Open AccessInterpreting differentiation landscapes in the light of long‐term linked selection
Author(s) -
Burri Reto
Publication year - 2017
Publication title -
evolution letters
Language(s) - English
Resource type - Journals
ISSN - 2056-3744
DOI - 10.1002/evl3.14
Subject(s) - selection (genetic algorithm) , adaptation (eye) , extant taxon , evolutionary biology , adaptive evolution , term (time) , genetic algorithm , biology , genome , natural selection , genomics , exploit , population genomics , population , computer science , artificial intelligence , genetics , gene , neuroscience , physics , computer security , demography , quantum mechanics , sociology
Identifying genomic regions underlying adaptation in extant lineages is key to understanding the trajectories along which biodiversity evolves. However, this task is complicated by evolutionary processes that obscure and mimic footprints of positive selection. Particularly, the long‐term effects of linked selection remain underappreciated and difficult to account for. Based on patterns emerging from recent research on the evolution of differentiation across the speciation continuum, I illustrate how long‐term linked selection affects the distribution of differentiation along genomes. I then argue that a comparative population genomics framework that exploits emergent features of long‐term linked selection can help overcome shortcomings of traditional genome scans for adaptive evolution, but needs to account for the temporal dynamics of differentiation landscapes.