The Differential Contribution by Individual Enzymes of - Genetics

Copyright 0 1988 by the Genetics Society of America

The Differential Contribution by Individual Enzymes of Glycolysis and Protein Catabolism to the Relationship Between Heterozygosity and Growth

Rate in the Coot Clam, Mulinia lateralis

Richard K. Koehn, Walter J. Diehl' and Timothy M. Scott Department of Ecology and Evolution, State University of New York, Stony Brook, New York I I794

Manuscript received June 2, 1987 Revised copy accepted September 10, 1987

ABSTRACT The locus-specific effects of heterozygosity upon individual growth rate were determined for 15

polymorphic enzymes among 1906 individuals from a single cohort sample of the marine bivalve Muliniu lateralis. Two measures of individual growth rate (total wet weight and shell length) were made at collection and after a period of growth in the laboratory. The correlation between heterozygosity and growth rate was independently determined for each locus using multiple linear regression, thereby providing a rank of individual locus effects; these differed significantly. The four estimated rankings of relative locus effects (initial length, initial weight, length added in the laboratory, and added weight) were not statistically different. That is, a locus with a large effect of heterozygosity on growth rate in nature had a similarly large effect on laboratory growth rate. The effect of a locus was not related to heterozygosity per se; some highly heterozygous loci had no detectable correlation with growth rate. The data contained two pairs of relatively tightly linked loci; in both cases one locus of a pair had significant effects on growth rate, while the other had no effect. Loci with large and significant correlations with growth rate synthesize enzymes which function in protein catabolism or glycolysis; heterozygosity in enzymes of the pentose shunt, redox balance, or other miscellaneous metabolic roles was not correlated with growth rate. Since the metabolic basis for the correlation is known to derive from individual differences in net energy status, particularly energetic costs of whole- body protein turnover, these data indicate that phenotypic effects (e.g., variation in growth rate) are determined by heterozygosity at the studied genes, not other linked loci.

I N recent years, numerous studies have tested for, or demonstrated, a relationship between multilo-

cus heterozygosity, as determined for a series of elec- trophoretically detectable enzymes, and growth rate, measured as age-specific size or weight (reviewed by MITTON and GRANT 1984; ZouRos and FOLTZ 1987). Such studies have much in common. First, in studies reporting a significant correlation, heterozygosity typically explains only 5- 10% of the variation in individual growth rate. Clearly, enviranmental and/or genetic factors other than the studied loci affect growth rate. Second, such studies have typically employed a small number of polymorphic enzyme loci; in 39 studies that we have reviewed, the modal number of studied loci was 5 and the mean was 6.0. One study (DANZMANN, FERGESON and ALLENDORF 1985) employed 14 loci. Last, the individual effects of heterozygosity on growth rate have generally been considered to be additive, each individual locus having a small (often statistically nonsignificant) effect. T h e relative effects of individual loci on growth rate have been estimated ex post facto by single locus statistical tests (e.g., a t-test comparing growth of heterozygotes

University, P. 0. Drawer GY, Mississippi State, Mississippi 39762.

Genetics 118: 121-130 (January, 1988)

' Present address: Department of Biological Sciences, Mississippi State

versus homozygotes) or a combined probability test. However, none of the published studies were specifi- cally designed to estimate differences among loci.

A few studies have reported either mixed results, wherein some samples exhibit a significant correlation between heterozygosity and growth rate while others do not (e.g., LEDIG, GURIES and BONEFELD 1983), or the absence of a correlation (e.g., WARD et a l . , 1985; MCANDREW, WARD and BEARDMORE 1986). Assum- ing the relationship between heterozygosity and growth rate to be universal among outbreeding species, the absence of a detectable correlation could be due to a variety of factors. These include (1) strong inbreeding and/or nonrandom mating in sampled or- ganisms, (2) limited parentage of sampled individuals (GAFFNEY and SCOTT 1984), and (3) sampling older cohorts, even if they are of known age, that may have experienced genotype-dependent viability prior to sampling (DIEHL and KOEHN 1985). Two other factors, one genetic and one environmental, may further militate against detection of the correlation, although neither has been adequately investigated. The energetic advantage (see below) enjoyed by more heterozygous individuals may contribute more significantly to enhanced growth in an environment of general

122 R. K. Koehn, W. J. Diehl and T. M. Scott

energetic stress. If a population has enjoyed abundant food and/or a moderate environment, genotype seems to have a smaller effect upon individual growth rate than when resources are scarce or the environment harsh (GAFFNEY 1986). In Mytilus edulis, for example, higher net energy balance is associated more with resistance to weight loss than with a capacity for weight gain (DIEHL, GAFFNEY and KOEHN 1986).

Last, individual loci might differ from one another in the degree to which each contributes to the correlation. Such differences could be due either to the different metabolic roles of their respective gene products and/or that each gene marks a different portion of the genome. In this situation, the magnitude of the correlation would be significantly influ- enced by the particular genes employed in a study. Since the number of loci studied is typically only five or six, this is a potentially serious problem, but only if the effects of individual genes can greatly differ.

