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Data from: Quantitative genetics of female mate preferences in an ancestral and a novel environment
Delcourt, Matthieu; Blows, Mark W.; Rundle, Howard D. — 2012-01-10 A female’s mate preference is a potentially complex function relating variation in multiple male phenotypes with her probability of accepting individual males as a mate. Estimating the quantitative genetic basis of preference functions within a population is empirically challenging yet key to understanding preference evolution. We employed a recently described approach that uses random-coefficient mixed models in the analysis of function-valued traits. Using a half-sibling breeding design in a laboratory-adapted Drosophila serrata population, we estimated the genetic (co)variance function of female preference for male sexual displays composed of nine contact pheromones. The breeding design was performed across two environments: the food to which the population was well adapted and a novel food that reduced average female productivity by 35%. Significant genetic variance in female preference was detected and the majority (64.2%) was attributable to a single genetic dimension (eigenfunction), suggesting that preferences for different pheromones are not genetically independent. The second eigenfunction, accounting for 24% of the total genetic variance, approached significance in a conservative test, suggesting the existence of a second, independent genetic dimension. There was no evidence that the genetic basis of female preference differed between the two environments, suggesting the absence of genotype-by-environment interactions and hence a lack of condition-dependent preference expression.
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Data from: Sexually antagonistic genetic variance for fitness in an ancestral and a novel environment
Delcourt, Matthieu; Blows, Mark W.; Rundle, Howard D. — 2012-01-10 The intersex genetic correlation for fitness (rwfm), a standardized measure of the degree to which male and female fitness covary genetically, has consequences for important evolutionary processes, but few estimates are available and none have explored how it changes with environment. Using a half-sibling breeding design, we estimated the genetic (co)variance matrix (G) for male and female fitness, and the resulting rwfm,in Drosophila serrata. Our estimates were performed in two environments: the laboratory yeast food to which the population was well adapted and a novel corn food. The major axis of genetic variation for fitness in the two environments, accounting for 51.3 per cent of the total genetic variation, was significant and revealed a strong signal of sexual antagonism, loading negatively in both environments on males but positively on females. Consequently, estimates of rwfm were negative in both environments (-0.34 and -0.73, respectively), indicating that the majority of genetic variance segregating in this population has contrasting effects on male and female fitness. The possible strengthening of the negative rwfm in this novel environment may be a consequence of no history of selection for amelioration of sexual conflict. Additional studies from a diverse range of novel environments will be needed to determine the generality of this finding.
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Data from: Evolutionary optimum for male sexual traits characterized using the multivariate Robertson–Price Identity
Delcourt, Matthieu; Blows, Mark W.; Aguirre, J. David; Rundle, Howard D. — 2012-12-10 Phenotypes tend to remain relatively constant in natural populations, suggesting a limit to trait evolution. Although stationary phenotypes suggest stabilizing selection, directional selection is more commonly reported. However, selection on phenotypes will have no evolutionary consequence if the traits do not genetically covary with fitness, a covariance known as the Robertson–Price Identity. The nature of this genetic covariance determines if phenotypes will evolve directionally or whether they reside at an evolutionary optimum. Here, we show how a set of traits can be shown to be under net stabilizing selection through an application of the multivariate Robertson–Price Identity. We characterize how a suite of male sexual displays genetically covaries with fitness in a population of Drosophila serrata. Despite strong directional sexual selection on these phenotypes directly and significant genetic variance in them, little genetic covariance was detected with overall fitness. Instead, genetic analysis of trait deviations showed substantial stabilizing selection on the genetic variance of these traits with respect to overall fitness, indicating that they reside at an evolutionary optimum. In the presence of widespread pleiotropy, stabilizing selection on focal traits will arise through the net effects of selection on other, often unmeasured, traits and will tend to be stronger on trait combinations than single traits. Such selection may be difficult to detect in phenotypic analyses if the environmental covariance between the traits and fitness obscures the underlying genetic associations. The genetic analysis of trait deviations provides a way of detecting the missing stabilizing selection inferred by recent metaanalyses.
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Data from: Estimating uncertainty in multivariate responses to selection
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Stinchcombe, John R.; Simonsen, Anna K.; Blows, Mark W.; Blows, Mark. W. — 2013-11-15 Predicting the responses to natural selection is one of the key goals of evolutionary biology. Two of the challenges in fulfilling this goal have been the realization that many estimates of natural selection might be highly biased by environmentally induced covariances between traits and fitness, and that many estimated responses to selection do not incorporate or report uncertainty in the estimates. Here we describe the application of a framework that blends the merits of the Robertson-Price Identity approach and the multivariate breeders equation to address these challenges. The approach allows genetic covariance matrices, selection differentials, selection gradients, and responses to selection to be estimated without environmentally-induced bias, direct and indirect selection and responses to selection to be distinguished, and if implemented in a Bayesian-MCMC framework, statistically robust estimates of uncertainty on all of these parameters to be made. We illustrate our approach with a worked example of previously published data. More generally, we suggest that applying both the Robertson-Price Identity and the multivariate breeder’s equation will facilitate hypothesis testing about natural selection, genetic constraints, and evolutionary responses.

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(Author: Blows, Mark W.)

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