Genome-Wide Search for Candidate Drivers of Adaptation Reveals Genes Enriched for Shifts in Purifying Selection (SPurS)

Abstract

An open question in comparative evolutionary genomics is whether or not certain loci are the primary drivers of divergence between taxonomic lineages or species groups. Alternatively, genetic drivers of species divergence may be evenly distributed across the genome. The increasing availability of genome sequences from diverse taxa has enabled the development of novel methods to address this question. Genomes of many highly diverged species may now be compared in order to tease apart genetic differences that drive adaptive or functional divergence, and genetic differences that are observed by chance and are not causally linked to traits that differ between species or lineages. In order to test the hypothesis that a particular subset of loci or genes is responsible for driving adaptive changes between mammals and non-mammals, we developed a novel comparative approach to identify sites that are highly conserved within lineages or species groups and diverge between them. Loci with a high concentration of these sites may be called Shifts in Purifying Selection (SPurS) because a change has occurred between two groups of species at some point in the past, and the shift is conserved (via purifying selection) over a long period of time. Evaluating 7484 orthologous gene copies from 76 vertebrate species, we developed an empirical distribution of SPurS across the genome between Synapsida (placental and non-placental mammals) and Sauropsida (birds, crocodilians, squamates, and turtles), and compared this distribution to the expected null distribution of SPurS using matched simulated data. We then identified a subset of genes that is enriched for SPurS, relative to the full set of genes and to their matched simulated alignments. These SPurS-enriched genes are thus likely candidate drivers of functional divergence or adaptation between the mammalian and non-mammalian species groups in our analysis. Investigators seeking to identify genetic drivers of inter-species evolution may find this method useful, and we provide a web-based software interface to facilitate its use.