To estimate the relative effects of individual genes on the correlation between heterozygosity and growth rate requires very special circumstances. First, a large number of polymorphic enzymes must be available to sufficiently assess potential differences among loci. Five or six genes, as has been typically employed in such studies, are simply not adequate to address this question. Second, the sample of genes must be diverse with respect to the metabolic roles of their respective products. This is critical for ultimately understanding the mechanism for the correlation, if for example, some metabolic pathways (and their constituent enzymes) are causally important in the correlation while others are not. Third, the study must be undertaken with a sample of individuals in which the various negating factors discussed above do not obtain.

The foregoing conditions are satisfied by the marine bivalve Mulinia lateralis. GARTON, KOEHN and SCOTT (1984) have demonstrated a correlation between heterozygosity and growth rate in this species, although that study involved only six polymorphic genes. With pelagically dispersed larvae and ex- tremely large population sizes, inbreeding is not likely to occur. Individuals of known age can be collected following larval settlement during the period of rapid juvenile growth. Lastly, an unusually large number of polymorphic and highly heterozygous loci have been identified in this species and the linkage relationships of many have been established (T. M. SCOTT unpublished data). Using M. lateralis, we will demonstrate large individual differences among genes in their contributions to the correlation of heterozygosity with growth rate. Moreover, those enzymes having a significant effect on growth rate do not represent a random sample of metabolic function.

MATERIALS AND METHODS

Growth and measurement of specimens: Settlement of M . lateralis larvae occurs locally for about 2 weeks during

May-June. Newly settled individuals were collected by dredging from Port Jefferson harbor, Long Island, New York, in June, 1985. Clams were brought to the laboratory and placed in a recirculating seawater system at 20" and 26% salinity (ambient conditions). Individuals were not fed prior to initial measurement. Initial shell lengths (Sli) and initial whole animal weights (Fwi) were recorded (N = 3726). All shell lengths (mean = 4.29 mm) were measured to the nearest 0.01 mm using vernier calipers and fresh weight was measured to the nearest 0.0001 g. Growth racks were constructed of plastic grids normally used for fluorescent lighting fixtures. After measurement, each animal was placed into an individual compartment (1 cm') and the rack sealed with 1 mm nylon mesh screening on both surfaces. Each rack held 414 individuals; the experiment required 9 racks. Over a 14-day period as completed, racks were placed into an aerated 250-liter seawater tank at ambient conditions. Clams were fed to excess from cultures of Zsochrysis galbana and Thalissiosira pseudonana (3H) cultured by the methods of GUILLARD (1975). Fifty percent of the water in the tank was changed every 2 days. After a 2-week growth period racks were removed (mortality = 18%) and frozen at -60 O for subsequent electrophoretic typing.

Over a 7-month period, individual clams were removed from the freezer, their final shell lengths (mean = 5.05 mm) measured (Slf) and a subsample ( N = 29) of each rack reweighed. Added shell length (Sla) was calculated by the difference between Sli and Slf. Final fresh weight (Fwf) was estimated using the regression of final fresh weight (Fwf) on final shell length (Slf) by the formula Fwf = (SIf2.')/2966 ( N = 260, r2 = 0.945). Thus, four different measures of growth rate were obtained for each individual clam. Since Fwf was obtained by estimate rather than directly, Fwa cannot be considered a wholly independent measure of growth rate.

Starch gel electrophoresis: Samples were prepared for electrophoresis by homogenizing whole animals in 0.05 M Tris-HCI (pH 8.0) buffer followed by centrifugation at 0" for 10 min at 7000 X g. The supernatant was used as the enzyme source. The 15 studied enzymes were: a-amino acyl peptide hydrolase (AP 1, EC 3.4.1. l), alanyl aminopeptidase (AAP, EC 3.4.1.-), phosphoglucomutase (PGM, EC 2.7.5.1 .), glucose phosphate isomerase (GPI, EC 5.3.1.9), enolase (ENOL, EC 4.2.1.1 l), nonspecific aminopeptidase (2 loci: AP2, AP3, EC 3.4.-.-), mannose phosphate isomerase (MPI, EC 5.3.14, isocitrate dehydrogenase (2 loci: IDH1, IDH2, EC 1.1.1.42), @-galactosidase (@-GAL, EC 3.2.1.23), superoxide dismutase (SOD, EC 1.15.1. l), 6-phosphogluconate dehydrogenase (PGD, EC 1.1.1.44) and malic dehydrogenase (two loci: MDH1, MDH2, EC 1.1.1.37). Two additional loci were studied for only a subsample of individuals, malic enzyme (ME, EC 1.1.1.40) and strombine dehydrogenase (SDH, no EC number assigned). ME was not resolved initially; only a subset (N = 1466) of the sample was scored at this locus. SDH lost activity upon freezing and only 77 individuals were scored. Data on SDH and ME were used to test interpretations based upon the 15 studied loci.

