker.

Despite differences in outgroup selection and data scor-

ing, all cladistic analyses produced the same, single, high-

ly consistent tree for the five Carolinian samples. The

inability to stably resolve the Caribbean samples is at-

tributed in large part to the low number of samples.

A plot of the consensus tree (Figure 4) on a map of

geographic distributions of the taxa (Figure 7) illustrates

that the Carolinian Donax species form a monophyletic

clade, while the Caribbean species may represent either

a clade (Figure 2) or grade (Figs. 5,6) depending on how

the limited data are analyzed. Although the genus Donax

Cl= 96

RI = 97

LENGTH = 28

Figure 6. Most parsimonious tree produced when all RAPD

markers listed in table 4 were scored as absent, polymorphic,

or fixed, and all characters were run unordered. Based upon

results of a previous analysis (Figure 4), the Black River pop-

ulation Donax denticulatus, was selected as the outgroup.

Figure 7. A plot of the consensus tree (Figure 4) on a map of

the locations of the collection sites for the nine sample popu-

lations of Donax used in this study. Open circles indicate species

that migrate with the tide. Solid circles indicate subtidal species.

Sample designations as in Table 1.

S. L. Adamkewicz and M. G. Harasewych, 1994

has been represented in the fossil record of the western

Atlantic since the Oligocene (Gardner, 1943:105), pro-

vincial boundaries have existed between molluscan fau-

nas of the Gulf of Mexico and the Caribbean Sea since

the late Oligocene or early Miocene (Petuch, 1988:48).

The Recent Carolinian and Caribbean Provinces com-

prise, respectively, the Caloosahatchian Province and a

portion of the larger Gatunian Province, both ranging

from the late Oligocene to the early Pleistocene (Petuch,

1988:fig.1). Thus, the considerable divergence between

Carolinian and Caribbean Donax faunas, which share at

most five of 17 markers (29% similarity), may have ac-

cumulated over a period of approximately 25 million

years.

The topology of the phylogenetic tree indicates that,

within the Carolinian province, the non-migratory, lower

intertidal to subtidal habitat is the more primitive among

Donax. Species occupying this habitat (D. texasianus,

D. parvulus and D. dorotheae) likely diverged as a result

of barriers to gene flow posed by the Mississippi River

and the emergence of peninsular Florida, respectively.

As D. parvulus appears to be the sister species of D.

variabilis, it is likely that D. variabilis originated in the

eastern Carolinian Province, although comparable RAPD

data on D. dorotheae may make possible a more precise

localization of the area of origin of D. variabilis.

ACKNOWLEDGMENTS

The authors are indebted to the staff of the Laboratory

for Molecular Systematics (LMS), National Museum of

Natural History, Smithsonian Institution, and particu-

larly to Darrilyn Albright, for technical advice. The au-

thors learned the RAPD technique at LMS and, with the

help of John Slapcinsky, now at the Field Museum of

Natural History, generated all of the RAPD data while

working there. George Mason University provided major

support for this project in the form of a sabbatical leave

for S.L. Adamkewicz while a grant from Jeffress Trust

provided her financial support. The authors thank Walter

Nelson, Florida Institute of Technology, Paul Mikkelsen,

Palm Beach County Department of Environmental Re-

source management, and Robert Vega, Texas Parks and

Wildlife Department, who collected some of the samples.

We are grateful to Prof. Diana Lipscomb and Mr. John

B. Wise of George Washington University for helpful

discussions on phylogeny reconstruction. $.L. Adamke-

wicz also wishes to thank her husband for his untiring

help in collecting specimens for this project and for all

earlier ones.

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macher, 1817) Mollusca: Bivalvia) suppressed under the

plenary powers; type species designated for Latona Schu-

macher, 1817. Bulletin of Zoolological Nomenclature 33(1):

19-21.

Moment, G.B. 1962. Reflexive selection: a possible answer to

an old puzzle. Science 136:262-263.

Morrison, J. P. E. 1971. Western Atlantic Donax. Proceedings

of the Biological Society of Washington 83(48): 545-568,

2 pls.

Nelson, W.G., E. Bonsdorff, and L. Adamkewicz. 1993. Eco-

logical, morphological, and genetic differences between

the sympatric bivalves Donax variabilis Say, 1822, and

Donax parvula Phillipi, 1849. The Veliger 36(4):317-322.

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Thessalonika: reflexive or apostatic selection? Oikos 51:

253-255.

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Page 60

Reeb, C.A. and J.C. Avise. 1990. A genetic discontinuity in

a continuously distributed species: Mitochondrial DNA in

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397-406.

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Donax denticulatus Linne. 2. Life History. Bulletin of

Marine Science 18:877-901.

THE NAUTILUS, Supplement 2

Watrous, L. E. and Q. D. Wheeler. 1981. The out-group

comparison method for character analysis. Systematic Zo-

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Welsh, J. and M. McClelland. 1990. Fingerprinting genomes

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Williams, J. G. K., Kubelik, A. E., Levak, K. J., Rafalski, J. A.

and Tingey, S.C. 1990. DNA polymorphisms amplified

by arbitrary primers are useful as genetic markers. Nucleic

Acid Research 18:6531-6535.

Appendix 1. Data matrix for initial cladistic analysis of Donax phylogeny. RAPD markers scored as absent (0) or present (1),

regardless of frequency. For sample designations see Table 1.

Samples

Outgroup

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Appendix 2. Data matrix for subsequent cladistic analyses of Donax phylogeny. RAPD markers scored as absent (0), polymorphic

(1), or fixed (2). For sample designations see Table 1.

Samples

Outgroup

DVF

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SeoooorrHNe-FoS]w

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THE NAUTILUS, Supplement 2:61-78, 1994

Page 61

Mitochondrial Genomes and the Phylogeny of Mollusks

Jeffrey L. Boore!

Wesley M. Brown

Department of Biology

University of Michigan

830 N. University Ave.

Ann Arbor, MI 48109-1048, USA

ABSTRACT

We are seeking a character set that reliably reflects the evo-

lutionary origin of the phylum Mollusca and the relationships

among molluscan classes. Such a character set must be: (1)

present in all taxa; (2) unambiguously homologous; (3) changing

at a rate appropriate for the taxonomic range; and (4) complex

enough to make convergence highly unlikely. The arrangement

of genes in mitochondrial DNA (mtDNA) appears to meet these

criteria. With only a few exceptions, the mtDNA of all met-

azoans contains the same 37 genes: 2 for ribosomal RNAs, 22

for transfer RNAs, and 13 for proteins. Comparing the ar-

rangements of these genes among the 17 taxa for which they

are known suggests that the rate of change is appropriate for

resolving higher level relationships. These genes could poten-

tially be arranged in >2 X 10° different ways; thus, the prob-

ability of the same order by convergence is very small. We

have determined the complete mtDNA sequence of the bivalve

Mytilus edulis (Hoffmann, Boore & Brown, 1992). ThismtDNA

differs from those of other metazoans in its unique gene ar-

rangement, in encoding an additional tRNA (tRNAmet(AUA)),

and in lacking one protein coding gene (ATPase 8). In order

to test whether these features are typical for mollusks, and to

investigate mitochondrial gene arrangements as a phylogenetic

character for molluscan relationships, we have determined the

mtDNA sequence for the polyplacophoran Katharina tunicata.

Katharina mtDNA contains the gene for ATPase 8 and has a

gene arrangement substantially different from that of Mytilus

and much more similar to that of Drosophila. The different

gene arrangements of Mytilus and Katharina provide numer-

ous character states for investigating molluscan class relation-

ships. By screening for gene junctions unique to one of these

two arrangements, it may be possible to find patterns of rear-

rangements which unite the remaining classes to reflect their

evolutionary history. The DNA sequence already obtained al-

lows rapid screening of other animals by two methods. First,

the polymerase chain reaction (PCR) can be used to selectively

amplify gene boundaries unique to one of these two arrange-

ments. Second, a large number of animals can be rapidly tested

for the general arrangement of several of the large, well-con-

served genes by Southern blot analysis. We compare the mi-

1 Present address: Department of Cell Biology and Neuro-

anatomy, University of Minnesota, 4-135 Jackson Hall, 321

Church St. SE, Minneapolis, MN 55455, USA

tochondrial genome arrangements of Mytilus and Katharina

and describe gene arrangement differences which are partic-

ularly useful for each of these approaches, based on: (1) the

phylogenetic information inherent in shared gene arrange-

ments; (2) the availability of well-conserved probe sequences

for Southern hybridization; and (3) the likelihood of sequences

suitable for PCR primers in adjacent genes. —

Key words: Mitochondrial DNA, Mollusca, Mytilus, Kathar-

ina, phylogeny, gene order.

INTRODUCTION

TRADITIONAL APPROACHES TO PHYLOGENY

Multicellular animals are grouped with fair confidence

into various phyla based on shared general body plans.

Establishing evolutionary relationships among the vari-

ous phyla, and among the various classes and orders

within each phylum, is much more speculative. Animal

phylogeny is most ambiguous at these high levels, where

the fossil record is least complete, homology of morpho-

logical structures is least discernible, and long periods of

time have erased traces of relatedness.

Paleontological studies are limited in resolving these

higher level relationships because of the scarcity of fossils

from the very early history of life. By the time of the

earliest fossil-rich period, the Cambrian, animal diversity

was considerable, with nearly all currently-recognized

higher taxa represented. Many early animal forms ex-

hibit unique morphologies not recognizable as inter-

mediate between other groups of animals.

Analysis of morphological data is confounded by the

great length of time that has elapsed since these taxa

diverged. Determining homologous structures among an-

imals with radically different body plans is contentious.

Convergence of morphological structures among various

animals is common and difficult to recognize. Hypotheses

based on considerations of functional morphology or re-

capitulation of embryological structures lack the desired

rigor and falsifiability. Many alternative, often contra-

dictory models of metazoan evolution have been pro-

posed, all based on interpretations of the same embry-

ological, paleontological, and morphological data sets.

Page 62

Nowhere are these difficulties more acute than in de-

termining the relationships among the various classes and

orders of the phylum Mollusca, or in determining the

sister taxon to this phylum. Although most classification

schemes agree on uniting the classes Scaphopoda, Bi-

valvia, Cephalopoda, Gastropoda, and Monoplacophora

into a monophyletic Conchifera, the relationships among

these classes are equivocal. Monoplacophora has been

suggested as the sister group to Gastropoda based on

studies of comparative morphology (Gotting, 1980) and

paleontological material (Knight & Yochelson, 1960). Sal-

vini-Plawen (1985) views Monoplacophora as basal to a

clade of the remaining four conchiferan classes. It has

also been suggested that Monoplacophora unites with

Gastropoda and Cephalopoda in the trichotomous Cyr-

tosoma (Runnegar & Pojeta, 1974). Cephalopoda is sug-

gested as the basal conchiferan (Gotting, 1980) or as the

sister group to Gastropoda (Wingstrand, 1985; Runnegar

& Pojeta, 1974). Finally, Scaphopods may be primitive

mollusks (Lindberg, 1985) or they may be included in a

clade with the Bivalvia and the extinct rostroconchs, the

Diasoma (Runnegar & Pojeta, 1974).

Relationships among the non-conchiferans are even

more ambiguous. Early classification schemes united

Aplacophora with Polyplacophora in the Amphineura,

first considering neither to be mollusks (von Ihering, 1876),

and later recognizing their molluscan affinity (Pelseneer,

1899). Some modern day classifications view a mono-

phyletic Amphineura as the basal group of mollusks (Po-

jeta, 1980; Haas, 1981) although some continue to ques-

tion their inclusion in Mollusca (Fretter & Graham, 1962).

Another view places Aplacophora as the primitive, basal

class of mollusk, creating a clade of the Polyplacophora

and the Conchifera (Gotting, 1980; Wingstrand, 1985;

Scheltema, 1988). Salvini-Plawen (1985) not only views

the Aplacophora in this basal position, but splits Apla-

cophora into two paraphyletic groups, the Caudofoveata

and the Solenogastres, a scheme supported by several

later studies (Meglitsch & Schram, 1991; Pearse et al.,

1987; Brusca & Brusca, 1990; Barnes, 1987; Nielsen, 1985,

1987). Still other analyses view the Conchifera as the

primitive group of mollusks, with the Polyplacophora,

Caudofoveata, and Solenogastres secondarily derived

(Marcus, 1958; Hadzi, 1953, 1963).

The closest sister taxon to the phylum Mollusca has

been suggested variously to be Annelida (Gotting, 1980;

Vagvolgyi, 1967), Arthropoda (Lemche, 1959a,b; Fretter

& Graham, 1962), Sipunculida (Inglis, 1985), Turbellaria

(Graham, 1955; Salvini-Plawen, 1972, 1980; Haas, 1981),

Echiurida, or Nemertina (see discussion in Salvini-Plaw-

en (1985) and Vagvolgyi (1967)). A clade of consisting

of Annelida and Mollusca is suggested to have been de-

rived from flatworms (Hammarsten & Runnstrom, 1925;

Boettger, 1959) or coelenterates (Beklemishev, 1963).

The debates on the relationships among molluscan

classes and on the evolutionary origin of Mollusca center

on alternative models of morphological change. These

models differ in interpreting which types of change are

feasible or common, to what extent convergence and

THE NAUTILUS, Supplement 2

parallelism occur, and which structures are homologous

among the various metazoan bauplane. Resolution of

molluscan relationships would permit many conclusions

regarding the evolution of the coelom, serially repeated

structures, and body segmentation.

MOLECULAR PHYLOGENIES

Molecular phylogenies based on comparing the sequenc-

es of nucleotides or amino acids have offered many new

insights into the evolutionary relationships among or-

ganisms. During the development of the technology to

make this feasible, some hoped that all questions of phy-

logeny would eventually be answered with a high con-

fidence using these techniques. Although it would be

hard to overstate the contribution of molecular ap-

proaches to evolutionary biology in recent decades, many

questions of organismal relationships remain recalcitrant.

Numerous molecular studies of metazoan relationships

have compared the nucleotide sequence of 18S ribosomal

RNAs (rRNAs). This molecule was chosen for sequence

comparisons in part because its high copy number in the

cells of many organisms allows sequence determination

directly (without the need for cloning the gene itself)

using the enzyme reverse transcriptase. Although they

effectively outline the broad pattern of relationships

among kingdoms of organisms (Pace et al., 1986; Woese

& Fox, 1977; Woese, 1987; Lake, 1988; Sogin, 1991;

Wainright et al., 1993), when applied to relationships

among metazoans these comparisons have yielded phy-

logenies that are mutually contradictory and difficult to

reconcile with patterns of morphological divergence

(Field et al., 1988; Lake, 1990; Patterson, 1989). While

only three molluscan classes are represented (Bivalvia,

Polyplacophora, and Gastropoda), various methods of

phylogenetic analysis of the 18S rRNA data yield con-

tradictory results of the relationships among these classes

and their relationships to other animals (see figure 1).

There are numerous limitations of DNA sequence

comparisons for phylogeny, especially when considering

ancient divergences: (1) With only four possible char-

acter states at each aligned position, homoplasy is com-

mon and difficult to recognize. (2) These characters states

are difficult to reliably polarize as primitive versus de-

rived. (3) Unequal rates of nucleotide substitution in

various lineages can lead to erroneous linkages when

using distance-based phylogenetic methods, or to the

“long-branch attraction” problem when using parsimo-

ny-based analyses (Felsenstein, 1978). By counting the

number of lineage-specific nucleotide substitutions for

20 taxa for a sample of 1000 rRNA nucleotides, Ghiselin

(1988) concluded that substitution rate varies over an 18-

fold range among the metazoa. (4) The effects of gene

conversion in multigene families may produce patterns

of change among groups of organisms that are difficult

to deduce (Arnheim, 1983; Sasaki et al., 1987; Walsh,

1985; Coen, Strachan & Dover, 1982). (5) Small subunit

rRNAs vary in length by almost a factor of two, so many

gaps must be introduced for nucleotide alignment. This

J. L. Boore and W. M. Brown, 1994 Page 63

Polychaete

A Pclychaete B Clams C Brachiopod

Brachiopod Sipunculid Chiton

Chiton Chiton Pogonophora

Pogonophora Snail Sipunculid

Oligochaete Brachiopod Oligochaete

Clams Pogonophora Snail

Sipunculid Oligochaete Clams

Snail Polychaete Brine shrimp

Human Brine shrimp Insect

Sea star Horseshoe crab Millipede

Brine shrimp Horseshoe crab

Planarian

Brine shrimp

Polychaete Insect Polychaete

D Oligochaete F Millipede Oligochaete

Clams Horseshoe crab Pogonophora

Brachiopod Clams Clams

Chiton Polychaete Chiton

Pogonophora Brachiopod Brachiopod

Sipunculid Chiton Sipunculid

Snail Pogonophora Snail

Brittle star Snail Brine shrimp

Human Oligochaete Insect

Brine shrimp Sipunculid Horseshoe crab

Planaria Human Millipede

Figure 1. Six evolutionary hypotheses resulting from 18S rRNA comparisons. In some cases, taxa that do not group within the

depicted clade have been omitted in order to emphasize the placement of the mollusks. (A) Tree from Field et al. (1988), derived

using a distance method of analysis for 839 aligned positions. Mollusca is paraphyletic with the inclusion of two annelids, a brachiopod,

a pogonophoran, and a sipunculid. Gastropoda is primitive; however, no scaphopods, cephalopods, aplacophorans, or monoplaco-

phorans are included in this analysis. (B) A portion of the rooted evolutionary tree from Lake (1990), using the method of evolutionary

parsimony with exactly the same data and alignments as in (A). Mollusca is paraphyletic with the inclusion of a sipunculid and a

brachiopod. (C)-(F) Various results of parsimony analyses from Patterson (1989). (C) A portion of the tree produced by a strict

consensus of the four shortest trees in a parsimony analysis of 544 aligned nucleotides. Data and alignment are the same as in A

and B, but with the addition of two prokaryotic 16S rRNA sequences as outgroups. (D) The tree produced using the same data as

for (C), but limiting the taxa analyzed to those depicted, and rooting the tree with the planarian sequence. (E) A portion of the

tree produced by limiting the analysis of (C) to only those 273 aligned positions which represent unpaired nucleotides in the rRNA

secondary structure. (F) A portion of the tree produced by strict consensus of three equally parsimonious trees, generated by limiting

the analysis of (C) to only those 271 aligned positions which represent paired nucleotides in the rRNA secondary structure. Taxa

used in these analyses: Clams-M ya arenaria and Spisula solidissima, Polychaete-Chaetopteris sp.; Brachiopod-Lingula reevi; Chiton-

Cryptochiton stelleri; Pogonophora-Riftia pachyptila; Oligochaete-Lumbricus sp.; Sipunculid-Goldfingia gouldii; Snail-Anisodoris

nobilis; Human-Homo sapiens; Sea star-Asterias forbesi; Brine shrimp-Artemia salina; Planarian-Dugesia tigrina; Insect-Drosophila

melanogaster, Millipede-Spirobolus marginatus; Horseshoe crab-Limulus polyphemus; Brittle star-Ophiocoma wendtii.

alignment is often so ambiguous that different portions

of the molecule are compared between the various or-

ganisms to eliminate regions which could not be satis-

factorily aligned (by subjective criteria). A sequence

alignment is fundamentally an hypothesis of homology

at each of the aligned positions; changing the alignment

of nucleotides can generate very different evolutionary

trees. (6) There is disagreement about which parts of the

rRNA sequence provide reliable data. Some contend that

the most reliable phylogenetic trees are generated by

using only the subset of nucleotides that are paired in

rRNA secondary structure (Smith, 1989), some argue that

the most reliable information is in unpaired nucleotides

(Wheeler & Honeycutt, 1988; in a study using 5S and

5.8S rRNA sequences), and some are unable to find a

significant difference between the two (Vawter & Brown,

1993). Various weighting schemes for these two subsets

of nucleotides lead to different hypotheses of relation-

ships and are based on intractable aspects of the evolu-

tionary history of the molecule (Dixon & Hillis, 1993;

Patterson, 1989: see Kraus et al., 1992 for discussion

about mitochondrial rRNA sequences). (7) Applying dif-

ferent tree-making methods to the same data frequently

yields very different results (e.g., see figure 1). These

methods differ in their assumptions of the evolutionary

process, and we have no reliable method for discerning

Page 64

which is most realistic. Most insidious is the tendency to

judge results most reliable when congruent to previously

accepted hypotheses of relationships. Such circularity

questions the potential contribution of molecular phy-

logenies.

MITOCHONDRIAL GENOMES

We are interested in discovering a better set of characters

for determining molluscan (and other metazoan) rela-

tionships. We seek a character set that reliably reflects

the evolutionary origin of the phylum Mollusca and the

relationships among molluscan classes. To be useful for

phylogenetic inference, there are several properties that

such a character set must possess: (1) Character states

should be determinable for all taxa so no states are shared

between organisms as “missing.” (2) Characters should

be demonstrably homologous among the organisms. (3)

Character states should be complex enough so that it

would be highly unlikely that the same character state

could have arisen independently in two or more lineages.

Therefore, identical character states would likely be

shared by two or more taxa only because of common

ancestry. (4) Character states should change at a rate

appropriate for the time span being investigated. Too

little change limits resolution; too much change obscures

relationships.

We are investigating a set of molecular characters that

appear to possess the above properties and show promise

to be useful for determining ancient divergences: the

arrangement of genes in mitochondrial DNA (mtDNA).

MtDNA exists as a discrete genome within the cells of

all metazoans, generally as a closed circular DNA of

about 14-17 kilobases (kb) (Wolstenholme, 1992a,b;

Brown, 1985; Wallace, 1982; Attardi, 1988)!. Although

much larger mtDNAs are occasionally found in a variety

of metazoan taxa, including Mollusca (Moritz, Dowling

& Brown, 1987; Snyder et al., 1987; LaRoche et al.,

1990), in none of these cases is there any evidence for

variation in gene content. MtDNA typically contains one

or more large non-coding sequences, which can vary

significantly in length among organisms. This region in

vertebrates (Clayton, 1991, 1992; Montoya et al., 1982;

Bogenhagen, Cairns & Yoza, 1985; King & Low, 1987)

and insects (Clary & Wolstenholme, 1985a) has been

shown to include elements for the control of replication

and transcription. Large variation in lengths of mtDNAs

has been due to variation in the length of this major non-

coding region (Brown, 1985; Harrison, 1989; Carr, Broth-

ers & Wilson, 1987; Harrison, Rand & Wheeler, 1985;

Fauron & Wolstenholme, 1976; Solignac, Monnerot &

Mounolou, 1986; Wilkinson & Chapman, 1991; Buroker

1 An exception is found among some (but not all) cnidarians,

where mtDNA is present as one or two linear molecules totaling

about 16 kb (Warrior & Gall, 1985; Bridge et al., 1992).

THE NAUTILUS, Supplement 2

et al., 1990; Monforte, Barrio & Latorre, 1993) or to

duplication of some portion of the mitochondrial genome

(Moritz & Brown, 1986, 1987; Zevering et al., 1991).

The arrangement of the genes in mtDNA appears to

meet the above four criteria for a character set to be

used for phylogenetic inference. The gene content of

metazoan mtDNA is well conserved. With few excep-

tions (Wolstenholme et al., 1987; Okimoto et al., 1991,

1992; Hoffmann, Boore & Brown, 1992), the mtDNA of

all animals examined contains the same 87 genes: 2 for

the small and large rRNAs of the mitochondrial ribosome

(s-rRNA and |-rRNA), 22 for transfer RNAs (tRNAs),

and 13 for protein subunits of the enzyme complexes of

the inner mitochondrial membrane [cytochrome oxidase

subunits I-III (CO1-3), NADH dehydrogenase subunits

1-6 and 4L (ND1-6, 4L), cytochrome b (cytb), and ATP

synthase subunits 6 and 8 (ATPase 6, 8)]. Mitochondrial

genes are certainly homologous among metazoa, not only

because of their functional identity and obvious sequence

similarity among metazoans, but also because of the high

degree of their similarity in these respects to the mito-

chondrial genes of non-metazoans. Table 1 shows that

each of the 15 protein- or rRNA-encoding genes has a

homologue in the mtDNA of one or more non-metazoan

organisms. It seems clear that these 15 genes were en-

coded in mtDNA prior to the origin of Metazoa, and

that the gene content of the mtDNA of extant organisms

was established prior to this radiation.

The arrangement of mitochondrial genes is a very

complex character set for phylogenetic inference, be-

cause there are a very large number of possible gene

arrangements. Assuming complete positional indepen-

dence of all genes and two transcriptional orientations,

these 37 genes could potentially be joined in greater than

2 X 10°? different arrangements; thus, the probability of

the same order arising independently in more than one

taxon is vanishingly small. Identical gene arrangements

would likely be shared only as a result of common an-

cestry, making homoplasy rare.

Preliminary studies suggest that the rate of change in

mitochondrial gene arrangement is appropriate for re-

solving ancient divergences. Although mtDNA evolves

rapidly in sequence (Brown, George & Wilson, 1979),

rearrangements in gene order appear rare. All 37 genes

are identically arranged in the mitochondrial genomes

of several vertebrates, including Homo (Anderson et al.,

1981), Bos (Anderson et al., 1982), Mus (Bibb et al.,

1981), Rattus (Gadaleta et al., 1989), Balaenoptera (Ar-

nason, Gullberg & Widegren, 1991), Phoca (Arnason &

Johnsson, 1992), Xenopus (Roe et al., 1985), Crossostome

(Tzeng et al., 1992), Cyprinus (Chang, Huang & Lo,

1994), and Gadus (Johansen, Guddal & Johansen, 1990),

although minor rearrangements have taken place in mar-

supial mammals (Paabo et al., 1991) and in birds (Des-

jardins & Morais, 1990, Desjardins, Ramirez & Morais,

1990). The gene arrangement of the mtDNA of the ceph-

alochordate Branchiostoma floridae (W. Brown & L.

Daehler, unpublished data) is very similar to that of

vertebrates. Similarly, mitochondrial genomes have un-

J. L. Boore and W. M. Brown, 1994

Page 65

Table 1. The 15 protein- or rRNA-encoding genes typical of metazoan mtDNA, and a listing of non-metazoan taxa in whose

mtDNAs homologous genes have been positively identified. Genes are abbreviated as in the text. Additional genes are also present

in these non-metazoan mtDNAs. The non-metazoan species are Paramecium aurelia, Leishmania tarentolae, Trypanosoma brucei,

Chlamydamonas reinhardtii, Marchantia polymorpha, Neurospora crassa, Saccharomyces cerevisiae, Schizosaccharomyces pombe,

Aspergillus nidulans, and Podospora anserina. Data are from Boer and Gray, 1991; Brown et al., 1985; Clark-Walker, 1989;

Cummings and Delmenico, 1988; Cummings et al., 1990a,b; Dewey et al., 1985; de Zamaroczy and Bernardi, 1986; Dyson et al.,

1989; Feagin et al., 1988; Gray and Boer, 1988; Ise et al., 1985; Lang et al., 1983; Oda et al., 1992; Pratje et al., 1989; Pritchard

et al., 1990; Simpson et al., 1987; Stuart and Feagin, 1992; Wolf and Del Guidice, 1988; Vahrenholz et al., 1985.

Cytochrome

oxidase ATPase Cyt NADH dehydrogenase rRNA

J 2 3 6 8 b ] ® 3 4L 4 D 6 Sml Lrg

Metazoa xX x xX xX xe xX x Xx xX xX xX xX xX xX x

Paramecium x xX xX xX xX xX xX xX xX x

Leishmania xX x x xX xX x x xX xX xX

Trypanosoma xX xX xX xX x xX xX Xx xX Xx

Chlamydamonas x x x x x x Xx x x

Marchantia x x x x xX x xX x x x xX x xX x

Neurospora x xX xX xX xX x xX xX x x x xX x xX

Saccharomyces xX x xX xX x xX xX xX

S. pombe x Xx x x x x x xX

Aspergillus x x x x x x x x x x x x xX x xX

Podospora x x x x xX xX xX xX xX xX xX xX xX xX xX

* ATPase 8 appears to be missing from the mitochondrial genomes

dergone little gene rearrangement among echinoderm

classes, with only a single large inversion separating the

arrangements of sea stars and sea urchins (Jacobs et al.,

1988; Cantatore et al., 1989; De Giorgi et al., 1991;

Himeno et al., 1987; Smith et al., 1989, 1990, 1998). In

each of these deuterostome phyla, organisms which have

been separated for over 500 million years share very

similar mitochondrial gene arrangements.

The traditionally accepted superphylum, Protostomia,

includes three major phyla: Arthropoda, Mollusca, and

Annelida. Drosophila and Apis represent the only genera

within arthropods for which the complete mtDNA se-

quences are published (Clary & Wolstenholme, 1985a;

De Bruijn, 1983; Garesse, 1988; Crozier & Crozier, 1993).

These two mitochondrial genomes are nearly identically

arranged, differing only by a few tRNA gene translo-

cations. Partial gene arrangements for numerous other

arthropods (including Artemia, Locusta, Aedes, Daph-

nia, Homarus, and Limulus) indicate that gene order is

highly conserved in this phylum (Batucus et al., 1988;

Hsuchen, Kotin & Dubin, 1984; Dubin, Hsuchen & Til-

lotson, 1986; McCracken, Uhlenbusch & Gellissen, 1987;

Uhlenbusch, McCracken & Gellissen, 1987; D. Stanton,

L. Daehler & W. Brown, unpublished data).

Representing pseudocoelomate animals, the mtDNA

of two nematodes, Caenorhabditis elegans and Ascaris

suum, have nearly identical gene arrangements (Wol-

stenholme et al., 1987; Okimoto et al., 1992), although

that of a third, Meloidogyne javanica, has a radically

different arrangement (Okimoto et al., 1991). Partial

genome organization has been determined for the par-

asitic flatworm, Fasciola hepatica (Garey & Wolsten-

holme, 1989) and is unique among animals examined to

of Mytilus and nematodes (see text).

date. Although gene rearrangements appear to be gen-

erally rare within a phylum, there are substantial dif-

ferences among the gene orders of each of these phyla.

Furthermore, the radically different arrangements of mi-

tochondrial genes that exist among several of the taxa

suggest that selection for any particular gene order is

minimal, and argues against this as a factor that might

promote convergence of gene order in separate lineages.

Comparisons of mtDNA gene arrangements may also

be useful for phylogeny at lower taxonomic levels. There

is evidence that the frequency of rearrangements of the

mitochondrial tRNA genes is greater than that of the

rRNA and protein genes. For example, the gene orders

of two diptera, Aedes (Dubin, Hsuchen & Tillotson, 1986,

Hsuchen, Kotin & Dubin, 1984) and Drosophila (Clary

& Wolstenholme, 1985a,b), differ in the relative positions

of two tRNA genes and by the relative inversion of a

third, but are otherwise identical insofar as can be de-

termined from the partial sequence of Aedes mtDNA.

The partial gene order determined for another insect,

Locusta, differs from Drosophila by one tRNA rear-

rangement (MacCracken, Uhlenbusch & Gellissen, 1987;

Uhlenbusch, MacCracken & Gellessen, 1987). Eight

tRNAs must be repositioned to interconvert the mito-

chondrial gene arrangements of Apis (Crozier & Crozier,

1993) and Drosophila. The mitochondrial genome ar-

rangement of several marsupials differs from that of pla-

cental mammals by translocations within a cluster of five

tRNAs (Paabo et al., 1991). As more gene orders become

available, useful information about phylogenetic rela-

tionships among even more closely related animal groups

(ordinal and subordinal levels) may occasionally be ob-

tained.

Page 66

COMPARISON OF THE MITOCHONDRIAL

GENOME ARRANGEMENTS OF

MYTILUS EDULIS (BIVALVIA) AND

KATHARINA TUNICATA (POLYPLACOPHORA)

We have determined the DNA sequence of 13.9 kb of

the 17.1 kb mitochondrial genome of the bivalve Mytilus

edulis, which is sufficient to identify all 37 mitochondrial

genes (Hoffmann, Boore & Brown, 1992). The arrange-

ment of genes in Mytilus mtDNA is radically different

from those that have been found in other metazoans.

With few exceptions, the arrangement of mitochondrial

genes appears to be very similar or identical in within-

phylum comparisons, so it was initially unclear whether

the unusual gene arrangements in Mytilus mtDNA was

typical of mollusks in general or characteristic of a more

restricted group of molluscan taxa. To investigate this,

and to evaluate further the potential of mitochondrial

genome structure as a useful phylogenetic indicator, we

determined the complete mtDNA sequence for the po-

lyplacophoran Katharina tunicata. The Katharina mi-

tochondrial gene arrangement differs substantially from

that of Mytilus and is much more similar to the mt DNAs

of other coelomate animals, including an annelid (Boore

& Brown, manuscript in preparation), and representa-

tives of other classes in the phylum Mollusca (W. Brown,

T. Collins & L. Daehler, unpublished data).

The mitochondrial genome of Mytilus edulis, in par-

ticular, contains several unusual features in comparison

with others previously characterized. Mytilus mtDNA

lacks a gene for ATPase 8. This gene is also absent from

the mitochondrial genomes of the three nematodes men-

tioned above, although presumably these absences rep-

resent convergent losses in the Mytilus and nematode

lineages. Mytilus mtDNA encodes 23 tRNAs, one more

than the typical metazoan mitochondrial complement.

The anticodon of the additional tRNA is complementary

to the codons for methionine, giving Mytilus mtDNA

two methionine tRNA genes. One of these genes specifies

a tRNA with the anticodon CAT, which is typical of

other metazoan mitochondrial tRNA™* genes; the other

is nearly unique among all genomes in having the an-

ticodon TAT. The arrangement of these 37 genes is high-

ly unusual, with few gene boundaries shared with any

other metazoan so far investigated. The reading frames

of the ND1, CO1, and CO8 genes vary significantly in

length from those of other metazoans, more so than found

in any previous comparisons. However, in other respects

this genome is typical of metazoan mtDNA. Aside from

the supernumerary tRNAmet genes, its gene content is

typically metazoan, its tRNA and rRNA genes are small

relative to those found in prokaryotic and eukaryotic

nuclei, its gene organization is highly compact, and its

genetic code appears to be identical to that employed in

several other metazoan mitochondrial systems. All genes

are encoded by the same DNA strand, as is the case in

other (but not all) metazoans.

Radical variation in the arrangement of mitochondrial

genes has been demonstrated previously in comparisons

THE NAUTILUS, Supplement 2

among metazoan phyla, most notably between nema-

todes and the other phyla examined. However, only mi-

nor variation in mitochondrial genome arrangement is

usually observed in within-phylum comparisons. It was,

therefore, surprising to find the mitochondrial gene ar-

rangement of another mollusk, the polyplacophoran Ka-

tharina tunicata, to be much more similar those of ar-

thropods, chordates, or echinoderms than to that of

Mytilus.

Katharina mtDNA encodes the 37 genes typical of

metazoan mtDNA, including the gene for ATPase 8 which

is absent from Mytilus mtDNA. There are at least three

possible explanations for the loss of the ATPase 8 gene

in the lineage leading to Mytilus after its separation from

the Katharina lineage: (1) The normal function of sub-

unit 8 of the ATP synthase complex is subsumed by

another protein subunit; (2) The function of ATPase 8

has become dispensable in the metabolism of Mytilus

mitochondria; or (3) The ATPase 8 gene has been trans-

ferred to the nucleus, and its gene product is now im-

ported into the mitochondria. If it could be determined

whether other mollusks share the absence of the ATPase

8 gene from mtDNA, such molecular or metabolic changes

could be a very complex derived character, robust for

phylogenetic analysis.

In addition to the 22 tRNAs typical of metazoan mi-

tochondrial genomes, Katharina mtDNA contains two

additional sequences that can be folded into structures

resembling tRNAs. If actual tRNAs, their anticodons (AAA

and AGA) would presumably recognize the codons UUU

and UCU as phenylalanine and serine, respectively. They

are, therefore, provisionally identified as tRNAPb(UU0)

and tRNAs*UCU) in figure 2. However, there are several

reasons to doubt that they actually function as tRNA

genes. The anticodons AAA and AGA are unprecedented

in metazoan mtDNA. None of the tRNAs encoded in the

mtDNAs of Katharina, Mytilus, or Drosophila have an

A in the 8rd (‘wobble’) position. Both of these putative

tRNAs have several mismatches within their stems and

neither has a T preceding the anticodon, as is found in

all other Katharina tRNAs. They do, however account

for nearly all of the nucleotides in what would otherwise

be unassigned sequence, and their predicted secondary

structures are no more aberrant than those of many other

mitochondrial tRNAs.

Figure 2 shows the mitochondrial gene arrangements

of Katharina tunicata, Mytilus edulis, and Drosophila

yakuba (the latter determined by Clary & Wolstenholme,

1985a). If we ignore the positions of tRNA genes, only

two rearrangements are necessary to interconvert the

gene arrangements of Katharina and Drosophila: a trans-

position of the CO8-ND8 segment, and an inversion of

the ND6-Cytb segment. The genes encoding tRNAs ap-

pear to rearrange at a much higher frequency, as has

been noted previously, with numerous tRNAs differing

in position between Drosophila and Katharina for both

nearest-neighbor genes, namely those for leu(UUR), lys,

asp, gly, ser(AGN), glu, ile, gln, met, and trp.

In contrast, there is little in common when comparing

J. L. Boore and W. M. Brown, 1994 Page 67

a F GEID \/ KL(CUN) V M(AUA)RAH S(UCN)

—S

4 = Ze) ~

ee M(AUe)> S(AGN)

F(UUU)? S(UCU)? £ H aT P LC(UUR) Vv MYOE KRI S(AGN)

| Vv — ~m

carne [co Bf as [olf mf fama m

D S(UCN) L(CUN) CWG AN

L(UUR) K G ANE H U S(UCN) L(CUN) V 1M wy

: sa) = wo Kk

Drosophila C01 C02} NDS | ND4 | S}//9 | Cytb NDI |l-rRNAlsrava | + | ND2

D RIE p Q ¢

S(AGN)

Figure 2. Comparison of mitochondrial gene arrangements among Katharina tunicata (Boore & Brown, submitted), Mytilus edulis

(Hoffmann, Boore & Brown, 1992), and Drosophila yakuba (Clary & Wolstenholme, 1985), with each genome aligned starting at

the gene for CO1. All genes of Mytilus are transcribed from left to right, as are all genes in the Katharina and Drosophila genomes

other than those designated by underlining to signify reverse orientation. Ignoring tRNA position differences, which are numerous,

rearrangements are shown by lines connecting gene pairs or blocks of contiguous genes (marked by a bar). Inversions are indicated

by a circular arrow. Gene designations are as follows: cytochrome oxidase subunits I-III, CO1-3; NADH dehydrogenase subunits

1-6 and 4L, ND1-6, ND4L; cytochrome b apoenzyme, Cytb; ATP synthase subunits 6 and 8, A6, A8; small and large ribosomal

subunit RNAs, s-rRNA, l-rRNA. Transfer RNAs are designated by the one letter code for the corresponding amino acid; the two

tRNAs each for serine and leucine are further differentiated by the codon recognized (UCN and AGN for serine; UUR and CUN

for leucine). M(AUA) of Mytilus mtDNA denotes an additional methionine tRNA and F(UUU)? and S(UCU)? designate additional

tRNA-like structures of Katharina mtDNA. UNK (unknown) designates the largest unassigned region of the Mytilus and Katharina

mtDNAs. A+T in Drosophila designates the A+T rich non-coding region.

the mitochondrial gene arrangement of Mytilus with three gene block, tRNA'\CUN)-tRNA!CUR)_NDI. The

either Katharina or Drosophila. Ignoring tRNA genes, only gene boundaries shared by the Drosophila and My-

only the two rRNA genes are in the same order and tilus mitochondrial genomes are those of CO2-tRNA*,

transcriptional polarity in the three animals. However, tRNA"-ND4L (although here the relative polarity of

in Drosophila and Katharina mtDNA (and many other tRNA" is reversed), and tRNA™'-ND2 (although here

metazoans) the two rRNA genes are separated by the tRNA™* of Mytilus is has the anticodon TAT whereas

tRNA”, whereas in Mytilus mtDNA they are separated the tRNA™* of Drosophila has the anticodon CAT).

by seven tRNAs, none of which is tRNA”. The only gene The genes of metazoan mtDNA are typically arranged

boundaries shared by the Katharina and Mytilus mito- very compactly. Introns are absent, intergenic nucleo-

chondrial genomes are those of tRNA''-ND4L and the tides are few, and genes frequently overlap or end on

Page 68

Taxa: a ly € | Taxa: a ly) © GG

State: 0 ONTO State: 0 Pe os)

A B

Taxa: a b oc d

State: 0O @ jl 1

€

Figure 3. An explanation of the method for analyzing the

evolutionary significance of patterns of mitochondrial genome

rearrangement. Each taxon is represented by a letter, with “a”

designated as the outgroup. Sharing a number for the character

state represents sharing a gene boundary; differing numbers

indicate that the taxa differ in the gene boundary. Three types

of patterns may occur: (A) taxa “b” and “c” share a primitive

gene arrangement (symplesiomorphy), since the “0” state ex-

isted prior to the origin of “b’, “c’, or “d”. Hence “b” and

“c” cannot be united to the exclusion of “d” by this shared

gene boundary. (B) taxa “b’, “c’, and “d” each have unique

gene arrangements (autapomorphies). (C) the only pattern of

gene arrangements that can be used to unite taxa. Because

taxon ‘“b” shares the “0” state with the outgroup, the state is

polarized to indicate “c’’ and “d” share the derived “1” state

as a synapomorphy. To place taxon “b” within the clade con-

taining ‘c’ and “d” would be less parsimonious, since it would

require either the reversion to the “0” state in taxon “b” or the

convergent gain of the “1” state in taxa “c” and “d”. Consid-

ering the large number of potential character states at each

gene boundary, such reversion or convergence to identical states

is improbable.

abbreviated stop codons (Wolstenholme, 1992a,b; Brown,

1985; Moritz, Dowling & Brown, 1987; Attardi, 1988).

Because genes often abut directly or overlap, any genome

rearrangement would require very precise breakage and

recombination for the resultant genome to produce func-

tional products. This barrier to recombination has been

offered as one possible explanation for the conservation

of arrangement of mitochondrial genes over long periods

of time (Brown, 1985). In Mytilus mtDNA there are five

lengthy intergenic sequences, four of which range in size

from 79 to 119 nucleotides and the fifth of which is 1.2

kb. It may be that the relatively lengthy regions of DNA

without apparent function between genes in Mytilus

mtDNA enable recombination, accounting for what ap-

pears to be an unusually rapid rate of rearrangement,

although this remains undemonstrated.

For most metazoans, mtDNA is inherited maternally

(Lansman, Avise & Huettel, 1983; Dawid & Blackler,

1972; Gyllensten, Wharton & Wilson, 1985). This is part-

ly due to the vastly greater number of mitochondria in

the egg cytoplasm than in the sperm. Sperm cells typi-

cally contain only a few mitochondria, and these are

localized in the midpiece, which is often excluded from

the egg during fertilization. Mytilus is a notable excep-

THE NAUTILUS, Supplement 2

tion in this regard. Its mtDNA is frequently inherited

biparentally and two or more variant forms of mtDNA

often occur within an individual, a condition known as

heteroplasmy (Hoeh, Blakely & Brown, 1991; Zouros et

al., 1992). Another bivalve, the scallop Placopecten, also

exhibits frequent heteroplasmy as well as large variations

in mitochondrial genome size (Snyder et al., 1987; Gjet-

vaj, Cook & Zouros, 1992; LaRoche et al., 1990). It is

possible that one or more of these unusual features is

responsible for the highly derived state of mtDNA in

Mytilus and, possibly, in other bivalves. This, however,

is very speculative, and a much broader survey of bivalve

mtDNAs is needed to determine when the radical vari-

ation in gene arrangement occurred.

ANALYSIS OF GENE ARRANGEMENTS

It would be overly simplistic and perhaps wrong to sug-

gest that a shared arrangement of mitochondrial genes

by itself indicates a close evolutionary relationship. Taxa

may share a gene arrangement because they inherited

it in an unchanged form which existed ancestral to the

divergence of the several taxa being considered (sym-

plesiomorphy; figure 3A); likewise, the gene arrange-

ments of closely related taxa may differ due to a rear-

rangement that is unique to one of the lineages

(autapomorphy; figure 3B). Neither of these patterns of

gene arrangement is indicative of phylogeny. The gene

arrangements that are useful for phylogenetic inference

are those which can be demonstrated, by comparison

with appropriate outgroups, to be shared in a derived

form (synapomorphy; figure 3C). Admittedly, most phy-

logenetic branching events will not coincide with mi-

tochondrial gene rearrangements. However, when a de-

rived arrangement is shared by two or more taxa, it is

extremely likely to indicate common ancestry.

We cannot infer that Katharina andMyftilus are dis-

tantly related simply because of the great number of

differences in the arrangement of their mitochondrial

genes. To infer such a distant relationship would be to

assume that mtDNA gene rearrangements occur in a

clock-like manner, an assumption that existing data re-

fute. The differences in gene order between these two

mtDNAs can only be interpreted as an autapomorphy,

given the data at hand, and therefore as phylogenetically

uninformative. In the same manner, we cannot infer that

Katharina and Drosophila share a more recent common

ancestor than Katharina and Mytilus based on the great-

er similarity of the Katharina and Drosophila gene ar-

rangements; this similarity is a symplesiomorphy, and

may represent the state of arrangement in the common

ancestor of all three taxa. As in figure 3A, all arrange-

ments of the ingroup taxa are equally parsimonious,

therefore these characters are not phylogenetically in-

formative.

It is critical that gene arrangements be determined

not only for several representatives of each of the classes

of Mollusca, but also for all potential outgroup taxa that

might be useful for determining whether gene rear-

rangements are primitive or derived. A larger survey of

J. L. Boore and W. M. Brown, 1994

animal mitochondrial genomes might reveal interme-

diate genome arrangements and, perhaps, identify non-

molluscan taxa that have these arrangements. However,

with increasing numbers of gene arrangements to com-

pare, determining precisely the most parsimonious pat-

tern of rearrangement becomes exponentially more dif-

ficult. Techniques are currently being developed to

provide computer analysis of genome rearrangements

(Sankoff et al., 1990,1992).

COMPARISON OF OTHER ASPECTS OF THE

MITOCHONDRIAL GENOMES OF

MYTILUS EDULIS AND KATHARINA TUNICATA

Molecular phylogenies have been limited largely to com-

parisons of linear sequences of nucleotides or amino ac-

ids. An entire field of scientific inquiry has developed

from the need to deduce phylogeny most accurately from

these sequence comparisons. However, genomes contain

many other complex features that can be compared, such

as the arrangement of genes, the relative positions of

deletions and insertions, the number and position(s) of

regulatory sequences, numerous sequence-based aspects

of transcription, translation, and DNA replication, vari-

ations in the genetic code, and secondary structures of

transfer and ribosomal RNAs.

The analysis and comparison of such characteristics

among the large and complex nuclear genomes of met-

azoans will be most informative, but is presently im-

practical. However, many of these features can be easily

accessed for comparison among the much smaller and

simpler mitochondrial genomes. Metazoan mtDNA is

25,000 times smaller than the smallest nuclear genome,

contains few non-coding nucleotides, has a consistent

gene complement and, at least in some organisms, does

not appear to undergo genetic recombination (see Wol-

stenholme, 1992a,b; Brown, 1985; Moritz, Dowling &

Brown, 1987; Wallace, 1982).

The tRNA genes are usually interspersed among the

protein- and rRNA-coding genes of metazoan mtDNAs.

Their product tRNAs fold into complex secondary struc-

tures due to internal base-pairing, and it is likely that

these structures are present in the polycistronic RNA

transcripts and are used as recognition sites by RNA

processing enzymes (Ojala et al., 1980; Ojala, Montoya

& Attardi, 1981). In Katharina mtDNA there are four

gene junctions which lack an intervening tRNA, and at

each there is a potential secondary structure that positions

the start codon of the downstream gene at an identical

relative location (Boore & Brown, submitted). If these

structures actually form in vivo, they may substitute for

tRNAs as signals for transcript cleavage. In Mytilus

mtDNA there are also sequences capable of forming

potential secondary structures in the several lengthy in-

tergenic regions, and these may also play a role in the

processing of the polycistronic transcript. By investigat-

ing mitochondrial RNA processing in mollusks, it may

be possible to determine whether these secondary struc-

tures actually form, whether they serve as signals for

processing enzymes, and whether any of the RNA pro-

Page 69

cessing mechanisms are evolutionarily derived for (or

within) Mollusca. Such information is, thus, potentially

relevant for molluscan phylogeny.

Animal mtDNA uses several variations of the genetic

code (see Jukes & Osawa, 1990, 1993, and Wolstenholme,

1992a,b). TGA specifies tryptophan. ATA specifies me-

thionine in all but echinoderm and cnidarian mtDNA.

AGA and AGG specify serine in echinoderms, arthro-

pods, nematodes, and platyhelminths, arginine in cni-

darians, glycine in ascidians, and are probably stop co-

dons in mammalian mtDNA. AAA usually specifies lysine,

but in echinoderm and platyhelminth mtDNA it specifies

asparagine. Comparisons of codon usage patterns and

protein alignments suggest that both Mytilus edulis and

Katharina tunicata mtDNAs have a genetic code that is

identical to that of arthropods. Two major protostome

phyla, Mollusca and Arthropoda, are therefore united in

this feature.

While nuclear genes initiate translation exclusively with

the methionine codon ATG, metazoan mitochondrial

genes employ several additional initiation codons, in-

cluding ATT, ATA, ATC, GTG, TTG, GTT, and ATAA

(see Wolstenholme, 1992b). In all but one case, it is un-

clear whether the initial amino acid of mitochondrial

proteins varies with the start codon used, or whether the

alternate start codons are somehow recognized by a

methionyl-tRNA when they occur as the initial codon of

a mRNA. For one human mtDNA gene and transcript,

Fearnley and Walker (1987) have determined by se-

quencing the corresponding protein that ATT in the

initiator position specifies methionine, but that it specifies

isoleucine when it is in an internal position. Katharina

mitochondrial genes appear to initiate translation with

ATG, ATA, and GTG. Mytilus mitochondrial genes ap-

pear to initiate translation only with ATG or ATA, al-

though the possible use of other start codons cannot be

ruled out due to significant ambiguity in determining

the start point of several genes.

Both ATA and ATG code for methionine within the

reading frames of mitochondrial proteins. It is not ob-

vious how the single methionyl-tRNA encoded in most

mitochondrial genomes discriminates initiation codons,

which are translated with N-formyl-methionine, from

internal methionine codons, since both may be either

ATA or ATG. For this reason, it is intriguing thatM ytilus

mtDNA contains two tRNAs for methionine. However,

since the codons expected to pair most efficiently with

each of these tRNAs (ATA and ATG; the anticodons of

these two tRNAs are UAU and CAU) are present as both

initiation codons and in internal positions, the differential

use of these tRNAs in initiation and protein extension is

not likely.

Termination of translation is also unusual in metazoan

mtDNA. In the mtDNA of protostomes all codons are

typically used within open reading frames except the

stop codons TAA or TAG. However, many genes end

with “abbreviated” stop codons of T or TA. In human

mitochondria, where it has been investigated, the gene-

specific message is precisely cleaved after a T or TA, the

first or first and second nucleotides of the terminal codon,

Page 70

after which the stop codon TAA is completed by poly-

adenylation of the gene specific message (Ojala, Montoya

& Attardi, 1981). Both of the mitochondrial genomes

characterized in this work appear to employ this mech-

anism commonly.

