MOLECULAR

APPROACHES TO STUDYING HELMINTH GENETICS AND PHYLOGENY

POPULATION

STEVENA. NADLER* Museum of Natural Science and Department of Zoology and Physiology, Louisiana State University, 119 Foster Hall, Baton Rouge, LA 70803-3216, U.S.A. (Received

I7 July 1989)

CONTENTS

INTRODUCTION

Ii

I. GENETIC

12 12 12 13 13 14 14 14

YARfABILlTY

ANI, POPULATION ~TR~rCTUR~ METHODS OF ASSESSING GENETIC VARIABILITY

Protein electrophoresis Restriction endonuclease site variation of nucleic acids Nucleic acid polymorphisms MEASURES OF VARIABILITY Protein variability

Restriction fragment length polymorphisms SELECTION VERSUS NEUTRAL MUTATION AND GENETIC DRIFT HELMINTH GENETIC VARIABILITY DATA GEOGRAPHIC VARIATION IN ALLELE FREQUENCIES NEUTRAL ALLELES AND POPULATION STRUCTURE

14 16 18 19

II. ~ULECULAR APPROACHES TO PHYLOGENY RECONSTRUCTION ADVANTAGES AND LIMITATIONS OF MOLECULAR DATA PHYLOGENETIC APPLICATIONS OF MOLECULAR DATA Protein electrophoresis Restriction endonuclease and nucleic acid sequence data METHODS OF DATA ANALYSIS Parsimony methods Distance methods Maximum likelihood methods Invariants Data resampling methods FINAL COMMENTS ACKNOWLEDGEMENTS REFERENCES

20 20 21 21 22 23 24 24 24 24 25 25 25 26

INDEX KEY WORDS: Helminths; variation; molecular evolution.

population

genetics;

phylogeny;

genetic

variability;

geographic

within and among natural populations (Lewontin, 1985). Empirical studies of genetic variation have been instrumental in understanding the genetic structure of populations. Likewise, biochemical and molecular approaches have revolutionized the field of systematic biology. Experimental methods to compare molecules of known homology among distantly related species have given evolutionary biologists the tools necessary to assess phylogenetic relationships among old and diverse groups of organisms (Wilson, 1985). During the past 20 years, biochemical and molecular genetic studies have revealed that most natural populations of animals are genetically heterogeneous (for review see Powell, 1975; Nevo,

INTRODUCTION THE disciplines

of biochemical and molecular genetics have provided population and evolutionary biologists with powerful techniques to investigate both microevolutionary and macroevolutionary questions. Since the pioneering protein-electrophoretic work of the 1960s (Harris, 1966; Lewontin & Hubby, 1966), population geneticists have applied biochemical and molecular methods to uncover genetic variation

* Present address and address for correspondence: Department of Biological Sciences, Northern Illinois University, DeKalb, IL 60115-2861, U.S.A. II

12

S. A. NADLER

1978). Moreover, many species show geographic variation in gene frequencies. The forces maintaining genetic variability and producing geographic variation have been the subject of considerable debate. Much of the discussion concerning genetic variability has focused on the ‘neutralisttselectionist’ controversywhether the majority of detectable genetic variation in populations is selectively neutral or is maintained by natural selection. Although the neutralist-selectionist debate has persisted for over two decades, it is unlikely to be resolved to the satisfaction of all participants in the near future. Regardless of the current state of the neutralistselectionist controversy, if many of the loci under study among populations behave as if they are selectively neutral or nearly neutral, then these loci will be useful for elucidating the genetic structure of populations. For example, protein-electrophoretic studies of multilocus design provide empirical estimates of allelic frequencies that are useful in characterizing the genetic structure of populations. Theoretical research by population geneticists has provided models to use allelic frequency data to study population structure, gene flow, genetic drift, and differences in effective population size (the size of the actual breeding population). Numerous species of vertebrates and certain free-living invertebrates have been studied and characterized at the population level (Avise & Aquadro, 1982; Nevo, Beiles & Ben-Shlomo, 1984). Unfortunately, helminthologists have rarely used the full potential of biochemical or molecular approaches to clarify basic population-genetic parameters, the most fundamental being the nature of a helminth deme (local interbreeding population). The amount of genetic variance distributed within and among demes (Wright, 1978; Slatkin, 1987) has not been reported for any helminth species. In essence, empirical studies of helminth population genetics are still in their infancy. Molecular methods have also proved to be of great utility in studies of systematic biology. Because morphological and molecular evolution appear to be decoupled (Wilson, Carlson & White, 1977) molecular data are extremely useful when morphological convergence and parallelism confound analyses of evolutionary history. Morphological analysis of phylogenetic relationships among many groups of helminths is hindered by these problems and a relatively low number of definable morphological characters. Although many hypotheses concerning the evolutionary histories of cestodes, trematodes, and nematodes exist, few data are available to test proposed relationships. Parasitologists have only recently applied biochemical approaches to the study of systematics (for review see Bryant & Flockhart, 1986). In addition to phylogeny reconstruction, molecular and biochemical methods can confirm the conspecificity of different life-cycle stages of parasites (Flockhart & Denham, 1984; Andrews, Beveridge, Adams & Baverstock, 1988) identify cryptic (sibling)

pecies (Nascetti, Paggi, Orecchia, Smith, Mattiucci & Bullini, 1986; Orecchia, Paggi, Mattiucci, Smith, Nascetti & Bullini, 1986), and discriminate between species of morphologically similar larvae isolated from host tissue (Flockhart & Bianco, 1985). Four general topics concerning parasite population and evolutionary genetics will be discussed in this review: (1) methods of assessing genetic heterogeneity; (2) genetic variability of helminth species and populations; (3) genetic geographic variation among helminth populations; and (4) systematic applications of molecular methods to helminthology.

I. GENETIC

VARIABILITY AND POPULATION STRUCTURE

METHODS OF ASSESSING GENETIC VARIABILITY Protein electrophoresis Gel electrophoresis of proteins remains one of the most useful and easily applied techniques in population genetics and systematics. Protein electrophoresis separates molecules primarily on the basis of differences in net charge, although there is some discrimination based on differences in molecular conformation. For the structural proteins surveyed in traditional electrophoretic studies (Harris & Hopkinson, 1976) a difference in migration usually reflects differences in the amino acid composition of the protein. If two conspecific individuals have homologous proteins that migrate different distances under the same electrophoretic conditions, then it is reasonable to conclude that the gene sequences encoding these proteins also differ. The term applied to an electrophoretically distinct enzymatic protein is isoenzyme, or isozyme. When pedigree analysis confirms that the isozymes at a locus are inherited in a Mendelian fashion, then it is appropriate to consider them alleles, or allozymes. Another term, electromorph, refers to proteins of identical electrophoretic mobility. Although differences in the electrophoretic mobility of isozymes indicate real structural differences, proteins of identical mobility (electromorphs) may contain amino acid differences that are not revealed under electrophoretic conditions. As a method for detecting genetic variation, protein electrophoresis has both advantages and limitations. One clear advantage over studies of variation in morphological characters is that electrophoretic phenotypes of individuals can be interpreted in a genetic context (as alleles at a locus). In contrast, the genetic basis of most morphological variation is unknown. However, it is evident that electrophoresis using only a single buffer system will separate only a limited number of alleles that differ by one amino acid substitution (Kreitman, 1983). Fortunately, the resolving power of protein electrophoresis can be improved substantially by repeating the experiments under several buffer conditions (varying the pH and ionic strength of the buffer), a

