Abstract
Polygenic adaptation is frequently associated with small allele frequency changes of many loci. Recent works suggest, that large allele frequency changes can be also expected. Laboratory natural selection (LNS) experiments provide an excellent experimental framework to study the adaptive architecture under controlled laboratory conditions: time series data in replicate populations evolving independently to the same trait optimum can be used to identify selected loci. Nevertheless, the choice of the new trait optimum in the laboratory is typically an ad hoc decision without consideration of the distance of the starting population to the new optimum. Here, we used forward-simulations to study the selection signatures of polygenic adaptation in populations evolving to different trait optima. Mimicking LNS experiments we analyzed allele frequencies of the selected alleles and population fitness at multiple time points. We demonstrate that the inferred adaptive architecture strongly depends on the choice of the new trait optimum in the laboratory and the significance cut-off used for identification of selected loci. Our results not only have a major impact on the design of future Evolve and Resequence (E&R) studies, but also on the interpretation of current E&R data sets.