Nuclear encoded tRNAs are invariant for a number

of primary and secondary structure features, such as the

typical “three-leaf clover’ structure, the nucleotides T,

pseudo-U, C in one arm (designated the TC arm) and

dihydrouracyl in another (the DHU arm; see Lewin,

1987). The tRNAs of metazoan mtDNA are much more

variable, both in primary and secondary structure. Nem-

atode mitochondrial tRNAs are especially unusual; each

tRNA is unpaired for the entire TYC arm. (Wolsten-

holme et al., 1987; Okimoto et al., 1991, 1992). This

feature is of great potential use for assessing the hypoth-

esis of monophyly of the Aschelminthes, the group into

which nematodes are often placed.

All sequenced metazoan mtDNAs contain two differ-

ent tRNA*™ genes, recognizing codons AGN and UCN,

respectively. It is common for one of these, the

tRNA*"4CN) to lack the potential for base-pairing in the

DHU arm, and this characteristic is found in both Ka-

tharina and Mytilus. However, in Katharina mtDNA

the DHU arm is unpaired in the second serine tRNA,

tRNAseUCN) as well. Since both serine tRNAs must be

charged with the same amino acid, perhaps in Katharina

the DHU portion of the tRNA structure is recognized

by the same charging enzyme. If true, and if other mol-

luscan taxa share this shift in tRNA structure and mech-

anism for serine tRNA charging, this would also be a

useful character for phylogenetic analysis. Sequence de-

termination of the serine tRNA genes from other mol-

lusks will allow us to assess this.

Based on analysis of DNA sequence alone, each of the

two mollusk classes investigated may encode one or more

tRNAs in addition to the normal metazoan complement

of 22. Mytilus mtDNA may contain an additional tRNA

for methionine; Katharina mtDNA may contain addi-

tional tRNAs for serine and phenylalanine. Further in-

vestigation of molluscan mtDNAs will reveal whether

the presence of supernumerary tRNA genes is common

in this phylum. If it is, then this may also indicate that

there are molecular mechanisms in the mitochondrial

system of some mollusks that are specific to the evolu-

tionary history of this phylum and that can be used for

phylogenetic inference.

Ribosomal RNAs also form elaborate secondary struc-

tures through internal base pairing. In comparisons of

rRNA gene sequences from various organisms, it is ap-

parent that deletion or addition of large structures in the

rRNA has been a common mode of evolution (Clary &

Wolstenholme, 1985b; Zwieb, Glotz & Brimacombe,

1981). Perhaps these large scale changes accompany a

shift in ribosome functioning. We are currently devel-

oping models of secondary structure for the small and

large rRNAs of these two mollusk mitochondrial genomes

in hopes of identifying structural variations that might

be used to infer relationships among molluscan lineages.

THE NAUTILUS, Supplement 2

FUTURE DIRECTIONS

Initially, it was surprising to find that the arrangement

of genes in the mtDNA of Katharina was so different

from that of Mytilus. Although radical variation in mi-

tochondrial gene arrangement has been noted in com-

parisons among phyla (as in nematode versus coelomate

mtDNAs), mitochondrial genome rearrangements ap-

pear to be infrequent within phyla. The very different

mitochondrial gene arrangements of Mytilus and Ka-

tharina provide numerous character states for investi-

gating molluscan relationships. By screening additional

molluscan mitochondrial genomes for gene junctions

unique to one of these two arrangements, and by com-

paring these arrangements with those of non-mollusks,

it may be possible to deduce the broad pattern of the

evolutionary history of Mollusca. Specifically, the first

goal is to investigate mitochondrial gene arrangements

in representatives of each of the remaining classes of

mollusks. Non-molluscan protostomes must also be in-

vestigated to help characterize gene arrangements as

primitive or derived.

Investigating gene arrangements by determining com-

plete mtDNA sequences is very costly and laborious.

With the knowledge gained from the complete mtDNA

sequences of Katharina and Mytilus, it may be possible

to employ less costly and easier methods to screen other

molluscan taxa for particular gene arrangements that are

likely to be phylogenetically informative. For example,

the polymerase chain reaction (PCR) can be used to

selectively amplify gene boundaries that are unique to

one of these two arrangements, and a large number of

animals can be rapidly tested for the arrangement of

several of the large, well-conserved genes by Southern

hybridization analysis.

The development of DNA amplification via PCR (see

Innis et al., 1989) has enabled DNA sequence determi-

nation without the difficult and time-consuming proce-

dures of restriction mapping and cloning. As outlined in

figure 4, a segment of DNA is amplified to sufficient

quantity for gel analysis and DNA sequence determi-

nation by employing two oligonucleotides complimen-

tary to flanking sequences. These oligonucleotides serve

as primers for the synthesis of new DNA strands by a

thermostable DNA polymerase.

The success of a PCR amplification is critically de-

pendent on the complementarity of the oligonucleotide

primers to the sequences flanking the DNA to be am-

plified. The complete mtDNA sequences of Katharina

and Mytilus aid in primer design for screening additional

molluscan mtDNAs in two ways. First, since closely re-

lated organisms are more likely to share sequence iden-

tities, the sequences of the primers can be chosen to

match well conserved portions of these two genomes,

increasing the likelihood of a successful amplification in

the target genome. Second, the gene arrangements

ofMytilus and Katharina mtDNAs give hypotheses of

gene arrangement to test on additional animals, since

the PCR can only be successful if the primers “face” one

J. L. Boore and W. M. Brown, 1994

another (see figure 4). Since there is a practical limit to

the size of a DNA sequence that can be successfully

amplified, primers must be selected in genes that are

likely to be closely spaced in molluscan mtDNA. Gene

arrangements to be investigated by PCR can be selected

based on both the likelihood of finding sequences suitable

for PCR primers in adjacent genes and on the amount

of phylogenetic information in the sharing of particular

gene arrangements.

One strength of this approach is that DNA sequence

information is concurrently gained, which can be used

in sequence-based phylogenetic analyses as a separate

test of relationships. In addition, this technique precisely

maps contiguous gene arrangements, and may identify

tRNA rearrangements which would be invisible to the

technique of Southern hybridization. Crude and highly

impure DNA preparations can be used for amplification,

including those made from ancient tissues and museum

specimens (Thomas, et al., 1990; Kocher et al., 1989).

PCR amplification also enables the analysis of DNA from

very small organisms and from tiny portions of tissue

from rare ones.

The main disadvantage of PCR is that it can not iden-

tify novel gene arrangements, but only test for hypoth-

esized arrangements (other than small gene insertions).

Primers must be designed to amplify a specific segment,

opposing one another over a short segment of DNA. If

the flanking sequences to which the primers are designed

have rearranged significantly, no amplification will oc-

cur. This negative result provides no information, be-

cause amplification may fail for numerous reasons in

addition to gene rearrangement (e.g., because there have

been mutations in a few nucleotides in the region com-

plementary to the primer sequences).

Figure 5 illustrates a gene arrangement that may be

amenable to investigation in other molluscan mtDNAs

through PCR amplification. The region to be amplified

is flanked by the genes for the I]-rRNA and cytb. Each

of these two genes individually has been successfully

amplified by PCR from a variety of organisms (Kocher

et al., 1989; D. Stanton and W. Brown, unpublished

data). The I-rRNA and cytb genes are well-conserved,

based on comparisons among widely divergent taxa; this

maximizes the likelihood of finding primer sequences

that are useful over a broad taxonomic range.

Determining the arrangement of these particular genes

in other mollusks may yield phylogenetically useful in-

formation. In Katharina and Drosophila mtDNAs, ND1

is between |-rRNA and cytb. This represents a symple-

siomorphy, since vertebrate mtDNAs share this charac-

teristic as well. The block of genes tRNA!MCUN)-

tRNAMCUR)_NDI is shared between the mtDNAs of Ka-

tharina and Mytilus, but in the latter this entire block

is translocated to another region of the genome. Any

mollusks that share this translocation with Mytilus

mtDNA are likely to have a common evolutionary history

with Bivalvia. In comparing the mtDNAs of Katharina

and Drosophila, the block tRNAS*(YC)-cytb-ND6-

tRNA? has been inverted. Any mollusks that share this

Page 71

S E

Digestion

S Electrophoresis

B Hybridization

E Eee

B S eo

B E Gene is

located here

Oligonucleotides matching flanking sequence

B ==>

ves | uccuny | nor seucny |__|

Double-stranded DNA

TUTTE

Heat to denature, cool to anneal primers

TTTTTITITITIIITIITITIIIITITITIITIITTTtittitittiittity

——_—

LITITITI TTI

Extend new strands

TTTTTTTTTTTTT TTT TTT TTT TTT ttt rrr tririttiiritT

——pe LLL

TOT

LUT TPIT TTT

Repeat for 20-40 cycles for exponential DNA amplification

Figure 4. Two alternative techniques for determining the ar-

rangement of mitochondrial genes. (A) The technique of

Southern hybridization (Southern, 1975). A cleavage map of

the relative locations of restriction enzyme sites in the mtDNA

is constructed. Each enzyme recognizes a particular short se-

quence of DNA (4-8 bp). E, S, and B in this figure represent

the locations of three independent restriction enzyme (EcoRI,

SalI, and BamHI) cleavage sites on the circular map of the

mitochondrial genome. The mtDNA is cleaved with each en-

zyme, the fragments produced are separated according to size

by electrophoresis through an agarose gel, the fragments in the

gel are transferred to a membrane and probed using a radio-

labeled DNA fragment that contains all or part of the gene of

interest. The fragment patterns generated by each restriction

enzyme are labeled E, S, and B on the depiction of the gel.

The radiolabeled probe will hybridize only to the fragments

of the mtDNA that contain the corresponding gene, shown in

bold. This information, when correlated with the mtDNA

cleavage map, provides the gene’s position in the mitochondrial

genome. (B) The technique of PCR amplification (Innis et al.,

1987). Oligonucleotide primers that are complementary to the

DNA sequence flanking the region of interest are determined

and synthesized. The double-stranded template DNA is heat

denatured, mixed with a vast excess of the oligonucleotides,

then cooled to allow annealing of the oligonucleotides to the

template. The oligonucleotides serve as primers for the synthesis

of new strands of DNA in a reaction using thermostable DNA

polymerase. This cycle of heat (denaturation) and cool (anneal

and synthesize) is repeated many times (typically 20-40) to

exponentially amplify the DNA region between the primers to

provide amounts that allow manipulation and determination

of the DNA sequence.

Page 72 THE NAUTILUS, Supplement 2

CUN

Drosophila T=cRNA 2]

Apis eer re ea a

UCN

CUNUUR

Katharina (eae ia ae a a

P| UCN

CUNUUR

syed line coz

UUR

VeAtCREARSS [Tea

vine JSS amore B

Echinoderms

fairies AND

He te tdogvas

Metridium

Figure 5. The arrangements of several mitochondrial genes particularly amenable to investigation by PCR (see text) and potentially

informative for molluscan phylogeny. Gene abbreviations are as in figure 2. Genes are transcribed from left to right except those

depicted below the main line to designate opposite orientation. The broken line shown for vertebrate mtDNA indicates a large,

undepicted portion of the genome. The positional relationships of genes in the insect and mollusk mtDNAs are depicted as in figure

2; the arrangement of these genes in mtDNAs of other organisms are shown for comparison (references in text except for Metridium,

D. R. Wolstenholme, personal communication). Genes are not drawn to scale.

inversion with Katharina are likely to also share a com-

mon ancestor with Polyplacophora. If the arrangements

of these genes is determined for representatives of all

molluscan classes, it should be possible to formulate a

phylogenetic hypothesis for the Mollusca, and to test the

hypothesis with additional gene arrangement data.

The second technique for rapidly screening mito-

chondrial gene arrangements is Southern hybridization

(Southern, 1975), which localizes genes relative to a phys-

ical map of the mtDNA. This technique is outlined and

described in figure 4. Cleavage sites for restriction en-

zymes which recognize specific short sequences of DNA

determine the physical map. Restriction endonuclease

cleavage generates DNA fragments, which are separated

by size using gel electrophoresis, visualized, and related

back to their position in the mtDNA. Gene-specific probes

that are labeled with a radioisotope are exposed to the

gel-separated DNA bands under hybridizing conditions.

The probes hybridize specifically to the DNA bands which

include the probe gene. The position of this gene can

then be correlated to the physical map of the mtDNA

and localized relative to other probed genes. The sub-

cloning necessary for determining the complete mtDNA

sequence of Katharina and Mytilus provides the gene-

specific probes necessary to this technique.

One limitation of the Southern hybridization tech-

nique is the requirement for a detailed cleavage map of

the mtDNA. This is most effectively accomplished if the

mtDNA can be recovered in pure form and in large

quantity, which is often difficult and may be impossible

for some small or rare organisms. The resolution of the

gene map will be limited by the spacing of the restriction

enzyme cleavage sites. The main advantages of Southern

hybridization are that 1) the relative location of widely

spaced genes can be determined, whereas PCR can only

be applied to contiguous blocks of closely adjacent genes

J. L. Boore and W. M. Brown, 1994

Drosophila CO3

Katharina

Mytilus

Page 73

Col

AGN

SI oR | 2 0) S| 2 [co

UA AGN UCN

Lae EE Bs eS coe

Vertebrates

ANCE

Echinoderms

Figure 6. The arrangements of several mitochondrial genes promising for Southern hybridization analysis (see text). Gene abbre-

viations are as in figure 2; genes are transcribed from left to right except those depicted below the main line to designate opposite

orientation (references in text). The broken lines shown for Drosophila and vertebrate mtDNAs indicates a large, undepicted portion

of the genome.

and 2) no prior hypothesis of gene arrangement is nec-

essary for Southern hybridization, in contrast to the case

for PCR.

Figure 6 shows the relative arrangement of four genes

in the Mytilus, Katharina, and Drosophila mitochon-

drial genomes that may be especially useful for inves-

tigating molluscan relationships. In general, the gene

arrangements of Katharina and Mytilus are difficult to

relate. However, discounting tRNA genes, the arrange-

ment of CO8, ND2, ND8, and CO1 differ only in that

ND2 and ND3 have exchanged positions. The arrange-

ment of these genes in Drosophila mtDNA is similar in

that CO8 is near ND3 and ND2 is near CO1, but these

two pairs of genes are separated by approximately 10 kb

of DNA sequence. Each of these four genes is well con-

served enough to expect that they could be detected in

the mtDNA of other mollusks by hybridization to probes

of Mytilus or Katharina mtDNA. Determining the ar-

rangement of these genes in the mtDNAs of other mol-

lusks might suggest whether the rearrangement that

brought ND3 near to ND2 occurred near the base of the

molluscan radiation. If so, it would provide a synapo-

morphy suggesting the monophyly of Mollusca. It would

also inform us about whether other classes of mollusks

share with Mytilus the derived condition of inverting

the positions of ND2 and ND§8, thus signaling a common

ancestry with Bivalvia.

Admittedly, most evolutionary relationships will not

be-resolved by comparisons of mitochondrial gene ar-

rangements. Genome rearrangements may not have oc-

curred during the period of shared history, or subsequent

rearrangements may have erased similarity. The main

advantage of this data set is that relationships are very

reliably inferred when accompanied by a genome re-

arrangement. The complete sequences of the mtDNAs

of Katharina and Mytilus facilitate even more rapid

investigation of the patterns of mitochondrial genome

rearrangments among mollusks. As more mtDNAs are

investigated for gene arrangement and other complex

molecular characteristics, higher level relationships among

mollusks and among other taxa may be resolved.

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THE NAUTILUS, Supplement 2:79-84, 1994

Page 79

The Mitochondrial Genome of Cepaea nemoralis (Gastropoda:

Stylommatophora): Gene Order, Base Composition, and

Heteroplasmy

Jonathan Terrett

Sue Miles

Department of Genetics

Queens Medical Centre

Clifton Boulevard

Nottingham, NG7 2UH, U.K.

Cromwell Road

Richard H. Thomas

Department of Zoology

The Natural History Museum

London, SW7 5BD, U.K.

ABSTRACT

The 14.1 kb mitochondrial genome of the terrestrial gastropod

Cepaea nemoralis has been cloned and completely sequenced.

Sequences coding for 13 proteins and the large and small sub-

units of ribosomal RNA have been identified. All metazoan

mtDNAs examined to date, except for the nematodes Caenor-

habditis elegans and Ascaris suum, and the bivalve mollusc

Mytilus edulis, contain an ATPase subunit 8 gene. The presence

of ATPase 8 in Cepaea mitochondrial DNA suggests that this

gene has been lost independently from the nematode and bi-

valve mitochondrial genomes. Commonly genes are encoded

on both strands of mtDNA molecules, and this is true of the

Cepaea mitochondrial genome, but not of the nematodes and

Mytilus. Base composition is the least biased of any reported

metazoan mitochondrial genome. Comparisons are made with

other metazoan mitochondrial genomes. The cloned genome

has been used to infer the presence of polymorphisms in the

size of mitochondrial genomes in Cepaea by analysis of the

lengths of restriction fragments. These polymorphisms have

aided the identification of heteroplasmic snails. A protocol is

described that can be used to extract intact gastropod mito-

chondrial DNA. This DNA is sufficiently free from inhibitors

for use in restriction enzyme digestions and for amplification

using the polymerase chain reaction.

Key words: Mitochondrial DNA, Mollusca, molecular evolu-

tion, heteroplasmy.

INTRODUCTION

The number of completely sequenced mitochondrial ge-

nomes is increasing rapidly and the evenness of taxo-

nomic sampling is improving. Sequences of seventeen

metazoan mitochondrial genomes are now available from

ten vertebrates [six placental mammals (Anderson et al.,

1981; Bibb et al., 1981; Anderson et al., 1982; Gadaleta

et al., 1989; Arnason et al , 1991; Arnason et al., 1992),

two fish (Chang & Huang, 1991; Tzeng et al., 1992), a

bird (Desjardins & Morais, 1990), and a frog (Roe et al.,

1985)], two insects (Clary & Wolstenholme, 1985; Crozier

& Crozier, 1993), two sea urchins (Cantatore et al., 1989;

Jacobs et al., 1989), and three nematodes (Okimoto et

al., 1992; Okimoto et al ., 1991). Many other taxa have

been sequenced in part and of these the complete gene

order is known for three, the mussel, Mytilus edulis

(Hoffmann et al., 1992), a sea star (Smith et al., 1989)

and the codfish, Gadus morhua (Johansen et al., 1990).

Analyses of these genomes are revealing a host of inter-

esting phenomena (reviewed in Wolstenholme, 1992), as

well as providing tools for population and phylogenetic

studies (Avise, 1989).

Mitochondrial sequences from molluscs promise to

greatly enhance our understanding both of the molecular

evolution of metazoan mitochondria and the evolution-

ary relationships of the molluscs themselves (Boore &

Brown, 1994). In this paper we present the order of

protein coding genes and ribosomal RNA (rRNA) genes

in the mitochondrial genome of Cepaea nemoralis and

compare it with those of other metazoans. Comparisons

of DNA sequence across the phyla can be used to infer

mechanisms of mtDNA replication and the mode of base

substitution. We make preliminary observations on these

points. We also present here a reliable protocol for the

extraction of mtDNA from gastropods which is suitable

for restriction fragment length polymorphism (RFLP)

studies and for polymerase chain reaction (PCR) ampli-

fication. Extraction of mitochondrial DNA from mol-

luscs, and in particular terrestrial gastropods, has been

problematic (Stine, 1989; J.S. Jones, personal commu-

nication); the availability of a simple and reliable method

opens up many possibilities for further work on these

animals.

MATERIALS AND METHODS

mtDNA extractions: Several protocols for the extraction

of mollusc mtDNA have already been published (Ski-

binski & Edwards, 1987, Stine, 1989). The following

Page 80

method combines procedures from both of these and can

be performed in less than two hours. It has been used

successfully and repeatedly on Cepaea and Helix (Ter-

rett, 1992) and Littorina (E. Rumbak, personal com-

munication). Snails are killed by placing at —80°C for 1

hour. They are then defrosted at 50°C for 5 minutes.

After removing the snail from its shell, the hepatopan-

creas is minced thoroughly with a scalpel blade and then

homogenised in 3 ml of 0.25M sucrose in TEK (50mM

Tris/HCl pH 7.5, 1OmM EDTA, 1.5% KCl (w/v)) in a

Dounce homogenizer (7ml) with five to ten strokes of

the “A’ pestle. The homogenate is transferred to two

1.5ml microfuge tubes. Nuclei and other cell debris are

removed by centrifuging at 6,000 rpm (low speed) in a

microfuge for two minutes. The supernatants are trans-

ferred to two fresh microfuge tubes, and mitochondria

collected by centrifugation at 13,000 rpm (high speed)

in a microfuge for five minutes. The soft mitochondrial

pellets are resuspended in 600 ul of 0.25M sucrose in

TEK, and then 600 ul of 1.1M sucrose in TEK is layered

beneath. Mitochondria are collected by centrifuging at

high speed in a microfuge for 10 minutes. The mito-

chondrial pellet is then resuspended in 600 pl of STE100

(100mM NaCl, 10mM Tris/HCl pH 8.0, 100mM EDTA)

and intact mitochondria are lysed by the addition of 80

ul of 10% Nonidet P-40 followed by gentle shaking.

Mitochondrial membranes are removed by centrifuga-

tion at high speed in a microfuge for one minute. Mu-

copolysaccharides are removed by the addition of 100

ul of 5M NaCl to the supernatant followed by 80 ul of

CTAB/NaCl (0.7M NaCl / 10% CTAB). This mixture is

shaken vigorously before incubating at 65°C for fifteen

to thirty minutes. The precipitate that forms contains

the mucopolysaccharides and is removed by filling the

tube with chloroform, shaking vigorously to form an

emulsion, and centrifuging at high speed for three min-

utes in a microfuge. The mtDNA containing supernatant

is removed and subjected to two phenol/chloroform ex-

tractions and one chloroform extraction before the nu-

cleic acids are precipitated. This is generally achieved

by adding an equal volume of propan-2-ol (20°C) to the

aqueous phase, shaking vigorously, and centrifuging im-

mediately at high speed in a microfuge for ten minutes.

The yield from the hepatopancreas of a single Cepaea

is not sufficient for restriction digest fragments to reliably

be seen on an agarose gel stained with ethidium bromide

(EtBr). However, up to fifteen restriction digests can be

visualised after Southern (1975) blotting and detection

using digoxigenin (Boehringer Mannheim).

Restriction enzyme digestions and cloning: C. nemor-

alis mtDNA was extracted as above, electrophoresed on

a 0.8% EtBr/agarose gel, and open circles were extracted

using GenecleanII (Bio 101). This mtDNA was then di-

gested with BamHI and cloned into AGem11 (Promega)

using LE392 host. The entire genome was then subcloned

into the SstI and HindIII sites of pGem7zf(+) (Promega)

maintained in E. coli strain JM101. All clones were ver-

ified as containing Cepaea mtDNA by probing against

THE NAUTILUS, Supplement 2

mtDNA extractions. Preparation of plasmid, and pha-

gemid DNAs were as in Sambrook et al. (1989).

Sequencing and sequence analysis: DNA sequences

were obtained using the dideoxy chain termination meth-

od (Sanger et al., 1977) from sets of deletion subclones

(Henikoff, 1984) and subsequent extraction of single

stranded phagemid DNA (Vieira & Messing, 1987).

Cepaea mitochondrial protein coding genes were

identified by the similarity of their inferred amino acid

sequences with those of Drosophila yakuba (Clary &

Wolstenholme, 1985) and humans (Anderson et al., 1981),

and in some cases verified by similarities in hydropathy

profiles (Kyte & Doolittle, 1982). rRNA genes were iden-

tified by the similarities of the DNA sequences of D.

yakuba and Cepaea.

Southern blotting and DNA hybrid detection: Standard

Southern (1975) blotting techniques were used to transfer

DNA onto nitrocellulose. The entire mitochondrial ge-

nome of C. nemoralis within its \ vector was used as a

probe after labelling with digoxigenin. Labelling and

detection procedures were done according to the man-

ufacturer’s instructions (Boehringer Mannheim). Blots

were washed in 0.1 x SSC at 65°C (2 <x 15 minutes).

Analysis: Inferred amino acid sequences were aligned

with the program CLUSTAL V (Higgins et al., 1992)

using the default parameters. Hydrophilicity plots were

produced using MacVector (IBI) and additional align-

ments and analyses were done with DNASTAR.

RESULTS

The entire mitochondrial genome of Cepaea nemoralis

has been sequenced. At this writing all of the genome

has been sequenced on one strand and approximately

4,000 bases of the 14,099 bp genome have been con-

firmed by sequencing both strands (Terrett, 1992). The

sequence has enabled the arrangment of the protein and

rRNA genes to be established and the base composition

to be analysed.

Southern blots of Cepaea mtDNA that had been di-

gested with Kpn1 show polymorphism in the size of the

mitochondrial genome and heteroplasmy.

DISCUSSION

Gene Content

The ‘full’ complement of thirteen protein coding genes

has been identified in the Cepaea sequence, i.e., cyto-

chrome b (cytb), cytochrome oxidase subunits I to II

(COI, COII, and COIII), NADH dehydrogenase subunits

1-6 and 4L (ND 1-6, 4L), ATP synthase subunits 6 and

8 (ATPase 6 and 8) and two rRNA genes (12S and 16S).

Many of the genes were easily identified by comparing

the Cepaea sequences with the Drosophila sequences

(Clary & Wolstenholme, 1985). However, although con-

served amino acid domains were identified in ND6,

NDAL, and ATPase 8 (Figures 1-3), these were not long

J. Terrett et al., 1994

Human MECN or ea te

PE: P.SPK

Drosophila IPEMAP- ISWLLLFEVESETFILFCSIN-YYSIMBTSPKSNELANTL NSH

cess? 2 sik ik slr le Sae5 5) IPSeeeeee N NSM K X

Cepaea GEL SEH/UY (GIP TEE TIeNTIFEL¢IHi=== FLV ETEASTPEKRPAANRNEH: LKLX

Figure 1. Amino acid alignment of the ATPase 8 protein se-

quences from Homo sapiens, Drosophila yakuba and Cepaea

nemoralis. Identical amino acids are indicated by single letter

codes between the sequences and conservative substitutions

(French & Robson, 1983) by colons.

enough to be confident of their identification. The sim-

ilarity of the hydrophilicity profiles of the proposed Ce-

paea proteins to those of other organisms (Figure 4) helped

to verify the identity of these genes.

Most metazoan mtDNAs encode an ATPase subunit

8. The exceptions to date are the nematodes Caenor-

habditis elegans and Ascaris swum (Okimoto et al., 1992),

and the bivalve mollusc Mytilus edulis (Hoffmann et

al., 1992). The presence of ATPase 8 in Cepaea mito-

chondrial DNA suggests that this gene has been lost in-

dependently from the bivalve and nematode mitochon-

drial genomes.

Has the function of ATPase 8 been taken over by some

other protein in mussels and nematodes? Have there been

two independent losses of the ATPase 8 gene from mi-

tochondrial lineages leading to mussels and nematodes?

Did a common ancestor of molluscs and nematodes re-

locate the mitochondrial ATPase 8 gene to the nucleus,

only for the Cepaea lineage to move it back again? More

sequences from molluscan taxa are required to answer

these questions.

The Cepaea ATPase 8 gene is adjacent to, but not

overlapping with, ATPase 6. However, in Cepaea ATP-

ase 8 and ATPase 6 are in the opposite orientation from

Drosophila, vertebrates, and echionoderms, where the

two genes overlap in the order ATPase 6—-ATPase 8. In

an attempt to explain the continued existence of mito-

chondrial genomes, von Heijne (1986) suggested that

ATPase 8 has not moved to the nuclear genome because

the overlap with ATPase 6 cannot be overcome. ATPase

6 remains encoded by mtDNA because hydrophobic do-

mains within the protein would act as signal sequences

causing it to be incorrectly transported (i.e. not to the

mitochondrial membrane). The absence of ATPase 8

Cepaea _CFISVYFLLASFSVAVCITLIFSTFIRSPLIML VFSFFALVCSVSSYVYF

Drosophia se a Sica Ce SUT GLUT TER UN en

Cepaea _TDFFPYLLYLVYVGGLLVLMLYMVRYFNNFSFLEGMYFSPAEGLVATCL-1

Y:b:l:::GG:LVL.IY:.. :N

Drosophila SPL vaitellce lect SUA GNEMENTC HR neSHPS Ere t

Cepaea —_—~FS-VLINVYLYGYTFVSSKALYSGASCYYSGMNLILLVLL-LLYVFLSVSF

Drosophila 1 GaP HSHETUUY WRU ESRI IS APRD LS TAL ET ISL

Cepaea MLRLGGRTFSVGITSRYLKAVLEYGNFGSW

Drosophila UNYLLETEEWKETKLEKGPLRUNSK

Figure 2. Amino acid alignment of the ND6 proteins of Cepaea

nemoralis and Drosophila yakuba. Similarities are as in Fig-

ure l.

Page 81

Cepaea MLVLLFF-LREKHF----FYF---KNSLLFSLLSLELVTLFVLYVCCTVI

Ascaris TIFIF------ ISF-LSLF-F--KWQRLMFILISLEFIVMSLFILFSGDL

Drosophila MIMILYWSLPMILFILGLFCFVSNRKHLLSMLLSLEFIVLMLFFMLFLYL

* * KKK

Cepaea SAHVTSMVLTCFFLCFAASGAAVG-CRYCSLSRCTDD-------- M

Ascaris NEMMF--FY---FMCFSVVSSVLGMVVMVGNVKFYGSD----LCLF

Drosophila NMLNYENY FSMMFLTFSVCEGALGLSILVSMIRTHGNDYFQSFSIM

Figure 3. Amino acid alignment of the ND4L proteins of Ce-

paea nemoralis, Drosophila yakuba, and Ascaris suum. Iden-

tical amino acids are indicated by asterisks, conservative sub-

stitutions by dots, and a conserved region is underlined.

from Mytilus and nematodes, and its relocation in Ce-

paea cast doubts upon the necessity of the overlap.

Gene order

When the first few mitochondrial genomes were se-

quenced the identical gene order seen in placental mam-

mals (e.g. Anderson et al., 1981) and a frog (Roe et al.,

1985), plus the possibility of deriving the gene order of

the protein and rRNA genes of a sea urchin (Cantatore

et al., 1989) from that of a vertebrate with only two

rearrangements (Wolstenholme, 1992), gave the im-

pression that gene order was likely to be very conser-

vative within phyla. The strikingly different gene orders

of the bivalve Mytilus and the pulmonate gastropod Ce-

paea show that mitochondrial gene order is not neces-

sarily at all conservative.

Figure 6 shows a linearised comparison of the genomes

of Mytilus and Cepaea. The lack of similarity in the

gene orders is striking. The Cepaea genome, unlike My-

tilus, contains genes encoded on both DNA strands. In-

ferring simple inversion events in either organism does

not increase the similarity. Cepaea and vertebrates share

some gene boundaries but the transcriptional orders are

all different, suggesting the similarity does not result

from shared ancestry. The difference in gene order be-

tween these two molluscs is by far the greatest reported

within any phylum.

The location of genes on both strands of the Cepaea

genome is particularly interesting because each set of

protein genes on each strand has a rRNA gene between

them (Figure 5). rRNA sequences have been inferred to

function during initiation of transcription of mtDNA

(Montoya et al., 1982). There are very few nucleotides

in the Cepaea mitochondrial genome that are not as-

signed to genes (Terrett, 1992). Previously sequenced

metazoan mtDNAs contain sequences involved in rep-

lication and transcription, e.g. the D-loop in vertebrates

(Clayton, 1992), and A+T rich regions in insects (Clary

& Wolstenholme, 1985). It will be interesting to see where

transcription and replication are initiated in the tightly

packed genome of Cepaea.

Base composition and codon usage

The base composition of mtDNAs was first shown to be

biased when Brown (1981) separated the two strands of

human mtDNA on a cesium chloride gradient by virtue

Hydrophilicity

Amino Acid Number

Figure 4. Hydrophilicity profiles of ATPase 8 proteins showing

the characteristic hydrophobic amino end and hydrophilic car-

boxy end.

of their different base compositions and thus their dif-

ferent molecular weights. This bias has now been char-

acterised in vertebrates as being caused by a bias towards

G and T on one strand, and towards C and A on the

other. The mtDNA’s of nematodes and Drosophila show

such a large bias towards A and T that the strands do

not differ significantly in density. Table 1 shows the base

compositions at the third positions of codons for the Ce-

paea protein genes, separated by coding strand. A and

T contents are similarly high on both strands and there

appears to be a slight bias against G on the minor (fewer

genes) strand.

A further indication of a small bias in the mtDNA of

Cepaea can be seen by examining the frequencies of the

two families of leucine codons. They are grouped as TTR

(R represents G or A) and CTN (N is any base). Thus

there are two TTR codons and four CTN codons. If codon

usage is independent of base composition then we would

expect roughly twice as many CTN codons than TTR

codons. However, in the A+T rich genome of A. swum,

the ratio of TTR:CTN codons is 6.7:1 (Okimoto et al.,

1992). Within the CTN group in A. suum the T bias is

obvious as 57 of 67 CTN codons are CTT. In Cepaea

fairly even use of these codons can be seen, the TTR:

CTN ratio being 0.81:1 for all proteins (the ratio for only

the minor strand is remarkably similar; 0.75:1) so that

the slight bias towards A and T is all that is evident. This

is reinforced by the CTN group as 206 codons are CTA/

T and 120 codons are CTG/C. The mtDNA of Mytilus

shows a greater bias (especially against C at the third

position of codons on the sense strand) but this bias is

very small compared with those of the vertebrates.

Polymorphism in genome size

As mtDNA’s are studied more at the population level,

and thus more individuals are screened, we are becoming

increasingly aware of polymorphisms in the sizes of mi-

tochondrial genomes within species. At the extreme, vari-

THE NAUTILUS, Supplement 2

16SrRNA

Cepaea nemoralis

14099 bp

Figure 5. The mitochondrial genes of Cepaea nemoralis in

their native circular arrangement. Most genes are transcribed

in the clockwise direction. The minor strand encodes five genes

transcribed in the other direction (small arrows).

ation can occur within one generation (Cook & Zouros,

1994). Figure 7 shows the existence of a size polymor-

phism in a Cepaea population. If this polymorphism is

as rapidly fluctuating as that in scallops (Gjetvaj et al.,

1992), our ability to use mtDNA restriction fragment

length polymorphisms to infer the population structure

of Cepaea will be limited. However, the sequence can

be used to design primers to amplify and sequence regions

of the mitochondrial genome not subject to the size vari-

ation.

That the mitochondrial genomes of Cepaea and My-

tilus cannot be aligned with respect to gene order shows

the potential within the molluscs of inferring relatedness

from gene orders (Boore & Brown, 1994). As with all

comparisons at the molecular level, plateaus will be

reached above which comparisons become meaningless.

This point is demonstrated with the Mytilus and Cepaea

gene orders. There is also great opportunity to study the

Table 1. Percent base composition at codon third positions in

the mitochondrial protein genes of Cepaea nemoralis. The

major strand encodes nine proteins and the minor strand en-

codes four proteins.

Percent base composition

Base Major strand Minor strand

G 19 13

A Di 23

T 36 38

C 18 26

J. Terrett et al., 1994

Page 83

Cepaea nemoralis

ND4L

12S :

ost) Le 2 ee EE SSS ed

ATP 8

Mytilus edulis

ND4L

12S

_@ (SI Sees aa Ee re eee sl

Figure 6. Linear representation of the mitochondrial genomes of Cepaea nemoralis and Mytilus edulis (Hoffmann et al., 1992).

Arrows indicate the DNA strand on which genes are encoded. Unlabelled sections of the genomes contain tRNAs and noncoding

sequences. There is no obvious way to derive one gene order from the other.

evolution of mtDNA at a fine level within the molluscs.

The polymerase chain reaction (PCR) could be employed

to speed up the production of these data.

ACKNOWLEDGEMENTS

We thank the SERC and the NERC for financial support,

and David Skibinski for useful discussions on extraction

procedures.

12346567

Figure 7. KpnI restriction digests of mtDNAs isolated from

individual snails. Lanes 1-3 were collected from Derbyshire

and 5-7 from Lincolnshire. Lane 4 is \ DNA cut with Hind

III. Lanes 1, 2, and 5 show fragments expected from the cloned

sequences. Thus lanes 6 and 7 contain a larger than expected

fragment. Lane 3 shows the expected fragments plus the larger

one present in lane 6 and this snail was probably heteroplasmic.

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THE NAUTILUS, Supplement 2:85-90, 1994

Page 85

The Highly Variable and Highly Mutable Mitochondrial DNA

Molecule of the Deep Sea Scallop Placopecten magellanicus

Douglas I. Cook!

1 Marine Gene Probe Laboratory

Department of Biology

Dalhousie University

Halifax, N.S., Canada, B3H 4J1

Eleftherios Zouros !2

2 Department of Biology

University of Crete and

Institute of Marine Biology of Crete

711 10 Iraklion, Crete, Greece

ABSTRACT

Whereas in the vast majority of animals the mitochondrial DNA

(mtDNA) molecule rarely exceeds 20 kb (kilobases) in length

and is size-invariable among conspecific individuals, in several

invertebrates, fish, amphibians and reptiles the length of this

molecule can be much larger and may vary within and among

individuals. An extreme case is presented by the deep-sea scal-

lop Placopecten magellanicus, where the molecule is, on av-

erage, 36 kb and may vary from 31 to 42 kb. Most of this

variation is due to arrays of tandemly repeated sequences whose

copy number varies among molecules. Such arrays (each con-

sisting of a different repeated sequence) occur in more than

one region of the mtDNA molecule. Once present, these arrays

allow for frequent errors to occur during DNA replication, with

the result that new size variants appear at a very high rate.

The resulting mtDNA size polymorphism may be instrumental

for long-term evolutionary phenomena (such as the rearrange-

ment of genes around the molecule), but, because of its rapid

turn-over, does not provide useful information for taxonomic

studies.

Key Words: mtDNA size variation, scallops, mtDNA evolu-

tion.

INTRODUCTION

Several recent reviews (e.g. Harrison, 1989; Avise, 1991;

Meyer, 1994) have dealt with the advantages of animal

mitochondrial DNA (mtDNA) as a tool for taxonomic

and population genetics studies. Briefly, these include

the ease with which the mtDNA can be separated from

nuclear DNA, the property of homoplasmy (i.e. that all

mtDNA molecules of an individual organism are iden-

tical), the accumulation of base substitutions at a faster

rate than in coding single copy nuclear DNA, and the

maternal transmission which is particularly useful for

studies of population structure in species whose distri-

bution is mainly affected by female dispersion.

With the exception of maternal inheritance (which

applies to the mtDNA molecule as a whole), these prop-

erties of the animal mtDNA appear to be true for nu-

cleotide variation, but not for variation caused by changes

in the length of the molecule. Length variations in animal

mtDNA were originally considered to be either very rare

or of negligible size (Attardi, 1985). This still appears to

be the case for homeotherms. In many species of inver-

tebrates, fish, amphibians and reptiles, however, the length

of the mtDNA molecule can vary substantially from in-

dividual to individual, and the same individual may car-

ry mtDNA molecules of different lengths (for review see

Moritz et al., 1987). It became clear from the first studies

of length polymorphism that this type of variation is

different from single nucleotide substitution in several

ways. Whereas nucleotide substitutions may occur more

or less randomly around the molecule, length polymor-

phism is localized in (or near) a specific region of the

genome, the region that controls the initiation of tran-

scription. Also, whereas nucleotide heteroplasmy (the

presence of two or more types of mtDNA molecules in

the same organism) is rare, length heteroplasmy is com-

mon. In fact, many length variants in several species

have been observed only in the state of heteroplasmy

(Willis, 1987; Bentzen et al., 1988).

There are two main types of mtDNA length variation

in animals. One is due to single duplications of part of

the molecule. The other is due to repeated sequences,

whose copy number vary among molecules. The level of

variation of the latter type [which is akin to the VNTR

(variable number of tandem repeats) polymorphism of

nuclear DNA] is generally much higher than that of the

first.

These differences between base substitution variation

and length variation suggest that the two types of mtDNA

polymorphism have quite different evolutionary dynam-

ics and, thus, can have different uses in population stud-

ies. This communication provides a short description of

size polymorphism of an exceptionally large mtDNA

molecule, that of the deep-sea scallop, and, also, reports

original observations about the rate with which new size

variants appear in this molecule.

Page 86

AN OVERVIEW OF THE mtDNA

OF THE DEEP SEA SCALLOP,

Placopecten magellanicus (Gmelin, 1791)

The mtDNA of the deep-sea scallop remains the largest

metazoan mtDNA reported (Snyder et al., 1987), even

though exceptionally large mtDNA molecules were re-

ported in the nematode Romanomermis culicivorax

(Powers et al., 1986) and bark weevils of the genus Pis-

sodes (Boyce et al., 1989). Figure 1 is a simplified version

of the restriction map showing the regions of the mol-

ecule at which size variation has been observed. Most of

the variation is contained within a part of the genome

defined by the EcoRI #1 site (arbitrarily positioned at

the 12 o'clock point of the circular molecule) and the

first SphI site clockwise from the EcoRI #1 site. Origi-

nally, it was thought that this part of the molecule con-

tained two adjacent yet independently varying sub-

regions, named “locus I” and “locus II’. Locus I consists

of tandemly repeated copies of a 1449 bp (base pair)

sequence, the number of copies varying from two to

eight. The molecule shown in figure 1 contains three

such repeats. The molecular basis of the polymorphism

at locus I was studied by LaRoche et al. (1990), and its

distribution in natural populations by Fuller (1991). Lo-

cus II is defined by the EcoRI #1 and the first KpnI site

clockwise from EcoRI #1. It is approximately 1000 bp

in length and varies in size by deletions or duplications

of as much as 450 bp. Subsequent analysis has shown

that a large part of locus II bears high sequence similarity

with the repeated sequence of locus I, so that the two

kinds of size variation cannot be treated independently

from each other. Locus III is positioned at the 8 o clock

region of the molecule, separated by more than 10 kb

from locus I. A large number of size variants occur at

this locus, varying from each other by increments of less

than 100 bp.

The occurrence of at least two independent size poly-

morphisms at two disjoint regions of the mtDNA is a

rare phenomenon. In addition to the deep sea scallop

(Fuller & Zouros, 1993), it has been observed in the

Icelandic scallop, Chlamys islandica (Gjetvaj et al., 1992).

It generates very complex patterns of heteroplasmy, so

that each animal may possess a different mtDNA profile.

The high level of heteroplasmy introduces, also, an ad-

ditional level of mtDNA variation, intra-individual vari-

ation, that does not exist for the nuclear DNA. Because

the state of variation at any given level is the outcome

of the interplay between deterministic (e.g. selection)

and stochastic (e.g. random drift) forces at that particular

level, the presence of intra-individual variation raises the

possibility of molecular (among molecules within the

individual) selection for mtDNA.

The apportionment of mtDNA variation at different

nested levels (among molecules within the individual,

among individuals within the population, among pop-

ulations within the species) has been the subject of several

theoretical and empirical studies (Birky et al., 1983; Bir-

ky et al., 1989; Rand & Harrison, 1989; Arnason & Rand,

1992). The latter have suggested that the largest .com-

THE NAUTILUS, Supplement 2

ponent of mtDNA size variation is the among-individuals

(within populations). Assuming neutrality, it is easy to

see that the ratio of “within individuals” to “among

individuals” components of variation depends on the rate

with which new variants arise in the population (the

mutation rate for length polymorphism) and on the rate

with which the resulting state of heteroplasmy “decays”

into homoplasmy through a mechanism of stochastic as-

sortment of the constituent mtDNA molecules (Solignac

et al., 1984; Rand & Harrison, 1986). It is obvious that

the higher the mutation rate is, the higher will be the

“within individuals” component. The high rate of het-

eroplasmy of scallop mtDNA suggests that the rate of

length mutation is very high in this molecule. No esti-

mates of mtDNA length mutation rates exist, however,

in the literature. We, therefore, attempted to obtain such

an estimate in the scallop.

HIGH MUTATION RATE FOR

LENGTH POLYMORPHISM

A direct estimation of the rate with which new length

variants appear in the mtDNA molecule cf the deep sea

scallop was attempted by examining the mtDNA of off-

spring from pair matings and comparing it to that of the

parents. We have confined our study to one family and

examined locus I and locus II, but not locus III. Total

mtDNA was extracted from one year-old progeny ac-

cording to the techniques described in Fuller (1991) and

Zouros et al. (1992a). Ten ug of DNA was digested with

EcoRI or a combination of SalI/Stul. The resulting frag-

ments were separated on 0.7% agarose, transferred to

nylon membrane and hybridized either to a PstI/PstI

clone of the repeat element of locus I (LaRoche et al.,

1990) or to an EcoRI/PstI clone of the fragment con-

tained between the EcoRI #1 and the first PstI site

clockwise from EcoRI #1 (Fig. 1).

Table 1 presents the results in a way that does not

require familiarity with the molecular data. The “ge-

notype’ for each individual animal refers to the state of

locus I and locus II. The characteristic number (varying

from 3 to 6) for each genotype indicates the number of

copies of the repeat element at locus I. A “minus” su-

perscript indicates a deletion at locus II. Individuals with

two numbers are heteroplasmic.

The mother was apparently homoplasmic for the type

of molecule that contains four copies of the repeat ele-

ment at locus I and carries no deletions or insertions at

locus II. This is the most common “genotype” in all

populations of this species (Fuller, 1991). The father was

heteroplasmic, with the 5 type representing the minority

of mtDNA molecules in this individual. In all, 87 off-

spring were scored. All of them had the mother’s mtDNA

type, either exclusively or in conjunction with another

type. Seventy-four offspring had only the mother’s type.

Of the remaining thirteen, eleven had an additional type

that was completely new (found in neither parent). In

two offspring (those of the genotype 4/3) the non-ma-

ternal type is similar to one of the two paternal types.

D. I. Cook and E. Zouros, 1994

scallop mtDNA

genome

WM size variable Locus I and II 2 Soul

Wj size variable Locus III P PstI

Sa Sall

Sp Sphl

St Stul

Figure 1. A restriction map of the mitochondrial DNA of the

deep sea scallop Placopecten magellanicus. The molecule shown

has three copies of the repeated sequence at locus I and is of

the standard type (i.e. it does not contain deletions or insertions)

at locus II. Its size is approximately 36 kb. The EcoRI site

placed at the 12 o'clock position is referred to in the text as

EcoRI #1 and is used as a reference point.

Theoretically this could be a case of paternal transmission

of mtDNA, a phenomenon known to be common in

another bivalve, the blue mussel Mytilus (Zouros et al.,

1992b). Yet, given that non-parental types (6, 5 and 4)

have appeared among offspring, it is equally or even

more probable that the type 3 molecule in the two off-

spring has resulted from a mutational event in the moth-

ers mtDNA rather than inherited from the father.

Assuming that the non-maternal types in all thirteen

progeny represent independent mutational events, the

mutation rate is 15%, a very high rate. If the type 3

molecule is attributed to paternal inheritance, the rate

would reduce to 12.5%, a trivial change from 15%. In

seven of the thirteen progeny the non-maternal type

resulted from a mutational event at locus I (types 3, 5

and 6) and in six from a mutational event at locus II

(type 4°). Thus the mutation rate is about the same (ap-

proximatelly 7.5 %) at each of these loci. It is, however,

possible that only one mutational event in the mother’s

germ line produced the 4 type, that this type was am-

plified stochastically in the germ cells and that copies

were transmitted to all six progeny. The same argument

Page 87

Table 1. The genotypes of the parents and of eighty-seven

offspring at locus I and locus II of the mtDNA of the deep-sea

scallop Placopecten magellanicus (for details refer to Figure

1).

Geno-

Individual type Comment

Mother 4 Four copies of the repeat element

at locus I; no detectable deletions

or insertions at locus II

Father 3/5 Heteroplasmic.

Most common molecule has three

copies of the repeat element at

locus I; no detectable deletions or

insertions at locus II. Less com-

mon molecule has five copies of

the repeat element at locus I and

a 443 bp deletion at locus II.

Like mother.

Heteroplasmic.

One type of molecule has four cop-

ies of the repeat element at locus

I; no detectable deletions or in-

sertions at locus II. The other

type has four copies of the repeat

element at locus I and a 443 bp

deletion at locus II.

74 offspring 4

6 offspring 4/4

4 offspring 4/5 Heteroplasmic.

One type of molecule has four cop-

ies of the repeat element at locus

I, the other type has five. No de-

tectable deletions or insertions at

locus IJ in either molecule.

2 offspring 4/3 Heteroplasmic.

One type of molecule has four cop-

ies of the repeat element at locus

I, the other three. No detectable

deletions or insertions at locus II

in either molecule.

1 offspring 4/6 Heteroplasmic.

One type of molecule has four cop-

ies of the repeat element at locus

I, the other six. No detectable de-

letions or insertions at locus II in

either molecule.

can be made for the four offspring with the genotype 4/

5, and the two offspring with the genotype 4/3. Under

this logic, the mutation rate becomes 4/87 or 4.5%, still

a high mutation rate.

MOLECULAR CHARACTERIZATION OF

SPONTANEOUS LENGTH MUTATIONS

To further characterize the length variants that appeared

in thirteen offspring, the DNA of these offspring and that

of the parents was digested with a combination of Sall

and Stul enzymes and hybridized to a clone containing

the EcoRI/PstI part of locus Il. From Figure 1 it can

be seen that this double digestion will decompose the

fragment defined by the first SalI site counter-clockwise

SNe eee eee ema,

Page 88

from EcoRI #1 and the first SalI site clockwise from

EcoRI #1 into three size-fragments: the “left flanking

region’ starting from the first SalI site and ending at the

Stul site of the first repeated element of locus I, a number

of Stul/Stul fragments of the size of the repeated ele-

ment, and the “right flanking region” starting from the

Stul site of the last repeated element and ending at the

second Sall site. All these fragments will react with the

EcoRI/Pstl clone, because this clone contains locus II

and a large part of the repeated element of locus I. The

seven offspring with the genotypes 4/6, 4/5 and 4/3

produced patterns identical to their mother, implying

that the non-maternal type in these offspring resulted

from spontaneous insertions of one or two complete el-

ements (for genotypes 4/5 and 4/6, respectively) or from

spontaneous excisions of a complete element (for geno-

types 4/3). In contrast, the “left flanking region” in all

offspring with the phenotype 4/4 was represented by

two bands, one identical and one shorter than the cor-

responding flanking region of the mother, implying that

a deletion has occurred in this region. Interestingly, the

shorter left flanking region of these offspring was iden-

tical with the corresponding region of the minor mole-

cule of the father, implying that the minor component

of the father’s mtDNA also contains the same sized de-

letion. In the father this deletion at locus II is followed

by five repeats at locus I, whereas in the offspring it is

followed by four.

