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A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Citation

Halabi, Keren; Levy Karin, Eli; Gueguen, Laurent; Mayrose, Itay (2020), A codon model for associating phenotypic traits with altered selective patterns of sequence evolution, Dryad, Dataset, https://doi.org/10.5061/dryad.pzgmsbcjc

Abstract

Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. These methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.

Funding

Edmond J. Safra Center for Bioinformatics

Koret-UC Berkeley-Tel Aviv University Initiative in Computational Biology and Bioinformatics

Edmond J. Safra Center for Bioinformatics