Abstract
Most traits are polygenic and the contributing loci can be identified by GWAS. Their adaptive architecture is, however, poorly characterized. Here, we propose a new approach to study the adaptive architecture, which does not depend on genomic data. Relying on experimental evolution we measure the phenotypic variance in replicated populations during adaptation to a new environment. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting is a powerful approach to distinguish between oligogenic and polygenic adaptive architectures. We apply this new method to gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We conclude that adaptive gene expression evolution is best explained by a highly polygenic adaptive architecture. We propose that the evolution of phenotypic variance provides a powerful approach to characterize the adaptive architecture, in particular when combined with genomic data.
Competing Interest Statement
The authors have declared no competing interest.
