Accurate Detection of Convergent Amino-Acid Evolution with PCOC. (7th July 2018)

• Record Type: Journal Article
• Authors: Rey, Carine; Guéguen, Laurent; Sémon, Marie; Boussau, Bastien
• Editors: Pupko, Tal
• Is Part Of: Molecular biology and evolution. Volume 35:Number 9(2018)
• Page Start: 2296
• Page End: 2306
• Publication Date: 2018-07-07
• Subjects: convergent evolution -- genomics -- bioinformatics -- echolocation -- C4 metabolism -- sequence evolution; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msy114
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: In the history of life, some phenotypes have been acquired several times independently, through convergent evolution. Recently, lots of genome-scale studies have been devoted to identify nucleotides or amino acids that changed in a convergent manner when the convergent phenotypes evolved. These efforts have had mixed results, probably because of differences in the detection methods, and because of conceptual differences about the definition of a convergent substitution. Some methods contend that substitutions are convergent only if they occur on all branches where the phenotype changed toward the exact same state at a given nucleotide or amino acid position. Others are much looser in their requirements and define a convergent substitution as one that leads the site at which they occur to prefer a phylogeny in which species with the convergent phenotype group together. Here, we suggest to look for convergent shifts in amino acid preferences instead of convergent substitutions to the exact same amino acid. We define as convergent shifts substitutions that occur on all branches where the phenotype changed and such that they correspond to a change in the type of amino acid preferred at this position. We implement the corresponding model into a method named PCOC. We show on simulations that PCOC better recovers convergent shifts than existing methods in terms of sensitivity and specificity. We test it on a plant protein alignment where convergent evolution has been studied in detail and find that our method recovers several previously identified convergent substitutions and proposes credible new candidates.