A Bayesian Mutation–Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes. (12th October 2020)

• Record Type: Journal Article
• Authors: Rodrigue, Nicolas; Latrille, Thibault; Lartillot, Nicolas
• Editors: Pupko, Tal
• Is Part Of: Molecular biology and evolution. Volume 38:Number 3(2021)
• Page Start: 1199
• Page End: 1208
• Publication Date: 2020-10-12
• Subjects: nearly neutral evolution -- fitness landscape -- Dirichlet process -- Markov chain Monte Carlo; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msaa265
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: In recent years, codon substitution models based on the mutation–selection principle have been extended for the purpose of detecting signatures of adaptive evolution in protein-coding genes. However, the approaches used to date have either focused on detecting global signals of adaptive regimes—across the entire gene—or on contexts where experimentally derived, site-specific amino acid fitness profiles are available. Here, we present a Bayesian site-heterogeneous mutation–selection framework for site-specific detection of adaptive substitution regimes given a protein-coding DNA alignment. We offer implementations, briefly present simulation results, and apply the approach on a few real data sets. Our analyses suggest that the new approach shows greater sensitivity than traditional methods. However, more study is required to assess the impact of potential model violations on the method, and gain a greater empirical sense its behavior on a broader range of real data sets. We propose an outline of such a research program.