Computational Approach Quantifies Signatures of Selection Across the Genome

A Vanderbilt University-led team has developed a computational approach to gauge which types of evolutionary forces are at work at various genomic regions. As they report in PLOS Genetics, the researchers applied their framework, which considers nearly a dozen evolutionary measures, to data from more than 900 genome-wide association studies and generated an atlas of evolutionary signatures associated with a range of traits. They found, for instance, high levels of sequence conservation in most trait-association regions as well as signs of population differentiation for traits related to hair, skin, and pigmentation. Meanwhile, they noted a broad negative enrichment for signatures of balancing selection and that regions linked to late-onset Alzheimer's disease had an absence of enrichment for any evolutionary signatures. "In summary, our quantification of genomic signatures of selection on trait-associated regions advances our understanding of the genetic architecture of complex traits and illuminates the diverse forces that have shaped functional regions of the human genome," the researchers write.