1Department of Biology, Pennsylvania State University, 2Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 3Department of Integrative Biology, University of California, Berkeley
April 14, 2016 2:30, Imperial Ballroom B
While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. We designed the first set of likelihood-based methods that explicitly model the genealogical process under ancient balancing selection using a coalescent framework. Simulation results show that our methods for detecting ancient balancing selection vastly outperform previous approaches based on summary statistics, and are robust to demography. We apply the new methods to whole-genome sequencing data from humans, and find a number of previously-identified loci with strong evidence of balancing selection, including various HLA genes. Not only are our methods for identifying signatures of ancient balancing selection the most powerful developed to date, but they can also be applied to any organism with polymorphism data and an outgroup sequence. As such, we expect that our methods will be widely used by the genomics community to uncover the potentially numerous genomic regions that are under ancient balancing selection in many non-human species.