Antler size in red deer: heritability and selection but no evolution.
ABSTRACT We present estimates of the selection on and the heritability of a male secondary sexual weapon in a wild population: antler size in red deer. Male red deer with large antlers had increased lifetime breeding success, both before and after correcting for body size, generating a standardized selection gradient of 0.44 (+/- 0.18 SE). Despite substantial age- and environment-related variation, antler size was also heritable (heritability of antler mass = 0.33 +/- 0.12). However the observed selection did not generate an evolutionary response in antler size over the study period of nearly 30 years, and there was no evidence of a positive genetic correlation between antler size and fitness nor of a positive association between breeding values for antler size and fitness. Our results are consistent with the hypothesis that a heritable trait under directional selection will not evolve if associations between the measured trait and fitness are determined by environmental covariances: In red deer males, for example, both antler size and success in the fights for mates may be heavily dependent on an individual's nutritional state.
Full-textDOI: · Available from: Loeske E B Kruuk, Oct 22, 2014
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ABSTRACT: Knowledge of the underlying genetic architecture of quantitative traits could aid in understanding how they evolve. In wild populations it is still largely unknown whether complex traits are polygenic or influenced by few loci with major effect, due to often small sample sizes and low resolution of marker panels. Here we examine the genetic architecture of five adult body size traits in a free-living population of Soay sheep on St Kilda using 37,037 polymorphic SNPs. Two traits (jaw and weight) show classical signs of a polygenic trait: the proportion of variance explained by a chromosome was proportional to its length, multiple chromosomes and genomic regions explained significant amounts of phenotypic variance, but no SNPs were associated with trait variance when using GWAS. In comparison genetic variance for leg length traits (foreleg, hindleg and metacarpal) was disproportionately explained by two SNPs on chromosomes 16 (s23172.1) and 19 (s74894.1), which each explained >10% of the additive genetic variance. After controlling for environmental differences, females heterozygous for s74894.1 produced more lambs and recruits during their lifetime than females homozygous for the common allele conferring long legs. We also demonstrate that alleles conferring shorter legs have likely entered the population through a historic admixture event with the Dunface sheep. In summary, we show that different proxies for body size can have very different genetic architecture, and that dense SNP help in understanding both the mode of selection and the evolutionary history at loci underlying quantitative traits in natural populations. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.Molecular Ecology 03/2015; 24(8). DOI:10.1111/mec.13146 · 5.84 Impact Factor
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ABSTRACT: Evolutionary theory predicts that genetic constraints should be widespread, but empirical support for their existence is surprisingly rare. Commonly-applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially only tractable within a multivariate framework. However, multivariate genetic analyses of data from natural populations are challenging because of modest sample sizes, incomplete pedigrees and missing data. Here we present results from a study of a comprehensive set of life history traits (juvenile survival, age at first breeding, annual fecundity and longevity) for both males and females in a wild, pedigreed, population of red deer (Cervus elaphus). We use factor analytic modeling of the genetic variance-covariance matrix ( G: ) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints. We consider a range of metrics designed to assess the effect of G: on the deflection of a predicted response to selection away from the direction of fastest adaptation, and on the evolvability of the traits. We found limited support for genetic constraint through genetic covariances between traits, both within- and between-sex. We discuss these results with respect to other recent findings and to the problems of estimating these parameters for natural populations.Genetics 10/2014; DOI:10.1534/genetics.114.164319 · 4.87 Impact Factor
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ABSTRACT: Sexual selection promotes the prevalence of heritable traits that increase an individual's reproductive rate. Despite theoretically strong directional selection, sexually selected traits can show inter-individual variation. Here, we investigate whether red skin ornamentation, a rare example of a male mammalian trait involved in mate attraction, influences fecundity and is heritable in rhesus macaques (Macaca mulatta), and explore the mechanisms that are involved in maintaining trait variation. Interestingly, the trait is expressed by and is attractive to both sexes. We collected facial images of 266 free-ranging individuals and modelled skin redness and darkness to rhesus macaque vision. We used 20 years of genetic parentage data to calculate selection gradients on the trait and perform heritability analyses. Results show that males who were both darkly coloured and high-ranking enjoyed higher fecundity. Female skin redness was positively linked to fecundity, although it remains unclear whether this influences male selectiveness. Heritability explained 10-15% of the variation in redness and darkness, and up to 30% for skin darkness when sexes are considered separately, suggesting sex-influenced inheritance. Our results suggest that inter-individual variation is maintained through condition-dependence, with an added effect of balancing selection on male skin darkness, providing rare evidence for a mammalian trait selected through inter-sexual selection.Proceedings of the Royal Society B: Biological Sciences 09/2014; DOI:10.1098/rspb.2014.1602 · 5.29 Impact Factor