A new method to uncover signatures of divergent and stabilizing selection in quantitative traits

Abstract

While it is well understood that the pace of evolution depends on the interplay between natural selection, random genetic drift, mutation, and gene flow, it is not always easy to disentangle the relative roles of these factors with data from natural populations. One popular approach to infer whether the observed degree of population differentiation has been influenced by local adaptation is the comparison of neutral marker gene differentiation (as reflected in F ST) and quantitative trait divergence (as reflected in Q ST). However, this method may lead to compromised statistical power, because F ST and Q ST are summary statistics which neglect information on specific pairs of populations, and because current multivariate tests of neutrality involve an averaging procedure over the traits. Further, most F ST-Q ST comparisons actually replace Q ST by its expectation over the evolutionary process and are thus theoretically flawed. To overcome these caveats, we derived the statistical distribution of population means generated by random genetic drift and used the probability density of this distribution to test whether the observed pattern could be generated by drift alone. We show that our method can differentiate between genetic drift and selection as a cause of population differentiation even in cases with F ST = Q ST and demonstrate with simulated data that it disentangles drift from selection more accurately than conventional F ST-Q ST tests especially when data sets are small. © 2011 by the Genetics Society of America.