Subunit size and genetic variation of enzymes in natural populations of Drosophila

THEORETICAL

POPULATION

Subunit

BIOLOGY

330-341 (1977)

Size and Genetic Natural RICHARD

Department Institute

11,

Variation

Populations K. KOEHN

of Enzymes

in

of Drosophila

AND WALTER

F. EANES

of Ecology and Evolution,

State University of New York, Stony Brook, New York 11794, and of Ecology and Genetics, University of Aarhus, Aarhus, Denmark Received September

7, 1976

The relationships between various measures of enzyme polymorphism and subunit molecular weight of 11 dimeric Drosophila enzymes were analyzed with data from the current literature. All correlations were positive and highly significant. Eighteen percent of the variance of the numbers of alleles per sample for each locus and 60 “/u of the variance of the average numbers of alleles per locus were due to variations of subunit weight. Identical results were obtained from analyses of heterozygosity. Small subunit dimers exhibit a characteristic skewed frequency spectrum of alleles, while the alleles of larger subunit enzymes are more equal in frequency. These relationships suggest that enzyme polymorphism is related to the enzyme structure, particularly weight (size), of constituent subunits.

For more than 100 years, evolutionary biologists have been concerned with discovering the adaptive significance of genetic variation in populations of organisms. Several decades ago, contrasting views were debated as the “selectiondrift” controversy, but with the introduction of electrophoretic methodology and upon publication of Lewontin and Hubby’s now classic paper (Lewontin and Hubby, 1966) the problem was revitalized as the “neutralist-selectionist” debate (Kimura and Ohta, 1971; Lewontin, 1974; Nei, 1975). While widespread enzyme polymorphism in nature is now known, the adaptive significance of this variation is unclear (Lewontin, 1974; Ayala, 1976). According to the neutral theory (Kimura and Ohta, 1971; Nei, 1975), polymorphism is maintained by neutral and deleterious mutations as they interact with population size and population structure. Selectionists have attempted to demonstrate the adaptive significance of allozymes by relating various parameters of genetic heterozygosity to environmental variations (see Bryant, 1974), resource stability (Valentine, 1976), environmental patchiness and life-cycle interactions (Selander and either with regard to substrate Kaufman, 1973), and enzyme functions, heterogeneity (Gillespie and Kojima, 1968; Gillespie and Langley, 1974; 330 Copyright All rights

0 1977 by Academic Press, Inc. of reproduction in any form reserved.

ISSN

0040-5809

SUBUNIT SIZE AND GENETIC VARIATION

331

Johnson, 1974) or regulation of metabolism (Johnson, 1974). Though levels of genetic variation may often be correlated with any of these potential selective (and therefore, evolutionarily significant) forces, how individual enzyme loci are directly affected is generally unknown. Precise measurements of the adaptive role of enzyme polymorphism and the structural and functional bases for the adaptation will profoundly affect our understanding of the evolutionary process. Recently, it has become apparent that levels of enzyme polymorphism may be a function of molecular structure: There is a striking correlation of electrophoretic variability at specific enzyme loci among some species of Drosophila (Ayala et al., 1974; Koehn and Eanes, 1976) and a relationship between heterozygosity and enzyme subunit number in several organisms (Zouros, 1976; Ward, 1977). We have analyzed data from the current literature on enzyme subunit sizes and magnitudes of electrophoretic polymorphism in Drosophila. We shall demonstrate that for enzymes of dimeric subunit composition, 60% of the average per locus heterozygosity and numbers of alleles can be attributed to the size of their constituent molecular subunits.

