Abstract:Convergence is the process by which several species independently develop similar traits. This evolutionary process is not only strongly related to fundamental questions such as the predictability of evolution and the role of adaptation, its study also may provide new insights about genes involved in the convergent phenotype. We focus on this latter question and aim to detect the molecular basis of a given phenotypic convergence.
After pointing out a number of concerns with current detection methods based on a… Show more
“…We have not attempted to work at the level of entire gene sequences or even functional groups of genes, whereby the evidence obtained at the level of individual sites would be used collectively over the entire gene length or over several genes with a particular function to classify a gene or group of genes as convergent or not. However, other works have developed methods to work above the level of single sites ( Chabrol et al., 2017 ; Marcovitz et al., 2017 ), and our method is compatible with these. Both these approaches detect convergent substitutions that fit the definition of Zhang and Kumar (1997) and Foote et al.…”
Section: Discussionmentioning
confidence: 99%
“…(2015) , but use different approaches to classify genes as convergent or not. Chabrol et al. (2017) combine their site-wise analysis with a procedure involving simulations according to a null model to classify genes as convergent or not.…”
In the history of life, some phenotypes have been acquired several times independently, through convergent evolution. Recently, lots of genome-scale studies have been devoted to identify nucleotides or amino acids that changed in a convergent manner when the convergent phenotypes evolved. These efforts have had mixed results, probably because of differences in the detection methods, and because of conceptual differences about the definition of a convergent substitution. Some methods contend that substitutions are convergent only if they occur on all branches where the phenotype changed toward the exact same state at a given nucleotide or amino acid position. Others are much looser in their requirements and define a convergent substitution as one that leads the site at which they occur to prefer a phylogeny in which species with the convergent phenotype group together. Here, we suggest to look for convergent shifts in amino acid preferences instead of convergent substitutions to the exact same amino acid. We define as convergent shifts substitutions that occur on all branches where the phenotype changed and such that they correspond to a change in the type of amino acid preferred at this position. We implement the corresponding model into a method named PCOC. We show on simulations that PCOC better recovers convergent shifts than existing methods in terms of sensitivity and specificity. We test it on a plant protein alignment where convergent evolution has been studied in detail and find that our method recovers several previously identified convergent substitutions and proposes credible new candidates.
“…We have not attempted to work at the level of entire gene sequences or even functional groups of genes, whereby the evidence obtained at the level of individual sites would be used collectively over the entire gene length or over several genes with a particular function to classify a gene or group of genes as convergent or not. However, other works have developed methods to work above the level of single sites ( Chabrol et al., 2017 ; Marcovitz et al., 2017 ), and our method is compatible with these. Both these approaches detect convergent substitutions that fit the definition of Zhang and Kumar (1997) and Foote et al.…”
Section: Discussionmentioning
confidence: 99%
“…(2015) , but use different approaches to classify genes as convergent or not. Chabrol et al. (2017) combine their site-wise analysis with a procedure involving simulations according to a null model to classify genes as convergent or not.…”
In the history of life, some phenotypes have been acquired several times independently, through convergent evolution. Recently, lots of genome-scale studies have been devoted to identify nucleotides or amino acids that changed in a convergent manner when the convergent phenotypes evolved. These efforts have had mixed results, probably because of differences in the detection methods, and because of conceptual differences about the definition of a convergent substitution. Some methods contend that substitutions are convergent only if they occur on all branches where the phenotype changed toward the exact same state at a given nucleotide or amino acid position. Others are much looser in their requirements and define a convergent substitution as one that leads the site at which they occur to prefer a phylogeny in which species with the convergent phenotype group together. Here, we suggest to look for convergent shifts in amino acid preferences instead of convergent substitutions to the exact same amino acid. We define as convergent shifts substitutions that occur on all branches where the phenotype changed and such that they correspond to a change in the type of amino acid preferred at this position. We implement the corresponding model into a method named PCOC. We show on simulations that PCOC better recovers convergent shifts than existing methods in terms of sensitivity and specificity. We test it on a plant protein alignment where convergent evolution has been studied in detail and find that our method recovers several previously identified convergent substitutions and proposes credible new candidates.
“…An extension of this method, the "expectation" method of Chabrol et al (15) , also called msd, looks for sites with a high convergence index. This convergence index is the expected number of substitutions to a particular amino acid in lineages with the convergent phenotype.…”
Section: Methods Looking For Independent Substitutions To the Same Ammentioning
In evolutionary genomics, researchers have taken an interest in identifying in the genomes substitutions that subtend convergent phenotypic adaptations. This is a difficult question to address, because genomes contain billions of sites, many of which have substituted in the lineages where the adaptations took place, and yet are not linked to them. Those extra substitutions may be linked to other adaptations, may be neutral, or may be linked to mutational biases. Furthermore, one can think of various ways of defining substitutions of interest, and various methods that match those definitions have been used, resulting in different sets of candidate substitutions. In this manuscript we first clarify how adaptation to convergent phenotypic evolution can manifest itself in coding sequences. Second, we review methods that have been proposed to detect convergent adaptive evolution in coding sequences and expose the assumptions that underlie them. Finally, we examine their power on simulations of convergent changes, including in the presence of a confounding factor.
“…None of the following methods have been designed to detect convergent increases or decreases in selection efficacy, so we expect they should do much better at detecting convergent profile changes than convergent changes in selection efficacy. All methods except one (msd, [19]) assume that convergent lineages are known without uncertainty and that corresponding clades are given as input. Figure 2.Cartoon examples of the types of sites targeted by each type of method.…”
Section: Introductionmentioning
confidence: 99%
“…An extension of this method, the ‘expectation’ method of Chabrol et al [19]—also called msd—looks for sites with a high ‘convergence index’. This convergence index is the expected number of substitutions to a particular amino acid in convergent lineages.…”
In evolutionary genomics, researchers have taken an interest in identifying substitutions that subtend convergent phenotypic adaptations. This is a difficult question that requires distinguishing
foreground
convergent substitutions that are involved in the convergent phenotype from
background
convergent substitutions. Those may be linked to other adaptations, may be neutral or may be the consequence of mutational biases. Furthermore, there is no generally accepted definition of convergent substitutions. Various methods that use different definitions have been proposed in the literature, resulting in different sets of candidate foreground convergent substitutions. In this article, we first describe the processes that can generate foreground convergent substitutions in coding sequences, separating adaptive from non-adaptive processes. Second, we review methods that have been proposed to detect foreground convergent substitutions in coding sequences and expose the assumptions that underlie them. Finally, we examine their power on simulations of convergent changes—including in the presence of a change in the efficacy of selection—and on empirical alignments.
This article is part of the theme issue ‘Convergent evolution in the genomics era: new insights and directions'.
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