Electrophoresis for all enzymes was done in horizontal starch gels. GPI, PGM, ENOL, MDHl and MDH2 were run with a Tris-maleate (pH 8.0) buffer system. AP1, AP2, AP3, @-GAL, AAP were resolved with a LiOH system and MPI, SOD, and SDH with a Tris-borate-EDTA system (KOEHN, MILKMAN and MITTON 1976). IDH1, IDH2, PGD, and ME were run with a 0.2 M Tris-citrate pH 7.0 buffer system.

GPI, PGM, IDH, ME, PGD, MDH and MPI activities were detected by procedures outlined in SCHAAL and AN- DERSON (1974). AAP and SDH detection employed the

Locus-Specific Growth Effects 123

method of CARTON, KOEHN and SCOTT (1 984), &GAL by HARRIS and HOPKINSON (1976), and AP by SHAW and PRASAD (1 970).

Statistical procedures: A total of 3043 (82%) individuals survived the experiment. Of these, genotypes at the 15 loci and growth rate data are available for 1906 clams. All results reported here, except where noted, are from analyses based upon these 1906 individuals. Data manipulation and analyses were accomplished on an IBM 436 1 virtual machine at the Biological Sciences Computing Facility at Stony Brook. Statistical programs utilized were part of the Statistical Anal- ysis System Software (SAS Institute, Inc.) unless otherwise noted.

For the sake of the analyses reported here, each locus was defined as either 0 (homozygous condition) or 1 (heterozygous condition). Overall heterozygosity per individual is the number of loci in the heterozygous state out of the 15 studied loci. Model I linear regression was used to determine the relationship of the dependent effects (growth rate measures) to multilocus heterozygosity, the independent effect. With Fwa and Sla, multiple linear regression was further employed; the effect of Fwi on Fwa was statistically removed by its inclusion as an independent effect in the model. With Sla only, a slightly significant rack effect was present; and therefore, the effects of both rack and Sli were statistically removed. With multiple regression considering heterozygosity at individual loci as independent variables, the partial sums of squares (type 111 SS) were examined. The type 111 SS indicate the effects of an independent variable separately, holding the effects of the other variables constant.

The relative contributions of individual loci to the overall relationship between multilocus heterozygosity and measures of growth were determined by ranking the type 111 SS resulting from the inclusion of heterozygosity at each locus as independent effects. Significance of these effects was determined for each locus by F-tests, the ratio of the partial SS to the error mean square. Correlations between rankings were determined by Spearman’s rank correlation (SOKAL and ROHLF 198 1).

RESULTS

Sampling effects on heterozygosity/growth rate correlations: T h e relationship between multiple locus heterozygosity and the four measures of growth rate were all statistically significant (Sli: r = 0.255, P < 0.0001 : Sla, standardized for Sli: r = 0.052, P < 0.05; Fwi: r = 0.208, P < 0.0001: Fwa, standardized for Fwi: r = 0.132, P < 0.0001). Hence, multiple locus heterozygosity was significantly correlated with both individual growth rates in the natural environment and subsequent growth rates in the laboratory. While heterozygosity was correlated with both length and weight, correlations were smaller for both measures of added growth.

Despite the inclusion of 15 loci in the analyses, nearly three times the number employed by most previous studies, the magnitude of the correlation between heterozygosity and growth rate was very similar to previously reported values. For example, the relationship between heterozygosity and Sli (Fig- ure 1) was statistically highly significant (P < O.OOOl), but the coefficient of determination ( r2) was only

A

1 1 1 1 1 1 1 1 1 1 1 1 1

2 4 6 8 IO 12 14

HETEROZYGOSITY FIGURE 1 .-The relationship between individual heterozygosity,

based upon 15 loci, and initial shell length (Si, see text) among 1906 individuals of M. lateralis. Average Sli, with 95% confidence interval, is given for each heterozygosity class along with the sample sizes. The two variables are significantly correlated ( r = 0.255, P < 0.00 1) among individuals.

0.0648, essentially identical in magnitude to that reported by other authors.

The number of loci sampled has a measurable effect upon the magnitude of the correlation between heterozygosity and Sli. Individuals were randomly sub- sampled ( N = 350, to approximate sampling power of most previous experiments) from the data for a variable number of randomly selected loci, ranging from 5 to 13. Twenty such random samples were taken for each of the number of loci studied. Increased numbers of loci in the sample resulted in increased values of r2 (Figure 2) with a concomitant decrease in the confidence interval of the mean r2 for each sample class. As will be shown below, the magnitude of correlation is mainly dependent upon the specific loci that are selected rather than the numbers of loci in the sample.

