A Bayesian Mutation-Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes.
Dirichlet process
Markov chain Monte Carlo
fitness landscape
nearly neutral evolution
Journal
Molecular biology and evolution
ISSN: 1537-1719
Titre abrégé: Mol Biol Evol
Pays: United States
ID NLM: 8501455
Informations de publication
Date de publication:
09 03 2021
09 03 2021
Historique:
pubmed:
13
10
2020
medline:
25
6
2021
entrez:
12
10
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33045094
pii: 5921184
doi: 10.1093/molbev/msaa265
pmc: PMC7947879
doi:
Types de publication
Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1199-1208Commentaires et corrections
Type : ErratumIn
Informations de copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
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