ArticleMolecular biology and evolution2022
A Mutation-Selection Model of Protein Evolution under Persistent Positive Selection.
Article in Molecular biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Characterizing Physicochemical Selection in Protein Evolution with Property-Informed Models (PRIME).bioRxiv : the preprint server for biology · 2026Article
- Chloroplast genome comparison of Valeriana species with sequence variation, selective pressure, and divergence analysis.PloS one · 2026Article
- Estimating the proportion of beneficial mutations that are not adaptive in mammals.PLoS genetics · 2024Article
- Increased Positive Selection in Highly Recombining Genes Does not Necessarily Reflect an Evolutionary Advantage of Recombination.Molecular biology and evolution · 2024Article
- Quantifying microbial guilds.ISME communications · 2024Article
- Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.bioRxiv : the preprint server for biology · 2023Article
- Evolutionary Shortcuts via Multinucleotide Substitutions and Their Impact on Natural Selection Analyses.Molecular biology and evolution · 2023Article
- Beginner's Guide on the Use of PAML to Detect Positive Selection.Molecular biology and evolution · 2023Article
- Lifestyle Transitions in Fusarioid Fungi are Frequent and Lack Clear Genomic Signatures.Molecular biology and evolution · 2022Article
- Evolution of Amino Acid Propensities under Stability-Mediated Epistasis.Molecular biology and evolution · 2022Article
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2 authors.
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Abstract
We use first principles of population genetics to model the evolution of proteins under persistent positive selection (PPS). PPS may occur when organisms are subjected to persistent environmental change, during adaptive radiations, or in host-pathogen interactions. Our mutation-selection model indicates protein evolution under PPS is an irreversible Markov process, and thus proteins under PPS show a strongly asymmetrical distribution of selection coefficients among amino acid substitutions. Our model shows the criteria ω>1 (where ω is the ratio of nonsynonymous over synonymous codon substitution rates) to detect positive selection is conservative and indeed arbitrary, because in real proteins many mutations are highly deleterious and are removed by selection even at positively selected sites. We use a penalized-likelihood implementation of the PPS model to successfully detect PPS in plant RuBisCO and influenza HA proteins. By directly estimating selection coefficients at protein sites, our inference procedure bypasses the need for using ω as a surrogate measure of selection and improves our ability to detect molecular adaptation in proteins.
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