Relative effects of individual enzyme loci: With type I11 SS, the sequence by which variables are ana- lyzed does not affect the partial sums of squares. T h e type I11 SS for a given locus, resulting from multiple linear regression where Sli and heterozygosity a t individual loci are the dependent and independent effects, respectively, is a measure of the degree to which heterozygosity at that locus is correlated with Sli. T h e resulting 15 sums of squares, when ranked, reflect the relative correlation of heterozygosity at each locus with Sli. Eight of the 15 loci had individually significant sums of squares (Table 1) . For two loci, IDHl and PGD, heterozygotes exhibited a slightly smaller Sli than homozygotes, but not significantly (Table 1).


u L - z 0 0.06 t P

- 0.05-

Y I- Y 0

0 t

LL 0.04-

3 0.03- 0 LL LL

g 0.02 - V

w (3

a 4 0.01 - w

1 I I I I I I

I 3 9 '7 9 II 13 15 NUMBER OF LOCI

FIGURE 2.-The effect of the number of sampled loci on the correlation between initial shell length and individual heterozygosity. Twenty random subsamples of n loci from the 1906 individuals were made ( N = 350) and the correlation between heterozygosity at n loci and Sli determined. The average coefficient of determination (r'), with 95% confidence interval, is given for each of the numbers of loci tested. As the number of loci in the subsample becomes larger, the average re increases, along with a small concomitant decrease in the variance of the mean.

TABLE I

Relative contributions by individual locus heterozygosity to Sli

Rank Sli ss 1 2 3 4 5 6 7 8 9

10 11 12 13 14 15

ENOL A P l AP3 PGM lDH2 AP2 M P l @GAL SOD GPI AAP MDH2 MDHl IDHl PGD

28.5*** 13.0*** 12.8*** 10.3*** 5.9*** 4.7*** 3.3** 3.1** 1.3 0.7 0.4 0.06 0.001

(-) 0.2 (-) 0.5

Loci are ranked by type I11 sums of squares (SS) from multiple

was determined by F-tests (see text). For both IDHl and PGD, linear regression analyses and significance of individual locus effects

homozygotes were larger (but not significantly so) than heterozygotes. Since ranking is based upon the degree to which heterozygote lengths are greater than homozygotes, these loci rank last. The correlation between Sli and heterozygosity at the 15 loci was 0.255***; ** P < 0.01; *** P < 0.0001.

The same analysis applied to initial weight (Fwi) produced a very similar result (Table 2). Similarly, added shell length (Sla) and added fresh weight (Fwa), both standardized for initial values of length (Sli) and weight (Fwi), respectively, allowed two additional es- timates of the parametric ranking of individual locus effects (Table 2). Only one locus was individually significant in the analysis of Sla. Homozygotes added

TABLE 2

Relative contributions by individual locus heterozygosity to four measures of growth rate

Rank

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15

Sli

ENOL*** APl*** AP3*** PGM*** lDH2 * * * AP2*** MPl* * @GAL * * SOD GPl AAP MDHZ MDHl IDHl PGD

~~ ~~~~ ~

Sla(Sli) Fwi Fwa(Fwi)

A P l * * ENOL*** ENOL*** AP3 APl*** AP3*** PGM AP3*** PGM*** AP2 PGM*** AP2** AAP lDH2 * * * APl** ENOL @GAL* * MPl MDH2 MPI MDH2 GPI AP2 @GAL @GAL AAP GPl l D H 2 GPl AAP MDHl SOD lDH2 M P l MDH2 MDHl SOD MDHl SOD PGD IDHI PGD IDHl PGD (-) l D H l *

~~ ~

See Table 1 for basis of rankings and significance tests. Result for Sli is given in Table 1, but the partial sums of squares used to produce the other three rankings are not shown. Rankings reflect the relative contribution of a gene to the correlation between heterozygosity and growth rate as shell length (Sli) and weight (Fwi) achieved in nature and length (Sla) and weight (Fwa) added subse- quently in the laboratory. Added growth was standardized for initial size and weight (see text). Overall 15-locus correlations were r = 0.255*** (Sli), r = 0.052* (Sla), r = 0.208*** (Fwi) and r = 0.132*** (Fwa). * P < 0.05; ** P < 0.01; *** P < 0.001.

TABLE 3

Rank-order comparison of ranking in Table 2

Comparison 1.

Initial length/Added length 0.696** Initial length/Initial weight 0.971*** Initial length/Added weight 0.825*** Added length/Initial weight 0.718** Added length/Added weight 0.811*** Initial weight/Added weight 0.818***

**P<0.01;***P<0.001.

more weight than heterozygotes at the IDHl locus. A specific point of interest is whether the four

derived rankings are actually the same. A test of each ranking against another by Spearman's rank correlation demonstrated that in all possible combinations the rankings were highly correlated with one another (Table 3). Hence, a locus at which heterozygosity is highly correlated with growth rate in the natural environment (Sli and Fwi) is also highly correlated with growth in the laboratory (Sla and Fwa). Since the four rankings were not statistically different, a single ranking was made by averaging the four rank values for each locus in order to obtain the best estimate of the true rank.