To find out whether the deletion was exactly the same

in all six offspring with the phenotype 4/4, the region

between EcoRI #1 and the first KpnI site was cloned

from a molecule that did not carry the locus II deletion

and sequenced. Primers were designed from this se-

quence, and the corresponding region was amplified by

PCR (polymerase chain reaction) from several individ-

uals. In all 4/4 offspring and in the father the amplifi-

cation produced two products, a “long” product resulting

from molecules of type 4 (in the offspring) or type 3 (in

the father), and a “short” product resulting from mol-

ecules of type 4 (in the offspring) or of type 5 (in the

father). The short product was sequenced and found to

be identical in all cases. It differed from the long product

by the same deletion of 448 bp. The start and end points

of the deletion are marked by a sequence of 86 nucle-

otides that occurs twice within the EcoRI/KpnI frag-

ment.

DISCUSSION

The main results of this study can be summarized as

follows:

1. An exceptionally large number (15 %) of offspring

from a pair-mating were found to carry in the state of

heteroplasmy a new length variant of mtDNA not pres-

ent in the mother. It can be argued that these new types

were in fact present in the mother, but only in minute

amounts and that they were disproportionately trans-

mitted or amplified in a few offspring. This would mean

that the mother contained at least four minor types of

THE NAUTILUS, Supplement 2

DNA, in addition to the major 4 type. In their surveys

of natural populations, Fuller (1991) scored about 350

individuals and Zouros et al. (1992a) an additional 250

for heteroplasmy at locus I. The rate of heteroplasmy

was found to vary from 10% to 20%, but very rarely

(0.4%) was an individual observed with more than two

types of mtDNA molecules. On the basis of this obser-

vation, the possibility that the mother of the family we

examined was pentaplasmic (i.e. it contained five types

of molecules) appears unlikely.

2. All non-maternal types seen in the offspring were

previously known to exist in natural populations of the

species. Thus, length mutations cannot be of any arbi-

trary size, but rather occur in “quantum” steps whose

length corresponds to the length of a repeated sequence

or to the length of a unique sequence flanked by repeated

sequences.

These results provide direct support for several hy-

potheses regarding the origin and fate of length variation

of mtDNA. Indirect evidence for high mutation rate was

deduced from the high frequency of length heteroplas-

my in many species (Zouros et al., 1992a, Brown et al.,

1992; Arnason & Rand, 1992). More direct evidence for

high mutation rate was obtained in the nematode Ro-

manomermis culicivorax (Hyman & Slater, 1990), where

novel mtDNA forms were observed in lineages separated

by less than two hundred generations. In these experi-

ments it was not possible, however, to obtain even an

approximate estimate of mutation rate, because it was

not possible to monitor the appearance or loss of new

mtDNA variants at discrete generation intervals.

Length mutations apparently result from errors during

the replication of the molecule, and these errors are, in

turn, mediated by the presence of repeated sequences.

Possible mechanisms involve replication slippage (Haus-

wirth et al., 1984), competitive strand displacement (Bu-

roker et al., 1990), or recombination (Rand & Harrison,

1989), even though the latter appears less likely. Among

the thirteen mutational events we have observed, six

(those leading to the 4 deletion at locus II) involved the

excision of a unique 443 bp sequence flanked at both

sides by an identical 86 bp sequence. If these two iden-

tical sequences pair with each other at a certain stage of

DNA replication, the in-between unique sequence would

“loop out” and could be excised, thus leading to a deletion

event. Two other mutational events involved the short-

ening of the array of repeated elements at locus I by one

repeat (the type 3 molecule). This can also result from

an excision of a copy that looped out as a result of the

pairing of the two copies flanking, at both sites, the ex-

cised. copy. Finally, one event involved the insertion of

one copy of the repeated element (the type 5 molecule)

and another event involved the insertion of two copies

(the type 6 molecule). These events can be explained by

assuming that a segment of DNA looped out (as a result

of the pairing of two copies separated by one or two

other copies) and was replicated.

Whatever the exact molecular mechanism is for the

spontaneous changes of the length of the mtDNA mol-

D. I. Cook and E. Zouros, 1994

Page 89

ecule, it is clear that these changes require the presence

of repeated sequences and that, once this requirement

is met, they will occur at a very high rate. It is less clear

whether mutations of this kind are neutral to the forces

of natural selection acting on the individual, even though

there appears to be indirect evidence in support of neu-

trality (Zouros et al., 1992a). Intra-individual molecular

selection appears to favor smaller molecules over longer

ones (Rand & Harrison, 1986; Brown et al., 1992). Such

selection will eliminate molecules of larger size, unless

it is countered by a biased mutation rate favoring the

generation of longer molecules from shorter ones. In our

data no such bias is evident, but the number of mutations

we have observed is not large enough for a meaningful

test of this hypothesis.

The high mutation rate generates a large amount of

intra-individual and inter-individual variation, which

may be useful for the study of the evolution of the mol-

ecule itself, and may also provide the building blocks for

long-term evolutionary changes, such as gene re-arrange-

ments, known to have occurred on multiple occasions

(Hoffmann et al., 1992). However, this variation may

not be particularly useful for short-term evolutionary

studies, such as population structure and differentiation,

as the high mutation rate appears to homogenize con-

specific populations, overriding the differentiation caused

by gene flow (Fuller, 1991; Arnason & Rand, 1992). This

variation is also not suitable for “medium-term” evolu-

tionary studies, such as taxonomic studies at the species,

genus or family level because repeated sequences from

related species can be drastically different in their DNA

sequence. For example, Gjetvaj et al. (1992) found that

repeated sequences in six different species of scallops had

no appreciable sequence similarity with each other and

carried little information about species relatedness.

ACKNOWLEDGMENTS

The work reported here was supported by an NSERC

research grant and a Network of Excellence (OPEN)

grant to E.Z. Amy Ball has helped with the drawing of

Figure 1.

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THE NAUTILUS, Supplement 2

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THE NAUTILUS, Supplement 2:91-97, 1994

Page 91

Reconstruction of Phylogeny of 11 Species of Littorina

(Gastropoda: Littorinidae) using Mitochondrial DNA Sequence

Data

Elaine Rumbak!

David G. Reid

Richard H. Thomas

Department of Zoology

The Natural History Museum

London, SW7 5BD, U.K.

SS a

ABSTRACT

A gene phylogeny of eleven Littorina and two Nodilittorina

species was reconstructed using mitochondrial DNA sequence

from the small ribosomal RNA gene. The monophyly of the

genus Littorina is supported as is the inclusion of L. striata in

this genus. The deep intra-generic branches in Littorina are

well resolved but the sequence data are insufficiently variable

to resolve recent divergences. The phylogenetic trees obtained

are consistent with the morphological cladogram of Reid (1990a).

These data support in part the biogeographic hypothesis of

trans-Arctic migration of Littorina.

Key words: Littorina, Nodilittorina, phylogeny, 12S rRNA.

INTRODUCTION

Littorina is perhaps the most well-studied of all marine

gastropod genera. Nevertheless, only recently has any

information been available on the evolutionary relation-

ships within this genus. Using morphological compari-

sons, sparse palaeontological records, modern distribu-

tions and palaeoclimatic data, Golikov & Tzvetkova (1972)

discussed in a general way the evolution of Littorina

from warm-water ancestors in the genus Nodilittorina.

Cladistic analysis of anatomical characters has been used

by Reid (1986, 1989) to attempt a phylogenetic recon-

struction for all recognised generic and subgeneric groups

in the family Littorinidae. The resulting phylogenetic

classification replaced an earlier scheme, which had been

based largely on ill-defined features of shell and radula

as well as data on penis and sperm (e.g. Rosewater, 1970;

Bandel & Kadolsky, 1982). This cladistic analysis defined

Littorina as a monophyletic group, with sister-taxon No-

dilittorina. The same method was used to analyse rela-

tionships among the 18 species of Littorina then rec-

‘To whom correspondence should be addressed.

ognized (Reid, 1990a); this supported their classification

in five subgenera, but failed to resolve completely the

branching pattern.

An alternative approach to phylogenetic reconstruc-

tion in Littorina, independent of morphology, has been

the estimation of genetic distance from allozyme data

(review by Ward, 1990). Some studies have examined

only species from the northern Atlantic (Morris, 1979;

Warmoes, 1986; Ward, 1990; Knight & Ward, 1991),

and their results are consistent with those from the cla-

distic analysis of morphology, demonstrating close re-

lationships among members of the L. saxatilis complex

(L. saxatilis, L. arcana, L. nigrolineata), a greater dis-

tance to the pair in the L. obtusata complex (L. obtusata,

L. mariae), and a distant relationship of both groups to

L. littorea. Only two allozyme studies have included

examples of Littorina species from both the northern

Atlantic and the northern Pacific in the same analysis

(Boulding, 1990; Zaslavskaya et al., 1992). These agree

with the morphological cladogram in uniting members

of the subgenus Neritrema (Littorina species with direct

development, i.e. obtusata and saxatilis complexes, L.

sitkana, L. subrotundata and others not discussed here).

However, the branching order of species lower on the

cladogram, belonging to the subgenus Littorina (includ-

ing L. littorea, L. squalida, L. mandshurica, L. brevicula,

L. plena, L. scutulata) shows discrepancies. The basal

species of Littorina in Reid’s (1989, 1990a) scheme is L.

striata; this has been included only in the allozyme study

of Backlejau & Warmoes (1992), who discussed the tax-

onomic controversy surrounding the inclusion of this spe-

cies in Littorina, Nodilittorina or Melarhaphe, although

their results supported Reid’s classification in Littorina.

So far, comparison of DNA sequences has not yet been

applied to this problem. Sequence data is now widely

used in phylogenetic systematics to determine relation-

ships at all levels (e.g. reviews by Avise, 1989; Hillis &

Dixon, 1990; Simon, 1991), although examples among

molluscs are rare (e.g. Emberton et al., 1990). Mito-

Page 92

chondrial DNA is particularly useful for investigating a

variety of problems in systematics and population ge-

netics, since it is haploid, undergoes little or no recom-

bination and is generally transmitted across generations

only by females (Avise et al., 1987). Different mito-

chondrial genes or parts of genes have been shown to

evolve at a wide range of rates; rapidly evolving DNA

sequences can be used to study recently diverged taxa,

whereas conserved regions are suitable for distantly re-

lated taxa (Simon, 1991). The advent of modern molec-

ular techniques has made it possible to sample DNA

sequence variation from selected regions of these ge-

nomes quickly and from large numbers of individuals.

In this paper we use data obtained from direct se-

quencing of amplified mitochondrial DNA, using uni-

versal primers for part of the small ribosomal RNA gene

(Kocher et al., 1989). The sequence data are used to

construct a species-level gene phylogeny of the eleven

northern Atlantic and eastern Pacific Littorina species

so far available to us. This will provide a test, independent

of both morphology and allozymes, for the cladogram

of Reid (1989, 1990a). By including L. striata together

with two members of the sister-taxon Nodilittorina, the

disputed affinities of this species are investigated.

MATERIALS AND METHODS

Sample collection and DNA extraction: The different

species, numbers of individuals analysed, and collection

sites of Littorina used in this study are listed in Table 1.

After collection the animals were kept alive at 4°C for

not more than a week. Before dissection the animals were

anaesthetised in 7.5% magnesium chloride (w/v) solution

for 1 hour. Sex was determined by presence of penis or

pallial oviduct, and any individuals parasitised by trem-

atodes were discarded. The operculum and rectum, with

faecal pellets, were removed. For the larger species (> 10

mm shell length) only the digestive gland was removed

for DNA extraction, whereas for the smaller species the

whole animal was processed. For DNA extraction a mod-

ification of the guanidinium thiocynate method of Pitch-

er et al. (1989) was used. The coarsely chopped animal

was placed in equal volumes of Tris-EDTA (0.1M, pH

8.0) and GE reagent (5M guanidinium thiocynate, 1M

EDTA), a half volume of glass beads (Glasperlen, Braun)

added, and the sample shaken (2 min, 4°C, 2,000 rpm)

in a bead beater (Mikro-Dismembrator, Braun). The beads

and debris were removed by centrifugation (13,000 x

g, 15 min, 4°C). The supernatant was collected and half

a volume of ammonium acetate (7.5 M) added, before

treatment with phenol and chloroform to remove pro-

teins and pigments. The DNA in the sample was pre-

cipitated with ethanol, washed with 70% ethanol, dried,

and resuspended in sterile distilled water. The samples

were then stored at 4°C, or for long-term storage, — 70°C.

Polymerase Chain Reaction (PCR) and DNA sequenc-

ing: Amplification of part of the mitochondrial small

ribosomal RNA gene (12S rRNA) was carried out using

the universal 12Sa and 12Sb primers (Kocher et al., 1989).

THE NAUTILUS, Supplement 2

Each PCR was performed in a 100 ul volume consisting

of 67 mM Tris-HCL (pH8.8), 2mM MegCl,, 0.05% Tween-

20, 100 ng/ml bovine serine albumin, 40 pmoles of each

primer, 100 uM of each dNTP, 2.5 units Taq Polymerase

(Perkin-Elmer/Cetus), and 10-1000 ng template DNA.

The cycling parameters for amplification were an initial

5 min denaturation at 94°C, and then 30 cycles of 45 sec

at 94°C, 1.5 min at 55°C, and 2 min at 72°C. Precipitated

PCR products were then directly sequenced by the rapid

thermal cycling technique described in Embley (1991).

DNA sequence was determined for both strands. The

DNA sequences have GenBank accession numbers

u@5862-u@5874-v.

Sequence analysis and gene phylogeny reconstruction:

Sequences were aligned with the aid of the program

CLUSTALYV (Higgins et al., 1992), with minor adjust-

ments made by eye. Results from a range of analytical

methods were compared (review by Swofford and Olsen

1990). Analyses employing maximum parsimony criteria

were carried out with PAUP, version 3.0s (Swofford,

1990). Bootstrapped distance-based analyses were done

with CLUSTALYV (Higgins et al., 1992), which employs

Kimura's (1980) 2-parameter model for the calculation

of corrected pairwise distances and the neighbour-joining

algorithm of Saitou and Nei (1987) for the construction

of trees. The maximum likelihood method (Felsenstein,

1981) was carried out with PHYLIP, version 3.4 (Fel-

senstein, 1991). For further details of methodology con-

sult legends to figures 2 and 3.

RESULTS

Sequences of the 12S rRNA gene fragment (not including

the primer sequence) from eleven Littorina species and

two Nodilittorina species are shown aligned in Figure

1. No within-species variation was found for any of the

species used (for sample size see Table 1) except for L.

saxatilis. Both the South African and Welsh L. saxatilis

populations had two non-identical single base pair dif-

ferences, as well as a sequence in common with Isle of

Wight and Venice populations. Only the sequence in

common is presented here (Figure 1). Alignment of the

sequences was not difficult because this gene was found

to be fairly well conserved. There are 73 variable posi-

tions (including deletions and insertions) among the 374

sites aligned.

Phenetic analysis of the sequence data for each pair

of taxa is presented in Table 2. The total number of

transversions and transitions, as well as the number of

transversions relative to transitions, increase from left to

right in the table (i.e. L. saxatilis to N. trochoides). Like-

wise, the genetic distance (calculated from Kimura’s

(1980) 2-parameter estimator, which allows transitions

and transversions to occur at different rates) increases

from top to bottom in the species matrix. Since the order

of the species in Table 2 is based on the morphological

cladogram of Reid (1990a), these trends reflect the in-

creasingly distant relationships between species. These

data show the expected transition bias (Brown et al.,

E. Rumbak et al., 1994 Page 93

N. radiata TCTTAGGC-A TAAATAAATT TAAATATTTA CTAGAGTACT ACGAATAAAA 50 L. saxatilis

N. trochoides MGos= a ACenosoonoe oSo0e TA.A. 50

L. striata {So des C= Sadne esasanusee sodas TT.T. 50 de arcane

L. keenae CG. s==ed€os ec@eocesoen Seance Wer 50 15%) 1 L. nigrolineata

L. scutulata 6 oooscesess ds==cosde sscescoese so00- Cossm SH) 0.01 Units Tevarine

L. plena > oassogooco dGs=Sso0ne aacsccscaa soegosuooS 50 : ‘i

L. littorea ol soooned4nouo slls=seba6e stoodeoado sooocgdods 50 L. obtusata

L. subrotundata o gocdarso0o one==s0G60 Bsadcn9tsn Hsaobaooade 50

WO = oan cogs=o «oso obuoeey soe ==ceec0 soeencdog0 tooasco0dE 50 Epubrotundats

L. mariae mh ocsodssenn coe==Hoodn Saocob0ddd soomgaDOdn 50 L. littorea

I GOGH ocoacasdGo oceodeoees soe==ao0es Baooadoa0G0 asodcodeDD 50

L. arcana 6 O0nodo0000 cocsSpo0uc0 vodscroosy ogaboozcae 50 ei

L. saxatilis 0 aen00n0009 ooeFHS0006 ancccocods congbsoncos 50 L. scutulata

N. radiata CTATTTAAAA CTCAAAGAGC TTGGCGGTGC TITAGACTTC TCAGGGGAAC 100

IN, GuTGIEES = ©€Escancc0s ooeooeenes sogogdeace Woscoacad © cosooseace 100

lsc = = = =BEoocenodo ¢o000600005 aa00d0090 Wococgcas ® cooocoon0d 100

WNC ~=ss0000m0 doocodgnae! vosn0Gb009 Wosocsesne enanxtoogae 100

IL GGHGNEH! = =a 0c000070 annoacdned poasuobass Eoscoavcds os INa 5100.00 100

Innis e=oev0GQ0 voddoDDb0d oopOAOnoOoS BooOtRoDGK ssao0nGbocG 100

L. littorea S=co0g0bUO GOoGdOD00O FoHDdD0Dge oCosoDDODOO HasoDoOnDD 100

IL, GAROUCAG cP sa0g0000 coaneoccdo vovoeeogod seopecegds sau00009000 100

I QU1G3%) = p= aocagenny da0000gg0e BoevecooODD BoCCDBHDOD SHObsogDOD 100

ITE = = op onan0g00 gc0nGbeags FEDGoESedS SododeeDeD Soe pDodDOND 100

Wn OI s= 55000000 G00cG0R000 GocHabdo0S booaDd5GDG so0gG000DD 100

IL CHER = Bc onoand 9000060500 caba2DG0059 s00esGe005 S000000550 100

ik, SEIS = =p ogcG0Go aooceosonO BU0dGE5009 Ssdogbeu0c0 sO00000000 100

N. radiata CTGTCTCGTA ATCGACAGTC CACGAATCAA CCTTACCTTC TTTCGCG-AT 150

N. trochoides ....... Gag coocosd Gee ovoccoge Ws sooSo SWS Cs MGS; , iS0)

L. striata

L. keenae

L. scutulata

L. plena

L. littorea

L. subrotundata .

L obtusata

L. mariae

L. nigrolineata

L arcana

L. saxatilis

N. radiata CAGTATGTAT ACCGTCGTCG TCAGGTAACT TTTAAAAATA TAGAAGTTAG 200

N. trochoides ely

L, striata

L. keenae

L. scutulata

L. plena

L. littorea

L. subrotundata

L obtusata

L. mariae

L, nigrolineata

L, arcana

L. saxatilis

N. radiata

N. trochoides

L. striata

L. keenae

L. scutulata

L. plena

L. littorea

L. subrotundata .

L obtusata

L. mariae

L. nigrolineata

L arcana

L. saxatilis

N. radiata

N. trochoides

L. striata

L. keenae

L. scutulata

L, plena

L. littorea

L. subrotundata

L. obtusata

L, mariae

L. nigrolineata

L. arcana

L. saxatilis

N. radiata A-ATGACTTA TATGAAGGCG GACTTGAAAG TATGAATTAG TATAGAAATT 350

N, trochoides TGGTTT: -A. sso 9 AEG og ott SIEVO)

L. striata €.GTG....A 350

L. keenae SEs woo SIsX0)

L. scutulata -ACT....A 350

L. plena ogddCoanao 350

L, littorea sSShoo00ds «aotasodans “souceeouds otoamdoGoo) lOO ODL OEIC 350

IL GALE! o> yaase0g G0FGe0K00d “SoosoonoDS OnoUEOHODe gQoOdoDDODOK 350

L. obtusata Croaltenooa 350

L. mariae (C5 adtse 350

AGOGIEE o=-cocnbo vo=bo00G00 —vadobuaood cdaecdoGns0 DoonoduUdS 350

L arcana soceapaepos ca)

L. saxatilis poodG5owo.0 350

N. radiata AGCTCTGAAG ACTG 374

N. trochoides CG... 374

L. striata 5605 374

L. keenae 374

L. scutulata 374

L. plena 374

L. littorea 374

L. subrotundata ... 374

L obtusata 374

L. mariae 374

L. nigrolineata 374

L. arcana 374

L. saxatilis 374

L. keenae

L. striata

N. radiata

N. trochoides

Figure 2. Bootstrapped neighbour-joining tree constructed with

pairwise distances calculated using Kimura's (1980) 2-parameter

correction for multiple substitutions. Branches are drawn pro-

portional to their length. Produced with CLUSTALV (Higgins

et al., 1992). Sites at which any species has a gap have been

included in the analysis. Numbers on nodes are the percentage

of replicates in which the taxa to the right of the node occur

together. This is a bootstrap 50% majority-rule consensus tree

based on 1000 replicates. The tree is shown with the Nodilit-

torina species as an outgroup to root the tree. Arbitrarily groups

with less than 50% support have been collapsed to polytomies.

1982; Moritz et al., 1987) seen in other metazoan mi-

tochondrial sequences, and judging from the relatively

low ratio of transversions to transitions these sequences

are not yet saturated, even for the deepest divergences.

In all pairwise comparisons the number of transitions

exceed the number of transversions (Table 2). In general,

once transitions have become saturated, the transversions

continue to accumulate approximately linearly with time

well past the point at which transitions have reached

their asymptotic value (Miyamoto & Boyle, 1989).

Phylogenetic trees constructed using neighbour-join-

ing and maximum parsimony are shown in Figures 2

and 3 respectively. These trees are consistent with each

other, though the neighbour-joining tree shows slightly

more resolution of L. scutulata and of the L. saxatilis

complex. The maximum likelihood method tree (not

shown) had the same topology as the most parsimonious

tree. In the parsimony analysis a single most parsimo-

nious tree was obtained of length 185 steps. By permitting

the tree length to increase by 1 step, and taking a strict

consensus of the resulting trees, it was found that only

four nodes remained in the ingroup (supporting L. stria-

ta, L. keenae, the remaining species with the L. saxatilis

complex). At 187 steps the L. saxatilis complex collapsed;

the next branch to collapse was that separating L. keenae

and L. striata at 190 steps.

Figure 1. Aligned DNA sequences of a fragment of the mi-

tochondrial 12S rRNA gene from 13 species of littorinid gas-

tropods. Dots indicate that the sequence is identical to N. ra-

diata, dashes indicate deletions in one or more sequences relative

to other sequences shown.

Page 94

THE NAUTILUS, Supplement 2

Table 1. Localities and sample sizes of Nodilittorina and Littorina used in this study.

Species

N. trochoides (Gray, 1839)

N. radiata (Eydoux & Souleyet, 1852)

L. striata King & Broderip, 1832

L. keenae Rosewater, 1978

L. scutulata Gould, 1849

L. plena Gould, 1849

L. littorea (Linnaeus, 1758)

. subrotundata (Carpenter, 1864)

. obtusata (Linnaeus, 1758)

. mariae Sacchi & Rastelli, 1966

. nigrolineata Gray, 1839

. arcana Hannaford Ellis, 1978

. saxatilis (Olivi, 1792)

Se iS) Si ie

DISCUSSION

The branches nearer the base of both trees (Figures 2

and 3) are well resolved and are consistent with Reid’s

(1989, 1990a) concept of the monophyletic genus Lit-

torina with L. striata as its basal member. Strictly, our

data provide only a partial test of the inclusion of L.

striata in Littorina; clearly it does not cluster between

the two Nodilittorina species, but the hypothesis that it

could be a basal member of Nodilittorina cannot be

falsified without recourse to more distant outgroups.

However, it may be noted that the calculated genetic

distances (Table 2) show that in 6 of the 10 possible

comparisons with other Littorina species, L. striata is

closer to the Littorina than to either of the Nodilittorina

species. This is reflected in the branch lengths of Figure

2. In addition, midpoint rooting of the maximum par-

simony tree placed the tree root between the Nodilit-

torina species and L. striata. Previously there has been

some debate about the classification of L. striata, with

Cape d’Aguilar, Hong Kong

El Golfo, Lanzarote, Canary Is.

Pacific Grove, California, USA

Candlestick Park, San Francisco, California, USA

St. Lawrence, Isle of Wight, UK

West Angle Bay, nr Pembroke, Wales, UK

Charleston, Oregon, USA

Pembroke Dock, Wales, UK

West Angle Bay, nr Pembroke, Wales, UK

St. Govan’s Head, nr Pembroke, Wales, UK

Alberoni, Venice, Italy

Langebaan Lagoon, South Africa

St. Lawrence, Isle of Wight, UK

Locality Sample size

NPNNWHOWHNWHNWNHWHNWADWAWA KNW

most recent authors placing it in Nodilittorina on mor-

phological grounds (Rosewater, 1981; Bandel & Kadol-

sky, 1982). However, in their analysis of allozyme data

Backeljau & Warmoes (1992) also favoured inclusion in

Littorina. The terminal groupings of L. saxatilis, L. ar-

cana and L. nigrolineata (the L. saxatilis complex) and

L. obtusata and L. mariae (the L. obtusata complex) are

also supported, agreeing with the results of both mor-

phological (Reid, 1989; 1990a) and allozyme studies

(Warmoes, 1986; Ward, 1990; Knight & Ward, 1991;

Zaslavskaya et al., 1992).

At the more intermediate levels, however, neither tree

is well resolved. The maximum parsimony tree (Figure

3) is entirely consistent with the morphological clado-

gram of Reid (1990a; Figure 4), but does not resolve

relationships between the members of the subgenera Lit-

torina (L. scutulata, L. plena, L. littorea) and Neritrema

(L. saxatilis complex, L. obtusata complex, L. subro-

tundata). The neighbour-joining tree shows slightly more

Table 2. The number of transversion differences followed by the number of transition differences (above the diagonal) for the

374 sites of the 12S rRNA gene fragment, and the pairwise genetic distance calculated from Kimura's (1980) 2-parameter estimator

(below the diagonal). The first three letters of species names are used as abbreviations above columns.

sax arc nig mar obt

L. saxatilis — 1/0 2/1 1/5 1/5

L. arcana 0.003 — 1/1 0/6 0/6

L. nigrolineata 0.008 0.006 — 1/7 1/7

L. mariae 0.017 0.017 0.022 — 0/2

L. obtusata 0.017 0.017 0.022 0.006 —

L. subrotundata 0.022 0.020 0.025 0.025 0.025

L. littorea 0.031 0.028 0.028 0.0384 0.034

L. plena 0.037 0.034 0.040 0.028 0.034

L. scutulata 0.052 0.052 0.058 0.052 0.052

L. keenae 0.108 0.108 0.102 0.098 0.105

L. striata 0.177 0.180 0.180 0.184 0.176

N. radiata 0.185 0.189 0188 0.181 0.189

N. trochoides 0.219 0.219 0.219 0.207 0.207

sub

2/6

1/6

PPT

1/8

0.031

0.037

0.055

0.111

0.177

0.174

0.212

lit ple scu kee str rad tro

3/8 8/10 2/16 11/25 14/41 25/84 27/41

2/8 2/10 1/17 10/26 15/41 26/34 26/42

3/7- 8/11 2/18 9/25 16/40 27/383 27/41

2/10 2/8 1/17 10/23 15/24 26/32 26/39

2/10 2/10 1/17 10/25 15/40 26/34 26/89

3/8 8/10 2/17 11/26 14/41 25/81 25/41

— 4/12 3/21 11/26 16/40 28/32 28/40

0.046 — 1/19 12/28 17/41 28/32 28/89

0.070 0.058 — 11/29 16/42 27/36 27/438

0.112 0121 0121 — 20/41 28/30 24/85

0.180 0.187 0.187 0.195 — 25/33 22/48

0.188 0.188 0.200 0180 0.183 10/23

0.219 0.215 0.227 0.184 0.096 =

E. Rumbak et al., 1994

L. saxatilis

L. arcana

L. nigrolineata

L. obtusata

L. mariae

L. subrotundata

L. littorea

L. plena

L. scutulata

L. keenae

L. striata

N. radiata

N. trochoides

Figure 3. Bootstrapped maximum parsimony tree based on

analysis of 12S rRNA gene sequences produced with PAUP

(Swofford, 1990) using a branch-and-bound search. Options

used were furthest’ addition sequence; ACCTRAN; all minimal

length trees saved (MULPARS); zero-length branches collapsed;

gaps treated as missing (treatment of gaps as a fifth character

has no effect on the topology and has only a slight effect on

bootstrap values). Numbers on branches are the number of

inferred synapomorphies. The numbers on the nodes are the

percentage of replicates in which the taxa originating from

there occur together. Bootstrap parameters are as described for

Figure 2. The tree is shown with the Nodilittorina species as

an outgroup to root the tree. There are 158 character states

distributed over 57 informative characters. The tree is 185 steps

long.

resolution, as a result of the contribution of autapomor-

phies to the pairwise distances among taxa for which

there are few or no sites that are informative for parsi-

mony analysis. This tree (Figure 2) separates L. scutulata

in the same position as in the morphological cladogram,

but does not place L. plena as its expected sister-species

(Reid, 1990a). However, in view of the relatively low

bootstrap values at the node separating L. scutulata, little

confidence can be placed in this result. Disagreements

as to the position of L. scutulata and its probable sister-

species (Boulding, 1990; Reid, 1990a) are therefore not

yet resolved. Other disagreements between the morpho-

logical cladogram and allozyme-based trees (Zaslavskaya

et al., 1992) involve species from the northwestern Pacific

that have yet to be included in our study.

The morphological cladogram of Reid (1990a) has been

used as evidence of the origin of the Atlantic species of

Neritrema from a Pacific ancestor, an example of the

migration of marine fauna from the northern Pacific into

the northern Atlantic following the opening of the Bering

Strait during the Upper Pliocene (Reid, 1990b). Although

the present results do not resolve the relationships of

Neritrema, there is some support for this biogeographic

hypothesis, in that the Atlantic Neritrema species show

the lowest genetic distances among themselves (Table 2,

Figure 2).

The distance measures given in Table 2 show a close

relationship among species classified in the subgenera

Page 95

= Sy Sas

= iS aS a Se

QD S = = Sos S 5s 5 5

SOs ete se eee See:

r S$ 8 MSS Sos FS BS Ss 8 SS ss &

= SSS SSeS SSUES QE SESS SS

SSS BS ESSESESE SBE SESE SEHE SB &

RF oS & & ke VD Oy SS Sy SS ey 8 7) ts =

: SS SoS

SoS Ss 2 sO Ss oS th OS oN & as

o 8 8 Fo FG 8 SFTEB RAK GEE

De RR Sn Ee ee, Oe CRMC pO Oe ER? EGS Meters (3)

Sanita se SASS Asa es & ee

Figure 4. Morphological cladogram of 16 Littorina species,

redrawn from Reid (1990a). The following modifications were

made: exclusion of Mainwaringia rhizophila (now not consid-

ered a member of this clade, unpublished data); exclusion of

L. kurila (a synonym of L. subrotundata) and L. neglecta (a

probable synonym of L. saxatilis).

Littorina and Neritrema, which is surprising in view of

their rather marked morphological differences (Reid,

1989; 1990a). Both L. striata and L. keenae are relatively

distant from these and from each other, supporting their

classification in separate subgenera (Reid, 1989). The two

species of Nodilittorina used as the outgroup in this

analysis, N. radiata and N. trochoides, are also relatively

distant from each other; their shells are dissimilar, but

anatomically they show few differences and are presently

placed in the same subgenus, Nodilittorina. There has

not yet been a species-level analysis of phylogenetic re-

lationships in Nodilittorina.

The inference models used in this study to analyse the

sequence data do not assume a molecular clock’ (Swof-

ford & Olsen, 1990), and it is uncertain if the same

topology would result if a clock were assumed. If, how-

ever, the ‘molecular clock’ hypothesis, that genetic dis-

tance measures are proportional to the time of phylo-

genetic divergence, is tentatively assumed, one could

make the following crude estimates. For Littorina, two

nodes on the cladogram can be dated: the separation of

L. littorea from its Pacific sister-species L. squalida, and

the separation of the Atlantic Neritrema species from

the sister-taxon of this clade in the Pacific. The earliest

possible date for both of these separations is the opening

of the Bering Strait, dated at 3.5-4.0 million years (My)

Page 96

ago (Hopkins, 1967; Reid, 1990b; Vermeij, 1991). The

latest date is taken as the time of the onset of widespread

glaciation about 2.4 My (Shackleton et al., 1984; Loub-

ere, 1988) when the trans-Arctic migration route may

have been cut by climatic cooling. Littorina squalida

was not included in this study, but the sister-taxon of the

Atlantic Neritrema species is believed to be L. subro-

tundata (Reid, 1990a). The average distance between L.

subrotundata and the five Atlantic Neritrema species is

0.023 (Table 2), a divergence of 0.00575 per My (ac-

cepting the older estimate of the age of the Bering Strait).

This approximation permits tenuous estimates of the ages

of other nodes on the tree: 8 My for the separation of L.

plena plus L. scutulata (assuming these are sister-taxa)

from more recent species; 19 My for L. keenae; 32 My

for L. striata and therefore a minimum age of the clade

as a whole. These ages are probably too young and would

have become even more so had the latest separation date

been used in the calibration. The fossil record of Litto-

rina is very poor, and the older fossils, dating to the

Upper Palaeocene, cannot be assigned to the genus with

any confidence (Reid, 1989; 1990b). The oldest certain

member of the genus is L. sookensis from the lower

Miocene of Vancouver Island (approximately 22 My),

which is probably close to the modern L. keenae. The

Recent species L. squalida (sister-species of L. littorea)

has been recorded from the Middle Miocene of Kam-

chatka (approximately 15 My). It should be stressed that

this means of estimation of ages from molecular data

gives only very approximate results.

This study has shown that the 12S rRNA gene is in-

sufficiently variable to resolve the relationships among

recently diverged species such as members of the sub-

genera Littorina and Neritrema. However, it has per-

mitted well-supported resolution of the deeper branches

of the phylogeny. This is part of an ongoing study and

we now intend to sequence more variable portions of the

mitochondrial genome to resolve relationships more ful-

ly, including those at the intraspecific level. We propose

to examine as many as possible of the 21 species presently

classified as Littorina, in the attempt to derive a well-

resolved phylogeny for the genus. This will provide an

evolutionary framework for the large amount of ecolog-

ical and physiological data already available for the ge-

nus, and thus permit tests of adaptational hypotheses

(Reid, 1989; 1990a). It will also test hypotheses about

speciation and biogeography of marine invertebrates in

temperate latitudes for which this well-studied genus has

been used as an example (Golikov & Tzvetkova, 1972;

Reid, 1990b; Vermeij, 1991).

ACKNOWLEDGEMENTS

This work was supported by NERC grant GR3/7854.

We would like to thank Stephen A. Ridgway and James

T. Carlton for providing some of the samples used. As-

sistance in the preparation of figures was provided by

Gail Altschuler.

THE NAUTILUS, Supplement 2

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THE NAUTILUS, Supplement 2:98-110, 1994

Page 98

Small Ribosomal Subunit RNA and the Phylogeny of Mollusca

Birgitta Winnepenninckx

Departement Biochemie

Universiteit Antwerpen (U.I.A.)

Universiteitsplein 1,

B-2610 Antwerpen, Belgium Vautierstraat 29

Thierry Backeljau

Afdeling Malacologie

Koninklijk Belgisch Instituut voor

Natuurwetenschappen

Rupert De Wachter!

Departement Biochemie

Universiteit Antwerpen (U.1.A.)

Universiteitsplein 1,

B-2610 Antwerpen, Belgium

B-1040 Brussel, Belgium

ABSTRACT

We determined the complete sequence of the small ribosomal

subunit RNA of the pulmonate snail Onchidella celtica. This

sequence and the one recently determined for the chiton Acan-

thopleura japonica were added to an alignment of 25 18SrRNA

sequences of Metazoa, including three other Mollusca. The data

set was used to assess certain aspects of molluscan phylogeny

by distance matrix and character state methods. The trees ob-

tained were tested for effects of random and systematic errors.

The results of our analyses support: (a) molluscan monophyly;

(b) gastropod monophyly; (c) bivalve monophyly; (d) a sister

group relationship of Gastropoda and Polyplacophora. The po-

sition of the phylum among other Metazoa remains uncertain

due to a lack of representatives of many invertebrate phyla in

our data set. Most of our results are congruent with existing

hypotheses.

Key Words: 18S rRNA, phylogeny, Metazoa, Gastropoda, Bi-

valvia, Polyplacophora, Onchidella celtica.

INTRODUCTION

Historical Background

Many aspects of molluscan phylogeny are still uncertain.

The huge phenotypic diversity within the phylum ob-

scures the evolutionary relationships between the larger

molluscan taxa (e.g. von Ihering, 1876; Milburn, 1960;

von Salvini-Plawen, 1969, 1972, 1985, 1990a,b; Stasek,

1972; Gotting, 1980; Wingstrand, 1985; Scheltema, 1988;

Brusca & Brusca, 1990). Nevertheless, it is generally ac-

cepted that the “shell- bearing molluscs” (Conchifera,

i.e. Cephalopoda, Scaphopoda, Bivalvia, Gastropoda and

Monoplacophora) are monophyletic with Polyplacoph-

ora as sister group (e.g. von Salvini-Plawen, 1969, 1985,

1990a; Stasek, 1972; Gotting, 1980; Wingstrand, 1985;

Scheltema, 1988; Brusca & Brusca, 1990). Indeed, the

loss of spicules and the presence of three mantle margin

folds, an univalve shell consisting basically of three lay-

ers, jaws, a head with cerebrally innervated appendages,

1 Author for correspondence.

a nervous system differentiated in axons and ganglia, a

crystalline style and statocysts are considered to be syn-

apomorphies uniting the five conchiferan classes (e.g.

Gotting, 1980; von Salvini-Plawen, 1985; Wingstrand,

1985; Brusca & Brusca, 1990). However, different inter-

pretations exist about the phylogenetic relationships

within this subphylum. Milburn (1960) suggested three

conchiferan clades: Monoplacophora, Cephalopoda and

a Bivalvia-Gastropoda-Scaphopoda clade. The branching

pattern of these three groups and the topology of the

Bivalvia-Gastropoda-Scaphopoda clade, remains unre-

solved. Gotting (1980) proposed a Bivalvia-Scaphopoda

sister relationship and relied on the shell structure and

form of the larval shell to conclude that Gastropoda and

Monoplacophora are sister groups. Cephalopoda is then

a sister group to the other four conchiferan classes. How-

ever, Wingstrand (1985), Brusca and Brusca (1990) and

von Salvini-Plawen (1985, 1990a) considered “Monopla-

cophora’’ (i.e. class Tergomya sensu Peel, 1991 or Try-

blidiida sensu Wingstrand, 1985; see Peel, 1991 for a

discussion) as a sister group to the four other conchiferan

classes, which in turn consist of a Bivalvia-Scaphopoda

clade and a Gastropoda-Cephalopoda clade. The former

is characterized by the presence of a mantle surrounding

the entire body, reduction of the head and a laterally

compressed form. The latter is determined by the pres-

ence of a well developed head, dorsoventral elongation,

dorsal concentration of the viscera and shell coiling (Brus-

ca & Brusca, 1990). Except for the position of the “Mon-

oplacophora’”, this view agrees well with the division of

the Conchifera into the clades Diasoma (classes Bivalvia,

Scaphopoda and the fossil Rostroconchia) and Cyrtosoma

(classes ““Monoplacophora”, Gastropoda and Cephalo-

poda), which is widely accepted among paleontologists

(Runnegar & Pojeta, 1974, 1985; Pojeta, 1980; Steiner,

1992). Yet, Peel (1991) recently suggested that Cyrto-

soma and Diasoma are both polyphyletic.

The oldest fossil molluscs date from 570 MYA (e.g.

Runnegar & Pojeta, 1974, 1985; Valentine, 1980), near

the Precambrian-Cambrian boundary. This period was

marked by an explosive radiation of animals resulting in

the appearance of most extant invertebrate phyla (e.g.

B. Winnepenninckx et al., 1994

Table 1. List of 17 oligonucleotides complementary to con-

served regions in eukaryotic 18S rRNA genes. These were used

to determine the sequence of both strands of the 18S rRNA

gene of Onchidella celtica.

Corresponding position

in the 18S rRNA gene

Sequence! Strand? of Onchildella celtica

CTGGTTGATYCTGCCAGT R 4-21

GAAACTGCGAATGGCTCATT R 82-101

AATGAGCCATTCGCAGTTTC C 101-82

AGGGYTCGAYYCCGGAGA R 393-410

TCTCCGGRRTCGARCCCT C 410-393

TCTCAGGCTCCYTCTCCGG C 422-404

ATTACCGCGGCTGCTGGC C 605-588

CGCGGTAATTCCAGCTCCA R 097-615

TTGGYRAATGCTTTCGC C 990-974

TTRATCAAGAACGAAAGT R 1002-1019

CCGTCAATTYYTTTRAGTTT C 1188-1169

AATTTGACTCAACACGGG R 1221-1238

GGGCATCACAGACCTGTTAT C 1479-1460

ATAACAGGTCTGTGATGCCC R 1460-1479

TTTGYACACACCGCCCGTCG R 1666-1685

GACGGGCGGTGTGTRC C 1684-1669

CYGCAGGTTCACCTACRG C 1833-1816

1 Sequence positions where both purines (A and G) are present

are indicated by “R”, those where both pyrimidines (C and T)

are present by “Y”’.

2 Oligonucleotides with a sequence corresponding to that of the

RNA-like strand are indicated by a “R’, those whose sequence

is complementary to it, by a “C’.

Bergstrom, 1991; Erwin, 1991; Valentine, 1991). Several

aspects of the metazoan branching pattern still remain

confused due to the doubtful homology of the relatively

few morphological, anatomical and embryological char-

acters shared by different phyla (e.g. Nielsen, 1977; An-

derson, 1981; Inglis, 1985; Bergstrom, 1986; Ax, 1989;

Schram, 1991; Backeljau et al., 1993). Nevertheless, Mol-

lusca appear to be a monophyletic group belonging to

the Spiralia (i.e. Platyhelminthes, Nemertini, Mollusca,

Sipuncula, Echiura and Annelida, and probably Gna-

thostomulida and Entoprocta) (e.g. Wingstrand, 1985;

Brusca & Brusca, 1990; Willmer, 1990), but no syna-

pomorphies are known linking the Mollusca unambig-

uously to any other spiralian phylum (e.g. Wingstrand,

1985; Erwin, 1991). Some authors (e.g. von Salvini-Plaw-

en, 1990a) suggest a sister group relationship to Turbel-

laria (Platyhelminthes) considering the flat, often cili-

ated, ventral creeping foot as a synapomorphy relating

both phyla. Many others however, include the Mollusca

in the protostome clade (e.g. Wingstrand, 1985; Brusca

& Brusca, 1990; Willmer, 1990; Schram, 1991).

Biochemical and molecular characters have been in-

troduced as an independent source of phylogenetic in-

formation. A serological study of molluscs, echinoderms,

annelids and arthropods suggested that Mollusca are most

closely related to Annelida (Wilhelmi, 1944). Lyddiatt

et al. (1978) used cytochrome c amino acid sequence

data to deduce a sister group relationship between mol-

Page 99

luscs and echinoderms. In studies using 5S ribosomal

RNA (rRNA) sequences (Ohama et al., 1984; Hendriks

et al., 1986; Hori & Osawa, 1987), the Mollusca (rep-

resented by Bivalvia, Gastropoda and Cephalopoda) ap-

peared as a polyphyletic group. From the analysis of

Lenaers and Bhaud (1992) on the basis of partial se-

quences of 28S rRNA, Mollusca (represented by Mytilus

edulis) appeared to be a sister group to Annelida. Holland

et al. (1991) used partial small subunit (SSU) rRNA (18S

tRNA) sequences and suggested that Mollusca (repre-

sented by Mytilus edulis) and Arthropoda are sister taxa.

On the basis of mitochondrial SSU rRNA sequences the

Mollusca, represented by a prosobranch and a chiton,

appeared as sister group to the Annelida or as a para-

phyletic group including the latter phylum (Ballard et

al., 1992) . In all these studies, however, the data sets

were too limited to allow reliable conclusions. Field et

al. (1988) determined partial sequences of SSU rRNA

from representatives of ten different metazoan phyla

including four Mollusca, viz. an opisthobranch gastropod,

two bivalves and a chiton. Yet, different phylogeny in-

ference methods yielded contradictory results. Field et

al. (1988; see also Raff et al., 1989) used a distance

method to conclude that Mollusca form a clade with

Annelida, Sipuncula, Brachiopoda and Pogonophora.

However, the relationships between the five groups were

not resolved. Ghiselin (1988, 1989) reanalyzed this data

set with a ‘signature’ approach and concluded that mol-

luscs are a sister group to the Annelida sensu lato (i.e.

Annelida sensu strictu, Brachiopoda, Pogonophora and

Sipuncula). A maximum parsimony analysis of the same

data produced a similar clade containing Sipuncula, Po-

gonophora, Brachiopoda, Annelida and Mollusca (Pat-

terson, 1989) but with the latter two phyla not being

monophyletic. Lake (1989), who applied evolutionary

parsimony, also concluded that Mollusca are paraphy-

letic.

In a preliminary attempt, we use complete SSU rRNA

sequences to assess molluscan phylogeny. We consider

sequences to be complete if (1) the sequence of the entire

18S rRNA molecule is known or (2) if only a total number

on the order of 50 nucleotides at the 5’ and 3’ terminal

parts are missing because they are used as PCR primer

annealing sites (e.g. Rice, 1990; Littlewood, 1991). Hith-

erto, complete 18S rRNA sequences of only three mol-

luscan species viz., the bivalves Placopecten magellan-

icus and Crassostrea virginica and the gastropod

Limicolaria kambeul, have been published respectively

by Rice (1990), Littlewood (1991) and Winnepenninckx

et al. (1992) . In this paper we present the complete 185

rRNA sequence of the gymnomorphan snail Onchidella

celtica (Cuvier, 1817). A fifth molluscan sequence (Win-

nepenninckx et al. , 1993), that of the chiton Acantho-

pleura japonica (Lischke, 1873) is also included.

Small ribosomal subunit RNA sequences

SSU rRNA sequences combine several features that make

them appropriate for phylogenetic studies (Raff et al.,

Page 100 THE NAUTILUS, Supplement 2

Onchidella celtica 39 43

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Figure 1. Secondary structure model for the 18S rRNA of Onchidella celtica. Helix numbering from helix 19 onward has changed

with respect to the numbering used by De Rijk et al. (1992), due to the discovery of a tertiary structure interaction in helix 19

(Woese & Gutell, 1989).

B. Winnepenninckx et al., 1994

Table 2. The 18S rRNA sequence of the gastropod Onchidella celtica.

UAUCUGGUUGAUCCUGCCAGUAGUCAUAUGCUUGUCUCAAAGAUUAAGCC

AUGCAUGUCUAAGUUCACACUGUCUCACGGUGAAACCGCGAAUGGCUCAU

UAAAUCAGUCGAGGUUCCUUAGAUGACACGAUCCUACUUGGAUAACUGUG

GCAAUUCUAGAGCUAAUACAUGCUAUUCAAGCUCCGACCCUCUGGGGAAG

AGCGCUUUUAUUAGUUCAAAACCAAUCGCCGUGUGCUCUUCCCGGGGCCG

GGCGUCCCCCUUGGUGACUCUGGAUAACUUUGUGCUGAUCGCAUGGCCUU

UUGCGCCGGCGACGCAUCUUUCAAAUGUCUGCCCUAUUAAAUGCGAUGGU

ACGUGAUAUGCCUACCAUGUUUGUAACGGGUAACGGGGAAUCAGGGUUCG

AUUCCGGAGAGGGAGCAUGAGAAACGGCUACCACAUCCAAGGAAGGCAGC

AGGCGCGCAACUUACCCACUCCCGGCACGGGGAGGUAGUGACGAAAAAUA

ACAAUACGGGACUCUUUCGAGGCCCAGUAAUUGGAAUGAGUACACUUUAA

ACCCUUUAACGAGGAUCUAUUGGAGGGCAAGUCUGGUGCCAGCAGCCGCG

GUAAUUCCAGCUCCAAUAGCGUAUAUUAAAGUUGUUGCAGUUAAAAAGCU

CGUAGUUGGAUCUCAGGCGCAGGCGGGCGGUCCGGCUCGCGCCGCUCACU

GCCCGUUGUCUCCUGCCCUACCUGUUGCCGGCUCUCUCCCGUGGGUGCUC

UUCGCUGAGCGUCCGGGUGGC CGGCGCGUUUACUUUGAAAAAAUUAGAGU

GUUCAAAGCAGGCCUCGCCUGCCUGAAUAAUUGCGCAUGGAAUAAUGGAA

UAGGACCUCGGUUCUAUUUUGUUGGUUUUCGGAACUGGAGGUAAUGAUUA

ACAGGGACAAACGGGGGGAUUCGUAUUGCGGCGUUAGAGGUGAAAUUCUU

GGAUCGCCGCAAGACGAGCUACUGCGAAAGCAUUUGUCAAGAAUGUUUUC

AUUAAUCAAGAACGAAAGUCAGAGGCGAGAAGACGAUCAGAUACCGUCGU

AGUUCUGACCAUAAACGAUGCCGACCAGCGAUCCGCAGGAGUUGCUUCGA

UGACUCUGCGGGCAGCUUCCGGGAAACCAAAGUGUUUGGGUUCCGGGGGA

AGUAUGGUUGCAAAGCUGAAACUUAAAGGAAUUGACGGAAGGGCACCACC

AGGAGUGGAGCCUGCUGCUUAAUUUGACUCAACACGGGAAAACUCACCCG

GUCCGGACACUGUAAGGAUUGACAGAUUGAUAGCUCUUUCUUGAUUCGGU

GGGUGGUGGUGCAUGGCCGUUCUUAGUUGGUGGAGCGAUUUGUCUGGUUA

AUUCCGAUAACGAACGAGACUCUAGCCUAUUAAAUAGUUCGCCGGUCCCU

CGAUGCGCCGGCGCAACUUCUUAGAGGGACGAGUGGCGUUUAGCCAACGA

GAUUGAGCAAUAACAGGUCUGUGAUGCCCUUAGAUGUCCGGGGCCGCACG

CGCGCUACACUGAAGGAAUCAGCGUGGAUGCCUCCCUGGCCCGAAAGGCU

GGGAAACCCGUUGAAUCUCCUUCGUGCUAGGGAUUGGGGCUUGUAAUUCU

UCCCCAUGAACGAGGAAUUCCCAGUAAGCGCGAGUCAUAAGCUCGCGUUG

AUUACGUCCCUGCCCUUUGUACACACCGCCCGUCGCUACUAUCGAUUGAG

CGGUUCAGUGAGGGCAUCGGAUUGGUCUCGGUCUGGUGUUCGCGCACCGG

CACCGCUGGCCGAGAAGACGCUCGAACUCGAUCGCUUGGAGAAAGUAAAA

GUCGUAACAAGGUUUCCGUAGGUGAACCUGCGGAAGGAUCAUUA

Page 101

1989; Hillis & Dixon, 1991; Solignac et al., 1991; Woese,

1991): (1) universality; (2) constancy of function; (3) al-

ternation of conserved regions with variable ones, allow-

ing phylogenetic studies at a broad range of taxonomical

levels; (4) presence of conservative regions that allow the

design of “universal” primers; (5) a conservative second-

ary structure facilitating the identification of homologous

positions in regions with little sequence similarity; (6)

apparent absence of lateral gene transfer; (7) a large

information content (1800-1900 bp) (8) intraspecific se-

quence homogeneity among different gene copies (Ger-

bi, 1985; Dover, 1986).