Molecular systematics of helminths

method termed sequential electrophoresis (Coyne, 1982). In a study of hemoglobin variants of known amino acid sequence, sequential electrophoresis (employing three electrophoretic conditions) distinguished 85% of the total possible protein variants (Coyne, 1982). In contrast, only 40% of hemoglobin variants subjected to single-condition electrophoresis were discriminated (Ramshaw, Coyne & Lewontin, 1979). Sequential electrophoresis revealed twice as many alphaglycerophosphate alleles in Drosophila species as did a single-condition method (Coyne, Eanes, Ramshaw & Koehn, 1979). Of course, nucleotide substitutions that do not alter the amino acid content of proteins (silent substitutions), or those that result in an amino acid substitution that does not alter protein net charge or conformation cannot be discriminated by protein electrophoresis. However, differences detected by single-condition methods are real, and systematic conclusions made from single-condition experiments are usually supported by sequential-electrophoretic studies. The mode of inheritance and expression of most isozymes that have been studied is Mendelian and codominant (Lewontin & Hubby, 1966; Harris, 1970), and data from experimental crosses of trematodes (Paragonimus ohirai and Paragonimus westermani) support this conclusion for helminths (Agatsuma & Habe, 1985a,b). Additional support for the Mendelian inheritance and codominant expression of isozyme loci has been inferential (Fletcher, LoVerde & Woodruff, 1981; Agatsuma & Ito, 1985; Nadler, 1986), and is based on the conformance of many isozyme polymorphisms in natural populations to HardyWeinberg equilibrium expectations. One exception to these observations is the phosphoglucose isomerase locus of Schistosoma mansoni, which is codominant and sex linked (Jelnes, 1983). Certain protein loci are prone to post-translational modifications that alter electrophoretic mobility despite the absence of underlying nucleotide changes (McGovern & Tracy, 198 1; Davin, Morgan & Feldhamer, 1984). Careful interpretation of isoenzyme patterns is required to avoid incorrect estimates of genetic variability. The estimation of overall genomic variability in a species based on study of only 14-50 protein loci entails two critical assumptions. First, it must be assumed that most of the allelic variation at the loci studied has been revealed. Second, the structural loci studied must represent a random sample of all such loci, because different classes of protein loci differ in levels of variability. Although most recent populationlevel surveys of 14 or more loci incorporate enzymatic proteins of several different classes (oxidoreductases, transferases, hydrolases, lyases, isomerases), nonenzymatic structural proteins (e.g. albumin, hemoglobin, transferrin) usually comprise a small fraction of the loci sampled. Gillespie & Kojima (1968) noted that glucose-metabolizing enzymes are generally less variable than other enzymes. Certain of the more

13

rapidly evolving proteins, including non-specific esterases, transferrin, and enzymes such as carbonic anhydrase and ribonuclease, are not integral to complex metabolic pathways (Sarich, 1977). Because different protein loci tend to have different levels of variability (presumably because of functional constraints), studies of genetic variability can be biased by the type of loci surveyed. Restriction endonuclease site variation of nucleic

acids

Although the precise determination of variation at the nucleotide level requires sequencing of nucleic acids, an indirect approach to estimate this variation involves using restriction endonucleases. Restriction enzymes cut DNA molecules at specific recognition sequences; for example, the bacterial endonuclease EcoRl cleaves at the six-base sequence GfAATTC. Enzymes that recognize four-base sequences have been used more often in population studies because they have more recognition sites for a given length of sequence, and therefore have the potential to reveal more variation. For studies of restriction-site variation, DNA is digested with a restriction enzyme, and the resulting DNA fragments are separated by agarose or acrylamide electrophoresis, where they migrate according to size. The cut DNA fragments are visualized directly by end-labelling (Maniatis, Fritsch & Sambrook, 1982) or after transfer to a nitrocellulose (or nylon) filter (Southern, 1975), providing that a specific, labelled DNA probe is available to bind to and reveal the fragments on the filter. The presence or absence of restriction sites in the DNA under consideration will change the length of the fragments. Thus, these polymorphisms are referred to as restriction fragment length polymorphisms (RFLPs). By using double-digestion procedures to construct a physical map of restriction sites relative to each other, it is possible to profile the presence or absence of restriction sites among individuals. Because some regions of the genome tend to be highly variable, RFLP analysis may reveal higher variability than protein electrophoresis, and is often more useful for estimating genetic differentiation at the population level. Nucleic acid polymorphisms

Without question, nucleic acid sequencing represents the highest level of resolution for studies of genetic variation. Allele sequencing reveals not only the nucleotide differences between alleles, but when multiple copies of the same allele are studied, it reveals silent nucleotide substitutions (Kreitman, 1983). Providing that the reading frame of the gene is known, the nucleotide site(s) responsible for the amino acid difference(s) between alleles can be determined. When alleles from different taxa have the same sequence, there is no question that the alleles are identical. The same conclusion cannot be made from analysis of protein electromorphs or restriction site studies. Unfortunately, traditional cloning and sequencing

14

S. A. NADLER

approaches have been too labor-intensive for many population-level studies. The recent development of gene amplification procedures (Saiki, Scharf, Faloona, Mullis, Horn, Erlich & Arnheim, 1985; Saiki, Gelfand, Stoffel, Scharf, Higuchi, Horn, Mullis & Erlich, 1988) in combination with primer-mediated direct sequencing (Wrischnik, Higuchi, Stoneking, Erlich, Amheim & Wilson, 1987) have the potential to make sequencing approaches more feasible for studies of genetic variation in and among populations.

1978; Gorman & Renzi, 1979). However, under certain conditions small sample size can have deleterious effects on systematic studies (Archie, Simon & Martin, 1989). Finally, some populationlevel analyses of allelic frequency data rest on the unconfirmed assumption that the populations surveyed are in genetic equilibrium (Maruyama & Fuerst, 1984). SELECTION

VERSUS

NEUTRAL

GENETIC MEASURES

OF VARIABILITY

Protein variability

Three standard measures are used to describe levels of protein genetic variability within populations: polymorphism, mean heterozygosity, and allelism. Polymorphism refers to the proportion of polymorphic loci in the survey. Generally a locus is defined as polymorphic if the frequency of the most common allele does not exceed 95% (0.05 criterion), although some researchers consider a locus polymorphic if even a single variant is found at that locus. The probability of detecting an allele occurring at low frequency is dependent on sample size. Mean (or average) heterozygosity refers to the average percentage of loci heterozygous per individual. Mean heterozygosity is either reported as directly observed from the data (direct count), or as the estimated proportion of genes expected to be heterozygous per individual. under Hardy-Weinberg equilibrium conditions (expected heterozygosity). Allelism is the average number of alleles per locus per population sample. Restriction fragment length polymorphisms

Estimates of polymorphism and heterozygosity at the nucleotide level can be made indirectly from RFLP data. Fairly reliable estimates of the proportion of polymorphic nucleotide sites (P,,,), and the number of nucleotide substitutions per site (ci,,,) can be made when restriction maps are known (Kaplan & Langley, 1979; Nei & Tajima, 1983). When the locations of restriction sites are unknown, calculation of Pm, and H,, values requires additional assumptions (Nei & Li, 1979; Engels, 1981). Although computer-assisted calculation of these variability measures from large data sets is routine (e.g. for protein-electrophoretic data, see the program BIOSYS-1; Swofford & Selander, 1981), comparison of values between populations or between species is difficult. For example, mean heterozygosity values have large standard errors (Nei, 1978; Archie, 1985), which are influenced by both the number of loci and individuals surveyed per population sample. Although most studies survey 1440 loci, a larger number would provide a more precise estimate of genetic variability (Nei, 1978). In the calculation of genetic distance coefficients for systematic purposes, the number of individuals per taxon is less important; generally twofive individuals have been considered sufficient (Nei,

~UTA~ON

AND

DRIFT

Given that electrophoretically detectable mutations are common in natural populations, much debate has focused on how this variability is maintained. For neutral alleles (those with selection coefficients at or fluctuating near zero), Kimura (1968) proved that even with relatively low mutation rates and moderate population sizes, equilibrium heterozygosity can be high. The number of generations required to reach equilibrium can also be high; Nei (1975) suggested that the number of generations is approximately equal to the reciprocal of the mutation rate. In fact, mean heterozygosity is influenced by both the mutation rate and the effective population size of the species under consideration. Marked bottlenecks in population size will delay the establishment of genetic equilibrium and thereby reduce heterozygosity (Nei, Maruyama & Chakraborty, 1975). The neutralist view is supported by the observation that there is a relatively constant rate of molecular evolution in homologous molecules from different lineages (the ‘molecular clock’; for review see Wilson et al., 1977; Zuckerkandl, 1987). However, the theory that most alleles in natural populations are selectively neutral (or near neutral) is difficult to test. Direct tests of fitness on a locus-by-locus basis can be performed (Koehn, Newell 81 Immerman, 1980; Koehn & Seibenaller, 1981) but falsification of neutrality for a locus, or even several loci does not falsify the hypothesis of general neutrality. In this respect, the neutralist view has often been misinterpreted to suggest that no loci are under the influence of selection. The question is really one of degree: what fraction of the alleles segregating in natural populations are maintained by natural selection? Neutralists propose that the majority of observed variation is the product of mutation and random genetic drift, and not natural selection (Kimura, 1968, 1983; King & Jukes, 1969). The classic example of a balanced genetic polymorphism, human sickle-cell hemoglobin, is often cited as the paradigm of the adaptive nature of allelic variation. Indeed, few other studies document the adaptive nature of individual alleles (Koehn & Hilbish, 1987). Testing the adaptive significance of allelic variation on a locus-by-locus basis is not only difficult, but probably an unrealistic way to assess the proportion of selectively neutral genetic variation, However, if the neutral theory is correct, then

Molecular predictions can be made concerning allelic distributions within breeding

the patterns

systematics

I~ENETICVARIABILITY

Species

Trematode Paragonimus westermani Paragonimus westermani Paragonimus westermani Schistosoma mansoni

ESTIMATES

FORHELMINTHS.CIUTERIA

* Mean for species studied. t n/a, not available.