MATERIALS

AND METHODS

Information is presently available on the molecular weight and subunit composition of 27 proteins in Drosophila melanogaster (O’Brien and MacIntyre, 1977). However, of these 27 proteins, only I1 are commonly studied in surveys of genetic polymorphism in natural populations of Drosophila. These are all dimers (except Ald) and include: superoxide dismutase (EC 1.15.1.1), 18,000 s.m.w. (Tegelstrom, 1975); alcohol dehydrogenase (EC 1.I. 1.l), 26,333 s.m.w. (Ursprung and Carlin, 1968; Sofer and Ursprung, 1968; Jacobson and Pfuderer, 1970; Schwartz et al., 1975); malate dehydrogenase (EC 1.I .I .37), 28,000 s.m.w. (O’Brien, 1973); cu-glycerophosphate dehydrogenase (EC 1.1.1.18), 32,067 s.m.w. (O’Brien and Maclntyre, 1972; Bewley et al., 1974); aldolase (EC 4.1.2.13), 39,750 s.m.w. (Brenner-Holzach and Levthardt, 1969, 1971); acid phosphatase (EC 3.1.3.2), 50,000 s.m.w. (MacIntyre, 1971); octanol dehydrogenase (EC 1.1.1. ?), 55,000 s.m.w. (Pipkin, 1969; Sueber et al., 1972; Courtright et al., 1966); glucose 6-phosphate dehydrogenase (EC 1.1.1.49), 76,375 s.m.w. (Steele et aZ., 1968); aldehyde oxidase (EC 1.2.1.3), 132,000 s.m.w. (Courtright, 1967); xanthine dehydrogenase (EC 1.2.3.2), 140,000 s.m.w. (Seybold, 1973; Candid0 et al., 1974); and alkaline phosphatase (EC 3.1.3.1), 150,000 s.m.w. (Beckman and Johnson, 1964; Harper and Armstrong, 1973). Only a few Drosophila monomer molecular weights are known, too few to permit an analysis like that below. These enzymes are all known structural dimers, except for aldolase, whose

332

KOEHN

AND

EANES

structure may be either a dimer or tetramer (Brenner-Holzach and Levthardt, 1969, 1971). In our analyses, we have assumed that aldolase is a tetramer. The relationships we describe below are all strengthened if aldolase is assumed to be a dimer. For each of the enzymes included in our study, the total number of electrophoretic alleles observed and their expected heterozygosities were tabulated from population samples reported up to and including 1975. These included a total of 84 population samples of 30 Drosophila species, though the number of samples per enzyme ranged from 17 to 57 (% = 41). No population samples were pooled, unless by the original author (these tend to be from the same geographic area). As a consequence, some species, such as D. ananassae, D. melanogaster, and D. willistoni, are represented by multiple samples in our analyses. We have used the data as reported and have made no distinction in treatment between different species, subspecies, semispecies, or multiple samples of the same species. There is some bias toward polymorphic loci, since monomorphic loci are not typically reported and/or sample sizes are not usually given. Results are presented as untransformed variables, but all statistical tests were performed on arcsin transformed heterozygosity values and log transformations of numers of alleles and subunit molecular weights. Both transformations normalize the sampling variance of these parameters. Several analyses were done in order to estimate the relationship between polymorphism and subunit weight. Analysis of variance with regression (Sokal and Rohlf, 1969) was performed on the entire data composed of 11 groups (enzymes) and 433 estimates of variation. Two separate analyses, one each for numbers of alleles and heterozygosity, were done. This provided a test of the source of total and among-group variation that is due to linear regression with subunit weight, and deviations from regression. Variance components from each analysis were used to compute the overall regression coefficient, the product-moment correlation coefficient (Y), and the coefficient of determination (r”). The last is a measure of the proportion of variation in the two measures of polymorphism that can be attributed to variation of subunit size. The variables were estimated from samples of a few dozen to several thousand individuals per locus. Since the observed number of electrophoretic alleles is heavily sample-size dependent, a reanalysis was performed for estimates of polymorphism based on samples of 400 to 600 genes only. This has the desirable effect of reducing the sampling variance in the original data. Since the variance of heterozygosity is only slightly effected by sample-size heterogeneity, this analysis of variance was not done on among-group variations of heterozygosity. Finally, the average number of alleles per locus and the average per locus heterozygosity were computed. The correlation and regression statistics were determined between these unweighted averages and subunit molecular weight.

333

SUBUNIT SIZE AND GENETIC VARIATION RESULTS

There is highly significant positive correlation between the observed number of electrophoretic alleles per sample for each locus and their respective subunit molecular weights (r -= 0.422; p < 0.001). Wh en the analysis is performed on the average numbers of alleles/locus, the correlation is also significant, where approximately 60% of the variation in the average number of alleles/locus is explained by subunit weight (Table I). Enzymes composed of the smallest subunits (~25,000s.m.w.) exhibit an average of about 2.5 alleles over the 84 species populations, but enzymes with subunits of about 140,000 s.m.w. average 3.5 to 4.0 alleles per locus (Fig. 1). TABLE

I

.a Summary of the Results of Correlation and Regression Independence of Measures of Enzyme Polymorphism Their Respective Subunit Molecular Weights

Tests of the and

Variable

df

Y

72

Number of observed alleles per sample for each locus

431

0.422**

0.178

9

0.777%

0.603

431

0.413**

0.171

0.753*

0.567

113

0.526**

0.277

9

0.795**

0.632

Average number of alleles/locus Observed heterozygosity for each locus i-lverage heterozygosity

per sample per locus

Samples of 212 = 400 to 600 only Number of observed alleles per sample for each locus :lverage

* P

number of alleles/locus

9

0.02; ** P _. 0.001.