Gene cloning

Much sequence information on rRNAs has been obtained

by direct RNA sequencing using reverse transcriptase

(Lane et al., 1985; Solignac et al., 1991) or by direct

sequencing of the rRNA genes after PCR amplification

(Saiki et al., 1988). Both techniques are very rapid. Yet

we prefer to clone and sequence the 18S rRNA genes,

for direct RNA sequencing has some disadvantages: (1)

RNA is less stable than DNA; (2) subsequent checking

of sequences is not possible; (3) sequencing of regions

with strong secondary structure is difficult; (4) reverse

transcriptase has a rather high error frequency; (5) only

one strand is available and thus two-strand verification

is not possible. All this results in an overall error rate of

about 1% (Lane et al., 1985). Although PCR amplifica-

tion eliminates a great deal of these problems, it also has

some drawbacks (Hillis & Dixon, 1991): (1) Taq poly-

merase has a high error rate, viz. 210-4 to <1X10°

according to Eckert and Kunkel (1991) and 2.75 10°

according to Bej et al. (1991); (2) the 3’ and 5’ parts of

the gene itself have to be used as primer annealing sites,

if the sequence of the adjacent regions is unknown; (3)

direct sequencing of PCR amplified fragments is difficult

(e.g. Gyllenstein, 1989); (4) the product is afterwards not

available to others for verification. By cloning the PCR

product prior to sequencing, the latter two problems can

be overcome, but the sequencing of numerous clones is

necessary to avoid an enhancement of the error rate

Page 102

Distance 0.1

92, Rattus norvegicus 1

Mus musculus

Homo sapiens 1

O16

Echinorhinus cookei

Tenebrio molitor

Artemia salina

Eurypelma californica

Crassostrea virginica

100 Acanthopleura japonica

| 0 Onchidella celtica

Limicolaria kambeul

100

Anemonia sulcata

Oryctolagus cuniculus

Turdus migratorius

Heterodon platyrhinos

Alligator mississippiensis

Xenopus laevis

Ps Latimeria chalumnae

ee ‘ Squalus acanthias

81| Sebastolobus altivelis

Fundulus heteroclitus

Herdmania momus

Oedignathus inermis

Placopecten magellanicus

Schistosoma mansoni 1

Opisthorchis viverrini

Paramecium tetraurelia

THE NAUTILUS, Supplement 2

Vertebrata

Chordata

Tunicata

Crustacea

Insecta

Crustacea Arthropoda

Acyrthosiphon pisum Insecta

Chelicerata

Pivatvia

Polyplacophora |Mollusca

_|sestronoaa

Trematoda Platy =

helminthes

Cnidaria

Ciliata

Figure 2. Neighbor-joining tree based on the 18S rRNA sequences from 27 Metazoa. All sequences were complete except for the

following (number of sequenced nucleotides between brackets): Turdus migratorius (1753), Alligator mississippiensis (1691),

Heterodon platyrhinos (1717) and Latimeria chalumnae (1777). Paramecium tetraurelia was chosen as an outgroup. Bootstrap

values are indicated at the root of each clade, but only if they exceed 50%.

(Bevan et al., 1992). This of course reduces the time

advantage of PCR amplification.

MATERIALS AND METHODS

Animals: Specimens of Onchidella celtica collected at

Vila Franca do Campo (Sao Miguel, Azores) were frozen

alive and preserved at -80°C. Voucher material was de-

posited in the collections of the “Koninklijk Belgisch

Instituut voor Natuurwetenschappen , Brussels (general

inventory number, I.G. No. 28053).

DNA extraction: Digestive glands of ten specimens were

pooled and homogenized under liquid nitrogen in a pre-

chilled mortar and transferred to 15 ml of preheated

(60°C) 2% CTAB buffer (2% (w/v) CTAB; 0.2% (v/v)

2-mercaptoethanol, 1.4 M NaCl; 20 mM EDTA; 100 mM

Tris-HCl pH=8; 100 ug/ml proteinase K). After incu-

bation at 60°C for 30 min., further extraction was done

Table 3. Organisms that were used as outgroup in our analyses.

Species Position

Zea mays angiosperms

Neurospora crassa ascomycetes

Saccharomyces cerevisiae ascomycetes

Rhodosporidium toruloides basidiomycetes

Gracilaria lemaneiformis red algae

Porphyra umbilicalis red algae

green algae

dinoflagellates

Chlorella ellipsoidea

Volvox carteri

Prorocentrum micans

Giardia duodenalis diplomonads

Trypanosoma brucei kinetoplastids

Paramecium tetraurelia ciliates

Oxytricha nova ciliates

apicomplexa (Sporozoa)

slime molds

Plasmodium berghei

Dictyostelium discoideum

B. Winnepenninckx et al., 1994

Distance 0.1

90° Rattus norvegicus 1

98! Mus musculus

Homo sapiens 1

100

Tenebrio molitor

Artemia salina

Eurypelma californica

Anemonia sulcata

Zea mays

Echinorhinus cookei

Placopecten magellanicus

Crassostrea virginica

400 Acanthopleura japonica

a 04 Onchidella celtica

Limicolaria kambeul

Oryctolagus cuniculus

Turdus migratorius

91 |

59) Heterodon platyrhinos

Alligator mississippiensis

Xenopus laevis

os Latimeria chalumnae

100] Squalus acanthias

; Fundulus heteroclitus

Sebastolobus altivelis

Page 103

Vertebrata Chordata

Herdmania momus ~ Tunicata

Schistosoma mansoni 1 RASMACSSIA ie ee

Opisthorchis viverrini minthes

Oedignathus inermis Crustacea

Insecta

Crustacea Arthropoda

Acyrthosiphon pisum Insecta

Chelicerata

[pivaivia

_Polyplacophora Mollusca

pastropoaa

Cnidaria

Magnolic-

phyta

Figure 3. Neighbor-joining tree based on the same set of metazoan 18S rRNA sequences as in Fig. 2, but with Zea mays as an

outgroup. Bootstrap values are indicated as in Fig. 2.

as described by Winnepenninckx et al. (1993a). The DNA

yield amounted to 60 ug.

Gene cloning and sequencing: Restriction enzymes suit-

able for isolation of a DNA fragment containing the 18S

rRNA gene were identified as described by Winnepen-

ninckx et al. (1992). After digestion of 1.2 ug DNA with

BamHI and separation on a 0.8% (w/v) agarose gel,

restriction fragments of 4 kb containing the 18S rRNA

gene were eluted (Heery et al., 1990). Competent DH5a

E. coli cells (Gibco BRL Life Technologies; Gaithersburg,

USA) were transformed with these DNA restriction frag-

ments ligated into pBluescriptSK* (Stratagene; La Jolla,

California, USA). Colony screening was performed using

a PCR fragment of the gastropod Limicolaria kambeul

(Winnepennincksx et al., 1992), labeled with **P via nick

translation (Rigby et al., 1977). Plasmids were isolated

(Birnboim & Doly, 1979) from a single clone and se-

quencing was performed by the dideoxynucleotide

method (Sanger et al., 1977) using Sequenase 2.0 (USB;

Cleveland, Ohio, USA). The 18S rRNA primers used are

given in Table 1.

Sequence alignment and construction of phylogenetic

trees: The Onchidella celtica 18S rRNA sequence was

aligned with other SSU rRNA sequences present in our

database (De Rijk et al., 1992). Alignment was done

manually taking into account the secondary structure

features of the molecule, as described by De Rijk et al.

(1992). For tree construction, pairwise distances were

calculated using the formula of Jukes and Cantor (1969)

modified to take into account gaps (Van de Peer et al.,

1990). They served to derive neighbor-joining trees (Sai-

tou & Nei, 1987), whose reliability was tested by boot-

strapping (Felsenstein, 1985) over 100 replicates. Ac-

cording to the guidelines of Hillis and Bull (1993), only

branching points with bootstrap values higher than 70%

were considered to be reliable. Estimated internal

branches with bootstrap values above 70% should rep-

resent true clades over 95% of the time (Hillis & Bull,

Page 104

Distance 0.1

——

THE NAUTILUS, Supplement 2

98, Rattus norvegicus 1

99} Mus musculus

100|L Homo sapiens 1

Turdus migratorius

70 Oryctolagus cuniculus

Tenebrio molitor

Artemia salina

Eurypelma californica

Placopecten magellanicus

Crassostrea virginica

canthopleura japonica

Anemonia sulcata

Acyrthosiphon pisum

Giardia lamblia

Heterodon platyrhinos

Xenopus laevis

Latimeria chalumnae

eg Squalus acanthias

Echinorhinus cookei

" Sebastolobus altivelis

Fundulus heteroclitus

Alligator mississippiensis Vertebrata Ghoraaes

Herdmania momus Tunicata

j j hel-

EMSS 1 Giensen Ee es eee:

Opisthorchis viverrini Naeia

Oedignathus inermisCrustacea

Insecta

Arthropoda

Crustacea P

Chelicerata ul

‘jpivaivia

Polyplacophora| Mollusca

Gastropoda

Cnidaria

Arthropoda

Poly -

mastigotes

Insecta

Figure 4. Neighbor-joining tree based on the same set of metazoan 18S rRNA sequences as in Fig. 2, but with Giardia duodenalis

(often called Giardia lamblia or Giardia intestinalis) as an outgroup. Bootstrap values are indicated as in Fig. 2.

1993). All calculations were carried out with the TREE-

CON package of Van de Peer and De Wachter (1993).

Character state analyses using maximum parsimony were

performed using the package HENNIG86 (version 1.5;

Farris, 1989) with the heuristic algorithms MHENNIG*

and BB* combined. The results were summarized in a

strict consensus tree, i.e. a tree that contains only those

clusters that are common to all competing trees (“nelsen”

command of HENNIGS86). Nucleotides were treated as

non-additive characters and no differential weighting

was done.

RESULTS

Sequence Alignment

The 18S rRNA of Onchidella celtica (EMBL accession

number X70211), of which the nucleotide sequence is

shown in Table 2, is 1844 nucleotides long. The 3’ and

5’ termini of the gene were located on the basis of sim-

ilarity with those of other 18S rRNA sequences. Figure

1 shows a secondary structure model of the molecule in

accordance with the one published for Limicolaria kam-

beul (Winnepenninckx et al., 1992). Both models show

high similarity to each other and are in accordance with

the general model proposed for eukaryotic SSU rRNA

(De Rijk et al. 1992). Based on our latest insights into

the secondary structure of 18S RNA, modifications were

made in helices 19, 20, 21 and 38. The new gastropod

sequence as well as the one of Acanthopleura japonica

(Winnepenninckx et al., 1993b) were added to an align-

ment of other SSU rRNA sequences (De Rijk et al., 1992).

This alignment can be obtained on request. Trees were

constructed on the basis of a set of 27 metazoan sequences

which are either complete or nearly complete.

Distance Matrix Analyses

Figure 2 shows the neighbor joining (NJ) tree obtained

with the ciliate Paramecium tetraurelia as outgroup. It

B. Winnepenninckx et al., 1994

Page 105

Distance 0.1

——_——

95, Rattus norvegicus 1

99! Mus musculus

Homo sapiens 1

Turdus migratorius

Xenopus laevis

‘a Latimeria chalumnae

9 ‘oof Squalus acanthias

Echinorhinus cookei

73 Sebastolobus altivelis

Fundulus heteroclitus

80 Herdmania momus

Artemia salina

Tenebrio molitor

Eurypelma californica

Placopecten magellanicus

Crassostrea virginica

100 Acanthopleura japonica

on 109 Onchidella celtica

Limicolaria kambeul

100

Anemonia sulcata

Oryctolagus cuniculus

Heterodon platyrhinos

Alligator mississippiensis

Schistosoma mansoni 1

Opisthorchis viverrini

Paramecium tetraurelia

Crustacea

Insecta Arthropoda

Chelicerata

Acyrthosiphon pisum Insecta

Bivalvia

Polyplacophora| Mollusca

ta :

Vertebra ete See

Tunicata

Gastropoda 7

Trematoda Platyhel-

minthes

Cnidaria

Ciliata

Figure 5. Neighbor-joining tree obtained on the basis of a set containing all the 185 rRNA metazoan sequences of Fig. 2 except

Oedignatus inermis. Paramecium tetraurelia was used as an outgroup. Bootstrap values are indicated as in Fig. 2.

suggests that (bootstrap values in parentheses): (1) Mol-

lusca are a monophyletic group (100/100) within a rel-

atively poorly supported protostome clade (62/100); (2)

Gastropoda (100/100) and Bivalvia (99/100) are mono-

phyletic as well; (3) Polyplacophora appears as a sister

group to the Gastropoda (100/100). The tree also indi-

cates that : (1) Cnidaria are a sister group to Eubilateria

(100/100); (2) Acoelomata, represented by two Trema-

toda, are a sister group to the Eucoelomata (76/100); (3)

Arthropoda are a monophyletic group (88/100); (4) nei-

ther Insecta nor Crustacea are monophyletic; (5) Chor-

data (99/100) and Vertebrata (100/100) are both mono-

phyletic.

We attempted to assess the stability of our tree by

testing its sensitivity to the presence of specific taxa. First

we studied the influence of the outgroup by successively

replacing Paramecium tetraurelia by each of the 14

other organisms listed in Table 3. We observed only two

topological changes. In nine out of the 15 cases, the

topology shown in Figure 3 was obtained, i.e. the Pla-

tyhelminthes appeared as a sister group to the Arthro-

poda-Mollusca clade. In one case, the topology shown in

Figure 4 was obtained, viz. when the diplomonad Giar-

dia duodenalis, was chosen as outgroup. This organism

forms a very long branch in previously published trees

comprising organisms from different eukaryotic king-

doms (e.g. Van de Peer et al., 1993). In this case, the

aphid Acyrthosiphon pisum, which is also marked by an

exceptionally long branch, became a sister group to all

other Metazoa. The latter observation is probably due to

the fact that errors in distance estimation increase with

the amount of divergence. Long branches will provoke

an underestimation of the evolutionary distance and will

systematically attract each other, causing biased topol-

ogies (Felsenstein, 1978; Olsen, 1987; Swofford & Olsen,

1990; Lake, 1991). The changes in the position of the

Platyhelminthes, which do not have exceptionally long

branches, is probably not due to such a systematic error.

The low bootstrapping values on their branching point,

suggests uncertainty as to their position. Inclusion of rep-

resentatives of more invertebrate phyla might be helpful

in this case.

Page 106

_[pescnoste sulcata

Paramecium tetraurelia

| j-Heramania momus

|_| Oats emorehis W/ILW/AS'S IS aL Oat

Schistosoma mansoni

Ee erases celtica

ee ee californica

Artemia salina

peige

Tenebrio molitor

f—Latimeria chalumnae

ees

omo sapiens

Lise. musculus

f—Acanthopleura japonica

LY ptimicotaria kambeul

Gignathus inermis

p 2 HeoOseerem magellanicus =|

es virginica | |

L| [racyrthosiphon pisum |

iS Squalus acanthias

| j-Fundulus heteroclitus

psoas colons altivelis

LE Pehenorhinus cookei

Xenopus laevis

po Seeeoson platyrhinos

Alligator mississippiensis

res migratorius

ryctolagus cuniculus

THE NAUTILUS, Supplement 2

Cnidaria

Ciliata

Tunicata Chordata

Trematoda Platyhel

| minthes

Polyplacophora Mollusca

Gastropoda

Chelicerata

Crustacea Arthropoda

| a8ecce

Vertebrata Chordata

Rattus norvegicus |

Figure 6. Strict consensus tree constructed from three maximum parsimony trees (length=3114 steps; c.i= 0.51) obtained by

applying the MHENNIG* + BB* option of Hennig86 on the 706 informative positions of the same alignment as in Fig. 2 and with

Paramecium tetraurelia chosen as outgroup.

Subsequently, we constructed 27 trees with Parame-

cium tetraurelia as outgroup, but each time omitting one

species. Only one topological change was observed: when

excluding Oedignathus inermis, Acyrtosiphon pisum

branched off first within the arthropod clade (Figure 5).

The fact that this change involves the species with the

longest branch, again points to the above mentioned “long

branch effect” (Felsenstein, 1978; Swofford & Olsen,

1990). Since the placement of the two Platyhelminthes

was ambiguous (cfr. Figures 2 and 3) and since we sus-

pected Acyrthosiphon pisum to be a source of systematic

errors, we removed all three species from our data set

to assess their impact. However, the topology of the tree

we obtained did not differ from the one in Figure 2.

Character State Analyses

The 28 species analysed, with Paramecium tetraurelia

as outgroup, yielded 706 informative sites. A position is

informative if it contains at least two different nucleo-

tides, each of them present in at least two species (Nei,

1987). Ambiguous nucleotides were not used to ascertain

the informative character of a position. Three maximum

parsimony (MP) trees of 3114 steps and with a consis-

tency index (c.i.) (Kluge & Farris, 1969) of 0.51 were

found. The strict consensus tree shown in Figure 6 sug-

gests that (1) Mollusca, Bivalvia and Gastropoda are

monophyletic groups; (2) Polyplacophora appear as a

sister group to Gastropoda; (3) Arthropoda are a mono-

phyletic clade in which Chelicerata branch off first; (4)

Insecta are monophyletic but Crustacea are paraphyletic;

(5) Vertebrata are monophyletic. Ten different data in-

put orders did not change this topology. Again we tested

the stability of our results. If the placement of a taxon

is biased, its removal should cause an increase of the

consistency index (Swofford & Olsen, 1990). We checked

this by successively removing those species, the position

of which appeared unstable in our distance matrix anal-

yses, viz. Acyrthosiphon pisum, Schistosoma mansoni,

Opisthorchis viverrini, and a fourth species, Mus mus-

culus, which occupied a stable position. Each time we

identified the informative positions anew and applied

HENNIG86 with Paramecium tetraurelia as outgroup.

Omitting Acyrthosiphon pisum increased the c.i. to 0.53,

while removing any of the other species did not change

the c.i. This again suggests that the placement of Acyr-

thosiphon pisum is liable to a systematic error. As for

the ambiguous position of the Platyhelminthes, this may

B. Winnepenninckx et al., 1994

Page 107

_|Fetetonse sulecata

Paramecium tetraurelia

__ peesssyosom mansoni

Opisthorchis viverrini

ee celtica

[et eolakia kambeul

[jeeetzzcstcee japonica

Crassostrea virginica

Placopecten magellanicus

Oedignathus inermis

p BeMebELo molitor

Artemia sali

= alina

| prreranania Calli ronnaca

Herdmania momus

p scnamorinaus cookei

Ps ebas coLolsus altive

| Erunduius heteroclit

qualus acanthias

Latimeria chalumnae

| j-Xenopus laevis

Alligator missi

ae migrator

Homo sapiens

Heterodon platyrhinos

Cnidaria

Ciliata

Platyhel —

minthes

Trematoda

Polyplacophora} Mollusca

Gastropoda

Bivalvia

Se gis eal

Crustacea al

Insecta Arthropoda

Crustacea

Chelicerata

Tunicata

lis

Chordata

Vertebrata .

ssippiensis

ius

Crore cee cuniculus

, ts musculus

Rattus norvegicus

Figure 7. Strict consensus tree constructed from two maximum parsimony trees (length=2741 steps; c.i=0.53) obtained with the

MHENNIG*+BB* option on the 658 informative sites of the same alignment of Fig. 2 from which the insect Acyrthosiphon pisum

was removed.

be due to the lack of other invertebrate phyla and classes.

Figure 7 shows the strict consensus tree of the two MP

trees (length=2741; c.i=0.53) obtained when Acyrtho-

siphon pisum was excluded. All our conclusions based

on the tree in Figure 6 remain valid, but in addition the

bilaterian pentachotomy of Figure 6 is now resolved.

Mollusca appear as a sister group to a clade containing

Arthropoda and Chordata. It is also suggested that (1)

Bilateria are monophyletic; (2) Acoelomata are a sister

group to Eucoelomata; (3) Chordata are monophyletic.

DISCUSSION

The monophyletic character of the Mollusca, the Bivalvia

and the Gastropoda, which is supported by all our trees,

is generally accepted (e.g. Brusca & Brusca, 1990; Will-

mer, 1990; von Salvini-Plawen, 1985, 1990a; Gotting,

1980). Using globin amino acid sequences, Goodman et

al. (1988) agreed with these views. The 5S rRNA based

analyses of Ohama et al. (1984), Hendriks et al. (1986)

and Hori and Osawa (1987) also confirmed gastropod

monophyly. Ghiselin (1988, 1989) supported molluscan

monophyly. But Patterson (1989) and Lake (1989) did

not corroborate these well established views, while the

question was not resolved by Field et al. (1988; see also

Raff et al., 1989).

In both the distance and MP trees, we find the chiton

included within the conchiferan clade as a sister group

to the Gastropoda. This result is in contrast with the

results of anatomical (e.g. Milburn, 1960; Stasek, 1972;

Gotting, 1980; Scheltema, 1988; Brusca & Brusca, 1990;

von Salvini-Plawen, 1990a) and paleontological (e.g.

Runnegar & Pojeta, 1974; Pojeta, 1980; Peel, 1991) stud-

ies. Neither Field et al. (1988; see also Raff et al., 1989),

nor Ghiselin (1988, 1989) or Lake (1989) were able to

resolve the position of the Polyplacophora, while Pat-

terson (1989) suggested that Polyplacophora and Brach-

iopoda are sister taxa. Using mitochondrial SSU rRNA

sequences (Ballard et al., 1992), the class either appeared

as a sister group to the Gastropoda-Annelida clade or

formed together with the Gastropoda a sister group to

the Annelida. Addition of more molluscan representa-

tives to our data set is necessary to investigate the con-

flicting position of the Polyplacophora.

Our current data set is also not sufficiently represen-

tative to draw conclusions on the position of the Mollusca

among other Metazoa. From our NJ analyses, the phylum

appears as a sister group to the Arthropoda (see also

eee ee ee rere ————

Page 108

Holland et al., 1991) but this topology is insufficiently

supported by bootstrap values. According to the char-

acter state analysis it branches off before the Chordata-

Arthropoda clade. Data from additional invertebrate

phyla should be included.

All our current analyses strongly support the view that:

(1) Arthropoda is a monophyletic group and (2) Verte-

brata, Chordata and Bilateria are monophyletic. These

observations are in agreement with the results of some

classical (e.g. Ax, 1989; Brusca & Brusca, 1990; Schram,

1991) and molecular studies (Ghiselin, 1988, 1989; Pat-

terson, 1989; Raff et al., 1989; Winnepenninckx et al.,

1992). Contradictory views on these aspects of metazoan

phylogeny were given by e.g. Lake (1989), Willmer (1990)

and Fryer (1992). However our analyses do not allow

conclusions on the status of the Acoelomata and the mono-

or paraphyletic character of the Insecta and Crustacea.

It is beyond the scope of this paper to expand on meta-

zoan evolution, however the congruence of most of our

results with independently derived hypotheses suggests

that complete 18S rRNA sequences are a reliable tool to

assess the phylogeny of the Mollusca and other metazoan

groups.

ACKNOWLEDGMENTS

We are indebted to Dr. A.M. Frias Martins (University

of the Azores) for helping to collect Onchidella celtica.

The investigations were performed in the framework of

the Institute for the Study of Biological Evolution of the

University of Antwerp. This work was supported by

FKFO Grants 2.0023.94 and 2.0003.93. B. Winnepen-

ninckx holds an I.W.O.N.L. scholarship.

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Page 111

Preliminary Ribosomal RNA Phylogeny of Gastropod and

Unionoidean Bivalve Mollusks

Gary Rosenberg

Academy of Natural Sciences

1900 Benjamin Franklin Parkway

Philadelphia, PA 19103 USA

George M. Davis

Academy of Natural Sciences

1900 Benjamin Franklin Parkway

Philadelphia, PA 19103 USA

Gerald S. Kuncio

Department of Medicine

University of Pennsylvania

Philadelphia, PA 19104 USA

M. G. Harasewych

Department of Invertebrates

National Museum of Natural History

Smithsonian Institution

Washington, D.C. 20560 USA

ABSTRACT

Sequences of about 150 nucleotides in the D6 region of the

large (28S) ribosomal molecule were obtained from 20 union-

oidean bivalves and 13 gastropods, including 9 truncatellids, 1

muricid, 1 cancellariid, 1 melongenid, and 1 pleurotomariid.

These were analyzed along with sequences from Emberton et

al. (1990) for 8 pulmonates, a helicinid and a pomatiopsid.

Rates of divergence varied by a factor of two, with unionoidean

and the helicinid sequences differing by 15-20% relative to

mouse, pulmonates by 22-24%, neogastropods by 24-27%, and

rissooideans by 27-32%. Length variation among sequences

occurred mainly in the D6 loop, and complementary mutations

were seen in the D6 stem. Cladistic analysis found 24 equally

parsimonious trees; the strict consensus supports monophyly of

Unionoidea, Rissooidea, Pulmonata and Stylommatophora.

Monophyly of Neogastropoda is not contradicted.

Some groupings are anomalous when compared to mor-

phology-based phylogenies. Helicinidae groups with Uniono-

idea, Pleurotomariidae with Neogastropoda, and Geomelania

(Truncatellidae) with Pomatiopsidae. In each case, addition of

taxa that intersect long branches (e.g. Chitonidae, Patellogas-

tropoda) might show that characters interpreted as synapo-

morphic are plesiomorphic or convergent. The observed group-

ing of Muricidae and Cancellariidae is well-supported, indicating

that cancellariids are a highly derived group within the Sten-

oglossa. Pleurotomariidae are more closely related to the other

gastropods in the analysis than are Helicinidae, supporting Ha-

szprunar s (1988) anatomy-based conclusion.

To date, sequence studies of mollusks have not overturned

phylogenies based on morphology, but rather have helped in

choosing among competing morphology-based hypotheses. Like

morphological data, sequence data are subject to problems of

convergence, unequal rates of evolution, and choice of taxa.

Classifications must be based on all available data to maximize

the potential for detecting convergences and correctly resolving

phylogenetic relationships.

Key words: Gastropoda, Bivalvia, 28S ribosomal RNA, phylog-

eny, cladistics, rates of divergence.

INTRODUCTION

Ribosomal RNA (rRNA) and rDNA sequences have prov-

en to be valuable and versatile sources of data for phy-

logenetic inferences. The great variation in rates of evo-

lution of different parts of rDNA allows evolutionary

investigations from the level of population and species

through kingdom, by study of appropriately variable

regions. This variation has caused debate as to the reli-

ability of some types of rDNA sequence data in phylo-

genetic analysis, but it has become clear that, when an-

alyzed with care, all parts of the sequence are potentially

informative (Wheeler & Honeycutt, 1988; Swofford &

Olsen, 1990; Hillis & Dixon, 1991; Dixon & Hillis, 1993).

Ribosomal sequences have most often been used in de-

termining relationships among bacteria (e.g., Woese &

Olsen, 1986) and vertebrates (e.g., Hedges et al., 1990),

but can be used with any organism (e.g., Sogin et al.,

1986; Field et al., 1988).

Of the more than 150 phylogenetic studies of rDNA

sequences published to date (Hillis & Dixon, 1991), only

a few have been devoted to mollusks. Ghiselin (1988)

looked at molluscan origins using 18S rRNA, Emberton

et al. (1990) at pulmonate relationships using D6 28S

rRNA and Tillier et al. (1992) at gastropod phylogeny

using D1 28S rRNA. These studies have demonstrated

the potential for rDNA sequences to sharpen and resolve

ideas of molluscan phylogeny, particularly at the ordinal

level and above.

We have supplemented the 10 gastropod sequences

obtained by Emberton et al. (1990) with data from 33

more molluscan species. All 43 sequences were used in

this study with the aims of 1) analyzing aspects of caen-

ogastropod, archaeogastropod, and unionoidean relation-

ships, 2) surveying variability in 28S rRNA sequences in

mollusks, and 3) examining how choice of taxa affects

Page 112

THE NAUTILUS, Supplement 2

Table 1. Localities and catalogue numbers of voucher specimens for this study. Depository is the Academy of Natural Sciences

of Philadelphia (ANSP) unless otherwise noted; USNM = United States National Museum. Condition: f = frozen; | = lyophilized;

w = whole live animal. Voucher lot of Anodonta imbecillis was collected in 1974; tissue sample was from same population in 1975.

See Emberton et al. (1990) for vouchers of Helicina orbiculata, Oncomelania hupensis, Biomphalaria glabrata, Mesodon inflectus,

Mesodon normalis, Neohelix albolabris, Triodopsis hopetonensis, Haplotrema concavum, Mesomphix latior, Ventridens cerinoi-

NE of Swedesboro, Gloucester Co., New Jersey

Ramah Borrow Canal, Iberville Parish, Louisiana

Lake Lacawac, Lake Ariel, Wayne Co., Pennsylvania

Deep Creek, Nanticoke River, Sussex Co., Delaware

Pit River, SW of Canby, Modoc Co., California

Kyles Ford, Clinch River, Hancock Co., Tennessee

Ramah Borrow Canal, Iberville Parish, Louisiana

Ouachita River, Arkadelphia, Clark Co., Arkansas

Kyles Ford, Clinch River, Hancock Co., Tennessee

North of Quickstep, Trelawny Parish, Jamaica

deus.

Species Condition Locality

Anodonta cataracta ]

] Swartswood, Sussex Co., New Jersey

A. grandis ]

A. imbecillis ] Magnolia Springs, Jenkins Co., Georgia

Amblema plicata f Bogue Chitto Creek, Dallas Co., Alabama

Elliptio complanata ] Swartswood, Sussex Co., New Jersey

]

Fusconaia cerina f Bogue Chitto Creek, Dallas Co., Alabama

Gonidea angulata ]

Lampsilis teres f Bogue Chitto Creek, Dallas Co., Alabama

L. claibornensis f Bogue Chitto Creek, Dallas Co., Alabama

Megalonaias boykiniana ] Ochlockonee River, Leon Co., Florida

Obliquaria reflexa f Bogue Chitto Creek, Dallas Co., Alabama

Quadrula cylindrica l

Q. quadrula f Bogue Chitto Creek, Dallas Co., Alabama

Plectomerus dombeyanus ]

Pleurobema cordatum ]

Unio pictorum f Shropshire Canal, north of Chester, near

Mollington Grange, England

Uniomerus tetralasmus ] Magnolia Springs, Jenkins Co., Georgia

Cumberlandia monodonta l

Margaritifera falcata ] Siletz River, Lincoln Co., Oregon

M. margaritifera ] Locust Creek, Schuylkill River, Pennsylvania

Perotrochus maureri f 90 miles east of Charleston, South Carolina

Truncatella sp. WwW Harrison Point Lighthouse, Barbados

T. caribaeensis Ww Bay side, Mile 57, Grassy Key, Florida Keys

T. clathrus Ww Bay side, Mile 57, Grassy Key, Florida Keys

T. pulchella Ww Bay side, Mile 57, Grassy Key, Florida Keys

w Falmouth, Trelawny Parish, Jamaica

T. reclusa Ww Cumaca, Northern Range, Trinidad

T. scalaris Ww Falmouth, Trelawny Parish, Jamaica

T. subcylindrica w The Fleet, Dorset, England

Geomelania sp. Ww

G. typica Ww Wallingford, St. Elizabeth Parish, Jamaica

Busycon carica f Cape Henlopen, Sussex Co., Delaware

Mancinella deltoidea f South Beach, Miami, Dade Co., Florida

Progabbia cooperi f Off La Jolla, San Diego Co., California

Catalogue no.

333526, 341937

334429, 341946

341888

333563

373820, A12742

334428

339430

339340

397248

339965

373821, A12744

397249

346111

397247, A12722

335041

397246, A12728

vouchers not kept

340629

350622

353138

341956

339339

334867

USNM 875218

397286

397275

397278

397274

397264

397285

397263

397280

397283

397284

USNM 847010

USNM 870850

USNM 846054

phylogenetic inference. The results presented here must

be considered preliminary until data for longer sequenc-

es and additional ordinal level taxa are available.

MATERIALS AND METHODS

We obtained sequences from 20 unionoidean bivalves

and 13 gastropods, including 9 truncatellids, 1 muricid,

1 cancellariid, 1 melongenid, and 1 pleurotomariid. Spe-

cies names, localities, voucher information, and higher

classification are given in Tables 1 and 2. Truncatellid

RNA was obtained by homogenizing live animals, other

gastropod RNA from frozen tissue, and unionoidean RNA

from lyophilized or frozen tissue. Methods for sequenc-

ing followed Emberton et al. (1990) and were done in

the same laboratory, using the same primer for the D6

region, complementary to nucleotides 2099 through 2118

for mouse as published by Hassouna et al. (1984). Each

species was sequenced at least twice, or more often as

necessary to resolve ambiguities in nucleotide identity.

Sequence alignment: Gross alignment of the sequences

was easily achieved because of large conservative stretch-

es in the D6 flanks. The MALIGN program of Wheeler

and Gladstein (version 1.73, 1993), was used to refine the

manual alignment. The following weights (costs), with

options alignaddswap and treeaddswap, yielded align-

ments that matched overall the manual alignments of

the D6 flanks, while providing improvement in details:

G. Rosenberg et al., 1994

Page 113

transitions 1, transversions 3; internal gaps 10; leading

gaps 5; trailing gaps 5.

Phylogenetic analysis: Informative and variable nucle-

otide positions, indicated by “i” or “v” in Figure 1, were

analyzed using Hennig86. The sequence of commands

“mhennig; bb; ie*;” was used, which guarantees finding

all of the most parsimonious trees. All characters were

equally weighted and unordered (command “‘cc-.”).

Those gaps marked with a hyphen (-) in Figure 1 were

scored as characters, except for the deletion from posi-

tions 74 to 79 in Truncatella clathrus. Species that showed

no differences in sequence were combined for the pur-

pose of the phylogenetic analysis.

RESULTS

Aligned sequences are shown in Figure 1. The 5’ flanking

region (positions 1-46), and the 3’ flank (positions 99-

161) are conservative, and only a few gaps were inserted

to align the sequences. The D6 loop shows considerable

variation in length, and were too variable in the non-

pulmonate gastropods to be reliably aligned. A number

of complementary changes can be seen in the stem re-

gion, positions 47-55 and 90-98( Figure 2).

Among the 48 species, 26 different sequences were

found. All species with identical sequences were confam-

ilial. As reported by Emberton et al. (1990), sequences

were invariant among the four polygyrids. Among 20

unionoideans, only 6 different sequences were found.

Cumberlandia, Gonidea and the two Margaritifera all

had distinct sequences. The other 16 unionids differed

from each other by at most one nucleotide, falling into

two groups, referred to here as the Anodonta and Am-

blema groups. In contrast, sequences differed strongly

among truncatellids: each of the nine species had a unique

sequence. Within the genus Truncatella, all species dif-

fered from each other by at least five nucleotides. Dif-

ferences were concentrated in the D6 loop, and involved

significant variation in length, in addition to nucleotide

substitution. Only a partial sequence was obtained for

Perotrochus.

Molluscan sequences differed from those of mouse at

15 to 32 percent of the sites (Table 3). Sequences from

the unionoideans and Helicina were the most conser-

vative, differing from mouse at 15 to 20 percent of sites.

Gastropods, excluding Helicina, differed from mouse at

22 to 32 percent of sites, with pulmonates showing less

sequence divergence (22 to 24 percent) than neogastro-

pods (24 to 27 percent) and rissooideans (27 to 32 per-

cent). é

Use of published sequences (Gutell & Fox, 1988) from

Mus, Rattus, Xenopus or Homo as outgroup did not

affect polarization of characters. Sequences for Caenor-

habditis, Physarum and Saccharomyces were more di-

vergent from molluscan sequences than were vertebrate

sequences, and in some regions could not be aligned

satisfactorily with them. They were therefore judged less

appropriate as outgroups. The sequence from Drosophila

(Tautz et al., 1988), shown in Figure 1, could be aligned,

Table 2. Higher classification of genera for which sequence

data were analyzed. Classification follows Davis and Fuller

(1981) for Unionoidea, Haszprunar (1988b) for Gastropoda,

Rosenberg (1989) for Rissooidea, Kantor and Harasewych (1992)

for Neogastropoda and Emberton et al. (1990) for Pulmonata.

Bivalvia Neogastropoda

Paleoheterodonta Stenoglossa

Unionoidea Muricoidea

Unionidae Muricidae

Unioninae Mancinella

Unio Melongenidae

Ambleminae Busycon

Amblema Cancellarioidea

Megalonaias Progabbia

Plectomerus Pulmonata

Quadrula Basommatophora

Pleurobemini Planorboidea

Elliptio Planorbidae

Fusconaia Biomphalaria

Pleurobema Stylommatophora

Uniomerus Holopoda

Gonideini Polygyroidea

Gonidea Polygyridae

Lampsilini Mesodon

Lampsilis Neohelix

Obliquaria Triodopsis

Anodontinae Holopodopes

Anodonta Rhytidoidea

Margaritiferinae Haplotrematidae

Margaritifera Haplotrema

Cumberlandia Aulacopoda

Gastropoda Zonitoidea

Neritopsina Zonitidae

Neritoidea Mesomphix

Helicinidae Ventridens

Helicina

Vetigastropoda

Pleurotomarioidea

Pleurotomariidae

Perotrochus

Caenogastropoda

Neotaenioglossa

Rissooidea

Pomatiopsidae

Oncomelania

Truncatellidae

Truncatellinae

Truncatella

Geomelaniinae

Geomelania

but differs from the molluscan sequences at twice as

many sites as does the mouse sequence. Of 148 nucleotide

positions scored in bivalves, 35 (24%) are variable relative

to mouse, whereas 72 (49%) are variable relative to Dro-

sophila. This degree of divergence made Drosophila un-

reliable as an outgroup.

Out of 153 alignable sites, 73 (48%) are variable in

mollusks relative to mouse and 55 are potentially infor-

mative for cladistic analysis. With mouse as the outgroup,

cladistic analysis yielded 24 equally parsimonious trees,

the strict consensus tree of which is shown in Figure 3.

THE NAUTILUS, Supplement 2

Page 114

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DISCUSSION

Analyses of rRNA data must take into account several

complicating factors: the reliability of the alignments,

bias in nucleotide composition, the ratio of transitions to

transversions, and the affect of complimentary mutations

in base-paired regions. The latter two are often handled

by weighting the data in various ways. The significance

of results, in terms of the reliability of nodes in a phy-

logram, is often assessed by bootstrapping.

Reliability of Alignments

Hillis and Dixon (1991) noted that alignments are often

ambiguous when sequences differ by more than 30 per-

cent in a given region. Except in the D6 loop, the mol-

luscan sequences exhibited less than 30% divergence, and

alignment was not problematic. In the phylogenetic anal-

ysis (Figure 3), all variable and informative nucleotide

positions in the D6 loop were included, except numbers

62 to 69 (Figure 1). The alignment of these and of nu-

cleotides 70 to 78 was uncertain in the rissooideans and

neogastropods because of length polymorphism and se-

quence variation; most of these sequences are shown flush

right with no gaps inserted. When characters 70 to 78

for these taxa were excluded from the analysis, the same

consensus tree as shown in Figure 8 was obtained, except

that all rissooideans formed a unresolved polychotomy,

save the two Geomelania, which grouped together.

Bias in Nucleotide Composition

The sequences analyzed in this study exhibited a signif-

icant bias in favor of guanine and cytosine: the GC:AU

ratio of mouse was 3:1, and all taxa had a ratio greater

than 1.3:1 (Table 3). If mouse and mollusks had evolved

this bias independently, it might affect the reliability of

the mouse sequence as an outgroup for polarizing char-

acters, because convergences could be mistaken for ple-

siomorphies. Because the sequences of mouse and mol-

lusks have diverged only 15 to 30%, as discussed above,

it is unlikely that the large GC biases evolved indepen-

dently in these taxa. Nevertheless, as a control, the anal-

ysis was rerun with bivalves as outgroup, and with bi-

valves plus Helicina as outgroup. Topology of the ingroup

was not affected by the change in outgroup.

Weighting of Character Data

Differential weighting schemes for character data are

often used when analysis of a data set gives poorly re-

solved or unexpected phylogenetic inferences. If subsets

of the data can be reasonably regarded as being less likely

to suffer from homoplasy, they are given more weight.

In rRNA sequences, transversions can be up to five times

less frequent than transitions and are sometimes accorded

greater weight (Crother & Presch, 1992). Mishler et al.

(1988) suggested weighting according to the observed

ratio of transitions to transversions in a given data set,

but cautioned that this ratio is not likely uniform among

Page 115

000000000 000000000

444555555 999999999 paired

Taxon 789012345 012345678 sites

Mouse CGUCGCCGC GCCGCGACG 8

Anodonta group CGUCGCCGC GCGGCCACG 8

Amblema group CGUCGCCGC GCGGCCACG 8

Gonidea CGUCGCCGC GCGGCCANN 8

M. margaritifera CGUCGCAGC GCUGCNACG 8

M. falcata CGUCGCAGC GCUGCNACG 8

Cumberlandiaa CGUCGCANC GCGUNNACG 7?

Helicina CGUCGCAGC GCUCCNACG 7?

Perotrochus 2222222227 GCUGAAGCG ?

Truncatella sp. CGCUUGGGC GCUCAAGCG 8.5

T. clathrus CGCUUGGGC GCCCAAGCG 9

T. scalaris CGCUUGGGC GCCCNAGCG 9

T. pulchella CGCUUGGGC GCUCAAGCG 8.5

T. reclusa CGCUUGGGC GCUCAAGCG 8.5

T. subcylindrica CGCUUGGGC GCUCAAGCG 8.5

T. caribaeensis CGCUUGGGC GCUCAAGCG 8.5

Geomelania sp. CGCUUGGGC GCUCAAGCG 8.5

G. typica CGCUUGGGC GCUCAAGCG 8.5

Oncomelania CGUUUGGGC GCUCAAACG 8.5

Busycon CGCUUCGGC GCUGAAGCG 8.5

Mancinella CGCUUCGGC GCUGAAGCG 8.5

Progabbia CGCUUCGGC GCCGAAGCG 9

Biomphalaria CGUCUCGGC GCUGACACG 75

Polygyridae CGUCUCGGC GCUGACACG LD

Haplotrema NGUCUCGGC GCCGACACG 8

Mesomphix CGUCUCGGC GCCGACACG 8

Ventridens NGUCUCGGC GCCGACACG 8

Figure 2. Detail of the D6 stem regions. Numbers across the

top correspond to nucleotide positions in Figure 1. These regions

fold back on each other (position 47 corresponding to 98, 48

to 97, etc.); base-pairs form where cytosine (C) matches guanine

(G) and adenine (A) matches uracil (U). Mutations can disrupt

the pairing, and complementary mutations sometimes restore

the pairing. Inferred complementary mutations are in boldface.

The number of paired sites is shown in the left column for each

taxon. (The weaker pairing of uracil with guanine is counted

as 0.5). Note that only a few species have all nine stem positions

paired; complementary mutations do not always occur.

taxa or in different regions within a sequence. Wheeler

(1990) suggested a combinatorial weighting method based

on observed nucleotide distributions among taxa, but this

method assumes that there are no hidden intermediate

states, and has been criticized on the grounds that it was

applied a posteriori to trees based on equally weighted

data (Albert & Mishler, 1992).

The observation of compensatory mutations in base-

paired stem regions of rRNA molecules has led to the

suggestion that such regions should be excluded from

analyses, or weighted one-half because of non-indepen-

dence of characters (Steele et al., 1988; Wheeler & Ho-

neycutt, 1988). In contrast, Smith (1989) found that re-

sults based on paired nucleotide positions were more

reliable than those based on unpaired positions. Hillis

and Dixon (1991) and Dixon and Hillis (1993) found that

paired regions can contain most of the informative sites

in some analyses, and suggested that paired regions be

down-weighted by no more than twenty percent, because

compensatory mutations do not always occur. This is true

in the mollusk data, where perfect complementarity is

not maintained (Figure 2).

We have opted to run our data with equal weights for

Page 116

o. Q, Ss a .

5B 8 2 Ss S

i= = & q nm

Sree So) Stans 3 3 3

3 = Ss = = SR

2 9F 8 8 Go SS eee cece eres

3 ss Se 8 s sa & S BS 8 &

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Sos Seo SS EF S&S H FS sf ff F &

133 1454 73 o3f 214 sat 20} o3f 92

| 74 1464 2641084 264 774 85

75 1544 57 454 1544 92

2 77 82 57. 120

53 78 93 77.

113 79 113

123 8 120 37.

124 155 123 58

125 135 113

131 70 144

42. 76

124

T. scalaris

THE NAUTILUS, Supplement 2

2 Simic:

eS ae s @

2 8 3 gS ee ee, Soe le eames

= a eth So SS oe GS a Ae eee

SB Bok 8. SE BE Chik Soret

Soh ee IR ee Osi awe Se Seem

eos S Nw © 8S SR gh ae

58 61 56: 79% 494 264 70 294 70

60 764 57 734 724 139 1154 72

61 58 58 964 73

70. 60 1344 77.

71 80 824

8 81 88

92.

75. 139

4 71

39 112

22 113

115

49 85

50 89:

60 115

70 125

95, 137:

96: 142

32:

42.

53.

80:

Figure 3. Strict consensus of 24 equally parsimonious trees of length 205 resulting from cladistic analysis of the sequence data. The

consistency index of each of the most parsimonious trees is 0.64, the retention index is 0.81, and the rescaled consistency index is

0.52. Characters having states that define each node are indicated by nucleotide number. These characters support the nodes in

each of the 24 most parsimonious trees making up the consensus tree, as shown using the character tracing feature of MacClade

3.01 (Maddison & Maddison 1992). Characters whose assignment to a node is ambiguous are not shown.

all characters for two reasons. First, because weighting

schemes for transitions versus transversions and for com-

pensatory mutations are still controversial, we prefer the

assumptions of equal weighting to those that these schemes

require. Second, the purpose of weighting is to compen-

sate for the misleading effects of undetected homoplasy.

(Homoplasy that has been detected is not misleading.)

Undetected homoplasy exists when there are hidden in-

termediate character states between taxa that appear

identical for a particular character. Given a sufficient

number of undetected homoplasies, taxa that are con-

vergent can be mistakenly inferred to be closely related.

This is the long branch length problem first noted by

Felsenstein (1978). One cannot know a priori what weights

(if any) will overcome the long branch problem for a

particular data set. Also, weighting cannot determine

unknown intermediate states, so weighting cannot com-

pletely overcome the problem. Often, however, taxa can

be added to the analysis that will intersect long branches,

revealing the intermediate states. We therefore view con-

vergence in sequence data primarily as a problem of

taxon sampling rather than of weighting. In the following

discussions, we attempt to identify areas where the ad-

dition of taxa is likely to change the relationships shown

in Figure 3.

Reliability of Nodes

Hillis and Bull (1998) have recently shown that bootstrap

proportions are conservative estimators of the probability

of a clade’s being real, if certain conditions are met.

Hedges (1992) has shown that the number of bootstrap

G. Rosenberg et al., 1994

Page 117

Table 3. Differences in sequence and nucleotide composition between mollusks and mouse. If a position was not scored in a species,

it was considered to match the consensus sequence for the higher taxon to which the species belongs. For example, at position 30

(figure 1), all unionoideans were considered to have “A,” even though the nucleotide was not scorable in some species. Similarly,

at the 3’ end, unionoidean sequences were all considered to extend to position 160, rissooideans to 153, neogastropods to 161, and

pulmonates to 155. Positions 62 to 69 for mouse shown by pluses (+) in figure 1 are CGCGGCGU, extending from the 5’ side.

Sequence Nucleotide differences Total compared Percentage difference GC/AU

Mouse — — — 3.1

Anodonta group 24 147 0.16 2.3

Amblema group 24 147 0.16 DP)

Gonidea 22 147 0.15 no)

Margaritifera falcata 30 147 0.20 1.6

M. margaritifera 24 147 0.16 1.9

Cumberlandia 25 147 0.17 1.9

Helicina 27 139 0.19 2.1

Perotrochus 16 70 0.23 2.2

Truncatella sp. 42 143 0.29 1.4

T. clathrus 42 145 0.29 1.8

T. scalaris 4] 145 0.28 1.9

T. pulchella 46 148 0.31 1.6

T. reclusa 48 145 0.30 1.6

T. subcylindrica 46 146 0.32 a

T. caribaeensis 46 145 0.32 17

Geomelania sp. 38 140 0.27 117

G. typica 39 140 0.28 1.6

Oncomelania 38 140 0.27 1.4

Busycon 36 149 0.24 1.9

Mancinella 40 152 0.26 1.9

Progabbia 4] 153 0.27 1.8

Biomphalaria 34 142 0.24 1.6

Polygyridae 34 143 0.24 Wa

Haplotrema 33 143 0.23 1.8

Mesophix 32 143 0.22 1.6

Ventridens 33 143 0.28 1.8

replicates necessary for bootstrap proportions to be re-

liable is much higher than typically used in phylogenetic

studies. We attempted to bootstrap our data using the

general heuristic algorithm in PAUP 3.1.1 (Swofford,

1993). Unfortunately, some bootstrap replicates gener-

ated more than 5,000 equally parsimonious trees, and

with available computing power, it was not possible to

complete the several hundred replicates needed to obtain

reliable bootstrap values. Felsenstein (1985), however,

has shown that when all characters are perfectly com-

patible, bootstrapping will show significant support for

a group if it is defined by at least three characters. There-

fore, groups defined by fewer than three characters in

Figure 3 cannot be considered to have significant sup-

port. Groups defined by three or more characters might

not be significant if some of the characters are homo-

plastic, or incorrectly polarized.

Because an explicit, morphology-based cladistic anal-

ysis of gastropod phylogeny has not yet been published

(see Bieler, 1990), we could not perform a combined

analysis of molecular and morphological data (see Bull

et al., 1993; Eernisse & Kluge, 1993). We have instead

attempted to evaluate on a case-by-case basis the evi-

dence supporting the major clades shown in Figure 3.

Particular characters are referred to in the form “21>A,”

meaning position 21, character state A.

Archaeogastropoda

Two taxa traditionally classified as archaeogastropods

were included in the analysis, Neritopsina (Helicina) and

Pleurotomariidae (Perotrochus). The Neritopsina (=

Neritimorpha, Neritoida) traditionally have been re-

garded as having strong affinities with the Caenogastro-

poda (Bieler, 1992). Recent classifications, however, have

reversed this, with Neritopsina being placed basally to

the Archaeo- and Caenogastropoda (Haszprunar, 1988a,

b; Healy, 1988; Hickman, 1988) on the basis of lack of

skeletal rods in the ctenidium, and on sperm morphology.

Haszprunar (1988a, b) regarded similarities of Neritop-

sina and Caenogastropoda as convergences due to the

specialized reproductive biology of Neritopsina.