ESTMATING

AVERAGE

Reference

18 18 18 18

0.12 0.06 0.0 0.13

0.035 0.033 0.0 0.04

Agatsuma & Habe, 1985b Agatsuma & Habe, 1985b Agatsuma & Habe, 1985b Fletcher et al., 198 1

18 15

0.0 0.0

0.0 0.0

Woodruff Woodruff

various

I6

n/a

0.03;

Baverstock

mainland

20 20

0.15 0.15

0.02 0.06

Lymbery Lymbery

11 11 21 21 22 22 22 21 38 38 24 24 18 27

0.54 0.54 0.62 0.57 0.50 0.32 0.50 0.24 0.21 0.17 0.17 0.25 0.22 0.03

0.141 0.193 0.10 0.17 0.21 0.12 0.11 0.10 0.066 0.053 0.03 0.02 0.085 0.008

Vrijenhoek, 1978 Vrijenhoek, 1978 Bullini et al., 1986 Bullini e/ al., 1986 Nascetti et al., 1986 Nascetti et al., 1986 Bullini et al., 1986 Bullini et al., 1986 Leslie et al., 1982 Leslie et al., 1982 Bullini et al., 1986 Bullini et al., 1986 Nadler, 1986 Bullini et al., 1978

28 27

0.07 0.03

0.02 0.015

Bullini et al., 1986 Bullini et al., 1978

28 18 18 18 18 18 18 18

0.11 0.11 0.33 0.33 0.38 0.17 0.11 0.17

0.03 0.04 0.10 0.135 0.137 0.05 0.02 0.05

Bullini Bullini Bullini Nadler, Nadler, Bullini Bullini Bullini

Australia, localities Australia, Tasmania

Mexico Mexico n/at n/a North Atlantic Mediterranean

Ocean Sea

n/a n/a Iowa, U.S.A. New Jersey, U.S.A. nla nla Louisiana, U.S.A Central-eastern Europe n/a Central-eastern Europe nla n/a nla Louisiana, Louisiana, nla n/a n/a

AND

F

Cestode Progamotaenia festiva (species complex) Echinococcus granulosus Echinococcus granulosus

Parascaris univalens Neoascaris vitulorum Toxocara canis Toxocara canis Toxocara cati Toxocara cati Toxascaris leonina Baylisascaris transfuga

(P)

P

Schistosoma japonicum Schistosoma mekongi

Parascaris equorum Parascaris univalens

FORDEF~N~NGPOLYMORPH~SM

No. loci surveyed

Locality

Mie (l), Japan Mie (2), Japan Ohita, Japan (mean of 22 strains) various localities Leyte, Phillippines Laos

Nematode Contracaecum sp. ‘I’ (larvae) Contracaecum sp. ‘II’ (larvae) Contracaecum osculatum ‘B Contracaecum rudolphii ‘A’ Anisakis simplex (larvae) Anisakispegrefli (larvae) Anisakisphysereris (larvae) Phocascaris cyslophorae Ascaris suum Ascaris suum Ascaris suum Ascaris lumbricoides Parascaris equorum Parascaris equorum

15

this test, all individuals must be scored for all loci surveyed because the frequency of minor alleles is an essential component of the analysis. Data required for the analysis include a table of allelic frequencies for the polymorphic loci and estimates of mean heterozygosity. Expected heterozygosity estimates from the allelic data can also be used because, contrary to intuition, estimating heterozygosity from the allelic data does not bias the mutation-drift test (Barrowclough, Johnson & Zink, 1985). A generalized test of the mutation-drift hypothesis involves comparison of the overall observed and

of

demes (Fuerst, Chakraborty & Nei, 1977). If most of the alleles detected by electrophoresis are selectively neutral, then patterns of the distribution of alleles should be the result of mutation and genetic drift (both stochastic processes). Chakraborty, Fuerst & Nei (1978, 1980) and others (Fuerst et al., 1977) have outlined procedures to test the results of genetic studies against predictions of the neutral (mutationdrift) theory, such as the Injinite Allele-Constant Mutation Rate Model (Chakraborty et al., 1980). In

TABLE

of helminths

U.S.A. U.S.A.

et al., 1987 et al., 1987 et al., 1985 &Thompson, & Thompson,

et nl., er al., et al., 1986 1986 et al., et al., et al.,

1986 1986 1986

1986 1986 1986

1988 1988

S. A. NADLER

16

expected distributions of allelic frequencies within demes. When heterozygosity values are low to moderate, all mutation-drift models predict a U- or J-shaped distribution of allelic frequencies, with few alleles distributed at intermediate frequencies (Barrowclough et al., 1985). H~L~INTH

GENETIC VARIABILITY DATA

Most endoparasitic helminth ‘populations’ or species surveyed have levels of genetic variation similar to those of free-living invertebrates (Table 1). The unweighted average level of polymorphism (P) and heterozygosity (r) among the 33 taxa in Table 1 are P = 0.23, B = 0.07. This level of average heterozygosity is comparable to that found in surveys of free-living invertebrates, excluding insects (E = 0.10; Nevo, 1978), although protein polymo~hism levels appear to be slightly higher in free-living invertebrates (P = 0.39; Nevo, 1978). Low levels of genetic variability in a single population of a parasite (Table 1) do not warrant the conclusion that the species lacks genetic variability. It is necessary to survey population samples from other areas of the species’ range before reduced variability at the species level may be inferred. Also, levels of mean heterozygosity for isoenzyme loci do not necessarily reflect levels of genetic variation at polygenic ‘fitness’ loci (Lande & Barrowclough, 1987). The use of laboratory-maintained ‘colonies’ of helminths may lead to erroneous estimates of genetic variability. In regard to schistosomes, for example, Fletcher et al. (1981) and Woodruff, Merenlender, Upatham & Viyanant (1987) noted that many laboratory populations of these trematodes have been maintained by passaging them through laboratory mice and snail intermediate hosts for decades, and that frequent population bottlenecks may account for the absence of variability in the laboratory strains. Furthermore, the observation that a ‘mouse passaged’ laboratory strain of S. munsoni had significantly lower polymorphism and mean heterozygosity than a ‘baboon-passaged’ laboratory ~pulation of the same strain (Fletcher et ui., 1981) was followed by a study suggesting that ‘mouse passage’ of this schistosome decreases genetic variability by host-induced selection against certain isoenzyme alleles (LoVerde, Dewald, Minchella, Bosshardt & Damian, 1985). Because this reduction in parasite genetic variability in murine hosts is substantial (and could reflect changes in other biological properties of the schistosomes) it is perhaps desirable to maintain levels of variability present in field samples if laboratory populations are to remain representative of natural populations. Because certain laboratory strains of schistosomes recently isolated from the field have no detectable electrophoretic variability (Woodruff et al., 1987), it is possible that natural populations may possess low levels of genetic variation. Genetic variability may be affected by the

