239T Poster - Population Genetics
Thursday June 09, 9:15 PM - 10:00 PM

Authors:
Alyssa Pivirotto ^1,3; Alexander Platt ⁴; Ravi Patel ^2,3; Sudhir Kumar ^2,3; Jody Hey ^1,3

Affiliations:
1) Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA; 2) Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA; 3) Department of Biology, Temple University, Philadelphia, PA; 4) Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA

Keywords:
Natural selection

To understand the evolutionary history of a population and expression of phenotypic traits including disease, we first have to understand how selection affects underlying mutations. Here, a new approach is described for assessing the evolutionary history of selection on non-synonymous mutations. The method makes use of the evolutionary probability (EP) approach that leverages a phylogeny with divergence times to assign each amino acid a posterior probability of appearing at a specific loci. We consider the EP of segregating alleles together with estimates of their age and frequency. If a mutation is under selection, we expect it to have a young age and to ultimately and quickly be lost or fixed in a population. Thus, these mutations under selective force would be younger than neutral alleles of the same frequency who reached that frequency due to random genetic drift. We observe in the UK10K sample of 7242 human genomes that derived mutations that have a low EP are younger on average than neutral mutations of the same frequency. This is expected if such alleles are deleterious. By the same reasoning, if derived alleles of high EP are under positive selection, then we expect these to also be younger on average. However, we find that evolutionary derived high EP alleles are older on average than neutral alleles of the same frequency. Our results combine allele age estimates with both evolutionary probability and frequency and reveal unexpected trends that indicate a more complex model of balancing selection on alleles of high evolutionary probability.