The sequence data show Pleurotomariidae rather than

Neritopsina to be more closely related to the other gas-

tropods, supporting Haszprunar’s morphology-based

classification. Trees with branching order (Pleurotoma-

riidae (Neritopsina (Caenogastropod Pulmonata))) are

three steps longer than those with the order (Neritopsina

(Pleurotomariidae (Caenogastropod (Pulmonata))). The

latter tree is supported by three characters: 94> A, 136>A

and 143>U. Only a partial sequence was obtained for

Pleurotomariidae, and several positions (32, 42, 51, 53),

may also support its derived position relative to Neri-

Page 118

topsina. The position of Pleurotomariidae is discussed

further under Caenogastropoda.

Neritopsina groups with the Bivalvia based on three

characters (31>A, 59>A and 88>U) whereas only a

single character supports grouping it with the Gastropoda

(133>G). All other nucleotide positions are uninforma-

tive as to its relationships. The three characters sup-

porting affinity with bivalves may prove plesiomorphic

for mollusks when sequences from other molluscan class-

es are added. The sequence of Neritopsina has diverged

relatively little from that of bivalves, and several places

where it has changed are uniquely autapomorphic (po-

sitions 21, 26, 82, 120, 135, 144). Sequences from addi-

tional taxa such as Patellogastropoda, Cocculiniformia,

and Neomphalidae might show that some of the auta-

pomorphies of Neritopsina are actually basal synapo-

morphies that will unite the Gastropoda.

Caenogastropoda

Neotaenioglossa, Neogastropoda and Pleurotomariidae

group together in our analysis, with Pleurotomariidae

basal to the Neogastropoda. This is consistent with Pon-

der’s (1973) hypothesis of archaeogastropod origins of

the Neogastropoda, and contradicts the monophyly of

Caenogastropoda. However, osphradial and spermato-

zoic characters have been found recently that indicate

that the Neogastropoda probably evolved from the high-

er mesogastropods (Haszprunar, 1988a, b; Healy, 1988;

Taylor & Morris, 1988). In Figure 3, sixteen characters

define branches leading to the Perotrochus lineage. In

Perotrochus, no data are available for ten of these be-

cause of the incomplete sequence, and two positions dif-

fer (80>U and 81>G). The single character that unites

Pleurotomariidae with Neogastropoda in our analysis

(124>C) is insufficient to refute morphological charac-

ters defining the Neogastropoda and is likely convergent.

Addition of taxa such as Littorinoidea or Cerithioidea

that would intersect the branch between Pleurotomari-

idae and Neogastropoda might reveal this convergence,

as might completion of the partial sequence for Pleu-

rotomariidae. Because the position of Perotrochus in Fig-

ure 3 is weak, it cannot be taken as contradicting the

monophyly of Caenogastropoda or Neogastropoda.

Neogastropoda

Taylor and Morris (1988) concluded on the basis on mor-

phological characters that Neogastropoda is monophy-

letic. If Perotrochus is excluded, the nucleotide sequenc-

es supports this monophyly, character 61>C being a

unique synapomorphy for the Neogastropoda. Another

character also supports the node (76>G) but with ho-

moplasy elsewhere in the tree. The relationships of the

three neogastropod taxa used in our study differ from

those postulated by Taylor and Morris (1988) who re-

garded Cancellarioidea to be a possible sister group of

Rachiglossa + Conoidea (i.e., Stenoglossa + Toxoglossa).

THE NAUTILUS, Supplement 2

In our analysis, the Muricidae and Cancellariidae group

together, with Melongenidae as a sister group. Three

characters support the monophyly of Muricidae and

Cancellariidae: 37> U (an insertion), 58>G and 113>C,

and none contradict it.

The relationship of Cancellariidae to other neogastro-

pod taxa has been uncertain, with the group having been

included by various authors in the Toxoglossa, Stenog-

lossa, and its own order, the Nematoglossa (see Petit &

Harasewych, 1990). Most subsequent authors have fol-

lowed Ponder (1973) in dividing the Neogastropoda into

the corresponding superfamilies Conoidea, Muricoidea

and Cancellarioidea. More recently, Kantor and Hara-

sewych (1992) noted anatomical similarities between

Cancellariidae and the stenoglossan family Volutomitri-

dae, and suggested that a reassessment of the taxonomic

rank and systematic position of these taxa was warranted.

The present data support the hypothesis that the Can-

cellariidae comprise a highly derived group within the

Stenoglossa, as reflected in such earlier classifications as

those of Thiele (1929) and Wenz (1943).

Neotaenioglossa

All of the neotaenioglossans studied are rissooideans. Five

characters support the monophyly of Rissooidea: 34> U,

39>U, 52>G, 93>C, 115>U. All of these are uniquely

derived, except 93>C, which is convergent with Heli-

cina. Within Rissooidea, Geomelania grouped with the

Pomatiopsidae rather that the Truncatellidae, but a num-

ber of morphological characters argue that it is a trun-

catellid. These include truncation of the apical whorls

of the shell, reduction in the number of anterior rachidian

cusps, the looping mode of locomotion, and shortening

of the pleuro-supraesophageal connective (Davis, 1979;

Rosenberg, 1989). The single nucleotide character that

appears synapomorphic for Geomelania and Pomatiop-

sidae (139>U) may prove to be plesiomorphic for ris-

sooideans when sequences from more taxa, such Assi-

mineidae and Hydrobiidae are added to the analysis.

Within the Truncatellinae, relationships were unre-

solved, except that Truncatella scalaris and Truncatella

clathrus grouped together as sister species. This grouping

is confirmed by allozyme and morphological data (Ro-

senberg, 1989).

Pulmonata

Our alignment for species treated by Emberton et al.

(1990) differs in minor details from their published align-

ment, and polarities of some characters have changed

with added data, but these differences do not affect in-

ferred relationships among the pulmonates. The mono-

phyly of Pulmonata is strongly supported by seven char-

acters and monophyly of Stylommatophora is supported

by three characters. No other nodes within the pulmo-

nates are supported by more than two characters.

G. Rosenberg et al., 1994

Page 119

Bivalvia

The sequence data support the distinction between Am-

bleminae and Margaritiferinae advocated by Davis and

Fuller (1981), but do not reflect the distinctiveness of

Anodontinae, which nests within Ambleminae (repre-

sented by Amblema and Gonidea in Figure 3). Six char-

acters give support for grouping Anodontinae and Am-

bleminae apart from the Margaritiferinae, but a few of

these would be plesiomorphic if Helicina were rerooted.

Only character 133>C supports the grouping of Ano-

donta with some of the amblemines. Unpublished se-

quences from the 5’ terminus obtained during this study

were also uninformative, containing only a single vari-

able site, corresponding to position 23 of Emberton et

al. (1990). Given the large body of immunological, elec-

trophoretic, and anatomical evidence showing the dis-

tinctiveness of the Anodontinae from the Ambleminae

(Davis & Fuller, 1981, Davis et al., 1981), we maintain

the tripartite subfamilial classification of Unionidae, with

Margaritiferinae as sister group to the clade containing

Ambleminae and Anodontinae. The sequences for Unio

and Amblema are identical, indicating that Ambleminae

may be a synonym of Unioninae, however, we refrain

from changing the taxonomy until more data sets for

Unio are available.

Sequence Variability in Mollusks

Emberton et al. (1990) found that 13% of sites in the D6

divergent domain of 28S rRNA were informative for

stylommatophoran phylogeny, but only 1% in the D6

flanking regions were informative. They concluded that

divergent domains of LrRNA would be of “some value

in resolving stylommatophoran phylogeny.” We have

found that the D6 region is more variable in mollusks

than anticipated from the results of the first study, with

23% of sites in the D6 flank and more than 70% in the

divergent domain being informative at some level for

molluscan phylogeny.

Variability in the bivalves and pulmonates is almost

entirely in the form of nucleotide substitutions; there are

only a few insertions and deletions. In the caenogastro-

pods, the D6 loop region is subject to considerable vari-

ation in length, in addition to nucleotide substitutions.

The selection of taxa for phylogenetic analysis is ex-

tremely important because taxa display varying rates of

DNA sequence evolution (slower in unionoideans, faster

in rissooideans); differing rates in different regions (slower

in the D6 flanks, faster in. the D6 loop); and different

proportions of substitutions versus insertion and deletions

in various taxa. A single species or genus often is not

representative of its higher taxon, as three examples show.

1.) Helicina has diverged from ancestral sequences

more slowly than the other gastropods, and groups with

the slowly evolving bivalves, perhaps because of retained

plesiomorphies, as discussed above.

2.) Margaritifera falcata has eight autapomorphies,

whereas M. margaritifera has none, and Cumberlandia

has three (Figure 3). No other unionoidean had more

than one autapomorphy. There were no convergent au-

tapomorphies between M. falcata and Cumberlandia,

but there easily could be between derived unionoidean

species. Such convergences can be mistaken for syna-

pomorphies, as we interpreted happened between An-

odonta and some amblemines.

3.) Truncatella resembles Mancinella and Progabbia

in having long D6 loop sequences; Geomelania and On-

comelania resemble Busycon in having short D6 loop

sequences. From positions 65 to 74, Truncatella sp. shares

six of eight nucleotides with Progabbia. The convergence

is due in part to compensatory mutations in the D6 loop.

Truncatella sp. has nine adenines between positions 72

and 82 some of which base-pair with six uracils between

positions 58 and 70. Progabbia has a corresponding A/U

rich region. The convergence is revealed as such by com-

parison to the sequences of close relatives. Thus, Trun-

catella clathrus shares no nucleotides with T. sp. in the

region where Progabbia shares six, but it is identical in

the D6 flanking regions.

Because species may not be representative of their

higher taxa, and because long branches attract, a mixture

of closely and distantly related species must be incor-

porated into phylogenetic analyses to minimize the chance

of convergences remaining undetected.

If convergence is undetected, it is often revealed by

comparison to relationships inferred from other data sets.

In our analysis, comparisons to morphological phyloge-

nies have identified several areas where the sequence

data by themselves seem to be misleading. Problematic

areas in Figure 3, the grouping of Anodonta with Am-

blema, Helicina with the bivalves, Perotrochus with the

neogastropods, and Geomelania with Oncomelania, are

not strongly supported by the sequence data, with the

alternative trees being in each case only one or two steps

longer. In the cases of Helicina and Geomelania, the

addition of taxa is likely to change the polarity of those

characters supporting the doubtful groupings. That is,

the problem is not necessarily convergence, but that ple-

siomorphy has been mistaken for apomorphy. With Per-

otrochus, addition of taxa such as patellogastropods might

also show that characters scored as autapomorphic are

synapomorphic with basal taxa. This would reveal the

convergence that groups Perotrochus with neogastro-

pods. In the case of Anodonta, adding taxa would not

help, but more variable sequences from another region

might.

To date, sequence studies of mollusks have not over-

turned phylogenies based on morphology, but rather have

helped in choosing among competing morphology-based

hypotheses. Like morphological data, sequence data are

subject to problems of convergence, unequal rates of

evolution, and choice of taxa. Phylogenies based on se-

quence data alone can be misleading. Molecular and

morphological data are often complementary, serving to

define different nodes within a tree. Analyses and clas-

sifications must be based on all available data to maximize

Page 120

the potential for detecting convergences and correctly

resolving phylogenetic relationships.

ACKNOWLEDGMENTS

Supported in part by NIH grant AI 11373-TMP to George

M. Davis. We thank Edward Theriot and two anonymous

reviewers for helpful comments on the manuscript, Cary]

Hesterman and Kathleen M. Monderewicz for technical

assistance, and S. Michael Phillips for providing labo-

ratory space at the University of Pennsylvania.

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THE NAUTILUS, Supplement 2:122-140, 1994

Page 122

Monophyly of Major Gastropod Taxa Tested from Partial

28S rRNA Sequences, with Emphasis on Euthyneura and

Hot-Vent Limpets Peltospiroidea

Simon Tillier!

Monique Masselot?

Jean Guerdoux2

Annie Tillier! 55, rue Buffon,

Laboratoire de Malacologie (CNRS

URA 699 and GDR 1005)

Muséum national d Histoire naturelle

F-75005 Paris, France

2 Centre de Génétique moléculaire

(CNRS UPR 2420)

CNRS

Avenue de la Terrasse

F-91198 Gif-sur-Yvette, France

ABSTRACT

In a sample of 24 species representing six higher Gastropoda

taxa (Patellogastropoda, Vetigastropoda, Neomphalina, Caen-

ogastropoda, Opisthobranchia, Pulmonata) plus outgroups, each

represented by a sequence of ca. 300 nucleotides from the 5’

end of their 28S rRNA, repeated jackknives and bootstraps using

either variable numbers of nucleotides or all the possible mono-

specific combinations of higher taxa support: (a) monophyly of

the Vetigastropoda and position of the Fissurelloidea as the

sister-group of the Pleurotomarioidea and Trochoidea; (b)

monophyly of the Caenogastropoda including Stenoglossa, but

not monophyly of the latter, which, however, is neither sup-

ported nor rejected; (c) monophyly of the Anaspidea and Pul-

monata; (d) monophyly of the Neomphalina and Apogastro-

poda, with the former the sister-group of the latter. The

monophyly of the Euthyneura is but weakly supported, as is

the monophyly of the three non-Anaspidean Opisthobranchia

included in the sample. The monophyly of the Patellogastro-

poda and Vetigastropoda is more likely than their paraphyly

in this data set, but may be artefactual.

Key-words: RNA, Gastropoda, phylogeny, bootstrap, jack-

knife, hydrothermal-vent limpets.

INTRODUCTION

After decades of relative stagnation, hypotheses on Gas-

tropod phylogeny at various levels have recently been

raised in greater number than ever before: for example,

the definition and relationships of various groups of pro-

sobranchs (e.g. Ponder (ed.), 1988; Haszprunar, 1988a,

c) and of pulmonates (e.g. Schileyko, 1979; Tillier, 1989;

Emberton et al., 1990) have been revised and are still

under discussion. In addition, the discovery of new, prim-

itive-like Gastropoda from such extraordinary environ-

ments as deep-sea hydrothermal vents has brought still

more interest to attempts to analyze ancient Gastropod

radiations (e.g. McLean, 1981), and their relationships

are still subject to discussion (e.g. McLean, 1990a, b).

In his phylogenetic classification of the Gastropoda,

Haszprunar (1988a, c) proposed the successive emer-

gences of thirteen higher taxa, as shown modified in

figure 1:

(a) Docoglossa = Patellogastropoda, of which the dis-

tinctiveness is recognized by all recent authors (see

Lindberg, 1988);

(b) “hot-vent ce” = Neolepetopsidae McLean, 1990,

hot-vent limpets later included in the Patellogas-

tropoda (McLean, 1990a);

pets (Haszprunar, 1988b);

(d) Neritimorpha = Neritopsina, which include ma-

rine, freshwater and terrestrial taxa;

(e) Neomphalina = “hot-vent a” = “tapersnout’ ;

(f) Vetigastropoda, which correspond to most of the

classical “archaeogastropods’ ;

(g) Seguenziina (Seguenziidae);

(h) Architaenioglossa, which include the land and

freshwater Cyclophoroidea and Ampullarioidea,

which are included with all the former taxa in the

grade Archaeogastropoda by Haszprunar (1988c)

but are considered as Caenogastropoda by Ponder

& Waren (1988);

(i) Caenogastropoda, which include most of the clas-

sical “mesogastropods”’ and the supposedly mono-

phyletic Stenoglossa = Neogastropoda;

(j) Campanilimorpha (Campanilidae), considered by

Ponder & Waren (1988) as members of the Caen-

ogastropoda; a position finally admitted by Ha-

szprunar (1992);

(k) Ectobranchia = Valvatoidea;

(1) Allogastropoda, a paraphyletic (?) taxon including

S. Tillier et al., 1994

several families of small snails, marine or rarely

freshwater, with a hyperstrophic protoconch in

addition to several anatomical synapomorphies;

(m) Euthyneura, including the Opisthobranchia

(mainly marine) and the Pulmonata (mainly fresh-

water and terrestrial).

All the taxa included in the Valvatoidea, Allogastro-

poda and Euthyneura may be grouped in the Heteros-

tropha (Ponder & Warén, 1988).

Even at such high taxonomic levels, many points are

still under discussion. In this context, molecular system-

atics, and in particular sequences of nucleic acids are

useful tools to bring new insights to phylogenetic rela-

tionships and to test hypotheses currently under discus-

sion. In former papers, Emberton et al. (1990) and Tillier

et al. (1992) have tested the use of 28S rRNA to elucidate

gastropod phylogeny and the latter have shown thai the

5’ extremity of 28S rRNA is suitable for partial resolution

of gastropod phylogeny at high taxonomic levels.

For any sequencing effort, a choice must necessarily

be made at some point between obtaining short sequenc-

es from many taxa, or obtaining long sequences from a

few taxa. The second option allows use of many char-

acters, and retains many characters per taxon even when

all regions of even slightly doubtful homology are elim-

inated. However, this option is not necessarily the better

one since species sampling has itself a strong influence

on the reliability of the groupings found (Lecsintre et

al., 1993). Here we use a data set corresponding to the

first case, which necessitates either the use of sites from

variable regions in order to keep the ratio of characters

per taxon sufficiently high (here between 3 and 4), with

resulting low reliability due to high homoplasy; or using

statistical methods which allow estimation of the reli-

ability of various groupings with and without variable

regions. The latter is done here using the methods pro-

posed by Lecointre et al. (1993 and in press). As shown

further, these latter methods may prove powerful for

testing the consistency of the trees under discussion with

a given set. However, one should never forget that they

are not doing more, and in particular one should not

confuse the reliability of the trees as a representation of

a given data set, which is discussed further, and their

reliability as a representation of the history of life, which

certainly cannot be estimated by internal statistical tests.

In the present paper, we address several of the points

under discussion in gastropod phylogeny using homol-

ogous sequences from 24 species listed in table 1 and

figure 1. These species were chosen from those available

to represent the diversity of the monophyletic taxa listed

above: Patellogastropoda, Vetigastropoda, Neomphalina,

Caenogastropoda including Stenoglossa, Opisthobran-

chia and Euthyneura. Both new data and application of

methods more sophisticated than those used formerly,

lead us to discuss two types of questions: some already

contested points, like the para- or monophyly of the

Archeogastropoda represented in our sample or the

monophyly of Neomphalina, Caenogastropoda and Eu-

thyneura; or to raise some seemingly formerly neglected

Page 123

points, like the monophyly and relationships of the Opis-

thobranchia and Pulmonata.

MATERIALS AND METHODS

Materials

Samples from 24 species were used (tables 1 and 2, figure

1): six Pulmonata (two Archaeopulmonata, one Basom-

matophora, and one Elasmognatha in addition to two

Stylommatophora); four Opisthobranchia (one of each

of the Cephalaspidea, Notaspidea, Anaspidea and Nu-

dibranchia); six Caenogastropoda; one Neomphalina (the

hot-vent Peltospiridae limpet Rhynchopelta concentrica

McLean, 1989); four Vetigastropoda; one Patellogastro-

poda; plus one Polyplacophora and one Bivalvia as out-

groups. The sequences correspond to the 5’ end of the

28S rRNA, starting from position 72 in the sequence of

Mus musculus in Hassouna et al. (1984), and include

214 to 222 nucleotides (alignment with the mouse se-

quence, table 1; positions homologous to positions 1-71

in the mouse have not been used because we miss them

in Buccinum, Pomatias, and Haliotis).

Total RNA was extracted from fresh or frozen tissues

by the guanidium thiocyanate-phenol-chloroform meth-

od (Chomezynski & Sacchi, 1987), sometimes using

RNAzol (Bioprobe) for extraction, and sequenced di-

rectly using the method of Qu et ai. (1983), with either

%2P or %S a» markers. The sequence of the probe is 5’-

AGGTAGATTCCGATTTATATGGCCGT-3’. Every

sequence was repeated from three to nine times and each

repetition was read at least two times by two different

readers (M.M. and A.T.). When necessary, sequencing

was repeated using deazaGTP (Barr et al., 1986).

Sequences were registered and handled, from database

to tree analysis, using the MUST package (Philippe, 1992).

The alignment was realized entirely by eye. In cases of

ambiguity in the position of a gap, gaps have been pref-

erably clustered between sequences, with the underlying

assumption that the occurrence of deletions or insertions

is more likely at homologous sites, and that substitutions

are more likely than independant deletions or insertions

in the ambiguous region (this maximizes the homology

of the gaps and minimizes the number of independant

deletions/insertions); and gaps have been preferably

clustered inside a given sequence, considering that elon-

gation of a gap is more likely than occurrence of a new

independant gap in the immediate neighbouring region

of the molecule.

In all analyses, only characters informative for parsi-

mony (i.e. exhibiting at least two states occurring in more

than one taxon) were used: 93 sites in the whole sequenc-

es, 65 sites for 24 species when the more variable regions

overlined in table 1 are removed. Relative rate tests (Wil-

son et al., 1977) were done both with and without the

variable regions overlined in table 1; all kinds of differ-

ences (transitions, transversions and gaps) have been used

with equal weights for this test as well as in the various

calculations.

Page 124

THE NAUTILUS, Supplement 2

Table 1. The raw data set: 28S r-RNA sequences oriented from 5’ to 3’, starting from position 72 of the mouse (included for

comparison, last line). Variable regions, removed from all analyses except BP/number of sites diagrams, are overlined. Identities

with the sequence of Helix aspersa (upper line) are denoted by hyphens, deletions by stars and undetermined nucleotides by the

standard code N. Numbers in the right row indicate the actual number of nucleotides.

Helix aspersa AAGGAUUCCC UCAGFUAACG GCGAGUGAAG CGGUAAUAGC CCAGCACC¥* GAAUCCCUCA ##4GUGUCAU *GCUG#ACGG GAA#CUGUGG

Placostylus fibratus ------- lIIF= (Gesctieeses scosssses 5 25 eae oescsss5 (3 eeesossess tit------- ¥----%---- --#------

Phytia myosotis jpesses Po eos Jcl\pom ccsemessos sos ec(fece sacca=o5 i} coaesoests GJjeoecece oees sae sos Jepaees

Siphonaria algesirae Neass== Ut ioe Soe Re aoc [\lIljs2 coseecas Bi oa2 ts sirsnae UU ocee{ieh (ecectasac ooo tse

Lymnaea stagnalis = = = ------- po Qrectcrace: sanSoncsas cos (Fecleee sesesons (3 oomcoss (Foo i Jeneass (f Usessiifjes= 225 Jaaess=

Succinea putrig = ------- lle Qeoctisesss oscessnes= so2ce5 Ar-- ---2---- 4k ------- (-- *#%------ ( #----#G--- --- LJP

Aplysia depilans eq{jacse||ae ([jectiscoas cocccensss 565 f\eclgeoce seasem== U3 psomess (Yoo Ukjessc|la= Yossi lies 225 jassoss

Archidoris tuberculata (--------- ae ee eee a aac Geena Ud eanence C-G ###-C#C-UC C-UC-#G--- U--#------

Actaeon tornatilis URS oes Ue Vag Oop cass ea Seer orion G=20s=-7co— = Re roo sero h elbooalllh Uciiljavoase, coe aoc

Berthella plugula N--------- (Geeciisecos oc Weecseses soc Recflecs soeccece 4% -----—- C-G ¥###-C-A--C C-UC-#GN-- N--#------

Qcenebra erinacea 99 --=----==- ---- Upees, [Jerosesces sos (FeUlfece s22ccons Oh oosesos C-- *#¥-CA--UC ¥----¥G--- --- Jesese=

KmeGWle TAMUUIG 9 Senescence snes ei aS Aa At -ae cocccens U3 esecess C--)*44-CA--UG f-—-- 8 G-oa eccnes

Buccinum undatum [JPaeeazess sacs RoNo== sees aetna nae GUC se iecaa eae Up ceonece (Pee UUUEeHIIG Uesect{fece: cen neers

CONT IEREG Cloinengi} = pesmeseees sano POG aaa See Uteess pooacces Ai Coss2e (Pee BUH eb UeaacUiece elit }\so2=<

Pomatias elegans (--------- ==> ea N--G--- -------- tt ------- (-- ##4--CGACG #----#GU-- --#--A---

Littorina littorea NN seas Macc. Foe e oso Neo ese accra s VU Grecia tecr ce Jase ae ULeWellll|t; Uecact tose [pat iecean=

Rhynchopelta concentrica ---------- ---- ee pe aa ae Feaiiese acancscs is Sosmece GAGHEE#*(——- (Cat 8 Ne

Monodonta lineata 8 = ---------- - eclipses geeesesse= sosces Gr--- -------- t# ------- CUG #**--UCUGC *---A¥G--- --- ¥[J-----

Calliostoma gizyphinum = ---------- ---- Refer ecsoticcocorce aos (ectiso>: scecedsoc id Senses CUG ###--UCUGC #--CA¥G--- -- G4U-N---

Haliotis tuberculata Nesgorcen car: Wiel eek | Neriaeosra rac Lpciyaes cceeace: GL} coaacce CUG *##--UCUGC *N-C-#G--- ---#--N---

Diodora graecg. 9 -nnnennnne =o t----- oe G--(--- -------- tk ------- (-- ###-G-GA-A CU---#G--- -G-A------

Patella vulgata Posoesse "oare Geacfine [lscac(foccs sacfjec(ises seelllelffos{t]|\ sasccas C-G CUC-GAC-UC G--C-UU--- --- +)

Acanthochitona fascicular N--------- Ce Fo INeScesS tors fe(qese cosce (Fes ecesec] A-G ###%G(C--G- A-UC-#CU-- --- LoCo

Kytilus edulis Y--------- (Y--¥---Y- ----An---- ---G--G--- Ye------ tk ------- G-- ###-CC-UGC GCUGC#-G-- A-##------

Hus musculus (ooesscace ccac Yocese caasacesc (G Recfiectecs csmnelfost}t} cose CGC CGC-C---GC G--GU##G-- A--UG--GC-

Helix aspersa UGUGUGGGAC GCCACCAGUC GCA*FUCAGA GG¥##*GCGC CGAAGUCCUC CUGAUCGGGG CUUCACCCAG *AGCGGGUGU AAGGCCUUU

BilAeostemlns Willoreai§ —— eeeeeaesss eessossse= sce Wlocffes scUAjdljo2 socesossse socecesss= cosessoses Jooeoss fea, ececess= *

Phytia myosoti§ 992 ~ == 22 n = annem n= - = -- ¥x----( --$44%---- ---------- ~------ fi-= =-=------- JoJo SS t

Siphonaria algesirae + -------- N- ---------- - J-#%----( --¥##E\-A- ---------- ------- A-- ---------- $------ N-- ------=--- k

Lymnaea stagnalis 9 2 ---------- ---------- --- ¥¥----( --¥4#4$--A- ---------- ------- A-- ---------- ¥--------- --------- t

SUCCIINGR MRI = = = § seseeseses socESshoSS So GFEC-G-- --¥###-Y-- ---------- ---------- ---------- F------2-- --------- *

Aplysia depilang 22 =--------= =--------- -- GFECGU-C -At##E--A- ---------- ------- A-- ---------- ¥--------- --------- $

Archidoris tuberculata § ----(----- -------- (We SGT Ge dy Sci Josas cossescese saesans [les sGaaloceah, Ufpileascos sacasscs= us

NOGAGOD THORAOBIITIG eoneggcsinc ones NelJeoe: RAAHEAG ecUUeclye d[jscoossco esceceesss ces [Wissel] Gescecooss osccosca= t

Berthella pluaula ---A----N- --N-A---C- UUG#%C-C-G AC###G--A- AC-------- ---- NA-A-- -CCUU---G¥ #U-------- (Roscocc= t

Ocenebra erinacea ece)\socona eacoileiicos clGecYh SoUULR [feo coosacsens casasecses: 9 (Gaaieease Joomacoace Gros o eS t

Nucella lapillus ---A------ ----A-U--- -UC#UC-GCC --####UG-- ---------- ---------- - (--U----- Jecsossses (Geosssceae ui

Buccinum undatua eedileceees alfscoclfece oflsUiFesU{h ocUIUU Y= sasteasas= sosegecess = (Forljosces Yecljescosc (Geoescos=

Calyptraea chinensis ==-Aq-=—-— =---A-(--— -UC#CG=-C0, —-¥¥#20¢ == -— (Gecilleoese Joo|jecose= ROS OSoS ¥

Pomatias elegans ---A--A--- -U--A-U--- -UCECGAUCC --¥###G-- ---------- ---- IRREnE sQecsssass Yaall|pocons Re---NEoN

Littorina littorea --~A------ ----A---- -UCECGACCG --#8#E#GA- ---------- ---------- - (--J----¢ *--------- (Gassoccne t

Rhynchopelta concentrica ---UG----- ----A-C--- -AC#GGGUCC UC#GUU---- - (Focooscse esesseccas ¢ (GaaiYococ(y, Lfp=os= []Ro (Geoscosce *

Monodonta lineata -------C# ¥G-UAUC-G- --U#G-GUCC CU##*#-J-- -(-------] ---------- - C-UU----U #--U------ (-------- i

Calliostoma gizyphinum = -------- G)+=-GGUC-G— =-C#A-GUCC CU#**4--—0-(—— == =o ooo ooo (GAliescall) Podliasosce aero

Haliotis tuberculata © ----- A-CGA #N-GUUC-G- AUC#UA-GC- CUXCCACU-- -C-------- ------- C-- -###)----- #--------- (-------- ‘

Diodora graeca 2eq|[osocec *G--UUC-G- -GU#CG-UCU CUt##S---- - Yessssee I] eesscesss= = C-UU----- (Fealljorcs= es(leeas'

Patella vulgata CK-AA---U- #-G--UC--- AGGCG--U-- CC##GUC--A AC------CG -G-GA-A--U G-G-U----- #-------- G-------- A

Acanthochitona fascicular C--A-A---- AG-CU-U--G C-G#*CGUUC --####-)-- -(G------- ---------- - C-U----- Jonacocess Ussencs C-#

Hytilus edulis ------=-- -U-UAUU-G- --G#¥*¥AU-U CC##GG-U-- -U-G------ ---------- -(--I]----- #--------- (-------- :

Hus muscuius SING S== BemeeH0C> BOAO GAUGE e= Gecaccee|I] ocascos A-- -CGAG---GU ¥G-AC----- fjosene GG-*

SS SSS SS SS SSS SSS SSS

a ———————————————— — —— eel

S. Tillier et al., 1994 Page 125

Table 1. Continued.

Helix aspersa FGCUGGUGCE CUCUCUGUGC GECCGCHGAG *F*CGUCUCA GGAGUCGGGU UGUUUGG 214

Placostylus fibratus eS) goo al eee Ie eos Wiklosscas> seseesscss sacosce 214

Phytia ryosotis er \oooo eas Go3< es gecliess (Mijgcmmass aassssssss sossoss 213

Siphonaria algesirae nel leone (Aneta aera Wipe Uijesoceq|) oases [ease cosesos 214

Lymnaea stagnalis aca U efesaoce cane (Wises QUWsssess||| oscsssasss so2s25 214

Succinea putris er Poat la eoce sli iam eee Uutecsocs)|| cosesosos= ssccces 214

Aplysia depilans ec acen2 Lelie) a visss UlMsocosos sssmesssos oescss A 213

Archidoris tuberculata | *--U-CG--* -GGCGC-C-- ------#--- #%%----(-- -------- | Ssceeso 214

Actaeon tornatilis jereetiecks MOI PSeS bua ess 1) ofS ae ooo 212

Berthella pluaula Jjeestises0 slbesli(le s=si|clboso Uk esoses|) coesssscs= =es25 A 214

Ocenebra erinacea uiiclipGess USIESG(IIe =seljpsticco ERlesscad() seecseasce sotasss 212

Nucella lapilius CASUESOUES sBESGRHI > =sclestioc= UQecaseq() eososssass ssaecsc 2:5

Buccinum undatua uilehle=(QUs =GRUBBHY = seclIesdocs Mujeoosad(Y seessscsss seosssc 215

Calyptraea chinensis ASUS CUGE-GGU0- GUS ooo Up eN See (oe 215

Pomatias elegans *A-CA-GCNG --GGUC-GU- -----%--- ##%------( --N---f]--- ------- 216

Littorina littorea A \eleecos UV SeHAUG=EH= eecljostiece Ut Mesoscall (Jecosssaso 2955225 al4

Rhynchopelta concentrica ¥*AGC--(--* GGGA--CGU- ---UC-#--- ###----(-- A--------- ------ A a1?

Honodonta lineata [MHtes(HS2 HHH eeilhe= lfecllIiiaso Ut oaca(ilIll) c22ssosss= Sessa al4

Calliostoma zizyphinum *AGC--CA-* #GGA--AG-- -U--UUC--- ¥¥¥----CUC ----- [pase scicsces al4

Haliotis tuberculata ¥NGC--CA-* GGGA-GAGA- -U#-UU#-C- ##G----CUC ---------- ------- al4

Diodora graeca Jalbestes2 HRROIE(= SU e(iltace 2 ococYI[0 csp ssasc Sosssce 216

Patella vulgata GUUC---CU* GGG---UCUG CC-G--GC-- UCGGUA-CUG C------ lee es{faso= 230

Acanthochitona fascicular *A-A--CAU* --GA-GCG-U A--UCU*--- ¥##----CUC A--------- ------- 213

Hytilus edulis Wile(Cae(illeys (HERI) = oe Besos II) seeseccseo soca A 215

Hus musculus *AGC--CC-* -CGG-GCGC- --G-U-#-G- ###C-UC-C ---------- -- (feces 222

Both parsimony and distance methods were used. For

parsimony, Hennig86 (Farris, 1988) was used to build

the initial trees, and DNABOOT of the PHYLIP package

(Felsenstein, 1990) was used for bootstrap. However most

of the trees which are discussed here, and result from

numerous jackknives and bootstraps (Felsenstein, 1985,

1988) detailed further, were obtained with the neighbor

joining algorithm (Saitou & Nei, 1987). This option was

taken not to favour distance methods, but simply because

obtaining the millions of trees analysed further would

have required much more CPU time than was available

(most analyses have been performed on a PC 386 (25

MHz) and a PC 486 DX (33 MHz): even if one estimates

that one run of Hennig86, with options m* and bbs,

takes 10 seconds, one million runs would take about four

months). Repeated jackknives of sites followed by boot-

strap estimates and the corresponding diagrams have

been obtained by the JACKBOOT, NJBOOT and

COMP BOO programs of the MUST package. Com-

binations of species from higher taxa followed by boot-

straps and the corresponding histograms have been ob-

tained by the programs. JACKMONO, NJBOOT and

MONO _ HIS of the same package (Philippe, 1992; Le-

cointre et al., 1993 and in press).

Testing the Reliability of the Trees

As noticed by many authors and discussed in detail by

Lecointre et al. (1993 and in press), whose procedures

are followed here, although for partly different purposes,

two principal factors determine the reliability of trees,

given accepted homologies and a method of tree con-

struction: the number of characters, here approximately

proportional to sequence length, and taxonomic sam-

pling.

Sequence Length:

A too short sequence length is generally invoked when

a node considered as true appears unreliable, and when

its bootstrap proportion is low. Although unavoidable in

our present state of knowledge of molecular evolution,

this argument should not be used without discussion since

it is unfalsifiable: whatever sequence length is used, one

can always invoke its shortness when expected results are

not met or prove unreliable for a given data set. Boot-

strapping, i.e. character sampling with replacement, is

usually performed to estimate the reliability of trees (Fel-

senstein, 1985): a tree is constructed from each of a high

number of replicate samples (here 1000), and the number

of times each grouping has been found is totaled. A

consensus tree is built using all majority nodes, i.e. keep-

ing the node which is the most abundant of several con-

flicting nodes. In the resulting tree a grouping, i.e. a node,

is considered reliable when it has been found in more

than 90, or even better, 95% of the replicates; this per-

centage is the boostrap proportion (BP) of the node.

Lecointre et al. (in press) have proposed an empirical

test for determining whether the reliability of any given

node might be increased by adding a definite number

of characters (here nucleotides). This test consists of: (1)

Page 126

Table 2. Material studied.

THE NAUTILUS, Supplement 2

Pulmonata

Helix aspersa Miller, 1774 (Stylommatophora). Around Besancon, France. 1989.

Placostylus fibratus (Martyn, 1784) (Stylommatophora). Ile des Pins, New Caledonia. Aillaud! 1990.

Succinea putris (Linné, 1758) (?Stylommatophora?, Elasmognatha). Chamarande, Essonne, France. Masselot! VI.1991.

Phytia myosotis (Draparnaud, 1801) (Archaeopulmonata). La Ville Abel, Ille et Vilaine, France. Tillier! 1.1992.

Siphonaria algesirae Quoy & Gaimard, 1833 (Archaeopulmonata). Malaga, Spain. Gofas! 1991.

Lymnaea stagnalis (Linne, 1758) (Basommatophora). Gif sur Yvette, Yvelines, France. Masselot! 1990.

Opisthobranchia

Aplysia depilans Gmelin, 1791 (Anaspidea). Roscoff, Finistére, France. III.1988 and III.1992.

Archidoris tuberculata (Cuvier, 1804) = Archidoris pseudoargus (Rapp, 1827) (Nudibranchia). Roscoff, Finistére, France. III.

1988.

Acteon tornatilis (Linné, 1758) (Cephalaspidea). Roscoff, Finistére, France. III.1992.

Berthella plumula (Montagu, 1803) (Notaspidea). Roscoff, Finistére, France. III.1992.

Caenogastropoda

Ocenebra erinacea (Linné, 1758) (Stenoglossa, Muricidae). Roscoff, Finistére, France. III.1988.

Nucella lapillus (Linné, 1758) (Stenoglossa, Muricidae). Roscoff, Finistére, France. III.1988.

Buccinum undatum Linné, 1758 (Stenoglossa, Buccinidae). France. 1990.

Calyptraea chinensis (Linné, 1758) (Calyptraeoidea). Roscoff, Finistére, France. III.1988.

Pomatias elegans (Miller, 1774) (Littorinoidea). Between Etampes and Pierrefite, Essonne, France, Masselot! VI.1992.

Littorina littorea (Linné, 1758) (Littorinoidea). Roscoff, Finistére, France. III.1988.

Neomphalina

Rhynchopelta concentrica McLean, 1988. HERO 91, Site Justinoir, 12°48’88”N, 103°56'50’S, 2630 m. 23.X1991.

Vetigastropoda

Monodonta lineata (Da Costa, 1778) (Trochoidea). Roscoff, Finistére, France. III.1988.

Calliostoma zizyphinum (Linné, 1758) (Trochoidea). Roscoff, Finistére, France, III.1988.

Haliotis tuberculata Lamarck, 1822 (Pleurotomarioidea). Roscoff, Finistére, France. III.1988.

Diodora graeca (Linné, 1758) (Fissurelloidea). Roscoff, Finistére, France. III.1988.

Patellogastropoda

Patella vulgata Linné, 1758. Roscoff, Finistére, France. III.1988.

Polyplacophora

Acanthochitona fascicularis (Linné, 1767). Roscoff, Finistére, France. III.1988.

Bivalvia

Mytilus edulis Linné, 1758. France.

jackknife, i.e. sample without replacement, of sites in

various numbers from 0 to n, n being the total number

of informative sites and p the number of samplings (p=4

if jackknife is performed for 10, 20, 30 and 40 sites); (2)

repeat each jackknife (for 10, 20, . . ., n—10 sites) q times;

(3) bootstrap the sites, i.e. sample with replacement, for

each of the pq jackknife replicates, and calculate trees

for 1000 bootstrap replicates. Finally bootstrap propor-

tions (BP) are extracted for every node having at least

one BP higher than 40% occurring in the resulting pq

consensus trees, for each of the p values. For each node

these BP may be plotted against the number p of sites

jackknifed (10, 20, 30, etc..).

From such diagrams Lecointre et al. (in press) distin-

guished empirically four types of nodes: those for which

BP increase in value and decrease in variation in such a

way that the additional sequencing necessary to reach

BP higher than 90% may be estimated (e.g. figure 16);

“promising” nodes, which may be interpreted as poten-

tially entering into the first category if number of char-

acters was increased (e.g. figure 6); those for which BP

decreases in both values and variation, in such a way

that one can estimate that those nodes will disappear if

characters are added; and finally those nodes for which

the diagram is uninformative or slightly informative (fig-

ures 7, 18), which implies that very long additional se-

quences are necessary to raise the BP (i.e. as far as they

are true ).

In this work, p=8 and q=70: the estimates discussed

further result from 560 consensuses of 1000 24 taxa—

trees. This number, in addition to the 5 million trees of

six or seven taxa detailed further, explains why the fast

neighbor joining algorithm is used in the repetitive boot-

strap procedures (NJBOOT, Philippe, 1992) rather than

the very much slower DNABOOT (Felsenstein, 1990),

which, to our knowledge, is the only available bootstrap

program based upon parsimony for PC. All diagrams

showing variation in BP as a function of the number of

jackknived sites—but none of the others—have been built

using the variable regions. For all points under discussion,

S. Tillier et al., 1994

Page 127

outgroup Mytilus, Acanthochitona

Patellogastropoda Patella

Cocculiniformia

Neritimorpha

Archaeogastropoda

Neomphalina Rhynchopelta

; Fissurelloidea Diodora

‘Vetigastropoda [_-—Perotomaroises Haliotis

Trochoidea Calliostoma, Monodonta

Seguenziina

Caenogastropoda

Opisthobranchia

Pulmonata Helix, Placostylus, Succinea

Architaenioglossa

Littorinoidea Littorina, Pomatias

Calyptraeoidea Calyptraea

Muricidae Ocenebra, Nucella

Buccinidae Buccinum

Valvatoidea

Allogastropoda [several paraphyletic taxa]

Cephalaspidea Acteon

Anaspidea Aplysia

Notaspidea Berthella

Nudibranchia Archidoris

Phytia, Siphonaria, Lymnaea

Euthyneura

Figure 1. Positions of the species sampled, indicated by their genus name in italics, in a phylogenetic tree modified from

Haszprunar’s (1988c) tree. Higher taxa represented in the sample in bold. Compare with figure 29.

the diagrams made without the hypervariable regions

are similar in shape to those shown here, but this shape

is truncated for a value of sixty sites.

Taxonomic Sampling:

As mentioned above and shown further, minor modifi-

cations in species composition of a sample may have

important effects on tree topology. These effects may be

analyzed, as in Lecointre et al. (1993 and in press), by

repeated jackknives of species followed by bootstraps.

However, the problem raised in the present paper is not

so much to study the stability of the nodes as to test the

monophyly and relationships of pre-defined higher taxa.

Another procedure proposed by Lecointre et al. (JACK-

MONDO) is used here: it consists of establishing all possible

combinations of species including a single species from

each higher taxon, followed by bootstrap of sites for each

combination (NJBOOT). This not only allows the analysis

of the impact of any single species on higher taxa rela-

tionships, but also diminishes the possible bias due to

differences in representative sampling of higher taxa un-

der study. A histogram of BP is built for every majority

node of which BP is higher than 1% (MONO _ HIS).

Such diagrams (e.g. figs 9, 10), not only show how BP

of any node are distributed when species sample is mod-

ified, but may also be used to display jointly the distri-

bution of all BP values for a node and the distribution

of the values of the same node when it includes any given

species choosen by the user: this is an efficient way to:

(a) measure the impact of any given species on reliability

of any node; (b) test the monophyly of any group of

higher taxa, as discussed further.

Here seven higher taxa are represented: outgroup (two

species), Patellogastropoda (one species), Vetigastropoda

(four species), Peltospiroidea (Neomphalina, one spe-

cies), Caenogastropoda (six species), Opisthobranchia

(four species), and Pulmonata (six species). The total

number of combinations of one species per higher taxon

is thus 1152, for each of which 1000 bootstrap replicates

have been calculated with the neighbor joining algo-

rithm. Two taxa, the Patellogastropoda and Peltospiro-

idea, are monospecific in this study. The latter is one of

the taxa under discussion; this is why the procedure has

been repeated without Patella; it has also been repeated

with and without the hypervariable regions overlined in

table 1: the discussions presented further result from

building approximately 5 million trees including six or

seven taxa and 65 to 93 characters. All histograms pre-

Page 128

THE NAUTILUS, Supplement 2

Table 3. Relative rate test using either Acanthochitona or Mytilus as an outgroup. Distances in % differences (sites informative

for parsimony), variable regions overlined in table 1 included.

Helix Placo Phyti Sipho Lymna Succi Aplys Archi Actae Berth Ocene

Acanthochitona 65.52 65.88 67.44 72.41 67.44 65.12 65.12 63.22 58.82 64.63 58.82

Mytilus 65.56 63.64 65.91 67.42 64.04 62.92 61.80 63.33 58.62 63.10 60.23

Nucel Bucci Calyp Pomat Litto Rhyne Monod Calli Halio Diodo Patel

Acanthochitona 59.09 64.37 65.91 63.53 67.82 54.55 58.62 59.09 62.07 63.22 69.23

Mytilus 61.54 62.92 65.93 62.50 62.92 59.06 53.33 57.14 64.37 61.54 68.48

sented have been obtained from the data set without the

variable regions overlined in table 1.

RESULTS

Relative Rate Test

In order to obtain reliable molecular phylogenetic pat-

terns, molecular rates of evolution of included taxa must

be as close as possible (Wilson et al., 1977; Felsenstein,

1978); this is tested by comparing the molecular distances

of the various ingroups with the outgroups, here Acan-

thochitona and Mytilus, and has been done with and

without the variable regions overlined table 1 (tables 3

and 4). Differences in evolutionary rates are not signif-

icant overall. In all cases: (a) Siphonaria and Patella

exhibit a high relative rate of molecular evolution, the

differential with other taxa being more accentuated for

Patella when variable regions are removed; (b) Rhyn-

chopelta and Acteon have a lower rate of substitution

than other taxa in the sample; (c) when the mean rate

is calculated for each of the six higher Gastropoda taxa

represented, the rates are similar overall except for the

faster Patellogastropoda and the slower Neomphalina—

each having a single representative in the sample; the

Vetigastropoda have a slightly slower mean rate than the

other higher taxa represented by more than one species,

whereas in Pulmonata the mean rate seems slightly high-

er.

Reliability of the Data: Some Ways to

Obtain the Desired Tree

Without the variable regions overlined in table 1, a con-

sensus of the 13 shortest trees found using 24 species

(figure 2) shows monophyly of higher level gastropod

taxa: Vetigastropoda, Caenogastropoda, and Euthyneu-

ra. However, Succinea emerges between Archidoris and

Aplysia, i.e. between representatives of two opistho-

branch orders; while Patella is found to be the sister-

taxon of the Euthyneura. These unexpected results raise

doubt as to the position of Rhynchopelta as the sister-

taxon of the Apogastropoda (Euthyneura + Caenogas-

tropoda). An overall compatible topology is found by

bootstrap using parsimony of the same data (DNABOOT,

figure 3), in spite of minor differences within Euthy-

neura and of the seemingly better resolution within the

Caenogastropoda, which however is not well supported

by bootstrap proportions. After modification of the com-

position of the sample, reduced to twenty species and

keeping only Acanthochitona as an outgroup, a bootstrap

based on the same data still provides a similar topology

(DNABOOT, figure 4). Finally the replacement of Acan-

thochitona by Mytilus as the outgroup in the latter data

set, provokes the shift of Patella to the sister-taxon of the

Vetigastropoda (i.e. monophyly of the Archaeogastro-

poda, figure 5). In addition to these changes, the shift of

Rhynchopelta as the sister-taxon of all other gastropod

taxa in the data set may be found by using NJBOOT

instead of DNABOOT (not shown).

Shifts in the position of several taxa, similar to those

induced by changes in the taxonomic composition of the

sample, may easily be provoked by minor changes in the

alignment of the sequences, especially when variable

regions are included (not shown). It is precisely those

taxa whose relationships are uncertain which shift the

most easily.

However, nodes that are modified by such minor

changes in the data set have bootstrap proportions that

are always much lower than 90%, whereas nodes with

BP that are the closer to 90% remain unchanged (mono-

Table 4. Relative rate test using either Acanthochitona or Mytilus as an outgroup. Distances in % differences (sites informative

for parsimony), variable regions overlined in table 1 excluded

Helix Placo Phyti Sipho Lymna Succi Aplys Archi Actae Berth Ocene

Acanthochitona 64.52 65.00 68.85 74.19 65.57 63.93 67.74 61.29 58.06 59.65 59.02

Mytilus 60.32 57.38 62.30 66.13 59.68 58.06 58.73 57.14 55.56 61.40 59.68

Nucel Bucci Calyp Pomat Litto Rhyne Monod _ Calli Halio Diodo Patel

Acanthochitona 59.68 62.30 64.52 60.00 65.57 51.61 54.84 55.56 55.00 54.84 63.49

Mytilus 58.73 60.66 61.90 59.02 60.66 50.79 49.21 54.69 65.00 56.25 73.44

S. Tillier et al., 1994 Page 129

Mytilus edulis

Acanthochitona fascicularis

Diodora graeca

Haliotis tuberculata

Monodonta lineata

Calliostoma zizyphinum

Rhynchopelta concentrica

Pomatias elegans

Calyptraea chinensis

Littorina littorea

Ocenebra erinacea

Nucella lapillus

Buccinum undatum

Patella vulgata

Berthella plumula

Acteon tornatilis

Archidoris tuberculata

Succinea putris

Aplysia depilans

Lymnaea stagnalis

2 Siphonaria algesirae

Phytia myosotis

Placostylus fibratus

Helix aspersa

Acanthochitona

Mytilus

Diodora

51 Haliotis

44 Calliostoma

79 Monodonta

67 Rhynchopelta

Pomatias

Calyptraea

39 91 29 Buccinum

44 Littorina

Gi 35 Nucella

66 Ocenebra

Patella

Ti Berthella

a Acteon

—— Archidoris

39 Aplysia

58 23 Succinea

ry) Lymnaea

Phytia

3 40 22 Siphonaria

29 Placostylus

ICY Helix

Figures 2-3. Parsimony tree (figure 2) and bootstrap proportions based on parsimony trees (figure 3) of the whole data set (table

1, without Mus). 2. Consensus of the 13 shortest trees obtained with Hennig86, options m+; bb+; nelsen. Data table 1, overlined

regions not taken into account. 3. Topology and bootstrap proportions of majority nodes obtained by parsimony (DNABOOT) from

the same data. BP in %, branch lengths in % of 1000 replicates (terminal branches = 100).

Page 130 THE NAUTILUS, Supplement 2

Acanthochitona fascicularis

Diodora graeca

5 Haliotis tuberculata

Tag Calliostoma zizyphinum

79 Monodonta lineata

100 Patella vulgata

Rhynchopelta concentrica

Mytilus edulis

Patella vulgata

Pomatias elegans

Calyptraea chinensis

24 Buccinum undatum

Littorina littorea

35 Ocenebra erinacea

64 Nucella lapillus

Actaeon tornatilis

Phytia myosotis

8 Siphonaria algesirae

35 Lymnaea stagnalis

Succinea putris

31 Placostylus fibratus

Helix aspersa

34 Diodora graeca

86 26

Haliotis tuberculata

Calliostoma zizyphinum

Monodonta lineata

Rhynchopelta concentrica

Pomatias elegans

Calyptraea chinensis

Buccinum undatum

Littorina littorea

Nucella lapillus

65 Ocenebra erinacea

Actaeon tornatilis

co) ‘

69 32

Lymnaea stagnalis

Phytia myosotis

34 Siphonaria algesirae

Placostylus fibratus

Succinea putris

Helix aspersa

Figures 4-5. Topology and bootstrap proportions in % (BP), calculated with DNABOOT from incompete samples. 4. Trees

obtained for 20 taxa , from the same alignment and regions as in figures 2 and 3, Acanthochitona as the outgroup. 5. Tree obtained

from the same data set, but with Mytilus substituted for Acanthochitona as the outgroup. BP in %, branch lengths in % of 1000

replicates (terminal branches = 100).

phyly of Vetigastropoda and subgroups; monophyly of

Caenogastropoda). This observation confirms previous

empirical recommendations (e.g. Felsenstein, 1985), and

leads us to regard as unreliable most of the nodes of the

trees displayed in figures 2, 3, 4 and 5. The obvious

solution to this problem is to use more taxa and longer

sequences, which would allow the use of more homol-

ogous sites. However, for both practical (cost!) and the-

oretical reasons discussed in the previous section, we con-

sider it more useful to analyze further within our data

set which information may, or may not, be considered

reliable.

