ArticleMolecular biology and evolution2021
A Bayesian Mutation-Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes.
Article in Molecular biology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers.
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11 citing papers in PubMed.
- Characterizing Physicochemical Selection in Protein Evolution with Property-Informed Models (PRIME).bioRxiv : the preprint server for biology · 2026Article
- Accurate prediction of substitution rates at protein sites with a mutation-selection model.Scientific reports · 2025Article
- Stochastic Character Mapping: An Under-Exploited Approach to the Study of Molecular Evolution.Journal of molecular evolution · 2025Article
- Estimating the proportion of beneficial mutations that are not adaptive in mammals.PLoS genetics · 2024Article
- Positive selection analyses identify a single WWE domain residue that shapes ZAP into a more potent restriction factor against alphaviruses.PLoS pathogens · 2024Article
- Positive selection analyses identify a single WWE domain residue that shapes ZAP into a super restriction factor.bioRxiv : the preprint server for biology · 2023Article
- Evolutionary Shortcuts via Multinucleotide Substitutions and Their Impact on Natural Selection Analyses.Molecular biology and evolution · 2023Article
- Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Evolution is not Uniform Along Coding Sequences.Molecular biology and evolution · 2023Article
- An Improved Codon Modeling Approach for Accurate Estimation of the Mutation Bias.Molecular biology and evolution · 2022Article
- A Mutation-Selection Model of Protein Evolution under Persistent Positive Selection.Molecular biology and evolution · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
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.
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