Université de Lyon, Université Lyon 1, CNRS, VetAgro Sup, Laboratoire de Biométrie et Biologie Evolutive, UMR5558, 69100 Villeurbanne, France.
École Normale Supérieure de Lyon, Université de Lyon, 69342 Lyon, France.
Proc Natl Acad Sci U S A. 2023 Mar 14;120(11):e2214977120. doi: 10.1073/pnas.2214977120. Epub 2023 Mar 10.
Adaptation in protein-coding sequences can be detected from multiple sequence alignments across species or alternatively by leveraging polymorphism data within a population. Across species, quantification of the adaptive rate relies on phylogenetic codon models, classically formulated in terms of the ratio of nonsynonymous over synonymous substitution rates. Evidence of an accelerated nonsynonymous 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 the McDonald and Kreitman test at the population level to quantify adaptation. Taking advantage of this relationship between phylogenetic and population genetics analyses, 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 the population-genetic test of adaptation can be reconciled and are congruent, paving the way for integrative models and analyses across individuals and populations.
蛋白质编码序列的适应性可以从跨物种的多序列比对中检测到,或者通过利用群体内的多态性数据来检测。在跨物种的情况下,适应性速率的量化依赖于系统发育密码子模型,这些模型经典地用非同义替换率与同义替换率的比值来表示。加速的非同义替换率的证据被认为是普遍适应的标志。然而,由于净化选择的背景,这些模型在敏感性方面可能存在局限性。最近的发展导致了更复杂的突变-选择密码子模型,旨在更详细地定量评估突变、净化和正选择之间的相互作用。在这项研究中,我们利用突变-选择模型对胎盘哺乳动物进行了大规模的外显子组分析,评估了它们在检测适应过程中的蛋白质和位点的性能。重要的是,突变-选择密码子模型基于群体遗传学的形式主义,因此可以与群体水平上的 McDonald 和 Kreitman 测试直接比较,以量化适应。利用系统发育和群体遗传学分析之间的这种关系,我们整合了整个外显子组的分化和多态性数据,跨越了 7 个属的 29 个种群,并表明在系统发育尺度上被检测到适应的蛋白质和位点也在群体遗传尺度上适应。总的来说,我们的外显子组分析表明,系统发育突变-选择密码子模型和适应的群体遗传检验可以被协调和一致,为个体和群体的综合模型和分析铺平了道路。