By reducing the original data to include only samples of 400 to 600 genes per locus, there is a substantial reduction in the sampling variance of estimating the numbers of alleles at a locus. In this case, approximately 28% of the total variation in numbers of alleles per sample for each locus can be explained by subunit size (Table I). As could be expected, average estimates of the number of alleles are not markedly altered by reducing the sampling variance in the original data. The correlation between average numbers of alleles per locus and subunit molecular weight is highly significant (Y = 0.795; p < 0.001) with 6394, of the variance of among locus means due to subunit size variation.

334

KOEHN

I

I

IO

20

I

40

SUBUNIT

AND

EANES

I

I

I

60

80

100

MOLECULAR

I

I

I

120 140 WEIGHT x IO-3

160

1. (X) Regression of average number of observed enzyme alleles per locus among 84 population samples of 30 Drosophila species on subunit molecular weight of the same enzymes from D. melunogaster. p = 2.1397 + 0.00001206X. (B) Same as A, but slope for samples of 2n = 400 to 600 only (see Table I). P = 2.8312 t 0.00002059X. FIG.

I

IO

20

4

40

SUBUNIT

FIG. 2.

I

I

I

I

I

60

80

100

120

140

MOLECULAR

WEIGHT

I

‘160

x Id3

Same as Fig. lA, but for average per locus heterozygosity. P = 0.0834 + O.OOOOO196X.

Approximately 17 and 51 o/0 of the variance of individual sample estimates of heterozygosity and the average locus estimates, respectively, can be explained by subunit size (Table I). Average heterozygosity per locus varies linearly from approximately 0.08 to 0.40 over the range of subunit weights represented in the data (Fig. 2). Heterozygosity is a function of both the number of alleles at a locus and their relative frequencies. Since the observed number of alleles increases as a

SUBUNIT

SIZE

AND

GENETIC

335

VARIATION

positive function of subunit molecular weight, it is not unexpected that per locus heterozygosity is also correlated with subunit size. The relationship of allele frequency distributions to variations in heterozygosity may be examined, independent of the number of alleles. The “L statistic” of Ewens (1972) is a measure of the shape of the allele frequency spectrum at a particular locus and was originally developed as a test of the neutrality hypothesis. For the infinite-allele model (Kimura and Crow, 1964) a locus having an observed number of alleles with a given sample size also has an expected allele frequency spectrum. L is a standardized measure of the allele frequency spectra under this neutral allele model. Loci with allele frequency distributions measured as L = 0.0 fit the expected distributions for neutral alleles, but loci with either skewed or uniform allele frequency distributions have L < 0.0 and L > 0.0, respectively. For example (Ewens, 1972), with a sample size of N = 350 and four observed alleles, L = 2.36 if the relative allele frequencies are 0.35, 0.30, 0.20, 0.15; L = 0.02 if the frequencies are 0.83, 0.11, 0.04, 0.02; and L = - 1.70 if the relative allele frequencies are 0.99, 0.005, 0.0025, 0.0025. Under the neutral hypothesis, L has zero mean and a standard deviation of one so that individual values of L can be approximately tested for significant deviation. Consistent with the suggestion of Ewens (1972), L is used in this study as a descriptor for comparing the average allele frequency spectra at different loci, rather than a test of neutrality.

- 1.2 20

40 SUBUNIT

60

so MOLECULAR

100 WEIGHT

120

140

160

x IO-’

FIG. 3. Relationship of average per locus L statistic (&SE) to subunit molecular weight. Skewed allele frequency distributions have L < 0.0 values (see text). Superoxide dismutase is not shown, since these data were unavailable to us for this analysis.