reproductive mode of the parasite. For example, the trematode P. westermani occurs in both a diploid and triploid form; the triploid has fixed heterozygosity at five protein loci, suggesting that it originated by hybridization and reproduces by parthenogenesis (Agatsuma & Habe, 1985b). Schistosoma mansoni is also capable of parthenogenesis (Basch & Basch, 1984), but the effects of parthenogenesis on genetic variation in ~histosomes remain to be investigated. Thompson & Lymbery (1988) have discussed how molecular data could clarify whether the cestode Echinococcus granulosus is predominantly self- or cross-fertilizing. Their protein-electrophoretic study (Lymbery & Thompson, 1988) revealed that E. granulosus strains are not monomorphic clones, and that the observed patterns of genetic variation suggest that both cross- and self-fertilization occur, althou~ it remains undetermined which mode is predominant. Estimates of genetic variability between conspecific populations of helminths differ widely (Table 1). For example, Nadler (1986) reported variability estimates for populations of the nematodes Parascaris equorum (P = 0.22, 7f = 0.085) and Toxocara cati (P = 0.17, H = 0.137), whereas Bullini, Nascetti, Paggi, Orecchia, Mattiucci & Berland (1986) reported P = 0.07, H = 0.02 for P. equorum, and P = 0.17, B = 0.05 for 7’. cati. Likewise, Bullini et al. (1986) reported P and H values of 0.17 and 0.03, respectively for European populations of the nematode Ascaris suum, whereas Leslie, Cain, Meffe & Vrijenhoek (1982) reported P = 0.21, r = 0.066 and P = 0.16, r = 0.053 for A. suum populations from Iowa and New Jersey (U.S.A), respectively. It is difficult to assess the statistical significant of these differences in heterozygosity because standard errors of the estimates are rarely reported. However, barring methodological differences among laboratories, these results may reflect differences in genetic variability among geographically distinct populations of these species. The existence of geographic variation would not be surprising, and has been confirmed for Australian mainland and Tasmanian isolates of the cestode E. gr~nuiosus (Lymbery & Thompson, 1988). Table 1 reveals that different populations and species of endoparasites may have different values of polymorphism and mean heterozygosity. Assuming that these estimates are accurate and the differences statistically significant, what mechanisms account for these differences? Here, again, the neutralistselectionist controversy becomes central to the issue, and it is important to re-emphasize that the debate between these two schools is essentially a matter of degree, not kind: what proportion of observed variation is maintained by natural selection? According to the selectionist viewpoint, variation in levels of genetic variation among species and populations is often positively correlated with levels of ecological heterogeneity (Selander & Kaufman, 1973; Nevo, 1978; Nevo & Beiles, 1988). Species or

Molecular systematics of helminths ~p~ations from ‘heterogeneous environments’ are hypothesized to have increased genetic variability in response to diversifying selection. This hypothesis is consistent with the earlier niche-width hypothesis of van Valen (1965) who predicted a positive correlation between genetic variation and ecological heterogeneity. Most selectionist exptanations propose that increased genetic variability is related to physiological processes. For example, it has been proposed that increased genetic heterozygosity may increase homoeostasis at the metabolic level (Nevo & Beiles, 1988). Studies testing for correlations between genetic heterozygosity and fitness, habitat type, or population heterogeneity have had mixed outcomes. Tests for a correlation between genetic heterozygosity and fitness have failed to demonstrate a general pattern, with certain studies finding no significant correlation (Mukai, Watanabe & Yamaguchi, 1974), others finding negative correlations (Gaines, McClenaghan & Rose, 1978), and still others finding positive correlations (Singh & Zouros, 1978; Smouse, 1986). Investigators have also searched for correlations between the width of the niche of a species (generalist vs specialist) and genetic heterogeneity (Nevo, 1978, 1983; Nevo et al., 1984); and between heterozygosity (or gene diversity) and the perceived ecological heterogeneity of the environment (Nevo & Beiles, 1988). These studies have found positive correlations between variables, although assessments of habitat heterogeneity were clearly subjective. In addition, the validity of these correlation analyses has been questioned (Nei & Graur, 1984). Balancing selection has been proposed as the mechanism maintaining genetic variation in natural populations, and under certain assumptions, the fitness of an individual can increase with an increase in the number of heterozygous loci (Karlin & Feldman, 1981). Both the heterozygote superiority (overdominance) and habitat heterogeneity arguments have been discussed for endoparasite isozyme data (Leslie et al., 1982; Bullini et al., 1986; Nadler, 1986; 1987a). In an electrophoretic study of ascaridoid nematodes, Bullini et al. (1986) concluded that species with a life cycle completed in a single homeothermic definitive host have significantly lower genetic variability (polymorphism and gene diversity) than species requiring both poikilothermic and homeothermic hosts for completion of their life cycle. These authors reasoned that in the two-host case, one protein allele may have greater fitness at one stage in the life cycle, whereas another allele may function optimally at another stage. In such a situation, heterozygosity would be favoured. Bullini et al. (1986) also argued that ascaridoid species with life cycles that are completed exclusively in homeothe~ic hosts are ‘buffered’ against environmental variation and, therefore, do not require genetic flexibility to cope with environmental heterogeneity. Species utilizing both poikilothermic and homeothermic hosts are subjected

to greater environmental

17

heterogeneity and thus benefit from increased genetic flexibility. Bullini et ai. (1986) also suggested that ascaridoids with low host specificity as larvae (e.g. Anisakis simplex) are subjected to extreme ecological heterogeneity because of the many species of fish that they have the potential to infect. Although the hypotheses of Bullini et al. (1986) are intuitively appealing, problems inherent in their experimental design and analysis compromise their conclusions. First, their classification of ‘direct’ or ‘indirect’ life cycles for ascaridoid species was erroneous. Although certain species of ascaridoid nematodes that infect mammals can complete a direct life cycle (Douvres, Tromba & Malakatis, 1969), few rely exclusively on this pathway, and some appear to use a broad spectrum of paratenic hosts in the natural course of their transmission. Little is known concerning how frequently the direct life cycle is completed by ascaridoid nematodes under natural conditions. Bullini et al. (1986) also argued that ascaridoids using several species of phylogenetically diverse paratenic hosts are subjected to extreme habitat heterogeneity. However, ascaridoids that can complete most of their larval development in the definitive host (e.g. P. equorum, A. lumbricoides), might encounter a heterogeneous array of microenvironments when they migrate and develop in different tissues of the host. Furthermore, ascaridoid species undergo larval development in eggs, and during this stage of development these larvae utilize metabolic pathways distinct from those used in the adult stage (Kmetec, Beaver & Bueding, 1963). Clearly. evaluating a parasite’s habitat heterogeneity is both complex and subjective. It is essentially impossible to assess what parasites perceive as environmental heterogeneity, and arguments implicating the stressful effects of changes in temperature, pH, osmolarity, or multiple-host life cycles, remain ad hoc. The hypothesis of increased genetic heterozygosity for certain parasite species (Bullini, 1982; Bullini et al., 1986; Leslie et al., 1982) is testable. If the heterozygous condition is selected for in certain species, then allelic frequency distributions should depart from random expectations to maximize heterosis. For example, Fig. 1 shows graphs of observed and expected allelic frequency distributions for protein-electrophoretic data on Toxocara canis, 7: cati, and P. equorum (Fig. 1; data from study of Nadler, 1986). These allelic frequency distributions are consistent with the infinite allele-constant mutation rate model of selective neutrality (Chakraborty et al., 1980). The KolmogorovSmirnov test was used to examine the fit of the distribution for each species, and none was significantly different from the distribution expected if alleles are selectively neutral (P level = 0.05). These intrapopulational results are inconsistent with the overdominance model, which predicts a distribution that maximizes heterozygosity (i.e. alleles at intermediate [0.50] frequency). Tests of other helminth

S. A. NADLER

18

14 4 al = m 10 %

Parascarisequorum

&I f6 z= 2 0.05 0.1 0.2 0.3 0.40.5 0.6 0.7 0.8 0.90.95 1 Allelic

frequency

classes

14 2 z

Toxocara

14

cati

Toxocaracanis

E

10

z

z

10

%

i6 2

E6 2 2

z2

0.05 0.1 0.2 0.3 0.40.50.60.7 Allelic

frequency

0.8 0.90.95 1

classes

0.05 0.1 0.2 0.3 0.4 0.5 0.6 0.70.8 0.90.95 1 Allelic

frequency

classes

FIG. I. Observed (solid) and expected (hatched) distributions of number of alleles by frequency for three species of ascaridoid nematodes. Observed distributions based on results of protein-electrophoretic studies of individuals (Nadler, 1986). Expected distributions calculated using the Infinite Allele-Constant Mutation Rate Model (Chakraborty et al., 1980).

species, incorporating larger sample sizes (> 100 individuals) and more gene loci (> 20) are needed to examine patterns of genetic variation in a quantitative and statistical framework. GEOGRAPHIC