Heterozygosity and growth rate: The level of heterozygosity of a locus should not be considered a priori evidence for its potential correlation with growth rate as the average rank position of a locus was uncorrelated with heterozygosity (r = -0.472; not


TABLE 4

Average relative contributions by individual locus heterozygosity to growth rate, with heterozygosity and metabolic

fundion for each locus

Average Rank locos rank Heterozygosity Function

1 ENOL* 2.25 0.653 Glycolytic 2 A P l * 2.50 0.750 Protein catabolic

AP3 * 2.50 0.735 Protein catabolic 4 PGM* 3.50 0.557 Pre-glycolytic 5 AP2* 5.50 0.650 Protein catabolic 6 BGAL* 7.75 0.808 Pre-glycolytic

IDH2 * 7.75 0.010 Redox balance 8 MPI* 8.00 0.786 Pre-glycolytic 9AAP 8.75 0.745 Digestive

10 GPI 9.25 0.675 Glycolytic 1 1 MDH2 9.50 0.039 Redox balance? 12 SOD 11.50 0.083 Detoxification 13 MDHl 12.25 0.079 TCA cycle? 14 IDHl 14.50 0.513 Redox balance

6PGD 14.50 0.496 Pentose shunt

Average rank was determined as the mean for each locus among four rankings in Table 2. Heterozygosity is calculated from observed allele frequencies. The specific function of MDHl us MDH2 is not known. * Loci which tested significant ( i ~ , heterozygotes > homozygotes) in at least one of four F-tests (see Table 2).

significant) in this study. This is obvious from an inspection of Table 4. The same result has been reported by BUSH, SMOUSE and LEDIC (1 987) for pitch pine. Loci with high values of heterozygosity are distributed over the entire rank order; IDHl and PGD tied for the last rank (Table 4) although each is highly heterozygous. In no test did AAP make an individually significant contribution to the correlation, ranking 9 out of 14, yet heterozygosity of AAP was third highest among the 15 loci.

Behavior of linked loci: Among the 15 studied loci, 2 pairs are known to be reasonably tightly linked. ENOL, the locus with the highest average effect on growth rate (Table 4) is linked to PGD (rank 14), with a recombination frequency of approximately 10% (T. M. SCOTT unpublished data). Similarly, AP2 had con- sistently large and significant effects with a rank of 5 and is linked to IDHl (also rank 14) with approximately the same recombination frequency. In each case, one locus of a pair had a large effect on growth rate while the other locus did not. In 11 1 pair-wise comparisons of loci, including the ENOLjPGD and AP2/IDH1 linked pairs, we found little evidence for linkage disequilibrium; genotypes at any one locus were randomly distributed among individuals with respect to the genotypes at any other locus in the study.

DISCUSSION

Our results demonstrate the locus-specific effects of heterozygosity on growth rate. Moreover, the degree of heterozygosity observed for a locus does not predict

the magnitude of the effect of heterozygosity on growth rate. Quite apart from the possible reasons for this, to be developed later, this observation can explain why other authors have sometimes not o b served a significant correlation in studies involving five or six loci. The specific genes in a sample can greatly affect the estimate of a correlation. For example, in a subsample of our data, composed of 350 random individuals and the 5 highest ranked loci (from Table l), heterozygosity explains about 10% of the variation in Sli (r2 = 0.0985). By contrast, for a similar random sample of the 5 lowest ranked genes, heterozygosity explains none of the variation in initial size (r2 = 0.0001). There is no way to adequately assess this point from a comparison of published studies, as different enzymes have been employed by various authors and homologies for many are impossible to establish. Polymorphic enzymes that are easily resolved by electrophoresis are common in those data, especially PGM, GPI, IDH, LAP, esterases, MDH and aminopeptidases. Homologies among studies for nonspecific peptidases and esterases are not known. The common use of MDH, IDH and GPI may militate against detection of a correlation, if our results have general application. On the other hand, PGM and APl (homologous with LAP) each have large effects and as such could be important in reported positive results.

The relative effect of each individual locus on growth rate was the same for the two measures of growth (length and weight) and for growth rate measured at two separate times (in nature and in the laboratory). This underscores the genetic influences upon growth rate that are due either to the studied enzyme genes or (if these are neutral) to associated genetic elements. However, our results with linked loci severely restrict the degree to which linked ge- nomic heterozygosity could be important, since we have demonstrated very different effects of linked enzymes in two cases. This observation does not however preclude the action of linked deleterious alleles. A recently arisen deleterious recessive allele could exist in strong linkage disequilibrium with one, but not the second, of two linked enzymes even though these are in linkage equilibrium. However, as we will discuss below, the loci exhibiting significant effects are not a random sample of metabolic function, whether they are members of known linkage groups or not.

