Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages
Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages
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DOI：
10.1093/oxfordjournals.molbev.a004148
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发表时间：
2002-06-01
影响因子：
10.7
通讯作者：
Nielsen, R
中科院分区：
文献类型：
--
作者：
Yang, ZH;Nielsen, R
非同义(氨基酸变化)与同义(沉默)替代率比率(omega=d(N)/d(S))提供了蛋白质水平上的自然选择的衡量标准。Omega=1、>；1和>；1表示中性进化，净化选择。和积极选择。以前使用这种方法来检测阳性选择的研究通常采取所有配对比较的方法，通过平均蛋白质中的所有位点来估计替换率。由于功能蛋白质中的大多数氨基酸都受到更广泛的结构和功能限制，而适应性进化可能只在几个时间点影响少数几个位点，这种在位点和时间上平均速率的方法效果不大。以前，我们开发了基于密码子的替代模型，允许omega比率在不同谱系或不同地点之间变化。在本文中，我们扩展了以前的模型，允许omega比率在不同位置和谱系之间变化，并实现了新的模型，在似然框架中，这些模型可能有助于识别沿预先指定的谱系的正选择，这些选择只影响蛋白质中的少数几个位置。我们将这些分支位置模型以及之前的分支和特定位置模型应用于三个数据集：灵长类动物的溶菌酶基因。肿瘤抑制基因BRCA1在灵长类动物的前部，以及被子植物中的光敏色素基因家族。新的和旧的模型都在溶菌酶和BRCA基因中检测到正选择。然而。只有新的模型检测到阳性，在PHY基因家族中基因复制后对谱系产生选择作用。对几个数据集的额外测试表明，新模型可能有助于检测基因家族进化中基因复制后的正选择。
The nonsynonymous (amino acid-altering) to synonymous (silent) substitution rate ratio (omega = d(N)/d(S)) provides a measure of natural selection at the protein level. with omega = 1, >1, and >1, indicating neutral evolution, purifying selection. and positive selection. respectively, Previous studies that used this Measure to detect positive,election have often taken all approach of pairwise comparison, estimating substitution rates by averaging over all site,, in the protein. As most amino acids in a functional protein arc Wider structural and functional constraints and adaptive evolution probably affects only a few sites at a few time points, this approach of averaging rates mer sites and Over time has little power. Previously, we de eloped codon-based substitution models that allow the omega ratio to vary either among lineages or among sites. In this paper we extend previous Models to allow the omega ratio to vary both among sites and among lineages and implement the new model,, in the likelihood framework, These models may be useful for identifying positive selection along prespecified lineages that affects only a few sites in the protein. We apply those branch-site models as well as previous branch- and site-specific models to three data sets: the lysozyme genes from primates. the tumor suppressor BRCA1 genes front primates, and the phytochrome gene family in angiosperms. Positive selection is detected in the lysozyme and BRCA genes by both the new and the old models. However. only the new models detected positive,election acting on lineages after gene duplication in the PHY gene family. Additional tests on several data sets suggest that the new models may be useful in detecting positive selection after gene duplication in gene family evolution.