Evidence map›Paper›PMID 27744408›Full record

ArticleMolecular biology and evolution2017

Detecting Adaptation in Protein-Coding Genes Using a Bayesian Site-Heterogeneous Mutation-Selection Codon Substitution Model.

Nicolas Rodrigue, Nicolas Lartillot

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In one paragraph

Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

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17citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. 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 · 2023
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Nicolas RodrigueDepartment of Biology, Institute of Biochemistry, and School of Mathematics and Statistics, Carleton University, Ottawa, Canada nicolas.rodrigue@carleton.ca.
Nicolas LartillotUniversité de Lyon, Laboratoire de Biométrie, Biologie Évolutive, Villeurbanne, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Codon substitution models have traditionally attempted to uncover signatures of adaptation within protein-coding genes by contrasting the rates of synonymous and non-synonymous substitutions. Another modeling approach, known as the mutation-selection framework, attempts to explicitly account for selective patterns at the amino acid level, with some approaches allowing for heterogeneity in these patterns across codon sites. Under such a model, substitutions at a given position occur at the neutral or nearly neutral rate when they are synonymous, or when they correspond to replacements between amino acids of similar fitness; substitutions from high to low (low to high) fitness amino acids have comparatively low (high) rates. Here, we study the use of such a mutation-selection framework as a null model for the detection of adaptation. Following previous works in this direction, we include a deviation parameter that has the effect of capturing the surplus, or deficit, in non-synonymous rates, relative to what would be expected under a mutation-selection modeling framework that includes a Dirichlet process approach to account for across-codon-site variation in amino acid fitness profiles. We use simulations, along with a few real data sets, to study the behavior of the approach, and find it to have good power with a low false-positive rate. Altogether, we emphasize the potential of recent mutation-selection models in the detection of adaptation, calling for further model refinements as well as large-scale applications.

Indexed as

Amino Acid SubstitutionCodonModels, GeneticAdaptation, BiologicalAmino AcidsBayes TheoremComputer SimulationEpistasis, GeneticEvolution, MolecularGenetic HeterogeneityMutationMutation RatePhylogenySelection, GeneticAmino AcidsCodonDirichlet processepistasisfitness landscapeMarkov chain Monte Carlonearly neutral evolution

Identifiers

PMID27744408
PMCPMC5854120

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.