With two exceptions (see below) the significant effects of heterozygosity upon growth rate are produced by enzymes that are protein catabolic, pre-glycolytic or glycolytic in metabolic function (Table 4). Genes without significant effects on growth rate code for enzymes with other miscellaneous metabolic functions, including the pentose shunt, digestion, main-


taining cellular redox balance and/or detoxification. PGM, P-GAL and MPI are pre-glycolytic and do not function in the direct sequence of glycolytic reactions from glucose to pyruvate, but each supplies carbon skeletons to glycolysis: PGM catalyzes the conversion of glucose- l-phosphate to glucose-6-phosphate, a glycolytic intermediate; @-GAL hydrolyzes &galactosides to free galactose, which upon phosphorylation to galactose-l-phosphate by galactokinase is converted to glucose- 1 -phosphate; and MPI converts phosphoryl- ated mannose (mannose-6-phosphate) directly to fructose-6-phosphate. Hence, we consider these three enzymes with the glycolytic group.

Two enzymes are exceptions to the foregoing pattern in our results: IDH2 is a NADP-dependent mitochondrial enzyme involved in redox balance, but had statistically significant effects on both Sli and Fwi, though the IDHl isozyme with presumably identical function did not. GPI, a main-line glycolytic enzyme, was without a significant effect on growth rate. The result with IDH2 is difficult to interpret. First, the gene is only weakly polymorphic, exhibiting the lowest heterozygosity of any gene in the study (Table 4). Indeed, of 1906 individuals in the sample there were only 14 heterozygotes, 7 each of two types. Both heterozygote classes were statistically greater in Sli (and Fwi) than the common homozygote represented by 1892 individuals. In the absence of adequate samples for both the heterozygote genotypes and the alternate homozygotes, we believe this result must be interpreted with some caution.

Glucose phosphate isomerase (GPI) is the second exception to a clear division by metabolic role between, enzymes with and without significant individual effects. Although alleles of GPI have been shown to be catalytically differentiated and potentially adaptive (WATT 1983; HALL 1985), the mass action ratios (i.e., [FGP]/[GGP]) are near the equilibrium constant (Keq = 0.3) in virtually every species that has been examined. Most authors conclude therefore that GPI pro- vides primarily a coupling function between the glucose-6-phosphate branch point and phosphofructoki- nase/fructose-l,6-bisphosphatase in glycolysis and glu- coneogenesis (NEWSHOLME and START 1973; ATKIN- SON 1977). The primary coupling function for the enzyme as a freely reversible reaction would not seem conducive for the catalytic properties associated with enzyme polymorphism to affect glycolytic flux, though it appears to do so in Colias butterflies (WATT and Boccs 1987). Of course, both energy metabolism and physiological demands for metabolic performance are drastically different between butterflies and clams. Perhaps more importantly, the reversibility (or ime- versibility) of a reaction is dependent on many factors (e.g., substrate/product ratios, inhibitors, etc.) and the contrast between our results and others on GPI could

be due to any one of several possible causes. Alanyl aminopeptidase (AAP) would appear to be

an exception, but it is not. Although the enzyme is protein catabolic in function, by substrate specificity and electrophoretic mobility, AAP in Mulinia is homologous with peptidase I1 in the bivalve, M. edulis; peptidase I1 cannot be involved in the maintenance of the protein pool (see below) since it is restricted in cellular distribution to the gut epithelium (MOORE, KOEHN and BAYNE 1980) where it would hydrolyze ingested protein.

Finally, we should note that a simple and clear distinction between enzymes of protein catabolism/ glycolysis vs. other functions may be an unreasonable expectation even though the distinction is likely cor- rect. Influences by metabolites of one pathway on enzymes in a different pathway are well-known (e.g., pentose shunt upon glycolysis via competitive inhibi- tion by 6-phosphogluconate of GPI) and reflect the complex organization of metabolism. In addition, while our data seem to support gene-specific influences on growth rate in a way that reflects their specific metabolic roles, in some cases genetic back- ground could act to obscure the clear-cut effect (or its absence) of a gene.

We can provide a further test of our interpretation, that effects on growth rate are due only to protein catabolic/glycolytic enzymes, by examining two additional loci with data that were available for only a part of the sample. Malic enzyme (ME) and strombine dehydrogenase (SDH) both function in regeneration of NADH. Since these are important to neither protein catabolism nor glycolysis, we must expect that heterozygosity at these two loci should not be significantly correlated with growth rate. For ME, data were available for 1466 individual clams (R = 0.3 14). This subset was subject to multiple linear regression analysis, as has been discussed earlier. The resulting ranking (with respect to Sli) was statistically compared to the ranking obtained for the entire data set (Table 1). The two rankings did not differ (r , = 0.954; P < 0.001). The same subset was then reanalyzed, but with the inclusion of the ME locus. In the resulting 16 locus ranking, ME had a rank of 10 and heterozygosity at this locus was not correlated with individual growth rate.

The same procedure was followed in the analysis of SDH (Fi = 0.377), although only 77 individuals were available for the test. Nevertheless, the ranking of genes based upon 77 individuals did not differ statistically from the ranking obtained from the full data set (r , = 0.91 1; P < 0.001). When SDH was included, it had a rank of 14 with no significant effect upon growth rate. Ideally, we would like to have had additional data on an enzyme of protein catabolism or


glycolysis to test the opposite prediction, but these were not available.