Monophyly of the Gastropoda and

Relationships of the Patellogastropoda

Using the complete data set, jackknives on increasing

number of sites correlate with bootstrap values increasing

S. Tillier et al., 1994 Page 131

in mean and decreasing in amplitude of variation (figure

6). The 84% BP obtained with 93 sites will probably

increase when more sites are used, and the monophyly

of the Gastropoda may be considered as established, at

least when Polyplacophora and Bivalvia are used as out-

groups.

The relationship of Patella to other gastropod taxa is

more difficult to establish. Three possibilities exist: (a)

Patella is the sister-group of other Gastropod taxa, a

position defended by Haszprunar (1988) and Lindberg

(1988); (b) Patella and the Vetigastropoda form a mono-

phyletic taxon, the “Archeogastropoda ’ in their classical

definition and position; (c) Patella and the Caenogastro-

poda + Euthyneura form a monophyletic group. In our

data set, the bootstrap proportions of the grouping (c)

seem to increase with the number of sites sampled; how-

ever, no value higher than 53% has been found, and the a

mean bootstrap value for 80 sites is less than 20%; fur- Number of informative sites

thermore this grouping has been found only 243 times

(of 1152) with bootstrap proportions not exceeding 15% nee 7

in our “jackmono” results. Consequently we reject this

grouping.

More surprisingly, the increase and variation of BP in

relation with number of sites sampled seems to favour

monophyly of Patella with the Vetigastropoda: BP of

the group Patella + Acanthochitona + Mytilus tend to

decrease in both mean and amplitude of variation as the

number of sites is increased (figure 7), and never exceed

32%; whereas BP of the group Patella + Vetigastropoda

seem to increase in mean and decrease in variation as

the number of sites sampled is increased, and reach 85%

(figure 8). However, the solution is not simple, as the 25

mean value of BP for 80 sites sampled is only ca. 40%,

which is not significant.

The result of BP calculated from combinations of seven

species from the seven higher taxa defined above is even 0

more ambiguous, and somewhat contradictory (figures 9 0

and 10). For both groupings, the histograms are bimodal,

the bimodality being far more obvious in figure 10 (Ar-

cheogastropoda monophyletic) than in figure 9 (Patella

= sister-group of other gastropods). The monophyly of

the Archeogastropoda is supported 531 times of 1152,

and reaches BP as high as 952, i.e. a value worth being

considered; the paraphyly of the Archeogastropoda is

Bootstrap Estimates

20 40 60 80

Number of informative sites

Figures 6-8. BP in relation to number of sites jackknived,

data set from table 1, Mus excluded. 6. Grouping of all Gas-

tropoda. 7. Grouping of all Gastropoda except Patella, i.e. for

the position of the Patellogastropoda (Patella) as the sister-

group of the other Gastropoda. Note that BP do not increase

as site number is increased. 8. BP in relation to number of sites

jackknived for the grouping of Patella with the Vetigastropoda

(Diodora, Haliotis, Calliostoma, Monodonta), i.e. for the

monophyly of the Archaeogastropoda: note that BP increase as

the number of sites sampled is increased. Number of sites jack- 0 20 __ 40 ie) 80

knived along the abscissa, BP in % along the ordinate; number NEIMAN TOMO AS

of jackknife replicates 70 for each number of sites, number of

bootstrap replicates of each jackknife replicate 1000.

Bootstrap Estimates

ce COC Ge G9 62S 255850 0 ese Seane

Page 132 THE NAUTILUS, Supplement 2

0 100

9 10

Figures 9-10. Histograms of BP of monospecific combinations of higher taxa for two positions of Patella, from data set table 1,

overlined regions not taken into account. 9. Grouping of the outgroup with Patella, i.e. the position of the Patellogastropoda as

the sister-group of the other Gastropoda (found 585/1152 times); BP for combinations including Mytilus shown in dark. 10. grouping

of Patella with the Vetigastropoda, i.e. the monophyly of the Archeogastropoda (found 531/1152 times); BP for combinations

including Acanthochitona shown in dark.

supported 585 times, with BP not exceeding 852, i.e. a

value too low to be considered highly significant, but

which could be raised by additional data. These unclear

results may be the consequence of long branch attract:

both Patella and Diodora exhibit rates of substitution

higher than in the other species of the sample.

The analysis of the distribution of taxa in the histo-

grams shows that high BP for monophyletic Archeogas-

tropoda are equally supported by all of the 24 species

except Acanthochitona, Diodora and Calliostoma which

support low BP exclusively: in other words, one may

obtain apparent monophyly of the Archeogastropoda at

a significant level of confidence by using another out-

group than Acanthochitona and by removing Diodora

and Calliostoma from the sample. The paraphyly of the

Archeogastropoda is favoured by using Mytilus as an

outgroup, is contradicted by Diodora, but is strongly

supported by Monodonta, whereas Acanthochitona does

not influence this node. Several explanations for the strong

bimodality of the Archeogastropod node may be found:

although it is improbable when considering BP discussed

further for Vetigastropoda, Diodora, which contradicts

both solutions, could belong to a clade other than the

Vetigastropoda; or the relative rates of substitution may

be involved: Patella and Diodora may aggregate because

both evolved faster (long branches attract), while the

influence of Monodonta may be explained by its slower

relative rate when Mytilus is taken as an outgroup (table

4).

It would be premature to reach any definitive conclu-

sion about the relationship of the Patellogastropoda, which

may be considered either as: (a) members of a mono-

phyletic Archeogastropoda, a solution that the present

results favour slightly, but not enough to reject the hy-

pothesis that it is due to long branches attract; or (b) as

the sister-group of the other gastropods or even a less

related taxon, a solution that is strongly favoured by the

morphological analyses cited above.

Monophyly and Relationships within the

Vetigastropoda

As discussed by Salvini-Plawen & Haszprunar (1987) and

Haszprunar (1988), the Vetigastropoda are characterized

morphologically by synapomorphic sensory “bursicles”

located at the efferent edge of each ctenidial leaflet;

common and distinctive types of tentacles and anterior

oesophagus epithelium; epipodial sense organs; high

chromosome number; and similar renal cell-types. With-

in the Vetigastropoda, the Pleurotomarioidea and Tro-

choidea, represented in this study by Haliotis and (Cal-

liostoma + Monodonta) respectively , are united by

aberrant osphradial characters. This implies that the Fis-

surelloidea, here represented by Diodora, are the sister-

group of (Pleurotomarioidea + Trochoidea).

Our data fully confirm this phylogenetic arrangement,

and contradict the more classical view, in which the

Pleurotomarioidea (Haliotis) are the sister-group of the

Fissurelloidea + Trochoidea. The latter view was de-

fended for example by Hickman & McLean (1990) and

supported by fewer sequences and other methods (Tillier

et al., 1992). Indeed BP on jackknives of various numbers

of sites strongly support, with little doubt: (a) the mono-

phyly of the Vetigastropoda (figure 11); (b) the mono-

S. Tillier et al., 1994

Bootstrap Estimates

0 20 40 60 80

Number of informative sites

Bootstrap Estimates

0 20 40

Number of informative sites

Bootstrap Estimates

Page 133

2 12

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8 3

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eh a ao aks

8 a 8 e

e 3 3

8 8

0 20 40 60 80

Number of informative sites

i |

j 4

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e 8

8 es

a e

20 40 60 80

Number of informative sites

Figures 11-14. BP in relation to number of sites jackknived from the data set of table 1. 11. Grouping of the Vetigastropoda

together, ie. monophyly of the latter (Diodora, Haliotis, Calliostoma, Monodonta). Note that BP increase as site number is

increased. 12. Grouping of the Pleurotomarioidea (Haliotis) with the Trochoidea (Calliostoma and Monodonta), i.e. Fissurelloidea

as the sister group of the latter. Note that BP increase as site number is increased. 13. Grouping of the Fissurelloidea (Diodora)

with the Trochoidea (Calliostoma, Diodora), i.e. Pleurotomarioidea (Haliotis) as the sister group of the latter. Note that BP do not

increase, but rather diminish as site number is increased. 14. Grouping of the Trochoidea, i.e. monophyly of the latter. Note that

BP may reach 100%, and vary very little, for 80 sites. Number of sites jackknived along the abscissa , BP in % along the ordinate;

number of jackknife replicates 70 for each number of sites, number of bootstrap replicates of each jackknife replicate 1000.

phyly of Haliotis and Trochoidea (figure 12) and refute

the monophyly of Diodora and the Trochoidea (figure

13); (c) the monophyly of the Trochoidea Calliostoma

and Monodonta, depicted in figure 14 for the sake of

showing the pattern produced by a nearly fully resolved

node.

Monophyly of Apogastropoda, Caenogastropoda,

Stenoglossa

Surprisingly, the monophyly of the Apogastropoda, i.e.

Caenogastropoda plus Euthyneura in our sample (figure

1), is not among the best supported groupings, although

an increasing BP with increasing number of sites sampled

indicate that this node could be confirmed by ca. 40

more informative sites (figure 15). The histograms of BP

for monospecific samples of each higher taxon are uni-

modal (figure 23) and reach higher values when hyper-

variable regions are retained (maximum 968 vs. 926,

mean 764 vs. 386). Analyses of the corresponding his-

tograms for BP without hypervariable regions show that

BP are lowered by Acteon (Cephalaspidea) and Berthella

(Notaspidea). As noted previously (Tillier et al., 1992)

and visible in table 1, opisthobranch D1-Cl sequences

DSS aE

Page 134

Bootstrap Estimates

0 6 80

20 40

Number of informative sites

THE NAUTILUS, Supplement 2

100 16

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0 20 40 60 80

Number of informative sites

Bootstrap Estimates

0 20 40 60 80

Number of informative sites

Figures 15-18. BP in relation to number of sites jackknived from the data set of table 1. 15. Grouping of the Apogastropoda

(Caenogastropoda + Euthyneura, figure 1), Rhynchopelta excluded. BP increase as site number is increased. 16. Grouping of the

Caenogastropoda (cf. figure 1). BP increase as site number is increased, and the maximum BP (100%) is reached and exhibits little

variation for 80 sites. 17. Grouping of Calyptraea and Stenoglossa (Buccinum, Ocenebra, Nucella). BP increase as site number is

increased, but the mean BP reached for 80 sites is far from highly significant values. 18. Grouping of the Stenoglossa (Buccinum,

Ocenebra, Nucella). BP decreases as site number is increased, suggesting possible polyphyly of the latter; compare with figure 17.

Number of sites jackknived along the abscissa , BP in % along the ordinate; number of jackknife replicates 70 per number of sites,

number of bootstrap replicates of each jackknife replicate 1000.

tend to differ more than usual from other gastropod

sequences, inducing unexpected fluctuations in BP. How-

ever, figure 15 suggests that longer sequences could re-

solve this problem at least at the level of the (Caeno-

gastropoda + Euthyneura) node. The polyphyly of the

Euthyneura cannot be excluded (see further).

The monophyly of the Caenogastropoda is very well

supported by our data (figure 16), although supported

thus far by a single synapomorphic morphological char-

acter, a highly distinctive type of osphradium (Haszpru-

nar, 1988a). The inclusion of the Stenoglossa within

Caenogastropoda is strongly supported by our sample,

and we reject the hypothesis of a non-caenogastropod

origin of the group (Ponder, 1973; Taylor & Morris,

1988). Fhe monophyly of the Muricidae (Ocenebra and

Nucella), as well as the monophyly of the Littorinoidea

(Littorina and Pomatias), are well supported (not shown).

More interesting is the lack of support for the monophyly

of Stenoglossa (Buccinum + Ocenebra + Nucella) (fig-

ures 1 to 4), which may not be an artifact: surprisingly,

the inclusion of Calyptraea with the Stenoglossa is better

supported (figure 17) than the monophyly of the Sten-

oglossa without Calyptraea (figure 18), which could in-

dicate the polyphyly of the Stenoglossa. The monophyly

S. Tillier et al., 1994

Page 135

Bootstrap Estimates

40 60 80

Number of informative sites

0 100

Figures 19-20. BP in relation to number of sites jackknived, and histogram of BP of monospecific combinations of higher taxa,

for the grouping of the Euthyneura (data set table 1, currently admitted relationships figure 1), overlined regions not taken into

account in figure 20). 19. Dot diagram: although BP increase as site number is increased, mean value for 80 sites is not highly

significant at all. Number of sites jackknived along the abscissa, BP in % along the ordinate; number of jackknife replicates 70 per

number of sites, number of bootstrap replicates of each jackknife replicate 1000. 20. Histogram from JACKMONO: BP for

combinations including Acteon shown in dark. Archidoris and Berthella correspond to the same distribution as Acteon; on the

contrary Aplysia occurs only in combinations forming the peak on the extreme right.

of Calyptraea and Buccinum cannot be rejected without

additional data (its BP increases slowly in relation to

number of sites to reach a mean of 380 for 80 sites;

maximum value 918, which is not neglegible). The pau-

city of taxa and number of sites in our sample precludes

any further comment other than underscore the need to

enlarge the data set for Caenogastropoda and Stenog-

lossa.

Monophyly of, and relationships within the

Euthyneura

As with the Caenogastropoda and for the same reason,

the monophyly of Euthyneura is not as well supported

as expected, considering that their monophyly based

mainly upon their pentaganglionate condition has not

been contested. Their BP increase with number of sites

sampled (figure 19), but are still far from significant

values for 80 sites. The analysis of the strongly bimodal

histogram of BP for monospecific samples of each higher

taxon shows that (figure 20): (a) the Euthyneura are very

strongly supported when Aplysia represents the Opis-

thobranchia (BP between 95 and 100%); (b) other Opis-

thobranchia occur only in combinations corresponding

to the lower mode, with BP between ca. 400 and ca. 900.

As for Apogastropoda, our sequences of non-Anaspidea

Opisthobranchia do not support monophyly of the Eu-

thyneura, either because of their autapomorphies or be-

cause the Opisthobranchia are polyphyletic, but not be-

cause they are too recent (at least one more external node

is well supported, see next paragraph). Their relative

rates of substitution do not appear sufficiently different

from the others to explain alone this lack of resolution

(tables 3, 4). Until more and longer sequences allow the

choice of either answer, several points may be made.

Within the Euthyneura, our data do not support clear-

ly the monophyly of Pulmonata alone in the total sample

(figure 21), but support even less their para- or polyphyly

(not shown). Our data do support strongly the monophyly

of Aplysia + Pulmonata (figure 22). Removing Aplysia

from the sample immediately raises the maximum ob-

served BP for Pulmonata from 544 to values between

900 and 1000. However, it cannot be concluded that the

Pulmonata are para- or polyphyletic since, in our data

set, no grouping within the Anaspidea + Pulmonata

clade shows a clear trend toward stability similar to that

of the clade as a whole. The hypothesis of the monophyly

of the Pulmonata remains the most probable considering

morphological characters (e.g. Tillier, 1984), but com-

bination of morphological and molecular data presented

suggests the position of the Anaspidea as the sister-group

of the Pulmonata (with the proviso that only four of the

nine opisthobranch orders recognized, for example, by

Boss (1982), are included in our sample). To pursue fur-

ther the analysis of this clade will require additional

molecular characters as well as re-evaluation of the mor-

phological data.

Our data do not provide any clear further indication

on relationships of the Cephalaspidea (Acteon), Notas-

pidea (Berthella) and Nudibranchia (Archidoris). The

groupings that seem the most promising are Notaspidea

+ Nudibranchia (BP reaching 932, but mean for 80 sites

Papenlae THE NAUTILUS, Supplement 2

Bootstrap Estimates

0 20 40 60 80 0 20 40 60 80

Number of informative sites Number of informative sites

Figures 21-22. BP in relation to number of sites jackknived for the grouping of the Pulmonata with (22) and without (21) Aplysia

(currently admitted relationships figure 1). 21. Without Aplysia, BP do not increase significantly as site number is increased. 22.

Aplysia included, BP increase as site number is increased, and reach highly significant values for 80 sites. Number of sites jackknived

along the abscissa , BP in % along the ordinate; number of jackknife replicates 70 per number of sites, number of bootstrap replicates

of each jackknife replicate 1000.

ca. 400!) and Cephalaspidea + Anaspidea + Pulmonata above and illustrated by the shift provoked by the change

(BP reaching 769, but mean for 80 sites ca. 200 only). of the outgroup (figures 4 & 5)). The inclusion of Rhyn-

Neither monophyly of the Opisthobranchia less Aplysia, chopelta in the group (outgroups + Patellogastropoda

nor paraphyly or even polyphyly of this taxon may be + Vetigastropoda) is supported by the monophyly of the

rejected. At the moment, a paraphyletic arrangement Apogastropoda (figure 15), and is not contradicted by

between emergence of the Caenogastropoda and that of the histogram of monospecific combinations of higher

the Anaspidea + Pulmonata clade appears to be the most taxa (figure 23). However, these data do not distinguish

reasonable when trying to synthetize available infor- between the four possible solutions (two of them shown

mation, in agreement with Haszprunar’s (1988c) frame- by figures 1 and 4, plus monophyly of Rhynchopelta +

work. However, the hypothesis of the early emergence Vetigastropoda, or monophyly of Rhynchopelta + Eu-

of the Euthyneura proposed by Ponder & Waren (1988: thyneura).

291) is worth investigating further. As in the case of the Patellogastropoda, the variation

of BP asa function of an increasing number of jackknived

sites is not conclusive, but suggests rejection of the pres-

Relationships of the N hali

eS tae dee gr ara ently favoured solution: the grouping (outgroup + Pa-

As could be expected from previous morphological anal- tella + Rhynchopelta). This grouping, with Neomphal-

yses (see Haszprunar, 1988a, b, c; McLean, 1990b), Rhyn- ina emerging between the outgroup and the

chopelta always roots very deeply within the trees ob- Vetigastropoda, as advocated by Haszprunar (1988a, b,

tained from our data set. In addition to the fact that it c), has not been found to have a BP higher than 1%. The

is the only representative of its group (due to the difficulty monophyly of Rhynchopelta and Patella is sometimes

in obtaining RNA from deep-sea gastropods), its position found, but too rarely (293/1152) and with too low BPs

makes its relationships still more difficult to analyze be- (mean ca. 1.5% for 80 sites!) to be retained, as confirmed

cause of the influence of proximal nodes (mentioned by its absence from BP of monospecific combinations of

Figures 23-28. Histograms of BP of monospecific combinations of higher taxa, with (23, 25, 27) and without (24, 26, 28) Patella.

23-24. Grouping of the Apogastropoda (Caenogastropoda + Euthyneura, figure 1), excluding Rhynchopelta. The high BP of

figure 23 are reinforced when Patella is removed from the sample (figure 24). 25-26. Grouping of Rhynchopelta with the outgroup

(including Patella in figure 25), with samples including (figure 25) or not including (figure 26) Patella. These combinations have

been found only 277 and 152 (of 1152) times. 27-28. Grouping of Rhynchopelta with the Apogastropoda, with samples including

(figure 27) or not including (figure 28) Patella. These combinations have been found 541 and 979 (of 1152) times; comparison with

figures 27 and 28 shows the much better support for monophyly of Neomphalina, Caenogastropoda and Euthyneura (compare with

figure 1).

S. Tillier et al., 1994 Page 137

Page 138

THE NAUTILUS, Supplement 2

outgroup

Patellogastropoda

Vetigastropoda

Neomphalina

Littorinoidea

Calyptraeoidea

Muricidae

Buccinidae

Cephalaspidea

Notaspidea

Nudibranchia

Anaspidea

Pulmonata

Figure 29. Diagram showing the best supported relationships

from data set of table 1; compare with figure 1. Monophyly of

Patellogastropoda + Vetigastropoda (= Archaeogastropoda) is

found better supported, although not conclusively, than their

paraphyly (long branch attraction); monophyly of the Opis-

higher taxa. We are therefore left with three possible

solutions: (a) Rhynchopelta belongs to supposedly mono-

phyletic Archeogastropoda, either as the sister-group of

(Patella + Vetigastropoda), as in figure 1, or as the sister-

group of the Vetigastropoda; (b) Rhynchopelta and the

Vetigastropoda form a monophyletic unit but the Ar-

cheogastropoda are paraphyletic; (c) Rhynchopelta and

the Apogastropoda (Caenogastropoda + Euthyneura) are

sister-groups, as in figure 4. None of these solutions has

produced a mean BP greater than 25% for eighty sites.

To analyze further our limited data set, it is more rea-

sonable to turn to monospecific combinations of higher

taxa, which equilibrate the respective samplings of the

latter, to try to find the most reliable solution.

Bootstraps have been calculated in monospecific com-

binations of higher taxa both with and without Patella;

allowing us (a) to consider only one problematic mono-

specific higher taxon at a time; (b) to eliminate one prob-

lematic taxon that not only is close to the taxon under

question and therefore influences the node(s) analyzed,

but also has a higher substitution rate than average, while

Rhynchopelta has a lower than average rate (see figures

23 and 24 for comparison). Comparisons of the BP ob-

tained for the various possible nodes (figures 25 to 28)

indicate that in our sample:

(a) Rhynchopelta, and thus presumably the Neom-

thobranchia (Cephalaspidea + Notaspidea + Nudibranchia +

Anaspidea) is not supported at all, whereas monophyly of An-

aspidea and Pulmonata is supported. Neomphalina (Rhyncho-

pelta) are found the sister-group of the Caenogastropoda +

Euthyneura included in the sample.

phalina, is probably not an outgroup to the Veti-

gastropoda + Apogastropoda clade (figures 25-

26);

(b) Rhynchopelta, Patella and the Vetigastropoda do

not constitute a monophyletic unit (this grouping

never found with a BP higher than 40%);

stitute a monophyletic unit (this grouping never

found with Patella included in the sample, found

7/1152 times with a maximum BP of 43% with

Patella excluded from the sample);

(d) the monophyly of Rhynchopelta and the Apogas-

tropoda is the best supported grouping, as shown

by figures 27 (Patella included) and 28 (Patella

not included).

Whether Peltospiridae and Neomphalidae are family-

rank taxa-in a superfamily Neomphaloidea as proposed

by Warén & Bouchet (1989), or are representatives of

two superfamilies in an order Neomphalina, as main-

tained by McLean (1990b), their close relationships are

currently admitted despite the lack of known synapo-

morphies. They have been reported to originate: (a) in

all cases, outside of the clade Vetigastropoda although

being “at an archeogastropod level of organization”

(Fretter, 1989); (b) between the outgroup and the Ve-

tigastropoda (Haszprunar, 1988a, b, c); or (c) among the

S. Tillier et al., 1994

Page 139

Architaenioglossa (“Vivipariformes’ Sitnikova & Staro-

bogatov, 1982; Golikov & Starobogatov, 1988). In relation

to Haszprunar’s (1988c) phylogenetic framework (figures

1, 29), support here found for the emergence of the

Peltospiridae (and Neomphalidae?) between the Veti-

gastropoda and the Caenogastropoda, confirm the first

hypothesis, refutes the second, and is compatible with

the third—which has been by far the least advocated.

However, no more definitive conclusion can be made

before data similar to those analyzed here are available

for both more Neomphalina and some Architaenioglossa.

CONCLUSION

In spite of this relative low level of resolution, the meth-

ods elaborated by Lecointre et al. (1993 and in press)

prove more powerful than “simple” jackknives and boot-

straps for such limited data sets as ours. Under such

conditions the power of these methods is doubtlessly in-

creased when they are used in a comparative way to

choose one among a finite number of solutions, as done

here, rather than to estimate the absolute reliability of

any single solution for a given data set—even if this is

what they were designed for, and how they should be

used as often as possible. Choosing the best among un-

equally poor solutions, as often done here, is a gamble—

it is not equivalent to finding the exact solution. However,

this estimation is justified in that, overall, our results

converge with those obtained from morphological anal-

yses. The methods used here may help to answer the

molecular systematist’s dilemma: more taxa, or more

characters?

Combining the nodes retained above, i.e. the phylo-

genetic hypotheses the best supported by our data set,

results in the tree shown in figure 29: (a) the Anaspidea

and Pulmonata form a monophyletic unit; (b) the posi-

tion and relationships of the other Opisthobranchia or-

ders are doubtful; (c) the Caenogastropoda are mono-

phyletic, but no reliable support has been found for

monophyly of the Stenoglossa families Buccinidae and

Muricidae—which however was not rejected either; (d)

the Neomphalina are the sister-group of the Apogastro-

poda; (e) the Vetigastropoda are monophyletic, while the

Fissurelloidea are the sister-group of the Pleurotoma-

rioidea + Trochoidea; (f) the Patellogastropoda and Ve-

tigastropoda may form a monophyletic unit Archeogas-

tropoda, which however must be tested by addition of

taxa.

All these hypotheses are not equally well supported:

the position of the Patellogastropoda is dubious and must

be confirmed by additional data from at least one or two

more taxa from this same group, as well as possibly by

additional sequence length. Given the shape of the

BP/number of sites diagrams, additional sequences are

required to increase the reliability of most of the other

proposed relationships: in nearly all cases discussed but

the Trochoidea and Caenogastropoda, more characters

could yield highly significant results in a non-compara-

tive way. Data of the same level of variability would

help to resolve the Euthyneura problem, whereas se-

quences of higher variability would possibly solve the

Pulmonata and Stenoglossa questions.

ACKNOWLEDGMENTS

We are greatly indebted to Hervé Philippe for providing

the programs used and to Guillaume Lecointre, Hervé

Le Guyader and André Adoutte for discussion, access to

their unpublished manuscripts and comments on the

present paper. Bootstraps using DNABOOT have been

done in the Centre Informatique du Muséum, MNHN.

We owe to Serge Gofas, Carmen Salas and to the staff

of the Roscoff marine station part of the material used.

Anders Waren sorted and determined the hot vent lim-

pets kindly provided by Michel Segonzac (IFREMER,

cruise HERO 91, chief Daniel Desbruyéres).

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THE NAUTILUS, Supplement 2:141-144, 1994

Page 141

Site-Directed Mutagenesis with the Polymerase Chain Reaction

for Identification of Sibling Species of Mytilus

Jonathan B. Geller!”

Dennis A. Powers

Hopkins Marine Station

Stanford University

Pacific Grove, CA 93950 USA

ABSTRACT

The large sample sizes needed for population and biogeograph-

ic studies make sequencing impractical as a means of quanti-

fying genotype frequencies. In a previous study, we identified

sequence variation in the mitochondrial 16S ribosomal gene

from mussels in a sibling species group (Mytilus spp.) that

discriminated mussels introduced to the west coast of North

America (Mytilus galloprovincialis) from native mussels (My-

tilus trossulus). In this study, we used site-directed mutagenesis

by the polymerase chain reaction (PCR) to transform a single

diagnostic nucleotide substitution into a restriction site. By using

a large (51 bp) oligomer as a primer, a size shift in cut and

uncut PCR products was visible on an agarose gel. Thus, PCR

followed by a restriction digestion allowed identification of

species-specific haplotypes in hours rather than days. This

method is applicable to any study in which rapid detection of

genotypes is desired. We show the presence of M. trossulus

haplotypes in Monterey Bay, California, extending its southern

range. We also present evidence for heteroplasmic individuals

that contain mitochondrial haplotypes indicative of both spe-

cies.

Key Words: Biogeography, genetic introgression, heteroplas-

my, mitochondrial DNA, mussels, Mytilus, sibling species.

INTRODUCTION

Sibling species are difficult to identify using morpholog-

ical criteria, perhaps because insufficient time for sub-

stantial morphological divergence has elapsed since ge-

netic isolation. Yet, because of the recency of divergence,

sibling species are especially important in the study of

speciation. Therefore the ability to describe the geo-

graphic distribution of sibling species is of considerable

interest. Mussels in the genus Mytilus are an example of

a sibling species group whose identification depends pri-

1 Current Address: Department of Biological Sciences, Univer-

sity of North Carolina at Wilmington, Wilmington, NC 28403-

3297. USA.

2 Author for correspondence.

marily upon genetic analysis. McDonald et al. (1991)

have summarized the biogeographic evidence provided

by analysis of the frequency and distribution of allo-

zymes: Mytilus edulis Linné, 1768 occurs primarily on

the Atlantic shore of North America and northern Eu-

rope. Mytilus galloprovincialis Lamarck, 1819 occurs in

southern Europe and as introduced populations else-

where. Mytilus trossulus Gould, 1850 occurs on the shores

of the northern Pacific Ocean. Our work has focused on

the invasion of Mytilus galloprovincialis onto the west

coast of North America. In this paper, we describe a

method for the rapid identification of M. trossulus and

M. galloprovincialis in a mixed population in central

California.

Analysis of mitochondrial DNA (mtDNA) polymor-

phisms within and between populations and closely re-

lated species has been used to explore the nature of spe-

ciation (Avise, 1986). The earlier investigations of mtDNA

variation were based on restriction fragment length poly-

morphism analysis, requiring purification of mtDNA,

restriction digestion, and end-labeling of DNA fragments

for visualization on autoradiographs (Hillis & Moritz,

1990). These procedures are time consuming and limit

the number of individuals that can be analyzed per pop-

ulation. More recently, the polymerase chain reaction

(PCR) and widely applicable universal primers have been

used to amplify regions of mtDNA from large numbers

of individuals. PCR products can then be analyzed by

sequencing or RFLP analysis. Sequencing of large num-

bers of individuals is usually beyond the scope of pop-

ulation and biogeographic studies, and RFLP analysis of

PCR products will not reveal variation in non-restriction

sites. Variation in non-restriction sites can be detected

by hybridization with oligonucleotide probes. However,

reliable selective hybridization typically requires several

proximate nucleotide differences, and time consuming

radioisotopic labeling, blotting, hybridization, and ex-

posure to autoradiographic film. We devised an alter-

native approach to detect a single diagnostic base pair

difference in the mtDNA genome of the Mytilus tros-

sulus and M. galloprovincialis.

Page 142 THE NAUTILUS, Supplement 2

M. gallo 5' ANAC ee re

M. tros 5' ASA G ee

primer TTGAAGGATGGTATGAAAGGGTTAAC(GC)AAG(GA)T(GT)CTGTGTCT(AG)AGAATT

50 375

Eco Rl

M. trossulus

Figure 1. A diagnostic Eco RI is created by introducing a mismatch in a PCR primer. Primer MYT16SA-RI changes the sequence

AAATTN to GAATTN (asterisk in shown sequence). Only where N is C (Mytilus galloprovincialis) is a restriction site produced.

Mytilus galloprovincialis and M. trossulus can thus be distinguished after an Eco RI digestion, as illustrated in the bottom panel.

We first used PCR to amplify a portion of the 16S

ribosomal RNA gene from the mitochondrial genome of

Mytilus trossulus and M. galloprovincialis (Geller et al.,

1993). These products were cloned and sequenced and

five diagnostic nucleotide substitutions were found. While

none of these substitutions were found within restriction

sites, one diagnostic substitution was in a region that

differed from an Eco RI site by a single base pair in M.

galloprovincialis, and by two sites in M. trossulus. We

used site-directed mutagenesis to alter one nucleotide

base within this region, producing a restriction site dif-

ference for the two species that can be analyzed on aga-

rose gels.

MATERIALS AND METHODS

Site-directed mutagenesis: Site-directed mutagenesis

takes advantage of the tolerance of PCR to mismatches

in oligonucleotides primers. To convert the site adjacent

to a nucleotide substitution into a restriction site, a mu-

tation was introduced in the five nucleotides upstream

of the substitution (Figure 1). By changing the sequence

AAATTN to GAATTN, an Eco RI site is created where

N is C. Thus, only Mytilus galloprovincialis will have

this site. To create a visualizable size shift on an agarose

gel after digestion with Eco RI, the primer was unusually

large (51 bp). The primer was designed to be degenerate

at other variable (but not diagnostic) positions to insure

annealing to all Mytilus haplotypes.

We used mussels that had previously been sequenced

as well as mussels of unknown genotype to demonstrate

this system of identification. Using the mutagenic primer

MYTI6A-RI (TTG AAG GAT GGT ATG AAA GGG

TTA AC(GC) AAG AAG (GA)T(GT) CTG TGT CT(AG)

AGA ATT) and MYT16SB (CCG TTC TGA ACT CAG

CTC ATG T), an approximately 425 bp segment of the

mitochondrial 16S ribosomal RNA gene was amplified.

Each reaction consisted of 2.5 ul 10X reaction buffer

(100 mM Tris (pH 8.3), 15 mM MgCl,, 500mM KCl, 1%

gelatin, 1% Nonidet—40, and 1% TritonX-100), 20 pmole

of each primer, 0.5 units of Tag DNA polymerase (Am-

plitag, Perkin-Elmer), 0.5 ul of a crude preparation of

total cellular DNA, and dH,0 in a total volume of 25 ul.

Thirty five cycles of one minute each of denaturation at

94°C, annealing at 54°C, and extension at 72°C were

performed on automated thermocyclers (Perkin-Elmer).

Restriction digests: Without purification, 10.3 ul of each

PCR product was digested at 37°C for 3-14 hr with 7

units of Eco RI using 1.2 wl of the manufacturer’s (US

Biochemicals) provided 10X buffer. Digests were ana-

lyzed on a 4% agarose gel (3% NuSieve, 1% SeaKem,

FMC Corp.).

RESULTS

Figure 2 shows the result of mutagenic PCR followed

by Eco RI restriction digestion for mussels with known

genotypes, and demonstrates the effectiveness and ease

of scoring of our method for sibling species identification.

All amplification products from previously sequenced

Mytilus galloprovincialis, drawn from Japanese and San

Diego populations, contained the mutant Eco RI site,

while all products from mussels with known Mytilus

trossulus haplotypes (from Tillamook Bay, Oregon)

lacked this restriction site.

J. B. Geller and D. A. Powers, 1994

Mytilus trossulus Mytilus galloprovincialis

i sea. ee eM

Figure 2. Eco RI digests of amplification products generated

with primers MYT16SA-RI and MYTI6SB. Only products from

Mytilus galloprovincialis were cut. Mytilus galloprovincialis

were individuals transported in ballast water as larvae from

Japan to Coos Bay, Oregon, where they were cultured to a size

sufficient for DNA extraction. Mytilus trossulus were from

Tillamook Bay, Oregon (see Geller et al. 1993 for details). M

indicates size marker (Hpa II digest of pBluescript KS+).

Figure 3 illustrates the application of this method to

an uncharacterized population from Monterey Bay, Cal-

ifornia. Our analysis showed that this is a mixed popu-

lation, containing both Mytilus trossulus and M. gallo-

provincialis. Some digestions produced both cut and uncut

fragments. In these cases, purification of the PCR product

followed by digestion with excess enzyme (which had

demonstrated activity on other PCR products) did not

eliminate the uncut fragment, suggesting the presence

of two mitochondrial haplotypes in these mussels. In

total, we found 26 M. trossulus, 26 M. galloprovincialis,

and 18 heteroplasmic individuals with haplotypes of both

species.

DISCUSSION

Previous studies have used analysis of PCR products to

identify sibling or closely related species. For example,

Hall and Smith (1991) used restriction digests of ampli-

fied mtDNA to distinguish African and European hon-

eybees. In the case of honeybees, restriction sites were

found that distinguish subspecies of Apis mellifera. An

example of an alternative approach is the study of Morin

et al. (1992), who used oligonucleotide mitochondrial

probes to distinguish subspecies of the chimpanzee (Pan

troglodytes). While useful in these particular studies,

both of these methods may not be broadly applicable.

For example, PCR products lacking diagnostic restriction

sites cannot be distinguished by digestion, and hybrid-

ization of oligonucleotide probes is most useful when

several substitutions are proximate. Further, many work-

ers may wish to avoid potentially hazardous and time-

consuming procedures using radioisotopes. Our method

using site-directed mutagenesis only requires that a re-

striction site can be created by alteration of a site con-

taining a diagnostic substitution.

It is important to note that our species assignments are

based on a single nucleotide difference, as assayed by

Page 143

Chia CG Chey Chiat ik Mian i Ofo-Clr

Figure 3. Eco RI digests of amplification products from mussels

of unknown genotype collected in Monterey Bay, California.

Mussels generating uncut products (upper bands; eg, lane O)

are typed as Mytilus trossulus, those generating cut products

(lower bands; eg, lanes D-J) are typed as M. galloprovincialis,

and lanes with both upper and lower bands (eg, lanes L and

N) are from heteroplasmic mussels.

the presence or absence of the mutagenic restriction site.

Without prior characterization of sequence variation

within and among species considered, undiscovered vari-

ation at a “diagnostic” site may lead to misassignment

of haplotype or species identity. In the example pre-

sented here, we tested the accuracy of this method of

identification by applying the assay to populations of

mussels from Tillamook Bay, Oregon (n=54) and sites

in Japan (n=45) that had been previously characterized

by allozyme electrophoresis (McDonald et al., 1991; Wil-

kins et al., 1981), and found complete agreement be-

tween the two techniques (Geller et al., 1994).

We are applying this method to our study of the geo-

graphic distribution of Mytilus trossulus and M. gallo-

provincialis on the west coast of North America. Prelim-

inary results are generally in accord with those reported

by McDonald and Koehn (1988) in their study of allo-

zyme distribution: M. trossulus is prevalent north of San

Francisco Bay and M. galloprovincialis is most common

in southern California. However, the results presented

in this paper demonstrate the presence of M. trossulus

haplotypes in Monterey Bay, south of San Francisco Bay,

and work in progress reveal M. trossulus haplotypes in

southern California. McDonald and Koehn (1988) did

not sample in Monterey Bay, and it is possible that their

sample of 50 mussels from southern California (25 each

from San Diego and Pt. San Luis) simply did not include

any M. trossulus. Notwithstanding the above, it seems

likely that some M. trossulus enzyme electromorphs

would have been found were they present. We hypoth-

esize that the M. trossulus haplotypes we find far south

of San Francisco Bay may reflect introgression of M.

trossulus mtDNA into M. galloprovincialis populations.

The species making up the Mytilus edulis complex are

known to hybridize where they overlap in distribution

(eg, Vainola & Hvilson, 1991), and mtDNA heteroplasmy

has been reported several times (Fisher & Skibinski, 1990;

Hoeh et al., 1991; Zouros et al., 1992). The presence of

heteroplasmic hybrid individuals in Monterey Bay is con-

sistent with our hypothesis.

Our previous study (Geller et al., 1993) of 16S ribo-

somal rDNA sequences did not reveal differences that

Page 144

distinguish Mytilus galloprovincialis and M. edulis. Thus,

our assay cannot be used unmodified in localities where

these two species coexist. However, once diagnostic nu-

cleotide variation is determined, new mutagenic primers

can be designed to apply to studies in these geographic

locations. Such studies may be important for resolving

the ongoing debate over the systematic status of these

two species (Gosling, 1984; Gardner, 1992; McDonald et

al., 1991).

ACKNOWLEDGMENTS

We thank J. Rosenthal for suggesting site-directed mu-

tagenesis. We also thank Dr. M.G. Harasewych for in-

viting JBG to participate in the 11'* International Mal-

acology Congress symposium on Molecular Techniques

and Molluscan Phylogeny. This work was supported by

a fellowship by the National Science Foundation, Divi-

sion of Ocean Sciences to JBG.

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THE NAUTILUS, Supplement 2

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THE NAUTILUS, Supplement 2:145-155, 1994

Page 145

Morphological and Genetic Variation in Greek Populations of

the Edible Snail Helix aspersa Miller, 1774

(Gastropoda, Pulmonata): A Preliminary Survey

Maria Lazaridou-Dimitriadou

Y. Karakousis

A. Staikou

Departments of Zoology and Genetics

School of Biology

Faculty of Sciences

Aristotle University of Thessaloniki

54006 Thessaloniki, Macedonia

Greece

ABSTRACT

For the study of genetic and phenotypic variation in allopatric

populations of the edible snail Helix aspersa, samples were

collected (20-40 adult animals/sample) from 24 different regions

on the mainland and the islands of Greece as well as Cyprus.

The morphometric data of the shell were analyzed using

principal component analysis (PCA). A dendrogram was con-

structed using UPGMA cluster analysis, based on the Mahalano-

bis distance between the morphometric parameters of all the

populations examined. It showed that the populations from the

regions of Peloponesos, the eastern mainland of Greece, Iraklion

(island of Crete), and the islands Hios and Cyprus constitute a

separate group from the western part of the mainland of Greece

and the islands of Crete and Paros.

No relationship was found between altitude and size (D +

W) of the animals.

A correlation existed between the size (H/D) of the animals

and precipitation (r = 0.6, P < 0.001) and between D and the

mean minimum annual monthly temperatures (r = 0.4, P <

0.001).

All the populations examined at the isoenzymic level were

found to be polymorphic. Three of the examined loci (a GPDH,

PMI, SOD) were found to be monomorphic in all populations

examined.

The percentage of polymorphic loci (P) ranged from 33.3 to

66.7% and the mean heterozygosity from 0.152 to 0.254.

Two alleles GPD-1B and LAP-1D were found in high fre-

quency in Western Greece but they were absent or in very low

frequency in Eastern Greece and the islands.

Key words: Polymorphism, allozymes, Helix aspersa.

INTRODUCTION

Helix aspersa Miiller, 1774, a terrestrial gastropod with

probable origin in the western Mediterranean (Sacchi,

1958) and widely introduced by man to continents (West

Europe and North America) and islands of the temperate

and tropical zones (Pilsbry, 1939), is one of the more

successful colonizing snails. H. aspersa’s adaptability is

accompanied by an intraspecific variability concerning

the polymorphism of the shell, its reproductive system,

and its biological cycle (Selander & Kaufman, 1975;

Chevallier, 1977; Crook, 1982; Madec & Daguzan, 1987;

Madec, 1989; Albuquerque de Matos, 1989; Bleakney et

al., 1989).

A visible polymorphism in shell size was found in H.

aspersa (Lazaridou-Dimitriadou et al., 1983) among

populations from two geographical regions of Greece,

the island of Crete and Peloponesos. This polymorphism

seemed to be related either to differences in the duration

of the drought period in the two regions and/or to genetic

differentiation. The aim of this study was to determine

whether there is intra- and interpopulation variation in

morphology and isoenzymes, and to discover the possible

correlation between the climatic factors and variation of

H. aspersa in Greece. Additionally, knowing that shell

size can have a genetic component in helicid and other

snails (Cook, 1965; Baur, 1984; Goodfriend, 1986), we

tried to determine if the morphological differentiation

of populations coming from the islands of Crete and

Peloponesos also manifests itself in biochemical poly-

morphism. If this is so, we have an apparent case of

White's “geographical races” (White, 1978) and the ex-

istence of two forms, H. aspersa aspersa and H. aspersa

major (Chevallier, 1977).

METHODS AND MATERIALS

Sampling: We sampled 24 populations of H. aspersa,

totalling 805 adult individuals (3 populations from the

northwestern part of Greece, 5 from Central Greece, 7

from Peloponesos, 8 from the Aegean islands and one

See ee

Page 146

{ ‘alimni

Kleion

andatfos — ile1

CRETE \

yim.

Figure 1. Sites of samples in Greece and Cyprus.

from Cyprus island) (average sample size per population

= 80) (figure 1).

In each sample, the specimens were taken in an area

of approximately 400 m?. The meteorological data were

obtained from the Data Department of National Mete-

orological Institute of Greece.

Living specimens were brought to the laboratory in

carton boxes, where they were aestivating.

Morphometric data: Morphometric and qualitative data

of the shell were taken immediately before electropho-

retic analysis.

The snails were weighed (W) and individually marked

on the shell. Maximum shell diameter (D), aperture di-

ameter (di), shell height (H) and shell thickness (T), were

measured with a digital calliper to the nearest of 0.01

mm. The aperture area (Ap) was copied on tracing paper

and measured with a planimeter. The color was recorded

according to Albuquerque de Matos’ system (1984) and

Table 1. Electrophoretic conditions and enzymes analyzed.

THE NAUTILUS, Supplement 2

number and fusion of bands was also noted. Four classes

existed for colour (yellow, brown, red, white), six for the

number of bands (0, 1, 2, 3, 4, 5) and 13 for the fusion

of bands (observed combination of fusion of the existing

bands).

Electrophoresis: For the assessment of the genetic poly-

morphism, 13 enzymatic systems were investigated using

starch gel electrophoresis. These enzymatic systems cor-

respond to 15 genetic loci. Buffers and tissues used are

shown in table 1. The alleles were named (A-E) from

greater to less mobility. Several esterase loci were present,

but only two loci with zymograms interpretable in Men-

delian terms were used.

The samples for the electrophoretic analysis were pre-

pared from the foot muscle and hepatopancreas (table

1) (after the complete removal of the intestine and wash-

ing in distilled water in order to remove any parasites

(Haralambidis et al., 1985). Organs were then finely cut

and homogenized in equal volume of 0.1 N CaCl,-1.7%

sucrose and stored at —20 °C for up to 15 days.

Statistical analysis: In order to look for geographical

variation, the morphometric and qualitative data of the

shells were subjected to principal component analysis

(PCA) using the Statview computer program for Mac-

intosh. The principal component analyses (PCA) were

done using either the morphometric characters or their

ratios (because H was highly correlated with D, di with

D, di with H and Ap with D): the maximum shell di-

ameter (D), the weight (W), the thickness of the shell

(T) and the ratios of height/maximum shell diameter

(H/D), of (di)/D, of di/H, and of D/Ap. Transforma-

tions to natural logarithms were used for D, W, T and

arcsin transformations for the ratios. To compare the

scores of the first 3 factors of the PCA, ANOVA test was

also made using Statview computer program for Mac-

intosh.

To determine relationships, the morphometric vari-

ables were correlated with the climatic data. Transfor-

mations to standard scores were used for the climatic

Enzyme Abbrev.

Aspartate aminotransferase AAT

Esterase EST

Esterase D ESD

a-Glycerophosphate dehydrogenase aGPDH

Glucosephosphate isomerase GPI

Isocitrate dehydrogenase IDH

Lactate dehydrogenase LDH

Leucine aminopeptidase LAP

Malate dehydrogenase MDH

Phosphomannose isomerase PMI

6-phosphogluconate dehydrogenase GPD

Phosphoglucomutase PGM

Superoxide dismutase SOD

E.C. no. Locus Tissue Buffer

2.6.1.1. 1 Hep. A

8.1.1. 2 Hep. B

3.1.1. 1 Hep. A

NI. 1 Foot A

5.3.1.9. 1 Hep. C

1.1.1.42. 1 Foot A

NodL PA 1 Hep. B

8.4.11. 1 Hep. C

1.1.1.37. a Hep. A

5.3.1.8. a Hep. C

1.1.1.49. ] Foot A

DUD llo 2 Hep. C

1.15.11. 1 Hep. B

A =0.13M Tris, 0.04 M citric acid, 0.018 M EDTA, pH =7.1 for gel buffer; 0.13 M Tris, 0.037 M Citric acid, 0.001 M EDTA,

pH =7.1 electr. buffer. B = Ashton et al. (1961). C = Smith (1976).

M. Lazaridou-Dimitriadou et al., 1994

Page 147

Table 2. The mean yearly meteorological data over 10 years (1980-1990). T = mean maximum annual monthly temperature,

Tmi = mean minimum annual monthly temperature, Tmax = maximum annual monthly temperature, Tmin = minimum annual

monthly temperature, Prec. = total annual precipitation in mm. Mean annual drought duration in days (estimated from the drought

period of the ombrothermic curve of each region from 1986 to 1990).

Localities (°C) Tmi Tmax

Igoumenitsa 26.98 9.32 37.32

Igoumen.—2 26.98 9.32 37.32

Preveza 25.72 8.66 35.2

Mesolongi 27.98 9.07 37.21

Nafpaktos 28.85 9.85 37.88

Athens 27.98 9.07 37.21

Halkida 28.21 8.39 39.9

Karystos 27.03 9.66 39.35

Lamia 25.86 6.08 40.08

Kam. Vourla 25.86 6.08 40.08

Paros 25.09 10.3 35.57

Kiato 27.76 8.01 39.01

Nafplio 26.85 8.33 88.43

Glykovrysi 7M 9.84 38.4

Karavas 28.88 8.88 41.38

Kyparissia 25.61 10.14 85.14

Zaharo 26.63 8.96 38.13

Karytaina 24.9 4.55 89.28

Kandanos 28.25 11.94 89.53

Tympaki 26.21 10.63 39.91

Siteia 25.82 11.16 35.13

Irakleio 26.12 11.02 86.33

Hios 26.56 8.98 36.1

Cyprus 28.3 10.1 39.5

data. The meteorological data, namely total annual pre-

cipitation (P) in mm, absolute maximum annual monthly

temperatures (Tmax), absolute minimum annual month-

ly temperatures (Tmin), mean maximum annual month-

ly temperatures (T), mean minimum annual monthly

temperatures (Tmi), were obtained from the Data De-

partment of National Meterological Institute of Greece

(table 2). The mean number of days of monthly drought

period (Dr) and the mean number of days of monthly

rainfall > 100 mm (Mr) were calculated from the om-

brothermic yearly curves.

Seven morphometric variables were used for the Ma-

halanobis distance. UPGMA cluster analysis (Sneath &

Sokal, 1963) was performed on the basis of Mahalanobis

distances (1936) using the morphometric data for the 24

populations.

Observed or expected heterozygosity, proportion of

polymorphic loci for each population, mean alleles per

locus, genetic distances (Nei, 1978) and F-statistics

(Wright, 1978) between populations were calculated us-

ing BIOSYS-1 (Swofford & Selander, 1981).

To investigate the genetic relationship among the ex-

amined populations, a dendrogram based on allelic fre-

quencies, using the complete linkage method based on

Nei’s genetic distance and a WAGNER tree, were con-

structed with the aid of BIOSYS-1 computer program.

To compare the degree of differentiation within and

between populations, hierarchical F-statistics analysis

Drought duration

Tmin Prec. (mm) (in days)

—2.35 975 120

0.036 850 153

—0.29 378 270

—2.53 726 129

—0.29 373 114

—1.92 376 207

0.59 666 198

— 597. 162

— 597 162

1.3 423 207

—0.61 476 165

=I] 527 150

—0.28 836. 180

= IL! 915 162

0.23 762 156

—3.23 896 156

—10.12 788 126

3.78 311 243

1.43 514 192

3.23 520 171

2.5 505 150

—1.5 O22 203

7.65 3851 210

(Wright, 1978) was performed using BIOSYS-1 computer

program.

Number of alleles per locus, the percentage of poly-

morphic loci, the observed (Ho) and expected hetero-

zygosity (He), and allele frequencies were each corre-

lated with the climatic characteristics of each region.