VARIATION

IN ALLELE

FREQUENCIES

Molecular methods may be used to determine the level of intraspecific geographic structuring within species of helminths. Genetic uniformity of population samples (as assayed by protein electrophoresis) suggests, but does not prove, that the population is panmictic. Genetic structuring may be present in the absence of morphological differentiation, or vice versa if the morphological differences are induced by the environment. Unfortunately, the issue of geographic genetic variation among helminth populations has been addressed only rarely. Most studies have involved a limited number of geographic isolates surveyed for relatively few protein loci. Although it is premature to infer much from these studies, they do suggest that different helminth species have different population

structures. Leslie et al. (1982) reported similar allelic frequencies for Iowa and New Jersey (U.S.A.) population samples of A. sum. Frequencies of predominant alleles at three polymorphic loci were similar at both localities. Because midwestern and eastern U.S.A. populations of A. suum exhibit little genetic differentiation, it is likely that gene flow among populations has been high, or cessation of gene flow recent (Larson, Wake & Yanev, 1984). In theory, gene flow among parasites of farm and domestic animals may be enhanced over intrinsic levels by transport of farm stock, spread of manure, and so on. Results of other protein-electrophoretic studies also suggest little intraspecific genetic divergence among helminth populations. McManus (1985) reported similar phosphoglucomutase allelic frequencies in samples of the cestode Ligula intestinal& obtained from intermediate hosts (fish) collected more than 200 km apart. Although allelic frequencies at a single locus cannot be considered a reliable indicator of gene flow, this observation suggests that the definitive hosts (birds) effectively disperse this cestode. Birds

Molecular systematics of helminths tend to have high vagility, and avian species are characterized by low levels of among-population genetic divergence (Barrowclough et al., 198s). Clearly, parasite gene flow will be influenced by many host factors including barriers to dispersal, size of home range, and the social structure and behavior of the host species. A few studies have suggested that helminth genetic differentiation increases as a function of increasing geographic distance between populations (isolationby-distance effect). Flockhart, Cibulskis, Karam & Albiez (1986) found no statistically significant allehc frequency differences among Onchocerca volvulus sampfes collected from within African villages. However, statistically significant frequency differences existed when pooled 0. volvulus samples were compared by country, although the overall levels of genetic differentiation between samples, as summarized by protein genetic distances, were small (Nei’s Distance values (D) = 0.001-0.037). Lymbery & Thompson (1988) found that four Australian mainIand samples of the cestode E. grunu~osus showed no significant differences in allelic frequencies at three polymorphic loci, but comparison of a Tasmanian sample with the pooled mainland samples revealed significant differences at two loci. Similarly, in a multilocus protein-electrophoretic study of schistosomes, Woodruff et at. (1987) found only minor differentiation among one of five ~ch~srosom~ j~po~icum isolates from the Philippines, and no differentiation among three Schistosoma mekongi isolates from Laos, or among three Malasian schistosome strains. In contrast, these authors reported moderate to high levels of genetic differentiation among S. japonicum strains from the Philippines, China, Formosa, and Japan. In fact, the high level of genetic di~erentiation between the Chinese and Philippine S. ~~~0~~~~~populations (Nei’s D = 0.45), led Woodruff et al. (1987) to question the conspecificity of these isolates. These few studies of the geography of genetic variation among helminths have proved valuable. However, studies of a broader scope incorporating both genetic and morphologic data are needed. Such studies require careful design and specimen collection, plus rigorous data analysis. Because little is known about the genetic structure of helminth populations, it would be best to characterize genetic and morphological variation on a microgeographic scale before comparing samples collected hundreds of kilometers apart. Ideally, population samples of helminths, each obtained from an individual host, would be collected from along a geographic transect and analyzed genetically and morphologically. Comparisons of host and parasite population structuring would also be of interest. Special attention must be given to preservation of frozen tissue samples and traditional anatomical preparations of hosts and parasites (see Dessauer & Hafner, 1984; Hafner, Hafner & Hafner, 1984; Pritchard & Kruse, 1982). A

19

detailed plan for studying geographic variation in vertebrates (Zink & Remsen, 1986) may be adapted for helminths. NEUTRAL ALLELES AND POPULATION STRUCTURE Natural selection can be more effective than genetic. drift in either preventing or establishing local differences in allelic frequency (Haldane, 1930; Nagylaki, 1975). However, in the absence of selection, unpredictable changes in allelic frequency will occur because of finite population size and genetic drift (Fisher, 1930; Wright, 1931). Unlike natural selection, genetic drift should have the same average effect on all nuclear genes (Slatkin, 1987), and will be opposed by gene flow. Population genetic theory indicates that one or more individuals exchanged between two populations per generation is sufficient to prevent different neutral alleles from becoming fixed in the two populations (Wright, 1931). Importantly, even without gene flow, little differentiation of local populations will occur if the average time a population persists in one area is less than the time it takes for genetic drift to fix neutral alleles (Slatkin, 1987). This time factor is also dependent on the effective population size for the species under consideration, and can be many generations. Allelic frequencies provide one indirect method to estimate tevels of gene flow between populations. However, the geographic distribution of allelic frequencies does not, by itself, indicate levels of gene flow. Indirect methods must discriminate among patterns resulting from gene flow and those resulting from natural selection and genetic drift. Two methods for estimating gene flow from allelic data have been used. One is Wright’s FSTstatistic, which estimates the standardized variance in allelic frequencies among demes (Wright, 1931, 1951). Wright (1931) proved that for alleles that behave as if they are selectively neutral, FsT = l/( 1 + 4Nm), where N = local population size, and m = average rate of immigration assuming that every deme is equally accessible to others (high dispersal ability). The parameter Nm (which represents both the relative level of gene flow to genetic drift and the number of individuals exchanged between demes per generation), can be estimated by rearranging Wright’s formula. Only if Nm is less than 1.0 will genetic drift cause high levels of interdemic differentiation (Slatkin, 1987). The other indirect estimate of gene flow (Slatkin, 1985) is calculated from frequencies of rare alleles (alleles found only in one or a few populations). Slatkin (1985) related the average frequency of alleles in a single population to a function of Nm: In [p(l)] = aln (Nm) + b, where p(l) is the average frequency of alleles in one population sampled, and a and b are constants defined by the number of individuals sampled per population.

20

S. A. NADLER

Wright’s and Slatkin’s methods produce consistent estimates of gene flow over a range of assumptions concerning population structure, selection, and mutation (Slatkin, 1987). Simulations have shown that for both methods, loci with different mutation rates and those subject to different selection regimes produce similar Nm estimates (Barton & Slatkin, 1986). However, if natural selection maintains different alleles at high frequencies in different populations, then an Nm of much less than 1.O would be estimated. This would suggest little or no gene flow between populations, regardless of the actual level. Obviously, then, gene flow estimates should not be based on one or two polymorphic loci. In general, estimates based on different loci are consistent, taking into account sampling error. When one locus is markedly inconsistent with all others, selection may be affecting that locus (Slatkin, 1987). Virtually no data pertaining to population structuring or gene flow are available for helminths. However, for heuristic purposes, I have used data from a previous study (Nadler, 1986) to calculate F statistics (Wright, 1965, 1978), for four populations of the nematode T. cati, each obtained from a different domestic cat host in New Orleans, LA, U.S.A. Mean F statistics (six polymorphic loci) were: F,s = - 0.022, F,T = 0.146, and FST = 0.165. Wright’s inbreeding coefficient (F,,) represents the level of inbreeding in individuals relative to their subpopulation. When F,, is near zero, random mating within subpopulations is indicated. Thus, in T. cati, mating between relatives within subpopulations occurs no more frequently than expected by chance. F,T measures the inbreeding of individuals relative to the total population. F,T measures the effects of non-random mating within subpopulations (F,,) plus population subdivision (FST). Therefore, when F,, = 0, F,T r FST. This is apparent in the case of the T. cati example, where F,, 2 0 and Fh z F,,. FSTvalues have great comparative value in studies of population structuring over geography or comparisons of population structure among species. Comparisons of FST for different helminth species collected from the same host populations could provide insights into how life history parameters of parasites may affect gene flow. Gene flow can retard genetic change by reducing the effects of natural selection and genetic drift. Conversely, gene flow can increase rates of genetic change, as Wright (1932, 1982) modelled in his ‘shifting balance’ theory. Whether gene flow retards or increases rates of genetic change depends on a population’s structure, particularly its demography. In species composed of small, isolated populations, genetic drift could result in a genotype of greater adaptive fitness. Gene flow between demes could spread this new genotype. This outcome is likely only if genetic drift can overcome selection and fix combinations of genes that constitute a genotype of enhanced fitness. For species that tend to have highly

clumped distributions, 1985), colonizations evolution.