Enzymes composed of the smallest subunits, such as alcohol a-glycerophosphate dehydrogenase, octanol dehydrogenase, and genase, exhibit significantly skewed frequency distributions (Fig. 3). While these loci are on the average polymorphic (Fig.

dehydrogenase, malate dehydroon the average l), they consist

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KOEHN

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EANES

principally of a single very common electrophoretic allele. Among the 19 species we have compared in this analysis, a large number of dz&rent electrophoretic alleles were observed at each of these loci, but the pattern of allele frequency distributions was the same, irrespective of allelic composition. For enzymes composed of larger subunits, allele frequency distributions are less skewed ( i.e., more equal average frequencies). The average value of L is correlated with subunit size (r = 0.766; P < 0.005) and about 60% of the variance of L averages is due to subunit molecular weight variation.

DIscussIoN The larger the enzyme subunits, the greater the number of observed electrophoretic alleles and the higher the average heterozygosity of these alleles. Relative allele frequencies are similar among species populations. The degree to which subunit size explains the variance in measures of polymorphism depends only weakly on which measure of polymorphism is used, but more significantly on whether individual sample observations or locus averages are regressed on subunit size. We should emphasize that subunit weight (size) of dimers explains a small, but measurable, proportion of the variance in measures of polymorphism in this large data set. This low, but statistically significant, correlation (r -= 0.413) would mean that single species tests of this relationship would generally be weak, unless a very large number of loci are used. The unexplained variance around each mean estimate of enzyme variation could be due to both random and deterministic forces, which would include among-population variations in population size and intensity of selection. Deviations of average measures of polymorphism from a rigid dependence on subunit size could be due to variations of molecular structure and function that are uncorrelated with subunit size. These would include differences in function (Johnson, 1974) and differences in structural interactions with other molecular entities (e.g., membranes and other enzymes). The latter has been shown to influence structural variation (Dickerson, 1971). The relationships we have described are little affected by individual error estimates of polymorphism, but would be significantly affected by our use of erroneous molecular weights and/or subunit number for the various enzymes. Both heterozygosity and molecular structure estimates have error variances associated with them, but we do not know their relative magnitudes. The former is small as long as population samples are large and probably of little consequence to our analyses, as long as we restrict our statements to “electroEstimation errors for molecular weights phoretically detectable variation.” are probably on the order of 5 to IO:/,, judging from the few examples of multiple estimates for some enzymes. This error rate is small relative to the

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SIZE

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sevenfold difference in subunit weight among the enzymes. Errors of this magnitude could not significantly affect the conclusion that genetic variation increases as some positive monotonic function of subunit size, but may effect estimates of the shape of the function. While we have used a linear model, when more data are available some other model may be preferable. If, however, subunit compositions of some enzymes are not what they are purported to be, the patterns of correlation we have reported could be substantially altered. For example, there is conflicting evidence on the subunit number of aldolase (see above). The molecular weight is about 159,000. In enzyme hybridization studies, five electrophoretic components were detected, suggesting a tetrameric molecular structure, as in humans (Horecker, 1975). Isoelectric focusing, however, separated only three components, favoring a dimer composition. is We have assumed a tetrameric structure, but if the enzyme in D~osophiZu actually a dimer, the proportion of explained variance in polymorphism due to subunit size would increase. A major source of linear deviation variance in this study has been due to acid and alkaline phosphatases. The molecular weights and compositions determined for D. melanogaster enzymes are at least as accurate as for other enzymes we have included. However, for nonspecific enzymes such as these, there is probably very weak homology from one species to another. When multiple loci are reported for a species, it is impossible to know which is homologous to the melanogaster enzyme whose structure and weight has been determined. The variation in estimates of polymorphism for these two enzymes is large and both loci contribute substantial among-group unexplained variance. Molecular weight and subunit data on additional D7osophilu enzymes is required before the dependence of polymorphism on subunit size can be fully examined. There is less electrophoretic variation of multiple subunit enzymes than of monomeric enzymes (Zouros, 1976; Ward, 1977). Within smaller subunit dimers there is less polymorphism than in large subunit dimeric enzymes. In Drosophila, there is essentially no molecular weight information available for monomers and tetramers. For dimeric enzymes in humans, the same relationship between subunit size and number of alleles has been found (Eanes and Koehn, unpublished), but a relationship was only weakly suggested for functional monomers. These data imply to us that the positive correlations of measures of polymorphism with subunit size are due to the relative effect of structural mutation on the function of enzymes of differing structural complexities. If the correlations with subunit size were mainly due to the production of selectively neutral variants at variable rates dependent on gene size, these correlations should be observed among all enzymes, irrespective of quaternary structure. However, there are many differences in the structure of the human and Drosophila data sets, most notably in overall levels of enzyme polymorphism as well as the relationship between the numbers of alleles and their hetero-