There are two separate, but related, questions that must be addressed: (1) why does enzyme heterozygosity have an effect within some metabolic pathways but not others, and (2) when effects occur, why are these different between heterozygous versus homozygous enzymes? We cannot provide simple and unequivocal answers to either question, but some reasonable pos- sibilities can be considered.

To address these points, we must consider the relationships among whole-organism energy status, the role of various metabolic pathways in energy metabolism and the potential effect of enzyme heterozygosity on energy balance. The energetic cost of maintenance metabolism is (as the phrase implies) that energy required for maintaining metabolic rate exclusive of other energy demands such as feeding, digestion, growth, reproduction, behaviors, acclimation, and so forth. The major energy demands of maintenance metabolism derive from protein turnover and ion gradient maintenance in membranes; maintenance metabolic rate reflects the ATP production required to meet these demands.

We can refocus our questions. First, does enzyme heterozygosity have an effect on energy balance, spe- cifically on maintenance costs? Judging from data on oxygen consumption, maintenance (or nonactive) rates have been shown to be lower in more heterozygous individuals of oysters (KOEHN and SHUMWAY 1982), mussels (DIEHL et al. 1985; DIEHL, GAFFNEY and KOEHN 1986), a salamander (MITTON, CAREY and KOCHER 1986) and a salmonid fish (DANZMANN, FER- GUSON and ALLENDORF 1987). Once the energetic demands of maintenance have been met, excess energy is available for growth (or reproduction, behavior, etc.). The lower the maintenance demand, the greater the available energy for all other energy- dependent functions. Indeed, the heterozygosity-dependent energetic advantage can be reflected in energy-dependent traits other than growth, such as re- productive effort (COTHRAN et al. 1983; RODHOUSE et al. 1986), behavior (GARTEN 1977) and response to energy demands (MITTON, CAREY and KOCHER 1986; R. C. VRIJENHOEK and J. D. WETHERINGTON, in prep- aration).

Second, does the effect of enzyme heterozygosity derive principally from enzymes in pathways more critical to maintenance metabolism? The answer seems to be in the affirmative, though our data are not unequivocal on this point. Protein turnover and ion gradient maintenance in membranes constitute the major energy demands of maintenance metabolism. HAWKINS, BAYNE and DAY (1986) have utilized 15N to measure protein pool metabolism in rapidly growing (more heterozygous) and slow growing (less het-

erozygous) individuals of M. edulis. They concluded that faster growth derived from decreased energy requirements for maintenance associated with greater efficiencies (protein synthesis per unit protein deposition) of protein synthesis. Energy “saved” by higher metabolic efficiencies in faster growing animals was used to effect increases in both ingestion and absorp- tion efficiency, thereby enhancing growth still further. Slow growing individuals, by contrast, had lower syn- thetic efficiencies reflected in elevated protein synthesis per unit deposition with consequent reduction of growth.

The large relative effects of heterozygosity in enzymes of protein catabolism is consistent with (indeed, expected from) the importance of whole-body protein turnover costs to metabolic maintenance cost differences among individuals of differing heterozygosity (HAWKINS, BAYNE and DAY 1986). Hence, protein catabolic enzymes are directly implicated as causative in their effects upon energetic status (and thereby, upon growth rate). These data argue forcefully against the majority of phenotypic effects deriving from linked deleterious alleles. That argument would have to be sustained by dismissing the actions of studied genes with metabolic functions that are required to produce the known physiological energetic phenotypes in favor of genes of unknown function.

Protein turnover is energy-dependent. Protein synthesis can account for about 10% of the basal oxygen uptake in humans (WATERLOW and JACKSON 1981) and with additional consideration for ribosomal and messenger RNA synthesis and protein breakdown, the cost of protein pool turnover is much greater. As such, turnover is dependent upon cellular energy from pathways for ATP production. Of these, only enzymes of glycolysis are adequately represented in this study. The large relative effects of heterozygosity in glycolytic enzymes may reflect the role of glycolysis as one source of ATPs for supporting the energy requirement of protein turnover.

One of the two NAD-dependent malate dehydrogenase enzymes (we do not know which) we have studied functions in regeneration of reducing equivalents. NADH is essential to ATP production during oxidative phosphorylation. Yet, heterozygosity of the MDH enzymes does not appear to effect growth rate variation. This may constitute evidence against our hypothesis for the important effects of heterozygosity in pathways critical to energy balance. On the other hand, many enzymes function in the maintenance of cellular redox balance, which therefore might negate the detection of any significant effects of heterozygosity at only one of these loci.

The two NADP-dependent isocitrate dehydrogen- ases function in the mitochondrial citrate shuttle; re-


ducing equivalents (i.e., NADPH) have no role in ATP production.