as in some parasites (May, may promote rapid genetic

II. MOLECULAR

PHYLOGENY

APPROACHES TO RECONSTRUCTION

For many groups of free-living organisms, biochemical and molecular approaches are now standard methods for reconstructing evolutionary history. Although molecular approaches to systematics are not universally accepted, their tremendous potential has often been enthusiastically endorsed (Gould, 1985). Because a group of organisms has only one evolutionary history, phylogenetic studies based on molecular characters should, in theory, be congruent and additive to studies based on morphological characters. Congruence among independent studies based on different suites of characters is strong evidence for a particular phylogenetic estimate. Incongruence between studies may have many causes including homoplasy, low resolving power of the technique (forcing dichotomous branches that are not strongly supported), or use of tree building algorithms with different evolutionary assumptions. ADVANTAGES AND LIMITATIONS OF MOLECULAR DATA Molecular data have several attributes that are attractive to evolutionary biologists, particularly those whose research involves organisms with few morphological characters available for study. However, molecular and morphological studies can be complementary (Hillis, 1987) and in combination may help resolve questions that cannot be addressed using a single approach. The number of potential characters is one advantage of molecular data sets. In theory, the number of characters is limited only by the number of non-repetitive nucleotide positions in the genome. Recent advances in the methodology of nucleic acid sequencing (Saiki et al., 1985, 1988; Wrischnik et al., 1987) allow molecular systematists to use a large number of nucleotide characters. Another significant advantage of molecular approaches is the range of phylogenetic questions that can be addressed. Because different genes (or regions of the same gene) may evolve at different rates (Gillespie, 1986), a broad spectrum of phylogenetic questions, ranging from recent speciation events to ancient lineage splits, can be studied. For example, mitochondrial DNA (mtDNA) tends to evolve rapidly (Brown, George & Wilson, 1979; Avise & Lansman, 1983) and can be used to elucidate phylogenetic relationships among closely related species (Brown & Wright, 1979). In contrast, some other genes are highly conserved, and have such slow rates of change that nucleic acid

Molecular systematics of helmi~ths

sequence comparisons can be made for virtually all living organisms. For example, regions of ribosomal RNA genes have been used to develop phylogenetic hypotheses relating representatives of phyla of extant animals (Field, Olsen, Lane, Giovannoni, Ghiselin, Raff, Pace & Raff, 1988; Cedergren, Gray, Abel & Sankoff, 1988). Finally, it is essential that the characters used for phylogenetic analysis are heritable, and not altered by environmental factors. Non-heritable variation is not considered to be a problem for nucleotide sequences, however, the proteins detected by electrophoresis can be modified by environmental factors, particularly as a result of improper handling of samples and posttranslational events (Dessauer 81 Menzies, 1984). Although it is known that the morphology of adult cestodes can be influenced by the definitive host species in which they develop (Schantz, Colli, Cruz-Reyes & Prezioso, 1976), studies of other helminths are needed to assess how frequently environmental and host factors alter parasite phenotypes. Despite the advantages of molecular data for phylogeny reconstruction, not all evolutionary histories are recoverable. Simulation studies have demonstrated that for stochastically evolving molecular characters, only some of the modelled phylogenies can be reconstructed reliably with molecular data (Lanyon, 1988). If the period of shared ancestry of two groups is short, then rapidly~vol~ng molecular characters have the highest probability of evolving derived states in the common ancestor of the species studied. However, if the period of shared ancestry is short and time since speciation is long, then these rapidly-evolving characters will continue to change (become autapomorphic), and their phylogenetic information will be lost. Furthermore, if speciation of the taxa under consideration occurred as a rapid evolutionary radiation, then slowly evolving molecular characters are not likely to change during the relatively short period(s) of common ancestry. Thus, these slowly evolving molecular characters will also not be informative for assessing phylogenetic relationships in the group (see tanyon, 1988 for full discussion). PHYLOGENETIC APPLICATIONS OF MOLECULAR DATA Protein electrophoresis The utility of protein-electrophoretic data for phylogenetic studies is generally limited to analysis of closely related species (Avise & Aquadro, 1982; Thorpe, 1983). However, the applicability of the technique cannot be inferred simply from taxonomic rank because species with substantially different levels of genetic differentiation may be ranked at the same taxonomic level. For example, multilocus electrophoretic studies of congeneric schistosomes (Woodruff et al., 1987), ascaridoid nematodes (Bullini, Nascetti, Ciafre, Rumore, Biocca, Montalenti & Rita, 1978;

21

Nascetti, Grappelli, Bullini & Montalenti, 1979; Nadler, 1987b), and anoplocephalid cestodes (Baverstock, Adams & Beveridge, 1985) revealed that species within a genus may be highly differentiated at the genetic level. In fact, levels of genetic distance between congeners of helminths (e.g. ascaridoid nematodes, anoplocephalid cestodes, s~histosomes) are often greater than levels reported between genera of mammals (Avise & Aquadro, 1982). If these helminth congeners have rates of protein change that are roughly equivalent to vertebrates, then it is likely that they diverged tens of millions of years before present (Bullini et al., 1978; Nadler, 1987b; Woodruff et at., 1987). Some helminths that are considered closely related based on mo~hological studies have been found to be distantly related genetically. For example, the genetic distance between the sibling species of the nematodes A. simplex and Anisakis pegrefii is characteristic of that found between sibling species of other animals (Nascetti et al., 1986). Thus, the applicability of protein-el~trophoretic methods to phylogen~tic analysis of helminths cannot be inferred directly from morphological distinctiveness among taxa; it must be tested on a case-by-case basis. High levels of protein differentiation (large genetic distances) hinder phylogenetic analysis because when Nei’s (1978) genetic distance measure approaches 1.OO,the amount of electromo~h similarity resulting from chance convergence becomes high (Maxson & Maxson, 1979). Thus, regardless of the tree-building method employed, the resulting trees may be misleading. In terms of cladistic analysis, few informative characters (synapomorphies) would be expected to be retained; those alleles that do unite taxa may result from convergence instead of shared derived ancestry. Few electrophoretic studies of helminths have focused on evolutionary history. In a study ofcestodes from marsupials, Baverstock et al. (1985) surveyed 18 taxa of Progamotaeniu at 16 presumptive gene loci. Because these taxa were highly differentiated at the genetic level, the species were clustered using the unweighted average-linkage method (UPGMA: Sokal & Sneath, 1963). This method will only reflect phylogenetic relationships if the rate of protein evolution has been roughly equal among all lineages (Tateno, Nei & Tajima, 1982; Baverstock et al., 1985). The resulting cestode phenogram (Baverstock et al., 1985) did not conform to expectations based on the assumption of host-parasite cospeciation, and these authors concluded that there was little evidence for cospeciation in the assemblage. Also, the genetic analysis revealed many more species of bile duct cestodes than did morphology, indicating that the Progamotuenia festiva complex contains many cryptic species. For many groups of helminths, protein electrophoresis will have greatest value as a taxonomic tool for identifying and disc~minating species. As is clear

22

S. A. NADLER

in the previous example of anoplocephalid cestodes, protein electrophoresis is useful for determining the number of genetic units (species) in a complex of morphologically similar forms. Fixed genetic differences between sympatric taxa are strong evidence that the forms are not interbreeding, and are therefore distinct (biological) species. The chromosomally and electrophoretically distinct ascaridoid nematodes Parascaris equorum and Parascaris univalens (sympatric parasites of equines) produce only F, hybrids under natural conditions (Bullini et al., 1978). The electrophoretic data reveal an absence of introgression between these morphologically undifferentiated species (Bullini et al., 1978) and this must be the result of a post-mating reproductive isolating mechanism. In an electrophoretic study of Anisakis larvae, Nascetti et al. (1986) found a complete absence of heterozygotes at certain polymorphic loci and significant departure from Hardy-Weinberg equilibrium expectations (heterozygote depression) at other loci. These results suggested that the Anisakis samples consisted of two distinct gene pools, and on this basis Nascetti et al. (1986) identified the samples as A. simplex and a new species, A. pegrefJi. The interpretation of electrophoretic data is not as straightforward for morphologically similar, but allopatric, taxa. High levels of genetic differentiation suggest strongly, but do not prove, that the taxa under consideration are separate (biological) species. In practice, however, when morphologically similar allopatric taxa have levels of genetic distance characteristic of other interspecific comparisons in the group, it is probable that these taxa are reproductively isolated. Restriction endonuclease andnucleic acidsequence data Characters obtained by restriction enzyme mapping of DNA have proved useful for phylogenetic analysis ofvertebrates (Hillis & Davis, 1986), but this approach has not been used to study helminth phylogeny. Restriction endonuclease studies of helminths have involved identification of species (Curran, Baillie & Webster, 1985), characterization of strains (Klassen, Thiessen & Dick, 1986), or genetic comparison of congeners (Chambers, Almond, Knight, Simpson & Parkhouse, 1986). Restriction endonuclease data are applicable to a wide range of phylogenetic questions, providing that sequences with appropriate rates of divergence are available for study. However, the greater resolution obtained by nucleic acid sequencing in combination with the advent of labor-saving directsequencing methods have caused many systematists to discontinue restriction endonuclease methods in favor of direct sequencing. Nucleic acid sequencing methods have the potential to resolve phylogenetic questions ranging from recent speciation events to divergences among ancient lineages. The ability to resolve evolutionary history at a particular level is dependent on finding a gene(s) with an appropriate rate of change. An advantage of

