QUANTITATIVE GENETICS OF SPRINT RUNNING SPEED AND SWIMMING ENDURANCE IN LABORATORY HOUSE MICE (MUS DOMESTICUS).

We tested the hypothesis that locomotor speed and endurance show a negative genetic correlation using a genetically variable laboratory strain of house mice (Hsd:ICR: Mus domesticus). A negative genetic correlation would qualify as an evolutionary "constraint," because both aspects of locomotor performance are generally expected to be under positive directional selection in wild populations. We also tested whether speed or endurance showed any genetic correlation with body mass. For all traits, residuals from multiple regression equations were computed to remove effects of possible confounding variables such as age at testing, measurement block, observer, and sex. Estimates of quantitative genetic parameters were then obtained using Shaw's (1987) restricted maximum-likelihood programs, modified to account for our breeding design, which incorporated cross-fostering. Both speed and endurance were measured on two consecutive trial days, and both were repeatable. We initially analyzed performances on each trial day and the maximal value. For endurance, the three estimates of narrow-sense heritabilities ranged from 0.17 to 0.33 (full ADCE model), and some were statistically significantly different from zero using likelihood ratio tests. The heritability estimate for sprint speed measured on trial day 1 was 0.17, but negative for all other measures. Moreover, the additive genetic covariance between speeds measured on the two days was near zero, indicating that the two measures are to some extent different traits. The additive genetic covariance between speed on trial day 1 and any of the four measures of endurance was negative, large, and always statistically significant. None of the measures of speed or endurance was significantly genetically correlated with body mass. Thus, we predict that artificial selection for increased locomotor speed in these mice would result in a decrease in endurance, but no change in body mass. Such experiments could lead to a better understanding of the physiological mechanisms leading to trade-offs in aspects of locomotor abilities. ness, both for laboratory and wild populations (Mousseau For ~ol~~enic traits, quantitative genetic analyses can be and off 1987; off and Mousseau 1987; Boake 1994 and used to study genetic constraints. Quantitative genetics com- references therein). prises statistical methods that partition the observed, within- ~~~~~i~ covariances (typically presented as correlations) population phenotypic variation of a continuously distributed slow the rate at which selection can move a multivariate trait (or traits) into components attributable to a causal model phenotypic mean value for a population towards its optimum of shared additive and nonadditive genetic and environmental value (~~~d~ 1988; ~~~~ld 1992). ~~~~~i~ correlations are effects. Various parameters can be estimated, but two are of not fixed entities and can themselves be altered by selection particular interest: narrow-sense heritability (h" the propor- (Lande 1984; Brodie 1992), For example, correlational se- tion of additive genetic variance to total phenotypic variance) lection (i,e., selection favoring particular trait associations and genetic correlation (r,, the standardized covariance be- (Lande and Arnold 19831) can lead to the formation of genetic tween additive genetic effects for two traits). Heritabilities covariance between traits, either by favoring pleiotropic mu- and genetic correlations can be estimated directly from sets tations (one gene affects multiple traits) or by creating link- of relatives obtained from breeding designs or indirectly from age disequilibrium (nonrandom association of alleles at dif- ferent loci). The relative constancy of genetic variance-co- variance matrices is important for long-term prediction of