A correlation analysis was performed between the Nei’s

genetic distance and the Mahalanobis distance.

RESULTS

I. MORPHOLOGICAL POLYMORPHISM

Interpopulational size variation was conspicuous. The

mean size of the largest population was statistically dif-

ferent (P < 0.01), nearly % to %4 larger than the mean

size of the smallest population. On the other hand, size

variation within populations was far less conspicuous (ta-

ble 3).

Shells were usually brown-yellowish, and, in most cases,

with 5 dark bands, apart from those from Preveza. Some

populations had less than 5 bands (3-14%), while in the

majority of populations some of the bands were fused.

The first (D + W) (size component) and the second

factor (H/D) (elevation component) of PC analysis dis-

tinguished Siteia, Hios, Cyprus and the regions of Pe-

loponesos, Kamena Vourla, Lamia, Halkida, Paros and

Irakleio as separate groups (table 4, figure 2), but ANO-

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Page 148

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‘IajoWIeIp ysos1e [[EYs :q 9104 M ‘snidAD pue 909015) wWoI] Dsuadsp xYaH jo sojdures oatjeyuasoidai FZ oY] Ul s1oxOeLEYO [[9Ys polpnjs ay} Jo s1O1I9 prepueys F sues “E 2[qUL,

M. Lazaridou-Dimitriadou et al., 1994

Page 149

Table 4. Measures of Variable Sampling Adequacy in Prin-

cipal Component analysis (Total matrix sampling adequacy:

0.495) and the eigenvalues and proportion of original variance

in PCA using only morphometric parameters after logarithmic

transformation.

Variance

Variable Adeq. Factor Magnitude proportion

H 0.258 ] 1.929 0.321

D 0.179 2 1.503 0.251

W 0.384 3 1.436 0.239

T 0.173 4 1.123 0.187

di 0.149 5 0.005 0.001

Ap 0.156

Bartlett Test of Sphericity—DF: 20, Chi Square = 7470.749,

P < 0.0001.

VA and Fischer LSD tests on the first three factors of

PCA showed statistically significant differences (P < 0.01)

only in the size of the snails between the populations

from Peloponesos and that from Siteia.

The dendrogram of UPGMA cluster analysis based on

Mahalanobis’ distances (figure 3) was consistent with PCA

results: the populations from the regions of Peloponesos

and Hios, Irakleio in Crete and Cyprus island and regions

from the SE Greece (Kamena Vourla, Lamia, Halkida)

constitute a separate group from Crete, NW regions of

Greece and Athens, Paros island and Karystos (Evia is-

land).

A correlation was found between the shell thickness,

the H/D and the annual precipitation (r = —0.365, P

< 0.01; r = 0.632, P < 0.001, respectively), between D,

the aperture area and the mean minimum annual month-

ly temperatures (r = —0.422, P < 0.001; r = —0.509, P

< 0.001, respectively).

IJ. BlIocHEMICAL POLYMORPHISM

A high degree of genetic variation was found in all pop-

ulations examined. Three loci (AGP, PMI, SOD) were

monomorphic in all populations examined, while the

remaining loci had up to 5 alleles (LAP-1 and EST-2)

(table 5).

The percentage of polymorphic loci ranged from 33.3

to 66.7% and the mean expected heterozygosity per locus

from 0.152 to 0.254.

Two alleles, GPD-1B and LAP-1D, were found in high

frequency in western Greece but were absent or occurred

in very low frequency in Eastern Greece and the islands.

A unique allele in high frequency in the locus PGM-2

was found in the population of Karytaina.

Coefficients of genetic identity and distance (Nei, 1978)

were calculated for all pairwise combinations of the 24

populations studied.

The mean values of genetic distance (D) between all

populations was 0.038 + 0.002 (N = 276) and ranged

from 0.001 to 0.131. Estimates of Hierarchical F statistics

analysis are shown in table 3. There is considerable dif-

Nafplio Ae

@ Kyparissia

Igoum.-2 °

Timpaki yeaa ZNO

Kandanos

Karistos

v Athens

o Igoum.-!

Siteia o

Nafpaktos

Factor 2 (Elevation) (26.2%)

-5

Factor 1 (Size) (36.5%)

Figure 2. Distribution of populations on Factor J and II scores

of principal component analysis based on morphometric data

of the shell characteristics in Helix aspersa.

ferentiation at all levels, but the significant point is that

the variance among populations of blocks within demes

(FDR) was greater than that between regions and the

total (Frs, FrtT) (table 6). It must be pointed out that

GPD had greater values of differentiation in the higher

levels (table 6). Average genetic distances within regions

used in hierarchical F statistics analysis are shown in

table 7. It is obvious that populations coming from north-

western Greece showed a degree of genetic distance from

the rest of the populations. This is also shown by a den-

drogram constructed using complete linkage method and

by the WAGNER tree (figures 4, 5).

To determine whether climatic parameters were cor-

related with allozymic variation, five climatic variables

were chosen, namely total annual precipitation (P), mean

maximum annual monthly temperatures (T), absolute

maximum annual monthly temperatures (Tmax), mean

annual drought period in days (DR) (from the ombro-

thermic curves) and mean annual rainfall duration >

ISLAND HIOS

CRETE IRAKLEION

ISLAND CYPRUS

KYPARISSIA

res] ZAHARO

NAFPLIO

E.GREECE LAMIA

PELOPON. GLYKOVRYSI

E-GREECE HALKIDA

KARYTAINA

moro] KARAVAS

KIATO

E.GREECE KAMEN.V.

eae [pene ee

TYMPAKI

IGOUM.-1

W. GREECE Ee

MESOLOGI

NAYPAKTOS -

ISLAND PAROS

E.GREECE ATHENS

ISLAND KARYSTOS

W. GREECE JGOUM.-.2

CRETE SITEIA

Figure 3. UPGMA cluster analysis based on Mahalanobis dis-

tances between 24 populations of Helix aspersa using morpho-

metric data.

Page 150 THE NAUTILUS, Supplement 2

Table 5. Allele frequencies at twelve enzymatic loci in 24 populations of Helix aspersa from Greece and Cyprus.

Locus Alleles Igoum. Igoum.—2 Preveza Mesol. Nafpak. Athens Halk. Karyst

AAT-1 A 1.000 1.000 1.000 1.000 1.000 1.000 0.944 1.000

B 0.000 0.000 0.000 0.000 0.000 0.000 0.056 0.000

EST-D A 0.125 0.250 0.319 0.569 0.653 0.708 0.681 0.444

B 0.083 0.208 0.306 0.306 0.208 0.236 0.236 0.444

C 0.417 0.250 0.181 0.014 0.042 0.056 0.056 0.042

D 0.375 0.292 0.194 0.111 0.097 0.000 0.028 0.069

EST-1 A 0.986 0.958 0.972 0.958 0.931 0.847 0.931 0.694

B 0.014 0.042 0.014 0.042 0.042 0.125 0.069 0.167

C 0.000 0.000 0.014 0.000 0.028 0.028 0.000 0.139

D 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

EST-2 A 0.189 0.347 0.236 0.333 0.347 0.236 0.208 0.083

B 0.444 0.319 0.222 0.347 0.347 0.222 0.306 0.333

C 0.194 0.222 0.389 0.189 0.069 0.194 0.194 0.375

D 0.139 0.083 0.153 0.125 0.194 0.167 0.278 0.167

E 0.083 0.028 0.000 0.056 0.042 0.181 0.014 0.042

GPD-1 A 0.167 0.153 0.264 1.000 1.000 0.986 1.000 1.000

B 0.653 0.833 0.639 0.000 0.000 0.014 0.000 0.000

C 0.181 0.014 0.097 0.000 0.000 0.000 0.000 0.000

IDH-1 A 1.000 1.000 1.000 1.000 0.875 1.000 1.000 1.000

B 0.000 0.000 0.000 0.000 0.125 0.000 0.000 0.000

C 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

LAP-1 A 0.417 0.403 0.375 0.917 0.708 0.458 0.611 0.958

B 0.000 0.000 0.014 0.056 0.028 0.153 0.167 0.000

C 0.097 0.089 0.056 0.028 0.125 0.292 0.111 0.028

D 0.403 0.375 0.472 0.000 0.139 0.042 0.000 0.014

E 0.083 0.153 0.083 0.000 0.000 0.056 0.111 0.000

LDH-1 A 0.972 1.000 0.847 0.931 0.944 0.944 0.861 0.917

B 0.028 0.000 0.153 0.069 0.056 0.056 0.139 0.083

C 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

D 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

MDH-1 A 0.347 0.417 0.375 0.441 0.529 0.542 0.403 0.444

B 0.333 0.306 0.278 0.441 0.265 0.208 0.375 0.319

C 0.264 0.014 0.236 0.029 0.088 0.056 0.125 0.125

D 0.056 0.264 0.111 0.088 0.118 0.194 0.097 0.111

PGM-1 A 0.889 0.958 0.986 0.944 0.944 0.931 0.917 0.972

B 0.056 0.028 0.000 0.028 0.056 0.056 0.000 0.028

C 0.056 0.014 0.014 0.028 0.000 0.014 0.083 0.000

PGM-2 A 0.889 0.944 0.958 0.972 0.972 1.000 0.819 0.917

B 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

C 0.111 0.056 0.028 0.028 0.028 0.000 0.167 0.083

D 0.000 0.000 0.014 0.000 0.000 0.000 0.014 0.000

PGI-1 A 0.986 0.944 0.986 0.931 0.931 0.889 0.917 1.000

B 0.000 0.028 0.000 0.069 0.000 0.000 0.000 0.000

C 0.000 0.000 0.014 0.000 0.042 0.028 0.042 0.000

D 0.014 0.028 0.000 0.000 0.028 0.083 0.042 0.000

N 36 36 36 36 36 36 36 36

Percent. 66.67 60.00 66.67 60.00 66.67 60.00 66.67 53.33

H .253 + .079 .233 + .079 .254+ .082 173+ .065 .208+ 065 .221 + 073 .240+ .068 .196 + .071

100 mm. Results showed that mean observed heterozy- DISCUSSION

gosity was negatively correlated with drought duration

(r = —0.419, P < 0.05). Individual alleles also gave

significant correlations with P at the level of P < 0.01

(EST-DA (r = —0.647), EST-DC (r = 0.581), EST-DD

(r = 0.797), GPD-1A (x = —0.753), GPD-1B (r = 0.762),

LAP-1B (r = —0.506), LAP-1D (r = 0.505), and as for

drought LAP-1A (r = 0.498)).

The study of shell morphometric characteristics of Helix

aspersa showed an interpopulation variation, but not any

trend in geographic variations of the seven variable char-

acters studied jointly. However, there seemed to exist a

noticeable cline in some of the characters such as the

thickness of the shell, peristome diameter, maximum

M. Lazaridou-Dimitriadou et al., 1994 Page 151

Table 5. Extended.

Lamia K. Vour Paros Kiato Nafplio Glykoy. Karavas Kyparis. Zaharo

1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.625 0.833 0.347 0.444 0.694 0.389 0.306 0.319 0.333

0.250 0.069 0.611 0.486 0.208 0.236 0.042 0.069 0.193

0.028 0.083 0.000 0.000 0.000 0.208 0.431 0.389 0.283

0.097 0.014 0.042 0.069 0.097 0.167 0.222 0.222 0.200

0.833 0.861 0.667 0.806 0.875 0.986 0.972 0.875 0.967

0.097 0.069 0.292 0.181 0.028 0.000 0.000 0.083 0.0383

0.069 0.028 0.042 0.000 0.042 0.014 0.028 0.042 0.000

0.000 0.042 0.000 0.014 0.056 0.000 0.000 0.000 0.000

0.347 0.181 0.222 0.264 0.181 0.514 0.689 0.208 0.333

0.222 0.417 0.458 0.264 0.292 0.264 0.028 0.278 0.300

0.250 0.153 0.167 0.222 0.292 0.069 0.111 0.319 0.150

0.167 0.222 0.125 0.069 0.181 0.111 0.111 0.181 0.217

0.014 0.028 0.028 0.181 0.056 0.042 0.111 0.014 0.000

1.000 0.917 0.986 1.000 1.000 0.569 0.792 0.944 0.550

0.000 0.042 0.014 0.000 0.000 0.431 0.208 0.056 0.450

0.000 0.042 0.000 0.000 0.000 0.000 0.000 0.000 0.000

1.000 1.000 0.972 0.986 0.972 0.958 1.000 1.000 1.000

0.000 0.000 0.028 0.014 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.000 0.000 0.028 0.042 0.000 0.000 0.000

0.653 0.639 0.903 0.875 0.708 0.917 0.944 0.708 0.817

0.111 0.083 0.000 0.014 0.042 0.042 0.000 0.000 0.000

0.139 0.194 0.069 0.097 0.189 0.000 0.042 0.292 0.183

0.014 0.028 0.028 0.014 0.083 0.000 0.000 0.000 0.000

0.083 0.056 0.000 0.000 0.028 0.042 0.014 0.000 0.000

0.875 0.931 0.931 0.917 0.903 0.972 0.972 0.986 0.983

0.125 0.069 0.028 0.083 0.097 0.028 0.028 0.014 0.017

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.000 0.042 0.000 0.000 0.000 0.000 0.000 0.000

0.389 0.333 0.625 0.403 0.333 0.319 0.194 0.389 0.333

0.431 0.417 0.208 0.389 0.403 0.264 0.444 0.236 0.417

0.111 0.167 0.056 0.083 0.139 0.361 0.097 0.167 0.183

0.069 0.083 0.111 0.125 0.125 0.056 0.264 0.208 0.067

0.931 0.819 0.944 0.917 0.917 0.889 0.931 0.889 0.967

0.056 0.139 0.056 0.083 0.028 0.111 0.056 0.083 0.000

0.014 0.042 0.000 0.000 0.056 0.000 0.014 0.028 0.033

1.000 0.889 1.000 1.000 0.889 1.000 0.972 0.972 1.000

0.000 0.028 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.083 0.000 0.000 0.111 0.000 0.028 0.028 0.000

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.972 0.889 0.917 0.944 0.944 0.944 0.903 0.903 0.967

0.000 0.083 0.000 0.000 0.000 0.000 0.000 0.000 0.000

0.000 0.028 0.069 0.014 0.056 0.056 0.097 0.097 0.000

0.028 0.000 0.014 0.042 0.000 0.000 0.000 0.000 0.033

36 36 36 36 36 36 36 36 30

53.33 66.67 66.67 60.00 66.67 66.67 66.67 66.67 60.00

213+ .071 .236+.064 194+ .063 .202+.069 .233+ .067 .215+.073 .190+.065 .227+ .074 .214 + .077

shell diameter and the ratio H/D along a gradient in

climatic conditions. The thickness of the shell was pos-

itively correlated with low precipitation as also shown

by Bar (1978) in Theba pisana, and the height of the

shell with high precipitation as mentioned by Goodfriend

(1986). In our case it seemed that aperture area and the

maximum shell diameter were negatively related to the

absolute minimum annual monthly temperature, sug-

gesting that larger snails survive better in colder condi-

tions, and that conditions of the environment might select

for size in land snails through differential mortality

(Goodfriend, 1986).

Additionally, a great variability between populations

was found at the biochemical level. However, there did

not exist any correlation between Mahalanobis and Nei’s

genetic distance of the 24 populations studied, and the

Page 152

Table 5. Extended.

THE NAUTILUS, Supplement 2

Locus Alleles Karyt. Kand Tympaki

AAT-1 A 1.000 1.000 1.000

B 0.000 0.000 0.000

EST-D A 0.222 0.681 0.792

B 0.222 0.083 0.028

C 0.431 0.194 0.097

D 0.125 0.042 0.083

EST-1 A 0.958 0.847 0.764

B 0.014 0.111 0.194

C 0.014 0.028 0.028

D 0.014 0.014 0.014

EST-2 A 0.611 0.444 0.458

B 0.042 0.181 0.125

C 0.028 0.083 0.083

D 0.181 0.139 0.333

E 0.139 0.153 0.000

GPD-1 A 1.000 1.000 1.000

B 0.000 0.000 0.000

C 0.000 0.000 0.000

IDH-1 A 1.000 1.000 1.000

B 0.000 0.000 0.000

C 0.000 0.000 0.000

LAP-1 A 0.861 0.708 0.500

B 0.000 0.083 0.043

C 0.139 0.125 0.186

D 0.000 0.028 0.086

E 0.000 0.056 0.186

LDH-1 A 1.000 0.667 0.889

B 0.000 0.333 0.111

C 0.000 0.000 0.000

D 0.000 0.000 0.000

MDH-1 A 0.338 0.472 0.333

B 0.250 0.222 0.431

C 0.294 0.153 0.181

D 0.118 0.153 0.056

PGM-1 A 0.838 0.917 0.917

B 0.167 0.083 0.056

C 0.000 0.000 0.028

PGM-2 A 0.278 1.000 0.972

B 0.500 0.000 0.000

C 0.000 0.000 0.000

D 0.222 0.000 0.028

PGI-1 A 1.000 0.833 0.958

B 0.000 0.042 0.000

C 0.000 0.069 0.028

D 0.000 0.056 0.014

N 36 36 36

Percent. 46.67 53.33 60.00

H .217 + .076 .238 + .07 .218 + .069

Siteia Hios Cypru Iraklei

1.000 1.000 1.000 1.000

0.000 0.000 0.000 0.000

0.552 0.450 0.371 0.743

0.086 0.450 0.143 0.186

0.224 0.075 0.357 0.071

0.138 0.025 0.129 0.000

0.879 0.525 1.000 1.000

0.086 0.150 0.000 0.000

0.034 0.325 0.000 0.000

0.000 0.000 0.000 0.000

0.362 0.400 0.329 0.671

0.121 0.300 0.186 0.014

0.190 0.000 0.114 0.271

0.103 0.100 0.329 0.043

0.224 0.200 0.043 0.000

0.966 0.875 1.000 0.929

0.000 0.125 0.000 0.000

0.034 0.000 0.000 0.071

1.000 0.850 1.000 1.000

0.000 0.150 0.000 0.000

0.000 0.000 0.000 0.000

0.776 0.825 0.957 0.586

0.017 0.000 0.000 0.029

0.052 0.175 0.000 0.343

0.052 0.000 0.043 0.043

0.103 0.000 0.000 0.000

0.948 1.000 1.000 1.000

0.052 0.000 0.000 0.000

0.000 0.000 0.000 0.000

0.207 0.275 0.257 0.300

0.379 0.275 0.243 0.300

0.328 0.375 0.329 0.057

0.086 0.075 0.171 0.343

0.897 1.000 0.986 1.000

0.103 0.000 0.000 0.000

0.000 0.000 0.014 0.000

1.000 1.000 0.971 1.000

0.000 0.000 0.000 0.000

0.000 0.000 0.029 0.000

0.000 0.000 0.000 0.000

0.966 1.000 0.986 0.000

0.017 0.000 0.000 0.000

0.000 0.000 0.014 0.000

0.017 0.000 0.000 0.000

29 20 35 35

60.00 46.67 46.67 33.33

.210 + .072 BP y-A0 eatin OF 6 .160 + .077 .152 + .064

degree of heterozygosity and the coefficient of variation

of the maximum shell diameter (D), shell height (H),

and shell thickness (T). The inconsistency between

UPGMA cluster analysis based on the Mahalanobis dis-

tances and the dendrogram found by cluster analysis of

complete linkage method using Nei’s identity, could be

the result of a size effect. If size correction is not used,

it seems that intracluster size variation masks intercluster

variation (Lazaridou-Dimitriadou et al., in press).

A unique allele (PGM-2B) that was found only in Kary-

taina’s population in high frequency may be due either

to founder effect or to altitude. A similar report for locus

PGM2 in Spanish C. nemoralis (Mazon et al., 1988) at-

tributed this to altitude. Since Karytaina is the only lo-

cality that had 555 m elevation, altitude may be the

causal factor in H. aspersa.

The fact that two alleles, GPD-1B and LAP-1D, were

found in high frequencies in Western Greece may be

M. Lazaridou-Dimitriadou et al., 1994 Page 153

Table 6. Wright’s hierarchical analysis between demes (D), subdivisions (S), and the total area (T).

AAT —0.004 —0.009 —0.010 —0.005 —0.006 —0.001

EST-D —0.004 —0.009 —0.010 —0.005 — 0.006 —0.001

EST-1 0.081 0.059 0.047 —0.024 — 0.037 —0.013

EST-2 0.027 0.011 0.009 —0.016 —0.018 —0.002

GPD 0.074 0.014 0.383 —0.065 0.333 0.374

IDH 0.065 0.018 0.016 —0.050 —0.053 —0.002

LAP-1 0.029 0.014 0.076 —0.015 0.048 0.062

LDH 0.021 0.005 —0.001 —0.017 —0.023 — 0.006

MDH 0.008 0.008 —0.001 —0.005 —0.009 —0.004

PGI — 0.006 —0.006 —0.005 —0.000 0.000 0.000

PGM-1 —0.003 0.001 — 0.002 0.004 0.001 —0.003

PGM-2 —0.045 — 0.037 — 0.052 0.008 — 0.007 —0.014

Total 0.044 0.017 0.058 —0,028 0.010 0.037

related to climatic factors (e.g., precipitation). Since their

frequencies were found to be significantly correlated to

mean annual precipitation, selective forces may be acting

on those alleles. However, a positive correlation between

the geographic distance of the continental populations

and the Nei’s genetic distance was found, and stochastic

processes cannot be excluded. Madec (1991) also reported

a similar change in two loci (MDH-1, PGM-s) from one

locality to the other. The same phenomenon has been

observed for C. nemoralis (Johnson, 1976) and H. aspersa

(Selander & Ochman, 1983).

The results of hierarchical F statistics showed that

heterogeneity is considerable at the intrapopulation level

as also reported by Selander and Ochman (1983) for H.

aspersa in California. However, the heterogeneity of Fpr

does not seem to support random genetic drift as the

cause for the genetic differentiation between localities.

1 97 93 % 8, 83 38

KAMEN. V

E.GREECE] HALKIDA

NAFPLIO

LAMIA

W. GREECE NAFPAKTO:

E.GREECE ATHENS

TYMPAKI

CRETE KANDANOS

IRAKLEION

KARAVAS

Peraroy as

ZAHARO

KYPARISSI

CRETE SITEIA

CYPRUS

ASTANDS [pee

KARYSTOS

PELOPON. KIATO

W, GREECE MESOLOGI

ISLAND HIOS

PELOPON. KARYTAIN.

PREVEZA

W, GREECE oun

IGOUM.-1

Figure 4. Cluster analysis of complete linkage method using

Nei’s genetic identity between populations of Helix aspersa.

This result is in accordance with the findings of Mazon

et al. (1988) in C. nemoralis.

The dendrogram found by cluster analysis of complete

linkage method using Nei’s identity (figure 4) showed

that there was not a considerable distance among the

populations studied, apart from the group of northwest-

ern Greek populations (I = 0.88). This slight differenti-

ation may be due to their geographical distance or to

KAM. VOURLA

ATHENS

KANDANOS

PAROS

ree KARYSTOS

HIOS

KIATO

NAFPAKTOS

NAFPLIO

TYMPAKI

IRAKLEION

GLYKOVRYSI

PREVEZA

IGOUMENITSA-1

IGOUMENITSA-2

ZAHARO

KYPARISSIA

KARYTAINA

CYPRUS

SITEIA

Figure 5. Distance—WAGNER’s tree based on allelic fre-

quencies of 24 populations of Helix aspersa.

Page 154

Table 7. Average genetic distance within regions.

THE NAUTILUS, Supplement 2

No. of

Regions population 1

1. N. Western Greece i) 0.010

2. Central Greece 7 0.084

3. Peloponessos 7 0.071

4, Aegean Islands 2 0.093

o, Grete 4 0.088

6. Cyprus 1 0.079

climatic reasons, if we take into account that two of their

alleles whose frequencies were high in that region (GPD-

1B, LAP-1D), were correlated positively with mean an-

nual precipitation. Such correlations might arise simply

by chance in such a restricted geographical survey, and

a larger number of independent correlations with the

same climatic variable is needed to test a real association.

However, climatic selection, at least in some cases, may

be involved in the genetic divergence of populations.

Since the island populations were not characterized

by a lower degree of heterozygosity and a higher degree

of genetic distance from the continental populations, sto-

chastic forces (e.g., founder effect followed to genetic

drift) were not the only ones to play an important role

in the genetic structuring. Rather, it seems that a com-

bination of forces is responsible for genetic differentia-

tion. Being edible, this species has been introduced by

man to many islands in a random way; its populations

on an island may either originate from a small sample

coming from any region, or may have evolved from the

introgression of the introduced and the preexisting pop-

ulations.

The genetic distance found between the populations

of the regions from northwestern Greece and the rest of

the populations was not as high as that found by Madec

(1991) between French and Algerian populations of He-

lix aspersa. On the basis of our results we cannot support

the presence of two geographical races. The northwest-

ern Greek populations comprised a separate group (fig-

ure 5), but populations from Crete and Peloponesos, which

we expected to be genetically different, were not.

ACKNOWLEDGMENTS

We thank S. E. R. Bailey (University of Manchester, UK)

for reading this paper. Thanks are also due to D. Sioula,

E. Alpogianni and N. Kifonidis for their technical help.

Financial support was provided by the Minister of Re-

search and Technology in Greece.

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THE NAUTILUS, Supplement 2:156-167, 1994

Application of Isoelectric Focusing in Molluscan Systematics

Thierry Backeljau’

Karin Breugelmans”

Herwig Leirs”

Teresa Rodriguez®

Dimitri Sherbakov*

1 Royal Belgian Institute of Natural

Sciences

Vautierstraat 29

Tatyana Sitnikova‘

Jean-Marie Timmermans!

Jackie L. Van Goethem!

Erik Verheyen!

3 Department of Animal Biology

Faculty of Biology

University of Santiago de Compostela

E-15706 Santiago de Compostela,

Page 156

B-1040 Brussels, Belgium Spain

2 University of Antwerp (RUCA)

Department of Biology Evolutionary

Biology Group

Groenenborgerlaan 171

B-2020 Antwerp, Belgium

Irkutsk, Russia

4 Limnological Institute

Siberian Division of the Russian

Academy of Science

ABSTRACT

The application of isoelectric focusing (IEF) in molluscan sys-

tematics is reviewed and illustrated using literature data and

unpublished analyses. IEF can be used as any other electro-

phoretic method, but is most appropriate for: (1) generating

complex species-specific banding profiles, (2) assessing overall

genetic similarities, (3) supplementing conventional electro-

phoretic techniques by resolving hidden protein variation and

(4) investigating minute organisms.

Key Words: Mollusca; systematics; phylogeny; population ge-

netics; protein electrophoresis; isoelectric focusing.

INTRODUCTION

Protein electrophoresis is still one of the most frequently

used molecular techniques in systematics and population

genetics. The basis for this technique is that mobility

differences of proteins in an electric field reflect changes

in their amino acid composition and thus mirror differ-

ences at the gene level. Hence, it is a simple, indirect,

way to look at gene pools.

However, as conventional electrophoretic methods only

detect mobility or molecular weight differences, they

may fail to resolve hidden protein heterogeneity caused

by amino acid replacements that are not accompanied

by substantial charge and/or molecular mass alterations

(Coyne et al., 1979; Ramshaw et al., 1979; Singh, 1979;

Ferguson, 1980).

Other separation methods such as Isoelectric Focusing

(IEF), may reduce this problem. IEF separates proteins

according to their isoelectric point (pl) (e.g., Righetti,

1983). To this end one creates a pH gradient by electro-

phoretic segregation of “carrier ampholytes’: (i.e. syn-

thetic polyaminopolycarboxylic acids) in a supporting

medium. Proteins placed in sucha pH gradient will move

according to their net charge until they reach a point

where the pH equals their pI so that their net charge

becomes zero and no further migration occurs. In this

way, IEF can separate protein fractions with pI values

differing by only 0.01 pH units (Drysdale, 1975; Righetti,

1983). Such resolution by charge is not normally obtain-

able by other electrophoretic methods and IEF is there-

fore well suited to examine hidden heterogeneity (Drys-

dale, 1975; Ross, 1977; Righetti, 1983; Cicchetti et al.,

1990).

In this paper we review the use of JEF in molluscan

systematics. We therefore provide a survey of IEF ap-

plications, after which we focus on IEF data treatment

insofar as this differs from other electrophoretic tech-

niques. For general technical accounts on the method

we refer to Righetti (1983) and Whitmore (1990a), even

though we present some basic guidelines in Appendix 1.

Authorships of the molluscan taxa mentioned are pro-

vided in Appendix 2.

REVIEW OF IEF APPLICATIONS IN

MOLLUSCAN SYSTEMATICS

Gastropoda: Pulmonata

The first applications of IEF in molluscan systematics we

could trace, were published by Saladin et al. (1976) who

used general egg proteins to distinguish between the

bulinids Bulinus liratus and B. obtusispira from Mad-

agascar. Ross (1977) studied glucose phosphate isomerase

patterns in Bulinus spp. but drew no conclusions. Sub-

sequently, Rollinson and Southgate (1979) investigated

five enzymes in 38 populations of four B. africanus group

T. Backeljau et al., 1994

Page 157

Figure 1. Agarose IEF (pH 4-6.5) of digestive gland esterases

in the Arion hortensis complex. A-D: A. distinctus (A: Bras-

schaat; B: Wilrijk; C: Hoogstraten; D: Wilrijk). E: A. hortensis

(Wilrijk).

species in Tanzania and found that B. nasutus is clearly

differentiated from the other three species. In a more

extensive survey of eight of the ten nominal species in

the B. africanus group, Wright and Rollinson (1979)

noted that certain enzyme profile combinations appeared

to be associated with some taxa and others with regional

distributions. Wright et al. (1979) found little hetero-

geneity within and between populations of B. senega-

lensis (based on five enzymes), but snails parasitized by

different trematodes were easily distinguished. Wright

and Rollinson (1981) investigated the same five enzymes

in 103 populations of the B. tropicus-truncatus complex

and found that diploid and tetraploid populations were

clearly different. These observations were used by Brown

and Rollinson (1982) and Brown et al. (1982) to char-

acterize B. truncatus in the southern part of its distri-

bution and to show that B. coulboisi from Lake Tan-

ganyika is only a southern form of B. truncatus. Similarly,

Brown et al. (1986) used IEF enzyme profiles to show

that B. guernei from West Africa is conpecific with B.

truncatus, while Southgate et al. (1985, 1989) relied on

Sg ele

= ain: ae

Wright and Rollinson’s (1979, 1981) work to demonstrate

that diploid Kenyan populations of B. tropicus can trans-

mit the fluke Schistosoma bovis and that snails parasit-

ized by different trematodes can be separated on the

basis of their IEF profiles. Rollinson and Wright (1984)

and Rollinson et al. (1990) surveyed several enzyme loci

in B. cernicus from Mauritius. Allele frequencies at these

loci showed clear spatial heterogeneities, but were re-

markably consistent over a period of six years. Finally,

Brown and Shaw (1989) and Brown et al. (1991) used

IEF of five enzymes to separate Kenyan B. tropicus, B.

truncatus and B. permembranaceus.

Backeljau (1985) conducted an IEF analysis of ester-

ases in sibling species of the Arion hortensis complex

(Figure 1). Mean intra- and interspecific band similarity

values showed that A. hortensis, A. distinctus and A.

owenii are clearly different. The same study also illus-

trated the striking difference between monomorphic IEF

profiles of uniparental species (e.g., A. intermedius) and

the highly variable profiles of allogamous species (e.g.,

A. hortensis and A. distinctus). Because of this, Backeljau

(1985) assumed that A. owenii might be a facultative

uniparental species. However, the specimens investigat-

ed were probably highly inbred for they belonged to a

captive stock derived from the original material used by

Davies (1977, 1979). Hence the lack of variation in these

profiles may have been caused by sustained inbreeding

as well. Finally, since the IEF profiles of A. owenii were

very similar to those of A. intermedius, Backeljau (1985)

suggested that the latter species belongs to the same

subgenus as A. hortensis s.]. This conclusion was further

elaborated by Backeljau and De Bruyn (1990). In a sim-

ilar way Backeljau et al. (1987) dealt with the A. fasciatus

complex (Figure 2). IEF profiles of albumen gland pro-

teins and esterases clearly separated three presumed spe-

cies: A. fasciatus, A. circumscriptus and A. silvaticus.

In contrast to A. hortensis and A. distinctus, but com-

parable to A. intermedius, A. fasciatus s.]. revealed a

remarkable “intraspecific” profile constancy (Figure 2),

even over large geographic distances. This was inter-

c) .

ae ele

Figure 2. Agarose IEF (pH 4-6.5) of digestive gland esterases in Arion circumscriptus (C) and A. silvaticus (S).

10 11 12

lie 925) Shae RS Orie eae 9

Figure 3. Detection of a cryptic species (genus Arion, subgenus

Kobeltia) by agarose IEF of albumen gland proteins in a 4-

6.5 pH gradient. 1-2: A. (K.) fagophilus (Alsasua, Spain); 3-4:

A. (K.) intermedius (8. Boeckhoute, Belgium; 4. Hamburg,

Germany); 5-6: A. (K.) distinctus (Deurne, Belgium); 7-8: un-

identified A. (K.) hortensis like species from southern France;

9-10: A. (K.) hortensis (Wilmslow, U.K.); 11-12: A. (K.) owenii

(11. Buncrana, Ireland; 12. London, U.K.).

preted as indicating uniparental reproduction and there-

fore Backeljau et al. (1987) suggested to consider A.

fasciatus s.l. as an agamospecies complex. A weight anal-

ysis suggested that the putative albumen gland protein

polymorphism in A. circumscriptus was not due to de-

velopmental differences. The limited esterase variation,

on the contrary, was assumed to be environmentally or

physiologically determined (e.g., Oxford, 1975, 1978).

Backeljau and De Winter (1987), finally, characterized

albumen gland protein profiles of two paratypes of A.

fagophilus in a qualitative IEF comparison of 10 arionid

species. This work revealed a fundamental difference in

the albumen gland proteins of the subgenera Kobeltia

and Carinarion on the one hand, and Arion and Mes-

arion on the other. A review of the use of albumen gland

proteins in arionid systematics was presented by Back-

eljau (1989). In this context, Figure 8 shows an unpub-

lished comparison of albumen gland profiles of six arion-

ids, indicating that an Arion (Kobeltia) hortensis-like

slug from southern France differs so much from three

morphologically extremely similar species (A. (K.) hor-

tensis, A. (K.) distinctus and A. (K.) owenii), that it

probably belongs to another (undescribed?) species.

In order to supplement morphological observations

Manga-Gonzalez and Rollinson (1986) surveyed five en-

zymes to differentiate seven Helicella species. Two en-

zymes, malate dehydrogenase and glucosephosphate

isomerase, were sufficient to separate all taxa.

Brito (1992) conducted a preliminary qualitative IEF

analysis of esterases in seven species of Zonitidae, rep-

resenting three genera and three subgenera. This work

showed that IEF is also useful for taxonomic purposes in

this group.

THE NAUTILUS, Supplement 2

Gastropoda: Prosobranchia

Using IEF of esterases and general proteins Sella and

Badino (1980) demonstrated that Mediterranean Patella

coerulea and P. aspera are distinct, yet closely related,

species, while P. lusitanica is very different (nomencla-

ture used by Sella & Badino, 1980).

In order to find taxon specific IEF profiles, Viyanant

et al. (1985) analyzed 12 specific enzymes in two species

and one subspecies of Bithynia in Thailand. Their work

showed that B. funiculata and B. siamensis siamensis

differ consistently in four enzymes, while the subspecies

B. siamensis siamensis and B. siamensis goniomphalos

only differ in their esterase profiles.

Unpublished preliminary IEF patterns of esterases and

general proteins of Baicalia species from Lake Baikal

(Russia) illustrate the performance of automated IEF

using PhastSystem (see Appendix 1). Figure 4 shows in-

terpopulation esterase heterogeneity in B. costata, while

Figure 5 compares esterase profiles of B. costata and B.

turriformis. Genetic variation at a monomeric, diallelic

esterase locus in this latter species is illustrated in Figure

6, while Figure 7 shows the monomorphic profiles of B.

bithyniopsis. Finally, two presumed species in the B.

herderiana complex, viz. B. ventrosula and B. herder-

iana laevis, reveal variable general protein profiles, but

little or no interspecific differentiation (Figure 8).

Qualitative IEF profiles were also used by Nyumura

and Hosokawa (1993) to separate two morphotypes of

the apple snail Pomacea canaliculata in Japan.

Mill and Grahame (1988) obtained a “reasonable” sep-

aration of the morphologically extremely similar Litto-

rina saxatilis and L. arcana after IEF of non-specific

esterases. In addition it was shown that L. saxatilis is

more variable and heterogeneous than L. arcana. Similar

results were reported by Dytham et al. (1992) and Mill

and Grahame (1992), who also observed a clinal change

in esterase variation in both periwinkles.

Bivalvia

Giinther and Hinz (1986) used IEF of amylases to sep-

arate two morphologically similar Pisidium species, viz.

P. personatum and P. nitidum. They also noted that two

alleles detected by native agarose gel electrophoresis were

not resolved by IEF. Yet, subsequently Gtinther and Hinz

(1988) remarked that IEF of amylases was superior to

agarose gel electrophoresis in differentiating 15 Pisidium

and three Sphaerium species. The same authors also an-

alyzed phosphoglucomutase with IEF and this, combined

with the amylase data, allowed them to confirm: (1) the

close relationship between P. hibernicum and the group

composed of P. henslowanum, P. supinum and P. lill-

jeborgii, (2) the close relationship between P. pulchellum

and P. subtruncatum and (8) the separate position of P.

amnicum.

Cephalopoda

Brahma and Lancieri (1979) assessed phylogenetic re-

lationships between Octopus vulgaris, Sepia officinalis

T. Backeljau et al., 1994

Page 159

A B

**@eent8e0 ©

a ae —

ee a

_ _ ae Ps

> -— BS SaiasS —_<— a>

2 € BY |e) ye) 10)

> €2a bb ) fb [ff 9

saad uy

—_— /- 2S hr, pil

| oa Bs se -

> nr na ame cee i cea — Se ee |

iii imc ala bor oa enn ila ye ‘S at ecteneAaide rial San a EM ee

Figures 4-7. Performance of PhastSystem in a preliminary IEF analysis of esterases in total body homogenates of some Baicalia

spp. from Lake Baikal. 4. Interpopulation heterogeneity in B. costata (A: Dva Brata; B: Varnachka) (pH 3-9). 5. Interspecific

differentiation between B. costata (A: Dva Brata) and B. turriformis (C: Dva Brata) (pH 4-6.5). 6. Genetic variation at a diallelic

monomeric esterase in B. turriformis (first four specimens from Dva Brata, next four from Varnachka; genotypes are indicated

above each lane) (pH 3-9). 7. Intrapopulation homogeneity of B. bithyniopsis (Bolskije Koty) (pH 3-9).

and Loligo vulgaris using IEF and immuno-IEF (= IEF

followed by an immunodiffusion test against antisera) of

eye lens proteins. Immuno-IEF showed a closer rela-

tionship between Sepia and Loligo, than between either

of these two and Octopus. “Classical” IEF, on the con-

trary was uninformative as only Octopus yielded inter-

pretable IEF profiles.

Levy et al. (1988) used IEF of general proteins of

mantle extracts to separate two sibling species of Bra-

zilian Eledone, viz. E. massyae and E. gaucha.

IEF DATA ANALYSIS

The preceding review shows that IEF data have been

used in three ways: (1) qualitatively, by seeking taxon

specific banding profiles, (2) phenetically, by calculating

band pattern similarities and (3) genetically, by inter-

preting the profiles in terms of loci, alleles and genotypes.

Figure 8. General silver staining of proteins in total body ho-

mogenates of Baicalia ventrosula (A-D) and B. herderiana lae-

vis (E-H) collected at Bolskije Koty (pH 4-6.5).

Page 160

S) 10

Figures 9-10. Hidden heterogeneity among albumen gland

protein profiles (Coomassie staining) of Arion hortensis (Mort-

sel, Belgium). 9. Vertical polyacrylamide gel electrophoresis in

a 7% gel showing no interindividual variation. 10. Agarose IEF

of the same specimens in a 4-6.5 pH gradient resolving hidden

variation in the protein bands near the application site. Migra-

tion patterns are indicated by arrows.

Qualitative analyses will not be dealt with further, as

they are amply illustrated in our review.

Phenetic analyses are usually performed on banding

profiles for which no genetic interpretation is possible

(e.g., general protein patterns, uniparental organisms,

etc.). Such patterns are compared by the band-counting

method (Ferguson, 1980), which treats each band as a

distinct character. To this end gels are examined on a

light table and adjacent profiles are compared pairwise

two under a magnifying lens. The “resemblance” be-

tween two profiles can then be expressed by a similarity

index, which usually relies on a ratio between shared

and unique bands (e.g., Lawson et al., 1980). The sim-

plest index was defined by Ferguson (1980):

where c = number of shared bands and m = maximum

number of bands in one of the two compared profiles

(e.g., Munuswamy, 1982; Backeljau, 1985; Backeljau et

al., 1987; Radice et al., 1988, Verheyen et al., 1991;

Phillips et al., 1992).

Three other binary similarity indices have also been

used for electrophoretic data. The coefficient of Mar-

ezewski and Steinhaus is defined as:

Cr Cc

M Am ar lp = ©

where c = number of shared bands, a; = total number

of bands in profile A and by = total number of bands in

profile B (e.g., Sywula and Bartkowiak, 1978). The

THE NAUTILUS, Supplement 2

matching coefficient of Jaccard (S,) and its modification

(Sj) by Czekanowski [often attributed to Dice or So-

rensen (Sneath & Sokal, 1973; Clifford & Stephenson,

1975)] are given by:

c 2c

5 =—$ ——= Ss-_—>—X{\ =———

J ay t by te May + by + 2c

where c = number of shared bands, ay = number of

unique bands in profile A and by = number of unique

bands in profile B. (e.g., Sella & Badino, 1980; Stoddart,

1983; Riutort et al., 1992). S, has been used by Nixon

and Taylor (1977) and Ribas et al. (1989) to estimate the

time of divergence between noninterbreeding taxa ac-

cording to Nei’s (1971) formula:

mi ae

2en7Q),

where D = -log.S,, c = the proportion of amino acid

substitutions detectable by electrophoresis, ny = the total

number of codons needed to code for a protein and Q),

= the rate of amino acid substitutions per site per year.

However, some assumptions and estimations made by

Nei (1971) may not be applicable to IEF profiles of

general proteins, because one cannot assign band ho-

mologies. Moreover, S; makes the unrealistic assumption

that each band is a unique protein species. Finally, the

estimation of c was based on charge characteristics only

and thus needs correction in the light of the resolving

power of IEF.

The statistical properties of 39 binary similarity indices

(including S, and S;,) have been compared by Shi (1993),

who recommended the use of Jaccard’s coefficient (S;),

because this index meets most statistical requirements.

Sym performs very well too (Shi, 1993), but gives more

weight to shared bands (2c). This may be an undesirable

property, since electrophoretic data tend to inflate sim-

ilarity indices due to the fact that shared bands do not

necessarily involve identical proteins (hidden heteroge-

neity). Even though IEF reduces the likelihood of such

chance similarities, it does not eliminate them and there-

fore Sj may be less appropriate. The statistical properties

of S; and Sy, have not yet been investigated. Hence their

performance relative to S, is unknown.

If bands can be characterized unambiguously (e.g., by

their pI values), one may construct discrete presence/

absence data matrices (see also Nixon & Taylor, 1977),

which can be subjected to multivariate ordination meth-

ods or parsimony programs (e.g., Thorpe, 1985). This

latter approach is conceptually similar to the “indepen-

dent allele” model, which treats each allele as a distinct

character with two states (presence/absence). However,

the application of this model is highly questionable if

not invalid (e.g., Murphy, 1993) and therefore it seems

more appropriate to use Gelfand’s similarity as an alter-

native:

eo Saw

where x, and y; are the frequencies of the ith band in

T. Backeljau et al., 1994

Page 161

populations X and Y, and Y is taken over the total number

of bands in both populations. Thus contrary to S, Sy, Sy

and Sjy, Sg is not applicable to individual comparisons,

but to group comparisons (e.g., Cline et al., 1992).

All similarity indices mentioned can be converted in

dissimilarities using:

DIS=i1—S

A computer program to calculate S,;, Sy and S, and the

corresponding DIS values has been written by Angus et

al. (1988). S; and Sy; can be calculated with the program

NTSYS-pe (Rohlf, 1993). General accounts on similarity

indices and their statistical properties can be found in

Constandse- Westermann (1972), Sneath and Sokal (1973)

and Clifford and Stephenson (1975).

Similarities or distances can be compared hierarchi-

cally. With S;, Sy, S; and Sj, for example, three levels

of relatedness can be considered: (1) intrapopulational,

(2) interpopulational and (8) interspecific (e.g., Backel-

jau, 1985). Average similarities can then be calculated

as the arithmetic means of all values for a given class of

comparisons. Differences between these means can be

tested with an estimation of the standard error of the

difference between two means (Farnsworth, 1978), a Stu-

dent-t-test or an analysis of variance followed by a Dun-

can Multiple Range test or a Student- Newman-Keuls test

(Sokal & Rohlf, 1981). These statistics require that the

data are independent, normally distributed and hom-

oscedastic (Sokal & Rohlf, 1981). Deviations from the

latter two assumptions can be dealt with by applying

data transformations or nonparametric tests (Sokal &

Rohlf, 1981; Hageman, 1992). The statistical treatment

of interdependent data (e.g., when single profiles con-

tribute to more than one comparison) is a much more

fundamental problem, which also applies to similarity

values calculated from other molecular data such as Ran-

dom Amplified Polymorphic DNA (RAPD) profiles

(Chapco et al., 1992). So, if mean Sp, Sy, S; or Spy values

are to be tested as outlined above, one should use each

individual in only one comparison, such that a set of

independent similarity values is generated. Gelfand’s in-

dex (Sc), on the contrary, can be compared statistically

by resampling techniques such as bootstrapping or jack-

knifing over bands (e.g., Crowley, 1992), followed by an

estimation of variances and confidence intervals using,

for example, an approach similar to that of Mueller and

Ayala (1982).

Finally, phenetic IEF data can yield information with

respect to the overall variability of organisms in relation

to environmental characteristics. Mill and Grahame (1988,

1992), for example, expressed esterase band heteroge-

neity among littorinid populations from different sites

and species by calculating the Shannon Wiener diversity

index for each sample as:

DIVERSITYsy = —Z pjlog.p,

where p; is the frequency of the ith band in the sample.

More generally, in phenetic protein similarity analyses

one must always consider possible environmental, de-

velopmental and seasonal variations before taxonomic

conclusions may be drawn (e.g., Backeljau et al., 1987).

Next to phenetic analyses, IEF data can also be inter-

preted genetically (e.g., figure 6; Rollinson & Wright,

1984; Theron et al., 1989; Alstad & Corbin, 1990; Rol-

linson et al., 1990; Alstad et al., 1991). Yet, such approach

is not always possible because IEF may occasionally yield

genetically uninterpretable profiles produced by artifac-

tual interactions between carrier ampholytes and pro-

teins (Hare et al., 1978; Righetti, 1983).

As the genetic analysis of IEF data proceeds in exactly

the same way as for other electrophoretic data, we refer

to the extensive literature on these methods for more

details (e.g., Richardson et al., 1986; Nei, 1987; Weir,

1990; Whitmore, 1990a; Hillis & Moritz, 1990). Com-

puter packages and programs for various aspects of elec-

trophoretic data analysis have been published by Swof-

ford and Selander (1981), Suiter et al. (1983), Swofford

and Berlocher (1987), Farris (1989), Lessios (1990) , Weir

(1990a, b), Felsenstein (1991), Swofford (1991), Lewis

(1992) [see also Whitkus, 1985, 1988], Quesada et al.

(1992) and Ota (1993). This list is not exhaustive. All

these programs were written for PC’s and larger com-

puters. Yet, there are also programs for Texas Instru-

ments calculators (Spikell & Blumenberg, 1977; Blu-

menberg & Spikell, 1978, 1980; Blumenberg, 1981).

DISCUSSION

Because of its generally higher resolving power, IEF

provides an effective tool to analyse hidden protein vari-

ation not detected by conventional electrophoretic meth-

ods (Figures 9-10). It is therefore a complementary tech-

nique, which is most conveniently used in conjunction

with others. An extreme example of this is two-dimen-

sional (2D) electrophoresis. In this approach proteins are

separated by IEF in a first dimension and by, for ex-

ample, SDS electrophoresis in a second dimension per-

pendicular to the first one. The resulting profiles often

show >100 protein spots and thus provide large data

sets. Yet, only very few applications of 2D-electropho-

resis in molluscan taxonomy have hitherto been pub-

lished (e.g., Miyazaky et al., 1988; Tsubokawa & Mi-

yazaki, 1993), but both studies clearly show the utility

of this method.

Since IEF concentrates proteins on the basis of their

isoelectric points it is also a convenient technique to

analyse minute organisms (e.g., Kazmer, 1991). More-

over, single IEF runs combined with general protein

stainings, often yield considerably larger numbers of dis-

crete characters (bands) than conventional electropho-

retic methods. This may be advantageous when only few

specimens can be screened (e.g., rare organisms). As such,

IEF also provides a means to perform quick preliminary

analyses of particular problems (e.g., in order to plan a

more extensive survey using other methods). Finally, IEF

seems a most efficient technique for species (taxon) iden-

tification, particularly since bands can be identified by

their pI values and thus can be compared between gels.

Page 162

THE NAUTILUS, Supplement 2

Needless to say that IEF can just as well be used for

conventional population genetic applications, even though

we believe that other electrophoretic methods will con-

tinue to dominate this field because of the lower costs

involved.

In conclusion, IEF is a technique that has much to

offer, particularly when employed in combination with

conventional electrophoresis. Nevertheless, its advanta-

geous features are currently far from fully explored or

exploited in systematic malacology.

ACKNOWLEDGEMENTS

We are much indebted to two anonymous referees who

provided valuable comments on an earlier draft of this

paper. Mr H. Van Paesschen (Brussels) and Mr R. Schaer-

laeken (Antwerp) kindly helped with the preparation of

the illustrations. This work was supported by F.J.B.R.-

grant 2.0004.91 and F.J.B.R.-M.L.-grant 30.35.

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Appendix 1. Basic guidelines for IEF experimentation.

Sample preparation

Either total body homogenates or specific tissues can be

used for IEF. Muscle, mantle, gonad and digestive gland

extracts are good sources to resolve specific enzymes,

whereas albumen glands, eggs and eye lenses (cephalo-

pods) are more convenient for general protein stainings.

Samples have to be prepared on ice to prevent heat

denaturation of the proteins. Since salts may distort IEF

gradients (Sévigny & Odense, 1985; Robinson, 1989;

Whitmore, 1990b), tissues are preferably homogenized

in distilled water (e.g. Sella & Badino, 1980; Manga-

Gonzalez & Rollinson, 1986), to which we add 20% (w/

v) sucrose (Backeljau, 1985, 1989). Yet, organic (e.g.,

Brahma & Lancieri, 1979; Viyanant et al., 1985) or dilute

inorganic (e.g., Wright & Rollinson, 1979; Ginther &

Hinz, 1986, 1988; Mill & Grahame, 1988) buffers are

tolerated too. Wright & Rollinson (1979) also added 1.0

mM of dithiothreitol, eaminocaproic acid and ethyle-

nediamine tetraacetic acid (EDTA) as enzyme stabiliz-

ers. Still many more extraction solutions are possible (e.g.,

Dixon & Arai, 1985; Sévigny & Odense, 1985; Kilias,

1988; Keyvanfar et al., 1988; Holmes et al., 1989; Rob-

inson, 1989; Payan & Dickson, 1990; Phillips et al., 1992).