nucleic acid sequence data is the unambiguity of the resulting homologous characters. In addition, typical nucleic acid data sets contain large numbers of characters, although many of these are phylogenetically uninformative. There are, of course, potential problems associated with the use of sequence data in phylogeny reconstruction. Because there are only five possibilities for a character (i.e. four nucleotides plus gaps) at any given site, the probability of convergence is high, especially for anciently diverged taxa. Alignment of sequences remains primarily subjective, and is compounded by the effects of substitutions and length variation, which increase with greater evolutionary divergence among taxa. In addition, virtually all methods of phylogenetic analysis depend on the assumption that each character evolves independently (Felsenstein, 1982) which may be invalid for functional nucleic acid molecules with secondary structure (Wheeler & Honeycutt, 1988). Mutations in regions of RNA where base pairing exists may cause strong selection pressure for complementary mutations in the pairing strand (Wheeler & Honeycutt, 1988). The extent of this nonindependence in larger ribosomal RNA molecules is unknown, but if such complementary changes are frequent it may prove necessary to identify and compensate for coevolving positions (Wheeler & Honeycutt, 1988). Phylogenetic investigations of helminth relationships based on nucleic acid sequence data have focused on ribosomal RNA molecules (Qu, Hardman, Gill, Chappell, Nicoloso & Bachellerie, 1986; Gill, Hardman, Chappell, Qu, Nicoloso & Bachellerie, 1988). Ribosomal genes are advantageous for phylogenetic studies because they evolve in a concerted fashion (Arnheim, 1983) and therefore genetic variants are rapidly fixed within reproductive units. Thus, for studies of genes that evolve in a concerted fashion, a single individual should be representative of the species. Because ribosomal genes contain both slowly and rapidly evolving domains (Hassouna, Michot & Bachellerie, 1984) RNA sequence data may be used to address an array of phylogenetic questions. Direct sequencing of rRNA is particularly applicable to studies of helminths and other parasites because RNA templates suitable for sequencing may be prepared from relatively small amounts (approximately 100 mg) of frozen tissue. Ribosomal RNA sequence data may resolve helminth phylogenies where other methods have failed. For example, the time scale of divergence for ascaridoid nematodes precludes meaningful protein-electrophoretic phylogenies (Nadler, 1987b), but some regions of small and large subunit rRNA have proved phylogenetically informative at the intergeneric and congeneric levels (Nadler, in preparation). Applications of sequence data to studies of helminth phylogeny have been limited. Qu et al. (1986) studied representative species of cestodes, trematodes, and nematodes, and Gill et al. (1988) studied the

23

Molecular systematics of helminths relationships among these taxa and certain filaria. Qu et al. (1986) demonstrated the applicability of direct sequencing of large subunit rRNA for analysis of helminth relationships. They used a simple averaging method for clustering K,, values (rates of nucleotide replacement) derived from aligned sequences of two 28s rRNA domains. The resulting phenogram was rooted at the midpoint of the longest branch; thus, it only represents phylogenetic relationships if rates of nucleotide change have been equal in all lineages. Another shortcoming of this (or any) distance approach is that the independent nature of the nucleotide data is obscured. Nevertheless, the phenogram of rRNA relationships (Qu et al., 1986) grouped some of the taxa as traditionally expected. For example, Onchocerca gibsoni and Brugia pahangi (Filaridae) are represented as sister taxa, and the cestode (Hymenolepis diminuta) and trematode (S. mansoni) are represented as sister taxa (among the taxa studied). Surprisingly, Nematospiroides dubius did not cluster with the other nematodes. In the other rRNA comparison of helminths (Gill et al., 1988), nine species, including five filiaroids, were sequenced for three domains of the large ribosomal subunit. A dendrogram was derived from the distance matrix for the two conservative rRNA domains; in it, three distinct groupings of helminths are present. One contains the two platyhelminth species, H. diminuta and S. mansoni. The second group contains the nematodes Cuenorhabditis elegans (free-living) and N. dubius (endoparasitic). The third group contains five filiaroid nematodes (0. volvulus, Onchocerca gutturosa, 0. gibsoni, B. pahangi, and Litomosoides carinii) plus an ascaridoid nematode (Parascaris sp.). By using a rapidly evolving sequence domain, Gill et al. (1988) resolved genetic relationships among the six taxa in the third group. Although the standard errors around the nodes of this phenogram were large, the clustering of these species conformed to traditional systematic expectations. Figure 2(A) depicts the relationships among representative taxa from the dendrogram of Gill et al. (1988). However, the finding that N. dubius and C. elegans do not cluster with the other nematodes is controversial (Gill et al., 1988). Cedergren et al. (1988) suggested that C. eZegans has a rapid mutation rate for rRNA genes (Cedergren et al., 1988), and this could confound any distance clustering procedure, including the approach used by Gill et al. (1988). However, Gill et al. (1988) addressed this problem by using relativerate tests (Sarich & Wilson, 1967); they reported that C. elegans and the other organisms studied had approximately equal rates of rRNA nucleotide change for the rRNA domains they studied. In contrast to the distance matrix analysis of Gill et al. (1988), my cladistic (maximum parsimony) reanalysis of their sequence data reveals that the nematode taxa studied represent a monophyletic group (Fig. 2B,C). Maximum parsimony analysis yielded five different phylogenetic trees of equal length, however, all five

l4r

Mus musculus Xenoous laevis Hym&o/epis diminuta Schistosoma mansoni Onchocerca gibsoni Litomosoides

A r

I

carinii

Nematospiroides dubius Caenorhabditis elegans 4

Saccharomyces

. r+E carlsbergensis 1 -M

2

4

C

::

;a

kl

3

; N c

FIG. 2. Analyses of nucleic acid sequence data for conservative domains of large subunit rRNA (data from Gill et al., 1988). Branch lengths are arbitrary; figures depict branching dichotomy only. Taxon abbreviations correspond to first letter(s) of genus name. Numbered groups are: 1 = vertebrates, 2 = cestodes/trematodes, 3 = nematodes, ?nd 4 = yeast. A. Dendrogram derived from pairwise distance matrix (after Gill et al., 1988; Fig. 2). 9. One of five ‘unrooted’ cladistic trees of equal length (15 1 steps) with a consistency index of 0.68. C. Phylogeny showing resolution of branching shared among all most parsimonious trees.

trees resolved the nematodes as monophyletic; the unresolved regions of the tree involve the branching order among vertebrates, yeast, and cestodes/ trematodes (Fig. 2C). METHODS OF DATA ANALYSIS Despite statements to the contrary, all available methods of inferring phylogenies have implicit assumptions about the evolutionary process (Felsenstein, 1982, 1988). There is no single method of analysis that estimates phylogenetic history under all possible conditions. As noted by Felsenstein (1988), inferring phylogenies should be viewed as “making an estimate of an unknown quantity, in the presence of uncertainty, and using a probabilistic model of the evolutionary process”. Presenting a single ‘best phylogeny’ as the result of a computer-assisted analysis of the data may be misleading because some alternative phylogenies may be equally acceptable from a statistical standpoint. The most commonly used approaches for inferring phylogenies from molecular data are discussed briefly in the following section. For more comprehensive discussion and debate concerning these methods the reader is referred to the following literature and references therein: Farris (1983), Felsenstein (1982,

24

S. A. NADLER

1988), Felsenstein & Sober (1986), Sober (1987) and Wiley (1981). Parsimony methods

