A Bayesian Mutation–Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

Rodrigue, Nicolas; Latrille, Thibault; Lartillot, Nicolas

doi:10.1093/molbev/msaa265

Cited by 14 publications

(21 citation statements)

References 36 publications

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“…Mammalian β − globin is one of the datasets from Yang et al . (2000a) where positive selection has been inferred, and confirmed using many other studies and methods (e.g., Rodrigue et al . (2021)).…”

Section: Resultssupporting

confidence: 76%

Evolutionary shortcuts via multi-nucleotide substitutions and their impact on natural selection analyses

Lucaci

Zehr

Pond

2022

Preprint

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Inference and interpretation of evolutionary processes - in particular of the types and targets of natural selection affecting coding sequences, are critically influenced by the assumptions built into statistical models for such analyses. If certain aspects of the substitution process (even when they are not of direct interest) are presumed absent or are modeled with too crude of a simplification, estimates of key model parameters can become biased - often systematically, and lead to poor statistical performance. Here, we performed a detailed characterization of how modeling instantaneous multi-nucleotide (or multi-hit, MH) substitutions impacts dN/dS based inference of episodic diversifying selection at the level of the entire alignment. The inclusion of MH reduces the rate (1.37-fold or 26.8%) at which positive selection is called based on the analysis of N = 9,861 empirical data-sets, while offering significantly better statistical fit to sequence data in 8.37% of cases. Through additional simulation studies, we show that this reduction is not simply due to loss of power because of additional model complexity. After a detailed examination of 21 benchmark alignments and a new high-resolution analysis showing which parts of the alignment provide support for positive selection, we reveal that MH substitutions occurring along shorter branches in the tree are largely responsible for discrepant results in selection detection. Our results add to the growing body of literature which examines decades-old modeling assumptions and finds them to be problematic for biological data analysis. Because multi-nucleotide substitutions have a significant impact on natural selection detection even at the level of an entire gene, we recommend that routine selection analysis of this type consider their inclusion. To facilitate this procedure, we developed a simple model testing selection detection framework able to screen an alignment for positive selection with two biologically important confounding processes: synonymous rate variation, and multi-nucleotide instantaneous substitutions.

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Section: Resultssupporting

confidence: 76%

Evolutionary shortcuts via multi-nucleotide substitutions and their impact on natural selection analyses

Lucaci

Zehr

Pond

2022

Preprint

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“…Mutation–selection models of codon substitution have been successfully used to study the distribution of selection coefficients in proteins ( Rodrigue et al 2010 ; Tamuri et al 2014 ), to detect selection shifts during adaptation ( Parto and Lartillot 2017 ), shifting balance ( Jones et al 2016 ), and to understand protein evolution given structural constraints ( Youssef et al 2020 ). Previous works have also accommodated a ω parameter within the mutation–selection model to detect adaptation at amino acid sites ( Yang and Nielsen 2008 ; Rodrigue and Lartillot 2017 ; Rodrigue et al 2021 ). However in these works ω is a separate parameter and not a function of the selection coefficients and thus its population genetics interpretation is not clear ( Rodrigue and Lartillot 2017 ).…”

Section: Discussionmentioning

confidence: 99%

A Mutation–Selection Model of Protein Evolution under Persistent Positive Selection

Tamuri

Reis

2021

Molecular Biology and Evolution

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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 non-synonymous 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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“…We ran the Bayesian software BayesCode (https://github.com/ThibaultLatrille/bayescode) on each protein-coding DNA alignment [49]. Each Monte-Carlo Markov-Chain (MCMC) is run during 2,000 points, with a burn-in of 1,000 points, to obtain the posterior mean of ω and ω 0 across the MCMC, as well as the 95% posterior credibility interval for genes and sites.…”

Section: Adaptation In Phylogeny-based Methodsmentioning

confidence: 99%

Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale

Latrille

Rodrigue

Lartillot

2022

Preprint

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Adaptation in protein-coding sequences can be detected from multiple sequence alignments across species, or alternatively by leveraging polymorphism data inside a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of non-synonymous over synonymous substitution rates. Evidence of an accelerated non-synonymous substitution rate is considered a signature of pervasive adaptation. However, because of the background of purifying selection, these models are potentially limited in their sensitivity. Recent developments have led to more sophisticated mutation-selection codon models aimed at making a more detailed quantitative assessment of the interplay between mutation, purifying and positive selection. In this study, we conducted a large-scale exome-wide analysis of placental mammals with mutation-selection models, assessing their performance at detecting proteins and sites under adaptation. Importantly, mutation-selection codon models are based on a population-genetic formalism and thus are directly comparable to McDonald \& Kreitman tests at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics, we integrated divergence and polymorphism data across the entire exome for 29 populations across 7 genera, and showed that proteins and sites detected to be under adaptation at the phylogenetic scale are also under adaptation at the population-genetic scale. Altogether, our exome-wide analysis shows that phylogenetic mutation-selection codon models and population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.

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A Bayesian Mutation–Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

Cited by 14 publications

References 36 publications

Evolutionary shortcuts via multi-nucleotide substitutions and their impact on natural selection analyses

Evolutionary shortcuts via multi-nucleotide substitutions and their impact on natural selection analyses

A Mutation–Selection Model of Protein Evolution under Persistent Positive Selection

Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale

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