We add 5 ul extraction solution per mg tissue, but

other proportions have been used too: Viyanant et al.

Page 165

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Whitmore, D. H. 1990b. Isoelectric focusing of proteins. In:

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Boca Raton, p. 81-105.

Wright, C. A. and D. Rollinson. 1979. Analysis of enzymes

in the Bulinus africanus group (Mollusca: Planorbidae)

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Wright, C. A. and D. Rollinson. 1981. Analysis of enzymes

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detection. Parasitology 79:95-105.

(1985) and Mill and Grahame (1988) homogenized in-

dividual snails in respectively 300 ul and 200 ul buffer;

Ginther and Hinz (1986, 1988) placed single Pisidium

specimens in 50 ul solution; Wright and Rollinson (1979)

and Sella and Badino (1980) used 1:1 proportions, while

Brahma and Lancieri (1979) prepared 2% (w/v) ho-

mogenates. Tissues may be homogenized with a pestle

and mortar (Mill & Grahame, 1988), a mixer (Sella &

Badino, 1980; Backeljau, 1989) or a sonicator (Giinther

& Hinz, 1986, 1988). Viyanant et al. (1985) first homog-

enized snails with a mixer and subsequently sonicated

the suspensions three times for 20 sec at 150 W. Ho-

mogenates are subsequently centrifuged during 30-45

min at 18000 X g (= 13000 r.p.m.) to 27000 X g (=

15000 r.p.m.) (4°C) (Backeljau, 1985, 1989). Following

regimes have also been reported: 25 min at 50000 X g

(Wright & Rollinson, 1979), 10 min at 6000 r.p.m. and

5 min at 12000 r.p.m. (Sella & Badino, 1980), 30 min at

12000 r.p.m. (Viyanant et al., 1985) and 4 min at 5000

r.p.m. (Herberts et al., 1989). Brahma and Lancieri (1979)

used glass fiber papers (5 X 10 mm) to absorb 20 ul

extract without centrifugation. Mill and Grahame (1988)

centrifuged their homogenates during 2.5 min at 4000

r.p.m. and freeze-dried the supernates. These were re-

hydrated with distilled water when needed.

Supernates can be stored at or below -70°C. Some

proteins, however, may denature at these temperatures

Page 166

Figure 11. IEF (pH gradient 3-9) patterns of esterases from

digestive gland homogenates of Bukobia sp. (Mufindi, Tanza-

nia) after more than five years of storage at -70°C. IEF was

performed with PhastSystem. Note the granulation caused by

undissolved Fast Blue RR (cf. figures 4-7).

(Sevigny & Odense, 1985; Privalov, 1990). For long term

storage, it is better to freeze complete individuals or

tissues, than to store extracts. Nevertheless, albumen gland

homogenates of arionids did not deteriorate over a period

of six years, even after repeated freezing and thawing

(Backeljau, 1989). Similarly, complete Bukobia speci-

mens, stored for more than five years at —70°C, still yield-

ed satisfactory and reproducible esterase profiles (figure

11). The need of fresh material and its storage are dis-

advantages of protein electrophoresis in general. How-

ever, Westheide and Brockmeyer (1992) published pro-

tocols for IEF of ethanol-fixed oligochaetes. Taylor et al.

(1994) reported the possibility of air-drying samples in

15% (w/v) trehalose.

Table 1. Programmed conditions for IEF separations in two

pH gradients in mini polyacrylamide gels using PhastSystem

(tested with esterases and albumen gland proteins).

pH 3-9

Sample appl. down at DD) 0 Vh

Sample appl. up at 2.3 0 Vh

Extra alarm sound at I 73 Vh

SEP 2.1 2,000 V Jo mA 35 Wo °C 75 Vh

SEP 2.2 200 V 25mA 3.0W 95°C 15 Vh

SEP 2.3 2,000 V 25mA 35 W 5°C 510 Vh

pH 4-6.5

Sample appl. down at 2 0 Vh

Sample appl. up at 1.3 0 Vh

Extra alarm sound at 1.1 73 Vh

SERS! 2,000 V 20mA 85 W 5°C 75 Vh

SERale2 200 V 20mA 385 W 5°C 15 Vh

SEPSIS 1,500 V 40mA 35W 5°C 510 Vh

THE NAUTILUS, Supplement 2

Table 2. Programmed silver staining procedure as used with

the PhastSystem development unit. EtOH = ethanol, HAc =

Acetic acid, TCA = Trichloroacetic acid. Background reducer

consists of 2.5 g sodium thiosulphate + 3.7 g Tris in 10 ml

reagent grade water; developer consists of 1 ml 2% formal-

dehyde + 150 ml 2.5% sodium carbonate.

Time T

Dev Solution In Out (min) (°C)

1 20% TCA 1 0 ) 20

2 10% EtOH 5% HAc 3 0 2, 50

3 10% EtOH 5% HAc 3 0 4 50

4 5% Glutaraldehyde 4 0 6 50

5 10% EtOH 5% HAc 3 0 3 50

6 10% EtOH 5% HAc 3 0 3) 50

7 reagent grade H,O 5 0 2 50

8 reagent grade H,O 5 0 2 50

9 0.4% AgNO, 6 0 10 40

10 reagent grade H,O 5 0 0.5 30

11 reagent grade H,O 5 0 0.5 30

12 developer 7 0 0.5 30

138 developer 7 0 3:5 30.

14 background reducer 8 0 15 30

15 reagent grade H,O 5 0 5 50

Casting and running IEF gels

IEF is usually performed in polyacrylamide (PAA) or

agarose gels. Information on PAA gel preparation is pro-

vided by Righetti (1983), Viyanant and Upatham (1985),

Nunamaker and McKinnon (1989), Robinson (1989),

Mork (1990), Whitmore (1990b) and Westheide and

Brockmeyer (1992). Agarose recipes can be found in

Righetti (1983), Sevigny and Odense (1985), Whitmore

(1986), Backeljau (1989) and Dixon and Arai (1989). Most

of these references also provide protocols for IEF running

conditions. Additional information can be found in Righ-

etti et al. (1990) and Whitmore (1990a).

Recently, LKB-Pharmacia introduced an automated

electrophoretic unit (PhastSystem) capable of executing,

among others, horizontal IEF in mini PAA gels of 50 X

43 X 0.385 mm (Olsson et al., 1988a). In this unit all

running conditions are controlled by a programmable

microprocessor. It achieves exactly the same resolution

as ‘manual’ IEF in larger gels, but in much shorter times

(+ 30 min). Table 1 lists our PhastSystem programs for

IEF separations of esterases and general proteins in two

pH gradients, while figures 4-7 and 11 illustrate some

separations obtained with these programs.

Gel staining

After IEF, gels can be stained for either nonspecific pro-

teins or specific enzymes. Recipes for the latter are es-

sentially the same as those published for conventional

electrophoresis (e.g. Harris & Hopkinson, 1976; Rich-

ardson et al., 1986; Morizot & Schmidt, 1990; Murphy

et al. 1990). Righetti (1983) provided a review of stain-

ings applied in IEF. Some recipes used for molluscs are

T. Backeljau et al., 1994

given by Wright and Rollinson (1979) and Manga-Gon-

zalez and Rollinson (1986).

Our recipe for esterase staining is as follows (Backeljau,

1985): dissolve 40 mg Fast Blue RR in a mixture of 25

ml 0.1M KH,PO,/NaOH buffer at pH 7.0 (= 6.804 g

KH,PO, + 1.164 g NaOH in 1000 ml H,0), 25 ml H,O

and 2 ml a-naphtylacetate solution (1% w/v a-naphty-

lacetate in 50% v/v acetone). Before pouring this solution

on the gel, it should be filtered to avoid precipitation of

undissolved Fast Blue RR (figure 11). Staining takes about

45 min.

General proteins are often stained with Coomassie

Brilliant Blue R-250 (= Serva Blue R), as outlined by

Backeljau (1989). Silver staining, however, is more sen-

sitive (e.g., Rabilloud, 1990). Several recipes are provided

by Righetti (1983). The programmed protocol we follow

with PhastSystem (Olsson et al. 1988b) is given in table 2.

Agarose and thin PAA gels can be dried and stored

after staining. PhastSystem gels can be kept as slides.

After prolonged storage (> two years) gels stained for

esterases may be covered by a white “dust”. This can be

washed away by rinsing the gel under gently running

tap water. Specific enzyme stainings are less stable for

long term storage. Therefore we recommend to photo-

graph or photocopy all gels.

Appendix 2. Systematic list of the molluscan taxa men-

tioned.

CLASS: GASTROPODA

Subclass: Prosobranchia

Fam. Patellidae

Patella aspera Roding, 1798

Patella coerulea Linnaeus, 1758

Patella lusitanica Gmelin, 1791

Fam. Bithyniidae

Bithynia funiculata Walker, 1927

Bithynia siamensis siamensis Lea, 1856

Bithynia siamensis goniomphalos (Morelet, 1866)

Fam. Baicaliidae

Baicalia (Baicalia) turriformis Dybowski, 1875

Baicalia (Maackia) costata Dybowski, 1875

Baicalia (Eubaicalia) bithyniopsis Lindholm, 1909

Baicalia (Eubaicalia) herderiana laevis Kozhov, 1936

Baicalia (Eubaicalia) ventrosula Lindholm, 1909

Fam. Ampullariidae (= Pilidae)

Pomacea canaliculata (Lamarck, 1804)

Fam. Littorinidae

Littorina saxatilis (Olivi, 1792)

Littorina arcana Hannaford-Ellis, 1978

Subclass: Heterobranchia (partim Pulmonata)

Page 167

Fam. Planorbidae

Bulinus liratus (Tristram, 1863)

Bulinus obtusispira (Smith, 1882)

Bulinus africanus (Krauss, 1848)

Bulinus nasutus (von Martens, 1879)

Bulinus senegalensis Miiller, 1781

Bulinus tropicus (Krauss, 1848)

Bulinus truncatus (Audouin, 1827)

Bulinus coulboisi (Bourguignat, 1888)

Bulinus guernei (Dautzenberg, 1890)

Bulinus cernicus (Morelet, 1867)

Bulinus permembranaceus (Preston, 1912)

Fam. Arionidae

Arion (Kobeltia) hortensis Férussac, 1819

Arion (Kobeltia) distinctus Mabille, 1868

Arion (Kobeltia) owenii Davies, 1979

Arion (Kobeltia) fagophilus de Winter, 1986

Arion (Kobeltia) intermedius Normand, 1852

Arion (Carinarion) fasciatus (Nilsson, 1823)

Arion (Carinarion) circumscriptus Johnston, 1828

Arion (Carinarion) silvaticus Lohmander, 1937

Fam. Urocyclidae

Bukobia sp.

Fam. Helicidae

Helicella sp.

CLASS: BIVALVIA

Fam. Sphaeriidae

Pisidium personatum Malm, 1855

Pisidium nitidum Jenyns, 1832

Pisidium hibernicum Westerlund, 1894

Pisidium henslowanum (Sheppard, 1823)

Pisidium supinum Schmidt, 1851

Pisidium lilljeborgii Clessin, 1886

Pisidium pulchellum Jenyns, 1832

Pisidium subtruncatum Malm, 1855

Pisidium amnicum (Miller, 1774)

Sphaerium sp.

CLASS: CEPHALOPODA

Fam. Sepiidae

Sepia officinalis Linnaeus, 1758

Fam. Loliginidae

Loligo vulgaris Lamarck, 1798

Fam. Octopodidae

Octopus vulgaris Cuvier, 1798

Eledone massyae Voss, 1964

Eledone gaucha Haimovici, 1988

Page 168

THE NAUTILUS, Supplement 2

AUTHOR INDEX

AdamkewiczoSilig = «cata ee ee eer ee 51

Backeljaus Ue oc. che, ce eee eae ae eee 98, 156

Booren iin: a. cgeee ene epee oe ve ee eee 61

Breigelimans: JK. cic. e ei ee ee eee 156

Browne WEME W siccetred eee ans ee ee eerie. Aree 61

Colgan, 31D]: "130s Gant arene ort ws eg ees Bb oe Pa 25

COOK Dil ok eae Oe aay ee IE MEE a 85

Davis. Gone ae We ce pie eee re Gite Re RNR Ree! 3, 111

De WachtereRy te eee er eee ee eee as 98

Emberton: KiGis ach eae ek eee ae bebe Rca 44

Geller Bi eae ce er eee eee re ere ena oR 2 141

Gwerdotxs.|& eae eee eee te ae Peer eee 122

Glaragernyen, MEG, ..ccscccececsrvvcccnvvscex 1, 51, 111

Kanak ousiss Years cere orem era ee on eae Ae, 145

Ki cio: 3S eee ee ee ene on ns ete 111

Lazaridou-Dimitriadou, M. ......................... 145

BEN oem age, seeeee Rr MRS ot apne bern SUN rN, xn re, Fane Been 2. 156

MESSE] Ot NIA rat MORN ge MORN pleted cr eee earch a eee an 122

NITES ES eae ris. cere cea eh ea ee ese Beet a aie Ne ea EE 79

Ponders Broke. oe eens i a ee re ea 25

ROWETSAD HA hoe eet ae ee ee a ee oo eae ire ae 14]

Reid DiGi oi ee va? fee eee es hee ee 91

OGTR METZ lg as fu lke cee brent rec hes Bree et we eee 156

RosenbergitG. ert ties o as es toe epee ee 111

Rtimbalk-3B eo ks ees ds, Sh 91

Shrerbakoyw Ds eee seus ety eo aia eee eee 156

Sitmikovarnly cee pee eee eee ae 156

StaikounAy cect) 2 hee an ne ee ee 145

METKELE Monk eel. eet Oe een OE CON ate eee 79

Teo ias Gee ee ee Pe ee 79, 91

WilliersVAe eee Se a Oe ee ee 122

TCI E RS ee ae ie nets Bho Ne ae 1, 122

Timimernvanss SM. sca gh accom ae ook bo oe eee 156

Van Goethenn ais <a lak, eananeils denacte ea 156

Verhéyens iB 29 ig eine pn ete, ae 156

Winnepenninckx, By 2 oe. oe ee 98

LOUVOS: NE tien a cotcocs We to EE Ch oe ee 85

Index

Acanthochitona 127, 128, 129, 130, 131,

132

Acanthochitona fascicularis 124, 125, 126,

129, 180

Acanthopleura japonica 98, 99, 102, 108,

104, 105, 106, 107

Acoelomata 105, 107, 108

Acteon 127, 128, 129, 138, 1385

Acteon tornatilis 124, 125, 126, 129, 1380

Acyrtosiphon pisum 102, 103, 104, 105,

106, 107

Aedes 65

Albinaria 12

Alligator mississippiensis 102, 103, 104,

105, 106, 107

Allogastropoda 122, 123, 127

Amblema 18, 118, 116, 117, 119

Amblema plicata 18, 112

Ambleminae 18, 19, 20, 118, 119

Amblemini 6, 7, 18, 19

Amphineura 62

Ampullariidae 167

Ampullarioidea 122

Anaspidea 122, 123, 127, 185, 136, 138,

139

Anemonia sulcata 102, 108, 104, 105, 106,

107

Anisodoris nobilis 63

Annelida 62, 65, 99, 107, 108

Anodonta 6, 18, 19, 20, 113, 116, 117, 119

Anodonta cataracta 6, 18, 112

Anodonta grandis 18, 112

Anodonta imbecilis 18, 112

Anodontinae 18, 19, 118, 119

Apis 65

Apis mellifera 148

Aplacophora 62

Aplysia 127, 128, 129, 135, 136

Aplysia depilans 124, 125, 126, 129, 130

Apogastropoda 122, 128, 188, 134, 135,

136, 188, 189

Archaeogastropoda 111, 117, 122, 123, 127,

128, 181, 182, 188, 189

Archaeopulmonata 123

Archidoris 127, 128, 129, 135

Archidoris tuberculata 124, 125, 126, 129,

130

Architaenioglossa 122, 127, 139

Arion 158, 167

Arion circumscriptus 157, 167

Arion distinctus 157, 167

Arion fagophilus 158, 167

Arion fasciatus 157, 167

Arion hortensis 157, 167.

Arion intermedius 157, 167

Arion owenii 157, 167

Arion silvaticus 157, 167

Arionidae 167

Artemia 65

Artemia salina 68, 102, 108, 104, 105, 106,

107

Arthropoda 62, 65, 99, 102, 108, 104, 105,

106, 107

SYSTEMATIC INDEX

Ascaris suum 65, 79, 81, 82

Aschelminthes 70

Aspergillus nidulans 65

Assimineidae 118

Asterias forbesi 63

Aulacopoda 113

Baicalia 158, 159

Baicalia bithyniopsis 158, 159, 167

Baicalia costata 158, 159, 167

Baicalia herderiana 158, 167

Baicalia herderiana laevis 158, 159, 167

Baicalia turriformis 158, 159, 167

Baicalia ventrosula 158, 159, 167

Baicaliidae 167

Balaenoptera 64

Basommatophora 113, 123

Berthella 127, 128, 129, 133, 135

Berthella plumula 124, 125, 126, 129, 130

Bilateria 107

Biomphalaria 113, 114, 115, 116, 117

Biomphalaria camerunensis 33

Biomphalaria glabrata 6, 7, 32, 34

Biomphalaria pfeifferi 6, 7, 32, 33

Biomphalaria straminea 33

Bithynia 158

Bithynia funiculata 158, 167

Bithynia siamensis goniomphalos 158, 167

Bithynia siamensis siamensis 158, 167

Bithyniidae 167

Bivalvia 62, 66, 71, 78, 98, 99, 102, 108,

104, 105, 106, 107, 111, 118,118, 119,

123, 181, 158, 167

Bos 64

Brachiopoda 99, 108

Branchiostoma floridae 64

Buccinidae 127, 138, 139

Buccinum 123, 127, 128, 129, 134, 135

Buccinum undatum 124, 125, 126, 129,

130

Bukobia 166

Bulinus 156

Bulinus africanus 156, 157, 167

Bulinus cernicus 38

Bulinus coulboisi 157, 167

Bulinus liratus 156, 167

Bulinus nasutus 157, 167

Bulinus obtusispira 156, 167

Bulinus senegalensis 157, 167

Bulinus tropicus 157, 167

Bulinus truncatus 157, 167

Busycon 118, 114, 115, 116, 117, 119

Busycon carica 112

Caenogastropoda 111, 118, 117, 118, 119,

122, 123, 127, 128, 180, 131, 133, 134,

135, 186, 1388, 139

Caenorhabditis 113

Caenorhabditis elegans 65, 79, 81

Calliostoma 127, 128, 129, 131, 132, 133

Calliostoma zizyphinum 124, 125, 126,

129, 130

Calyptraea 127, 128, 129, 134, 135

Page 169

Calyptraea chinensis 124, 125, 126, 129,

130

Calyptraeoidea 127, 138

Campanilidae 122

Campanilimorpha 122

Cancellariidae 111, 118

Cancellarioidea 113, 118

Carinarion 158, 167

Caudofoveata 62

Cepaea 34, 50, 79, 80, 81, 82

Cepaea hortensis 34

Cepaea nemoralis 13, 34, 79, 80, 81, 82,

83 152, 153

Cephalaspidea 123, 127, 133, 135, 186,

138

Cephalopoda 62, 98, 99, 158, 167

Cerion 32

Cerithioidea 118

Chaetopteris sp. 68

Chelicerata 102

Chion 50

Chitonidae 111

Chlamydomonas reinhardtii 65

Chlamys islandica 86

Chlorella ellipsoidea 102

Chordata 102, 103, 104, 105, 106, 107

Ciliata 102, 108, 104, 105, 106, 107

Cnidaria 102, 103, 104, 105, 106, 107

Cocculiniformia 118, 122, 127

Conchifera 62, 98

Conoidea 118

Crassostrea virginica 99, 102, 103, 104,

105, 106, 107

Crepidula 38

Crossostome 64

Crustacea 102, 103, 104, 105, 106, 107,

108

Cryptochiton stelleri 63

Cumberlandia 118, 116, 117, 119

Cumberlandia monodonta 18, 19, 112

Cyclophoroidea 122

Cyprinus 64

Cyrtosoma 62, 98

Daphnia 65

Diasoma 62, 98

Dictyostelium discoideum 102

Diodora 127, 128, 129, 181, 132, 188

Diodora graeca 124, 125, 126, 129, 130

Docoglossa 122

Donax 50, 52, 55, 56, 57, 58, 59

Donax denticulatus 51, 52, 54, 55, 56, 57

Donax denticulatus denticulatus 50

Donax denticulatus stephaniae 50

Donax dorotheae 50, 51, 59

Donax fossor 50, 51

Donax parvulus 50, 51, 52, 54, 55, 59

Donax roemeri protracta 50

Donax roemeri roemeri 50

Donax striatus 50, 51, 52, 54, 55, 57

Donax texasianus 50, 51, 52, 54, 55, 59

Donax variabilis 50, 51, 54, 55, 56, 59

Hee

Page 170

Donax variabilis roemeri 50, 51, 52, 54,

Donax variabilis variabilis 50, 51, 52, 54,

faye)

Donax vellicatus 50, 51

Drosophila 61, 65, 66, 67, 68, 71, 73, 80,

81, 82, 118, 114

Drosophila melanogaster 63

Drosophila yakuba 66, 67, 80, 81, 82

Dugesia tigrina 63

Echinorhinus cookei 102, 108, 104, 105,

106, 107

Echiura 99

Echiurida 62

Ectobranchia 122

Elasmognatha 123

Eledone 159

Eledone gaucha 159, 167

Eledone massyae 159, 167

Elimia livescens 10

Elimia virginica 9

Elliptio 6, 7, 9, 18, 19, 20, 113

Elliptio complanata 6, 7, 9, 18, 112

Entoprocta 99

Escherichia coli 80, 103

Eubaicalia 167

Eubilateria 105

Eucoelomata 105, 107

Eurypelma californica 102, 103, 104, 105,

106, 107

Euthyneura 122, 123, 127, 128, 131, 188,

134, 185, 136, 188, 139

Fasciola hepatica 65

Fissurelloidea 122, 127, 182, 183, 189

Fluvidona 25, 27, 28, 29, 30, 31, 33, 34,

35, 39, 40

Fonscochlea 25, 28, 29, 32, 33, 39

Fonscochlea accepta 28, 29, 30, 31, 82, 33,

34, 39, 41

Fonscochlea aquatica 28, 30, 31, 32, 33,

34, 35, 39, 41

Fonscochlea billakalina 28, 30, 31, 32, 35,

Fonscochlea variabilis 28, 30, 31, 32, 33,

35, 89, 41

Fonscochlea zeidleri 28, 30, 31, 32, 33, 34,

35, 39, 42

Fundulus heteroclitus 102, 103, 104, 105,

106, 107

Fusconaia 7, 9, 18, 20, 118

Fusconaia cerina 18, 112

Fusconaia flava 7, 9

Gadus 64

Gadus morhua 79

Gammatricula 12, 15, 17

Gammatricula chinensis 15, 16, 17

Gammatricula songi 15, 16, 17

Gastropoda 62, 91, 98, 99, 102, 108, 104,

105, 106, 107, 108, 111, 118, 118, 122,

128, 130, 181, 1382, 145, 156, 158, 167

Geomelania 111, 113, 118, 119

Geomelania sp. 112, 114, 115, 116, 117

Geomelania typica 112, 114, 115, 116, 117

Geomelaniinae 113

Giardia duodenalis 102, 104, 105

Giardia intestinalis 104

Giardia lamblia 104

Gnathostomulida 99

Goldfingia gouldii 63

Gonidea 18, 118, 116, 117, 119

Gonidea angulata 18, 112

Gonideini 18, 19, 113

Goniobasis 32, 33, 34

Goniobasis proxima 33

Gracilaria lemaneiformis 102

Haliotis 123, 127, 128, 129, 131, 1382, 133

Haliotis rubra 32, 33

Haliotis tuberculata 124, 125, 126, 129,

130

Haplotrema 118, 114, 115, 116, 117

Haplotrematidae 118

Helicella 158

Helicidae 167

Helicina 118, 114, 115, 116, 117, 118, 119

Helicinidae 111, 1138

Helix 79, 127, 128, 129

Helix aspersa 124, 125, 126, 129, 180, 145,

148, 149, 150, 152, 153, 154

Helix aspersa aspersa 145

Helix aspersa major 145

Herdmania momus 102, 108, 104, 105,

106, 107

Heterobranchia 167

Heterodon platyrhinos 102, 108, 104, 105,

106, 107

Heterostropha 123

Holopoda 113

Holopodopes 118

Homarus 65

Homo 64, 118

Homo sapiens 63, 81, 102, 103, 104, 105,

106, 107

Hubendickia 12

Hydrobia truncata 6, 10

Hydrobiidae 6, 7, 25, 27, 41, 42, 118

Insecta 102, 108, 104, 105, 106, 107, 108

Jullienia 12

Katharina 61, 66, 67, 68, 69, 70, 71, 72,

Katharina tunicata 61, 66, 67, 68

Kobeltia 158, 167

Lacunopsis 12

Lampsilini 7, 18, 19, 113

Lampsilis 6, 7, 18, 19, 20, 118

Lampsilis claibornensis 18, 112

Lampsilis teres 7, 18, 112

Latimeria chalumnae 102, 103, 104, 105,

106, 107

Leishmania tarentolae 65

Limicolaria kambeul 99, 102, 108, 104,

105, 106, 107

Limulus 65

THE NAUTILUS, Supplement 2

Limulus polyphemus 63

Lingula reevei 63

Littorina 33, 80, 91, 92, 94, 95, 96, 127,

128, 129, 134

Littorina arcana 91, 93, 94, 95, 158, 167

Littorina brevicula 91

Littorina keenae 98, 94, 95, 96

Littorina kurila 95

Littorina littorea 33, 91, 93, 94, 95, 96,

124, 125, 126, 129, 1380

Littorina mandshurica 91

Littorina mariae 91, 98, 94, 95

Littorina neglecta 95

Littorina nigrolineata 91, 93, 94, 95

Littorina obtusata 91, 93, 94, 95

Littorina plena 91, 93, 94, 95, 96

Littorina saxatilis 33, 91, 92, 93, 94, 95,

158, 167

Littorina scutulata 91, 93, 94, 95, 96

Littorina sitkana 91

Littorina sookensis 96

Littorina squalida 91, 96

Littorina striata 91, 98, 94, 95, 96

Littorina subrotundata 91, 93, 94, 95, 96

Littorinidae 91, 167

Littorinoidea 118, 127, 134, 188

Locusta 65

Loliginidae 167

Loligo 159

Loligo vulgaris 159, 167

Lumbricus sp. 63

Lymnaea 127, 128, 129

Lymnaea peregra 32

Lymnaea stagnalis 124, 125, 126, 129, 180

Maackia 167

Mainwaringia rhizophila 95

Mancinella 118, 114, 115, 116, 117, 119

Mancinella deltoidea 112

Marchantia polymorpha 65

Margaritifera 19, 20, 113

Margaritifera falcata 18, 112, 116, 117,

119

Margaritifera margaritifera 18, 112, 116,

117, 119

Margaritiferinae 18, 19, 20, 118, 119

Megalonaias 18, 113

Megalonaias boykiniana 18, 112

Melarhaphe 91

Meloidogyne javanica 65

Melongenidae 111, 113, 118

Mesarion 158

Mesodon 113, 114, 115

Mesomphix 118, 114, 115, 116, 117

Metazoa 98, 105, 107

Mollusca 61, 62, 63, 64, 65, 79, 98, 99, 102,

103, 104, 105, 106, 107

Monodonta 127; 128, 129, 131, 132, 183

Monodonta lineata 124, 125, 126, 129,

130

Monoplacophora 62, 98

Muricidae 111, 118, 118, 127, 184, 138,

139

Muricoidea 118, 118

Mus 64, 113, 129

Index

Mus musculus 102, 103, 104, 105, 106,

107, 128, 124, 125

Mya arenaria 63

Mytilus 10, 61, 65, 66, 67, 68, 69, 70, 71,

72, 73, 79, 81, 82, 87, 126, 128, 129,

180, 181, 182, 141

Mytilus edulis 61, 66, 69, 79, 83, 99, 124,

125, 126, 129, 130, 141, 144

Mytilus galloprovincialis 141, 142, 143,

144

Mytilus trossulus 141, 142, 148

Nassarius obsoletus 33

Nematoglossa 118

Nemertina 62, 99

Neogastropoda 111, 118, 115, 118, 119,

122

Neohelix 113, 114, 115

Neolepetopsidae 122

Neomphalidae 118, 188, 139

Neomphalina 122, 123, 127, 128, 136, 138,

139

Neomphaloidea 138

Neotaenioglossa 118, 118

Neotricula 12, 14, 15, 17

Neotricula lilii 14, 15, 16

Neritimorpha 117, 122, 127

Neritoidea 113, 117

Neritopsina 113, 117, 118, 122

Neritrema 91, 94, 95, 96

Neurospora crassa 65, 102

Nodilittorina 91, 92, 98, 94, 95

Nodilittorina radiata 93, 94

Nodilittorina trochoides 92, 93, 94

Notaspidea 123, 127, 133, 135, 188

Novisuccinea 6, 14, 16

Nucella 127, 128, 129, 134

Nucella lamellosa 32, 33

Nucella lapillus 32, 124, 125, 126, 129,

130

Nudibranchia 123, 127, 135, 138

Obliquaria 18, 19, 113

Obliquaria reflexa 18, 112

Ocenebra 127, 128, 129, 134

Ocenebra erinacea 124, 125, 126, 129, 130

Octopodidae 167

Octopus 159

Octopus vulgaris 158, 167

Oedignathus inermis 102, 108, 104, 105,

106, 107

Onchidella celtica 98, 99, 100, 101, 102,

108, 104, 105, 106, 107, 108

Oncomelania 18, 14, 15, 17, 118, 114, 115,

116, 117, 119

Oncomelania hupensis 13, 15, 16

Oncomelania hupensis quadrasi 6

Oncomelania minima 18, 15

Ophiocoma wendtii 63

Opisthobranchia 122, 123, 127, 185, 136,

138, 189

Opisthorchis viverrini 102, 103, 104, 105,

. 106, 107

Oryctolagus cuniculus 102, 103, 104, 105,

106, 107

Oxyloma 6, 14, 16

Oxyloma decampi gouldi 16

Oxyloma retusa 16

Oxytricha nova 102

Pachydrobia 12

Paleoheterodonta 113

Pan troglodytes 143

Paramecium aurelia 65

Paramecium tetraurelia 102, 104, 105,

106, 107

Partula 34, 35

Partula suturalis 32

Partula taeniata 32

Patella 127, 128, 129, 129, 130, 131, 132,

136, 138

Patella aspera 158, 167

Patella coerulea 158, 167

Patella lusitanica 158, 167

Patella vulgata 124, 125, 126, 129, 130

Patellidae 167

Patellogastropoda 111, 118, 119, 122, 123,

127, 128, 130, 182, 136, 1388, 189

Peltospiridae 123, 127, 138, 189

Peltospiroidea 122, 127

Perotrochus 118, 114, 115, 116, 117, 118,

119

Perotrochus maureri 112, 113

Phoca 64

Physarum 118

Phytia 127, 128, 129

Phytia myosotis 124, 125, 126, 129, 180

Pilidae 167

Pisidium 158, 167

Pisidium amnicum 158, 167

Pisidium henslowanum 158, 167

Pisidium hibernicum 158, 167

Pisidium lilljeborgii 158, 167

Pisidium nitidum 158, 167

Pisidium personatum 158, 167

Pisidium pulchellum 158, 167

Pisidium subtruncatum 158, 167

Pissodes 86

Placopecten 68

Placopecten magellanicus 85, 86, 87, 99,

102, 103, 104, 105, 106, 107

Placostylus 127, 128, 129

Placostylus fibratus 124, 125, 126, 129,

130

Planorbidae 6, 113, 167

Planorboidea 113

Plasmodium berghei 102

Platyhelminthes 99, 102, 103, 104, 105,

106, 107

Plectomerus 18, 113

Plectomerus dombeyianus 18, 112

Pleurobema 113

Pleurobema cordatum 18, 112

Pleurobemini 6, 7, 18, 113

Pleuroceridae 10

Pleurotomariidae 111, 118, 117, 118

Pleurotomarioidea 113, 122, 127, 132, 133,

139

Podospora anserina 65

Pogonophora 99

Page 171

Polygyridae 44, 46, 113, 116, 117

Polygyroidea 113

Polyplacophora 62, 66, 98, 102, 103, 104,

105, 106, 107, 108, 123, 131

Pomacea canaliculata 158, 167

Pomatias 128, 127, 128, 129, 134

Pomatias elegans 124, 125, 126, 129, 130

Pomatiopsidae 6, 7, 12, 13, 17, 111, 118,

118

Pomatiopsinae 13, 17

Porphyra umbilicalis 102

Progabbia 113, 114, 115, 116, 117, 119

Progabbia cooperi 112

Prorocentrum micans 102

Prosobranchia 158, 167

Protostomia 65

Pulmonata 111, 113, 117, 118, 119, 122,

123, 127, 135, 136, 138, 139, 145, 156,

167

Quadrula 7, 18, 19, 113

Quadrula cylindrica 18, 112

Quadrula quadrula 7, 18, 112

Quincuncina 7

Quincuncina infucata 7

Rachiglossa 118

Rattus 64, 113

Rattus norvegicus 102, 103, 104, 105, 106,

107

Rhodosporidium toruloides 102

Rhynchopelta 127, 128, 129, 134, 136, 188

Rhynchopelta concentrica 123, 124, 125,

126, 129, 130

Rhytidoidea 118

Riftia pachyptila 63

Rissooidea 111, 113, 115, 118

Romanomermis culicivorax 86, 88

Rostroconch 62

Rostroconchia 98

Ruminia decollata 10

Saccharomyces 113

Saccharomyces cerevisiae 65, 102

Scaphopoda 62, 98

Schistosoma bovis 157

Schistosoma japonicum 13

Schistosoma mansoni 102, 103, 104, 105,

106, 107

Schizosaccharomyces pombe 65

Sebastolobus altivelis 102, 103, 104, 105,

106, 107

Seguenziidae 122

Seguenziina 122, 127

Sepia 159

Sepia officinalis 158, 167

Sepiidae 167

Siphonaria 127, 128, 129

Siphonaria algesirae 124, 125, 126, 129,

130

Siphonaria jeanae 32, 33

Sipuncula 99

Sipunculida 62

Solenogastres 62

Spalax ehrenbergi 6

Spalax leucodon 6

Sphaeriidae 6, 167

Sphaerium 6, 158, 167

Spiralia 99

Spirobolus marginatus 68

Spisula solidissima 63

Squalus acanthias 102, 108, 104, 105, 106,

107

Stenoglossa 111, 118, 118, 122, 188, 134,

139

Strombus gigas 32, 33

Strongylocentrotus purpuratus 81

Stylommatophora 113, 118, 119, 123

Succinea (Novisuccinea) “Minn” 14

Succinea (Novisuccinea) chittenangoen-

sis 14, 16

Succinea (Novisuccinea) ovalis 14, 16

Succinea 14, 15, 16, 127, 128, 129

Succinea putris 16, 124, 125, 126, 129, 130

Succineidae 6, 7

Tatea 25, 27, 33

Tatea huonensis 33

Tatea rufilabris 33

Tenebrio molitor 102, 103, 104, 105, 106,

107

Tergomya 98

Theba pisana 151

Toxoglossa 118

Trematoda 102, 103, 104, 105, 106, 107

Tricula 12, 14

Triculinae 12, 13, 17

Triodopsis 113, 114, 115

Triodopsis albolabris 32

Trochidrobia 25, 28, 29, 32, 39

Trochidrobia inflata 31

Trochidrobia minuta 28, 30, 31, 32, 39,

Trochidrobia punicea 28, 30, 31, 32, 35,

39, 42

Trochidrobia smithi 28, 30, 31, 39, 42

Trochoidea 122, 127, 132, 133, 139

Truncatella 6, 7, 49, 113, 116

Truncatella caribaeensis 6, 112, 114, 115,

116, 117

Truncatella clathrus 112, 118, 114, 115,

117, 118

Truncatella pulchella 6, 112, 114, 115, 116,

117

Truncatella reclusa 112, 114, 115, 116,

117

Truncatella scalaris 112, 114, 115, 116,

117, 118

Truncatella sp. 112, 114, 115, 116, 117,

119

Truncatella subcylindrica 112, 114, 115,

116, 117

Truncatellidae 6, 7, 111, 113

Truncatellinae 113, 118

Tryblidiida 98

Trypanosoma brucei 65, 102

Tunicata 102, 108, 104, 105, 106, 107

Turbellaria 62, 99

THE NAUTILUS, Supplement 2

Turdus migratorius 102, 108, 104, 105,

106, 107

Unio 18, 118, 119

Unio pictorum 18, 112

Uniomerus 6, 7, 9, 18, 18, 118

Uniomerus tetralasmus 7, 9, 18, 112

Unionidae 6, 7, 18, 19, 20, 113, 119

Unioninae 113, 119

Unionini 18, 19

Unionoidea 111, 113, 19

Urocyclidae 167

Valvatoidea 122, 123, 127

Ventridens 118, 114, 115, 116, 117

Vertebrata 102, 103, 104, 105, 106, 107

Vetigastropoda 113, 119, 122, 123, 127,

128, 180, 131, 132, 183, 186, 138, 189

Vivipariformes 139

Volutomitridae 118

Volvox carteri 102

Wuconchona 12

Xenopus 64, 118

Xenopus laevis 102, 103, 104, 105, 106,

107

Zea mais 102, 103

Zonitidae 113, 158

Zonitoidea 113

Index

Page 173

ACCTRAN 95

agarose 71, 80, 86, 142, 157, 158, 160,

166, 167

algae 102

alignment 62, 63, 103, 104, 112, 115,

123

allogamy 157

allopatry 11, 21

allozyme 8, 44, 48, 51, 91, 92, 94, 95,

118

allozyme cladistics 44, 47, 48

allozyme coding 27

amino-acid substitution 160

amphibian 85

angiosperm 102

ANOVA 146, 147

apicomplexa 102

area effect 34

ascomycete 102

ATPase 61, 64, 65, 66, 79, 80, 81, 82, 83

autapomorphy 16, 46, 47, 48, 68, 94,

119

Bam HI 71, 80, 103

base composition 79, 82

basidiomycete 102

biogeography 44, 96

BIOSYS 27, 147

bird 79

bootstrap 92, 98, 95, 102, 108, 104, 105,

107, 116, 117, 122, 125, 126, 127, 128,

129, 130, 131, 182, 183, 134, 135, 136,

138, 139, 161

breeding structure 10

Burnaby’s correction 149

cellulose acetate electrophoresis 27

cesium chloride 81

character state analysis 106

character-state tree 46, 47, 48

chimpanzee 143

ciliate 102

cladistics 17, 44, 47, 48, 50, 51, 54, 57,

91, 92, 95, 116, 117

climatic factors 153, 154

cline 150, 158

cloning 3, 62, 70, 80, 82, 101, 103

CLUSTAL V 79, 92, 93

CO1 64, 66, 73, 80, 82, 83

CO2 64, 67, 80, 82, 83

CO3 64, 66, 73, 80, 82, 83

coding 27, 47, 81

codon 81

COMP BOO 125

compensatory mutations 115, 119

conditional allelic frequencies 27

consensus tree 55, 56, 57, 68, 98, 104,

106, 107, 111, 125, 128, 129

convergence 7, 55, 57, 61, 68, 111, 115,

118, 119

cryptic species 7, 158

SUBJECT INDEX

cytochrome b 64, 66, 71, 80, 82, 83

cytochrome c 99

D-loop 81

deazaGTP 123

deletion 88, 119, 123

density dependent selection 10

dinoflagellate 102

diplomonad 102

dispersal 33, 35

distance methods 44, 48, 63, 104, 125

diversity index 161

DNA 8, 5, 17, 21, 50, 51, 52, 53, 54, 55,

61, 62, 64, 66, 70, 71, 72, 73, 78, 80,

88, 89, 91, 101, 148, 161

DNA extraction 52, 78, 86, 92, 102

DNA polymerase 52, 71, 92, 142

DNABOOT 125, 126, 128, 129, 130

DNASTAR 79

echinoderm 78, 80, 99

Eco RI 71, 86, 87, 88, 142, 143

electrophoresis 145, 156, 158, 162

electrophoretic data 143, 160, 161, 162

enzyme 146, 157, 158, 165

evolutionary parsimony method 63

evolutionary process 17

F-statistics 25, 26, 30, 31, 35, 147, 149,

FREQPARS 45, 48

frequency-parsimony method 44, 48

frog 79, 81

Fpp 149, 153

Frs 149, 153

Frr 149, 153

F.7 10, 26, 27, 30, 31, 32, 34, 35, 153

gaps 62, 63, 93, 95, 113, 123

GC content 115

gene arrangement 68, 70, 71, 72, 85, 89

gene conversion 62

gene flow 25, 26, 28, 33, 34, 35, 59, 89

gene order 64, 65, 66, 79, 81

GeneClean 52, 79

genetic code 69

genetic distance 4, 5, 9, 10, 18, 17, 21,

45, 91, 92, 94, 95, 103, 147, 149, 151,

153, 154, 156

genetic drift 25, 86, 153, 154

genetic frequencies 141, 157

genetic isolation 141

genetic variation 145, 149, 151, 158,

159, 161

genome size 81

globin 107

Gor 32

Hae Ill 58, 54

haplotype 141, 142, 143

Hennig86 4, 15, 17, 44, 46, 47, 53, 104,

106, 107, 118, 125, 129

heteroplasmy 68, 79, 83, 85, 86, 87, 88,

141, 143

heterozygosity 10, 145, 147, 149, 150,

152, 154

HindIll 53, 54, 80, 83

homeotherm 85

homology 61, 62, 63, 64, 123

homoplasmy 85, 86

homoplasy 62, 64, 115, 116, 123

honeybee 143

hot-vent a 122

hot-vent c 122

hot-vent limpet 122

Hpa Il

hybrid zone 10, 148

hybridization 9, 18

hybrids 28

hybrizyme 10

hydropathy profile 79, 80, 81

IEF 156, 157, 158, 159, 160, 161, 162,

165

immuno-IEF 159

immunological distance 19

immunology 3, 18

independant allele model 160

information content 101

informative character 94, 95, 106, 123

informative site 114, 115, 131, 133, 134,

135, 186

insect 79

insertion 119, 123

introgression 10, 141, 154

intron 67

invertebrate 85

island model 26

isoelectric focusing 156, see IEF

isoelectric point 156, 161

isolating mechanisms 11

isozyme 25, 145

JACKBOOT 125

jackknife 122, 125, 126, 127, 130, 131,

132, 133, 134, 135, 136, 139, 161

JACKMONO 125, 127, 135

kinetoplastid 102

KpnI 80, 83, 86, 87, 88

long branch attraction 62, 105, 106, 116,

119, 132

MacClade 116

MacVector 79

Mahalanobis distance 145, 147, 151, 152

MALIGN 112

mammals 12, 79,81

mapping 70, 71, 72, 81

Page 174

marker 52, 58, 54, 55, 56, 57

maximum likelihood 92, 93

Mendelian segregation 57

migration 34

minimum-turnover method 44, 46, 47

mitochondrial DNA (mtDNA) 17, 21,

61, 64, 65, 67, 68, 69, 70, 71, 72, 78,

79, 80, 81, 82, 83, 85, 86, 87, 88, 91,

92, 108, 141, 143

mitochondrial genome 61, 64, 66, 68,

69, 70, 72, 79, 80, 83, 96, 141, 148

molecular characters 99

molecular clock 4, 68, 95

MONO HIS 125, 127

monophyly 122

morphological variation 145, 147, 150,

158

morphometric data 145, 146, 147, 149

morphostatic radiation 12, 13, 17

mouse 114, 115, 116, 117

MPI 28, 30, 31, 33, 34, 35, 47

mucopolysaccharide 79

MULPARS 95

multidimensional scaling 4, 7, 19, 20

mussel 78, 87, 141, 142, 143

MUST 1238, 125

mutagenesis 141, 142

NADH 64, 79

natural selection 4

NDI 66, 67, 71, 82, 83

ND2 78, 82, 83

ND38 66, 67, 73, 82, 83

ND4L 67, 80, 81, 82, 83

ND5 82, 83

ND6 66, 71, 80, 81, 82, 83

neighbor-joining 92, 93, 94, 102, 108,

104, 105, 107, 125

nematode 79, 81, 86, 88

neutral mutation 4, 89

niche 11, 51

NJBOOT 125, 126, 127, 128

Nm 26, 28, 30, 31, 32, 33, 34, 35

non-coding sequence 64, 82

nonparametric test 161

NTSYS 27

nuclear genome 69

nucleotide composition 115, 117

nucleotide substitution 85, 119, 123

oligonucleotide 99, 141, 143

ordered character states 48, 49, 57

ordination diagram 19, 20, 160

outgroup 94, 95, 101, 115, 122, 127

outgroup comparison 46, 47, 54, 55,68

p(l) 27, 30, 82, 34, 35

panmictic unit 28

paraphyly 99

parasites 157

parsimony analysis 99, 104, 111, 160

parsimony methods 44, 48, 62, 63, 68,

125

parsimony tree 93, 94, 107, 129

PAUP 4, 46, 92, 117

pBluescript 108, 148

PCA 145, 146, 147, 149

PCR 8, 50, 51, 52, 53, 61, 70, 71, 72, 73,

79, 83, 88, 92, 99, 101, 102,

103, 141, 142

periwinkle 158

phagemid 80

PhastSystem 158, 159, 166, 167

phenetic analysis 160

phenogram 17, 56, 153

phenotypic variation 145

PHYLIP 27, 92, 125

phylogenetic distance 95

phylogeny 17, 50, 44, 50, 58, 54, 56, 61,

62, 68, 69, 70, 91, 96, 98, 111, 122,

156

plasmid 80, 103

plesiomorphy 16, 48, 115

polyacrylamide 160, 166, 167

polycistronic transcript 69

polymorphism 48, 51, 55, 78, 81, 82, 85,

86, 145, 147, 149

polyphyly 17, 99

polytypic species 11, 13

population genetics 9, 17, 25, 54, 161

Prim network 4, 7, 16, 20

primer 51, 52, 53, 54, 55, 56, 61, 70, 71,

82, 91, 92, 99, 101, 112, 141, 142,

143, 144

Principal component analysis 4, 7, see

PCA

private alleles 27, 35

probe 71, 72, 79

protein 61, 64, 69, 78, 79, 81, 159, 160,

161, 165, 167

protein electrophoresis 156, 158, 161,

166

protein variation 156

PstI 86, 87, 88

radiation 9, 11, 21, 27, 98

radioisotope 142, 148

RAPD 50, 51, 52, 58, 54, 55, 56, 57, 58,

59, 161

rate of evolution 61, 62, 64, 85, 87, 88,

89, 92, 95, 111, 119, 128, 1382, 138,

160

relative rate test 123, 128

reliability of nodes 116, 123, 125, 127,

128

repeated sequences 85, 86, 87, 88, 89

reptile 85

restriction enzyme 72, 79, 103, 141

restriction map 86 ;

restriction site 142, 143

reversal 55, 57, 68

reverse transcriptase 62, 101

RFLP 17, 79, 82, 141

RNA extraction 123

RNA 38, 5, see rRNA, tRNA

RNAzol 123

rooting 94

rRNA 18, 21, 62, 63, 64, 65, 66, 67, 69,

THE NAUTILUS, Supplement 2

70, 71, 79, 80, 81, 82, 83, 91, 92, 96,

98, 99, 100, 101, 102, 108, 104, 105,

106, 107, 108, 111, 115, 119, 122, 128,

124, 136, 141, 142, 143

Sall 71, 86, 87, 88

sampling 141

saturation 93

scallop 82, 85, 86, 87, 89

SDS electrophoresis 161

sea star 78

sea urchin 79, 81

secondary structure 100, 101, 103, 104

selection 10, 25, 35, 86, 89

self fertilisation 33

Sequenase 103

sequence data 20, 21, 44, 81, 91, 99,

111, 112, 117, 119, 128, 124, 141

sequence length 124, 125

sibling species 141, 142, 143

similarity index 160, 161

slime mold 102

snail 145

Southern blot 61, 70, 71, 72, 73, 80

speciation 4, 10, 11, 17, 20, 25, 33, 34,

96, 141

species concept 10, 11, 21

Sphl 86, 87

SstI 80

statistical test 161

STATVIEW 146

stepping stone model 26

Stul 86, 87, 88

sub-cloning 72, 80

subspecies 13

symplesiomorphy 68, 71

synapomorphy 16, 68, 78, 95, 119

tapersnout 122

Tag polymerase 101

taxonomic sampling 78, 111, 119, 122,

125, 127

tertiary structure 100

tetraploid 157

transition 92, 93, 94, 113, 115

transversion 92, 93, 94, 118, 115

TREECON 104

trematodes 92, 157

tRNA 61, 64, 65, 66, 67, 69, 70, 71, 73,

two-dimensional electrophoresis 161

uniparental reproduction 157, 158, 160

unordered character states 48, 49, 53,

Do, OF

UPGMA 8, 14, 15, 17, 18, 44, 45, 46, 48,

56, 145, 147, 152

vertebrate 79

VNTR 85

WAGNER 147, 149, 153

weevil 86

weighting 48, 63, 115, 128

WRIGHT78 27

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S3IYVYGIT_ LIBRARIES SMITHSONIAN INSTITUTION NOILNLILSNI NVINOSHLINS S3I1YVYdIT LIBRARIES

NVINOSHLIWS S3Iuvug

NVINOSHLINS

NVINOSHLIWS

SMITHSONIAN

NVINOSHLIWS

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INSTITUTION NOILNLILSNI NVINOSHLINS S3!1YVYUEIT LIBRARIES SMITHSONIAN INSTITUTION NOILNLILSNI

x = c z rc

= S = 6 = S 3 S :

7 = Pe) E ee] = Pe) = 2

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= b = z = b = b }

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S3IuYVYEIT_LIBRARIES SMITHSONIAN NVINOSHLINS S3IYVYSIT LIBRARIES

2 ica z : z g eres

= _ \ = a = —_ —d = S\

> = Mine S a 4 = > = |

me ” J 2 ” a, me : wo” = ” . |

INSTITUTION NOILALILSNI_NVINOSHLINS S31YVYGIT_ LIBRARIES SMITHSONIAN _INSTITUTION | NOILNLILSNI

= ul 2 Ow = ul Fra wu |

2) Ses ” MG — o” = ‘ a” Sa (

= o = AWS ox = fe LA = oc |

= <x 4 RAN 4 < = < |

= e = : ; — (

= = a Wi ee = 2s = a |

O = re) 2 fo) = i o - |

Zz - Zz 2 ay z 2m) a = | .

_S3 buvugit LIBRARI ES_ SMITHSONIAN INSTITUTION _NOILALILSNI_NVINOSHLINS _S3 1yuvug ae LIBRARIES

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