Maximum parsimony is probably the most widely used method of inferring phylogenetic relationships. The goal of parsimony analysis is to find the arrangement of taxa (network) and branch points (nodes) that minimizes the number of character state changes (or steps) necessary to account for observed variation in the data set. This process is often referred to as ‘character optimization’. For nucleic acid sequence data, the goal of maximum parsimony is to find the network (unrooted tree) with the minimum number of base substitutions. The network is rooted by reference to one or a series of outgroups. Because of the computational difficulties associated with completing this process manually for data sets of even moderate size (number of taxa especially, but also characters), computer programs employing mathematical algorithms are used to either find or estimate the maximally parsimonious tree(s) (e.g. PAUP, D. L. Swofford, Illinois Natural History Survey; PHYLIP, J. Felsenstein, Dept. of Genetics, University of Washington, Seattle, U.S.A.). Different parsimony models vary in their evolutionary assumptions (Felsenstein, 1982). The popular Wagner model (Kluge & Farris, 1969) is less restrictive than other methods in that the ancestral character states do not need to be specified in advance, and there are no limits on the number of character state changes, or on reversals from a derived to an ancestral state. In contrast, the Dollo parsimony model allows one ‘forward’ change, but as many reversals as necessary (Felsenstein, 1982). The Do110 model is appropriate for analysis of complex characters such as RFLP data because losses of a restriction site (reversals) occur at much higher frequency than site gains. Justifications for the parsimony approach have included both statistical (Felsenstein, 1973; Sober, 1985), and hypothetico-deductive arguments (Wiley, 1981). Statistical justifications appear to be valid only when expected amounts of character change are low (Felsenstein, 1982). Thus, when changes in character states are rare, the phylogenetic tree that requires the fewest number of changes represents a reasonable interpretation of the data. In the hypothetico-deductive justification, each additional character state change is considered to require an additional evolutionary hypothesis. If each extra hypothesis is considered to be refuting the correctness of the phylogenet~c tree, then the parsimony criterion can be viewed as accepting the least rejected hypothesis. Difficulties in implementing parsimony methods for analysis of molecular data occur when polymorphism of character states is present and when rates of nucfeotide substitution are high. Polymorphism is problematic for protein-electrophoretic data where

multiple alleles are often present at variable loci. There is no consensus on the most appropriate treatment of polymorphic characters in parsimony analysis, although several different approaches have been discussed (Mickevich & Mitter, 1981; Fetsenstein, 1982). Distance methods

Distance methods do not use discrete character state data, but instead transform the original data into a pairwise matrix of distances, and then fit a phylogenetic tree to this matrix. It is necessary to assume that transformation of the data into pairwise distances does not result in a significant loss of info~ation. Another assumption is that the expected distances between taxa represent sums of branch lengths along the tree. The objective of distance methods is to minimize differences between observed and expected distances calculated for the resulting tree. lt is not necessary to assume a ‘molecular evolutionary clock’ (i.e. on average, nucleotide or amino acid substitutions accumulate at a nearly constant rate) to use distance methods; some methods do assume a stochastic clock, and others make no assumption about rates of molecular change. For example, one of the most widely used clustering methods, UPGMA, only works optimally if the data conform to a clocklike evolutionary model. The UPGMA method assumes that the length of each branch is proportional to evolutionary time. Other methods, such as that of Fitch & Margoliash (1967), calculate branch lengths based on the actual number of substitutions. This method is appropriate when rates of molecular change vary among different lineages, but not too widely (Felsenstein, 1982). Maximum fikelihood methods

Maximum likelihood is a statistical approach designed to choose a phylogeny that maximizes the probability of the data given a tree. The appeal of likelihood methods of inferring phylogenies has grown with the accumulation of large nucleic acid sequence data bases and the availability of computer programs to perform the calculations (e.g. PHYLIP; see reference above). One advantage of the maximum likelihood method is that, in certain cases, the likelihood-ratio test can be used to discriminate among alternative trees (Felsenstein, 1988). The main disadvantage of likelihood methods is that they require a parametric model of character change, and for many data sets this model may be inappropriate. In variants Invariants or operator metrics are applications of vector mathematics to the analysis of nucleic acid sequence data; these methods are insensitive to differences in branch lengths and rates of substitution at different sites (Cavender & Felsenstein, 1987; Lake,

Molecular

systematics

1987a, b). This method of analysis was developed because it was recognized that parsimony methods can support the wrong phylogeny when rates of nucleotide change in the peripheral branches of a tree are very different (Felsenstein, 19’78). Methods of invariant analysis are currently limited to testing the relationships among four taxa. In Lake’s method (1987b), the aligned sequences of the four taxa are examined for patterns of nucleotides (termed vectors). Lake (1987b) only considers vectors of the transversion class (those substitutions that exchange a purine for a pyrimidine, or vice-versa) as informative characters because they are much less frequent than transitions (Brown, Prager, Wang & Wilson, 1982). The distribution of vectors is then used to choose among the three alternative arrangements of four taxa and to evaluate the statistical significance of a given topology (Lake, 1987b). One of the drawbacks of Lake’s invariant analysis is that it is relatively uninformative for closely related species, where transversion differences among taxa may be rare.

Data resampling methods involve repeated random sampling from a data set to determine empirically the certainty in an estimate of phylogeny. For example, with nucleotide sequence data, if different sites support different phylogenetic hypotheses, a larger variability estimate will result than in the case where little homoplasy exists. Two approaches to data resampling, jackknifing and bootstrapping have gained popularity for analyzing the robustness of phylogenetic trees. Felsenstein (1985) described a bootstrap method of resampling phylogenetic data sets where characters are drawn randomly with replacement until a new data set of the same size as the original is obtained. With each resampling, some characters (e.g. nucleotide sites, isoenzyme loci) may be sampled more than once, and others not included. For each sample of characters, an estimate of phylogeny, using a specified analysis, is derived. Data resampling methods assume that the data points can be treated as having evolved independently on the same phylogeny. Felsenstcin (1985) developed this approach to assess confidence in particular groupings of species. If a group of species occurs in 95 of 100 bootstrap replicates, then the group can be considered to be supported (monophyletic) at the 95% confidence level. However, this application is valid only if the group to be tested for monophyly is chosen a priori, or if multiple-tests correction is applied to the outcome (Felsenstein, 1988). Mueller & Ayala (1982) developed a jackknife resampling method for genetic distances derived from protein electrophoresis. In this method, one locus is dropped at a time, and the branch lengths of the tree are recalculated each time. The values obtained are used to estimate the variance of the branch lengths. This method is also applicable to other distance data

of helminths

25

such as those derived from nucleic acid sequence comparisons. Recent emphasis on methods of assessing the reliability of phylogenies in a statistical framework (Felsenstein, 1988) stem from the problem that dichotomous branching structures (trees) can be constructed from data sets even when there is no strong support for the branch points. A complete discussion of the applications and limitations of such statistical tests has been published elsewhere (Felsenstein, 1988). FINAL COMME~ Parasitologists have rarely used the full potential of biochemical and molecular methods to study the population genetics and phylogeny of helminths. Multilocus genetic studies are needed to define the nature of helminth demes, and to assess the amount of gene flow among demes. These studies would be enhanced by parallel analyses of geographic variation in morphology. Although studies suggest that certain helminths may have relatively low levels of amongpopulation genetic divergence, it is unwarranted to extend this conclusion to other species. Helminths with different life cycles and ecology may have very different population structure. In addition, helminth population structure may be strongly influenced by elements of host biology, including the size of the home range, barriers to dispersal, and ethological factors. Mol~ular approaches shoufd also prove extremely valuable for studying the systematics of helminths. The high levels of protein genetic distance reported between many helminth congeners suggest that electrophoresis will remain most useful for identifying cryptic species, confirming the conspecificity of different life-cycle stages, and discriminating between species of morphologically similar larvae. For investigation of helminth evolutionary history, nucleic acid sequencing studies have the potential to resolve a wide range of phylogenetic questions. Initial studies (Qu et al., 1986; Gill et al., 1988) have revealed that direct sequencing of slowly evolving domains of ribosomal RNA is useful for comparisons of distantly related helminths; rapidly evolving domains are informative for more closely related species (Gill er al., 1988). However, although the evolutionary histories of helminths may be resolved by studying sequence domains with appropriate rates of change, it is important to recognize that not all evolutionary histories are recoverable. Finally, when possible, methods of phylogenetic inference that retain the character-state nature of the data should be used, and the robustness of the resulting trees tested. Acknowledgemmfs-I am grateful toT. P. Friedlander,

M. S. Hafner. and R. M. Zink for reading earlier drafts of the manuscript. I thank G. F. 3arrowclo~gh for providing the NEWTRL computer program. I also thank A. Nadler for

26

S. A. NADLER

typing assistance. This work was supported grants BSR-8607223 and BSR-8817329.

in part by NSF

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