In summary, individual variations in response to a specific metabolic demand will involve metabolic pathways that are most important to meeting that specific demand. Some pathways are important to energy metabolism while others are not. How might heterozygosity have effects on such pathways?

The biochemical genetic mechanism by which heterozygosity influences energy status is not presently known. However, the relationship between heterozygosity and maintenance costs, especially heterozygosity and protein turnover (HAWKINS, BAYNE and DAY 1985), imply that the heterozygosity mechanisms we seek to identify may be related to how genotype effects the cost of maintaining energetically important p t h - ways. The effect of heterozygosity would seem to reflect differences in the cost of maintenance of pathways that contain homozygous versus heterozygous enzymes. How might genotype effect such differences?

We suggest that the cost of pathway maintenance @e., biosynthesis and degradation of constituent enzymes) is inversely related to the magnitude of catalytic variation among the sequence of reactions in a pathway. This interpretation is suggested by the following considerations. When catalytic and/or stability differences exist between alternate homozygous enzymes at a locus, it is well known that the properties of the heterozygote are nearly always intermediate. That is, the catalytic differences, represented by the homozygotes, are “averaged out” in the heterozygote. It follows that as the reactions of a pathway are represented by greater numbers of heterozygous enzymes, the overall variance in catalytic variation in the pathway will be lower. To the extent that these catalytic variations are compensated for by enzyme biosynthesis, in order to regulate concentrations of inter- mediates, the cost of pathway maintenance (turnover of constituent enzymes relative to ATP production) would likewise be greater. More homozygous pathways would exhibit greater among-reaction variation with greater commensurate biosynthetic costs to facil- itate regulation.

A reaction step homozygous for a low activity enzyme may (in order to regulate substrate level) require a significant increase in biosynthetic cost, since individual enzymes in pathways are regulated collectively rather than individually (PETTE, LUH and BUCHER 1962; HENRIWWN et al. 1986). Such regulations may be more critical to maintenance of pathway flux during transient changes in metabolism than under steady-state conditions ( W A ~ and BOCCS 1987).

An interesting corollary of this hypothesis emerges in the results of experiments on artificial directional selection for increased growth rate. Animal strains

(principally mice and rats) selected for high versus low growth rate differ in a number of energy-related traits, including body composition, feeding efficiency, feed consumption and various aspects of energy metabolism (YUKSEL 1979; MALIK 1984). Some investi- gators have reported that weight standardized rates of metabolism are lower, not higher, in high growth rate strains, implying a greater metabolic efficiency, Le., higher rate of protein deposition per unit protein synthesis (Lorn, PALMER and KENNEDY 1946; PRIES- TLEY and ROBERTSON 1973; MFDRANO and GALL 1976a, b; KOWNACKI and KELLER 1978). These high growth rate selected strains exhibit the same charac- teristics of reduced weight-standardized respiration rates and apparent lower protein turnover (09. cit.) as more heterozygous outbred individuals. This requires that the same metabolic phenotype (i.e., reduction of respiration rate and protein turnover) must derive from either high heterozygosity on average, in the case of outbred animals, or homozygosity of speczj5c genotypes (in the case of artificial selection). The catalytic variation represented by homozygosity in outbred animak can be reduced in selected strains since artificial selection can “capture” those homozygous genotypes at each locus that collectively represent low average catalytic variation among enzymes. We are not aware of any study that has simultaneously measured selective response in growth rate, metabolic rate and change in heterozygosity.

An obvious alternative to the foregoing hypothesis would consider the effects of environmental variation on the catalytic properties of homozygous versus heterozygous enzymes. Heterozygotes by virtue of the fact that they are composed of two enzymes differing in catalytic optima are thought to be “buffered” against environmental variation more strongly than homozygous enzyme genotypes. While this may be of possible importance, we do not consider it a major factor in our data. The effects of heterozygosity on metabolism (KOEHN and SHUMWAY 1982; GARTON 1984; MITTON, CAREY and KOCHER 1986; DANZ- MANN, FERGUSON and ALLENDORF 1987) and growth rate (CARTON, KOEHN and SCOTT 1984; this study) have been demonstrated under constant laboratory conditions. A constant laboratory environment should either negate or significantly diminish the effects of heterozygosity, if these are due to physical environmental variation. We note that the correlation between heterozygosity and laboratory growth rates was generally l e s s than with growth rates in nature; this may have resulted from the minimal variation of the laboratory environment.

Whatever the mechanism by which heterozygosity affects metabolic efficiency, our data do allow the point to be experimentally approached. The known differences in relative effect of heterozygosity among

LocusSpecific Growth Effects 129

enzymes permits the design of experiments with very specific expectations. This work is currently ongoing.

We are grateful to a number of colleagues for comments on the manuscript, especially PATRICX GAFFNEY and MAUREN KRAUSE. This work was supported by National Science Foundation grant BSR8415060. This is contribution No. 644 from the Program in Ecology and Evolution, State University of New York, Stony Brook, New York 11790.

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Communicating editor: M. T. CLEGC

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