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zygosities. It may be unjustified to extrapolate interpretations between the two groups, and this point should perhaps be left open to further examination, at least until molecular weights of DrosophiZu monomeric enzymes are available. The lower levels of polymorphism in multimeric enzymes suggest that structural variation of these enzymes is constrained (Ward, 1977), relative to monomers, at least in those multimers with small subunits. Hence, a reasonable interpretation of our results is that a mutational alteration of primary structure may or may not be deleterious in monomers, but when an altered subunit must combine with another to form the functional molecule, variations in its primary structure will generally be strongly selected against. This implies that the proportion of sites critical to the maintenance of quaternary structure in multimers may not be constant with variations in size. The highly skewed allele frequency distributions (L < 0.0, Fig. 3) are compatible with models of mutation to deleterious alleles (Kimura and Ohta, 1973; Ohta, 1973, 1974; Ohta and Kimura, 1975a,b). In this study, only small subunit enzymes exhibited significantly skewed allele frequency distributions. If selection restricts the allelic diversity of small subunit multimers, then what is the adaptive significance of the high levels of polymorphism of large subunit multimers? It is clear that more variation occurs in these enzymes, but our results do not provide a clear interpretation for this finding. These variations may be either adaptively important or selectively neutral. If these variations are assumed to be neutral, our results are in general agreement with expectations for neutral polymorphisms. However, to determine the adaptive status of existing variants in various structure classes of enzymes will require other kinds of data, for example, knowledge of allelic differences in biochemical properties. There are several important implications of our results that arise quite For example, electrophoresis does not irrespective of our interpretations. detect all alleles at enzyme loci. Nonelectrophoretic alleles have been identified by their properties of thermal stability (Bernstein et al., 1973) and response to molecular sieving (Johnson, 1976). We would predict that more “cryptic” alleles will be detected for large subunit enzymes and monomers than for small subunit multimers. What little information is presently available tends to support this expectation, where the average number of thermostability alleles per electrophoretic allele has been described as 1.00 Adh alleles (Milkman, 1976), 1.45 Odh alleles (Singh et al., 1975), and 1.74 Xdh alleles (Bernstein et aZ., 1973). Variants were sought, but not found, for c+Gpdh (Milkman, 1976). It is obvious that levels of enzyme polymorphism are not distributed randomly over all loci. Theoretical models and simulations need to accommodate this observation to the extent that a particuZar enzyme will generally reside in a specific variability class. A unique implication of our findings is that variation hypotheses based on subunit size and/or structural complexity are testable. Molecular structure

SUBUNIT SIZE AND GENETIC VARIATION

339

can be more accurately characterized than “environmental heterogeneity” or effective population size. That is not to say that these are unimportant in maintaining genetic polymorphism in nature. Rather, that “average heterozygosity” is a composite of several evolutionary forces that appear to contribute disproportionately to variation of enzymes of different structure. This may ultimately provide the key to understanding if and to what extent specific evolutionary forces operate at specific enzyme loci in nature.

ACKNOWLEDGMENTS D. J. Futuyma, M. Nei, G. B. Johnson, and R. Milkman read an earlier version of the manuscript. During this work, R. Koehn was supported by USPHS Career Award GM-28963 and W. Eanes was a research assistant on USPHS Research Grant GM-21133 to R. Koehn. F. Immerman summarized the polymorphism data from published sources and these are available to interested persons as Evolutionary Genetics Research Reports 22 filed at British Library Lending Division, Boston Spa, Wetherby, Yorkshire, LS23 7BQ (U.K.) and John Crerar Library, Chicago, Illinois 60616 (U.S.A.). We are indebted to S. O’Brien and R. MacIntyre, who generously provided an unpublished summary of structures of D. melanogaster enzymes. We thank F. J. Ayala and S. Prakash for unpublished data, This is Contribution 163 from the Program in Ecology and Evolution, State University of New York, Stony Brook, N.Y. 11794.

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