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A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and Its Application to Influenza A Virus

机译:检测蛋白质序列方向进化的最大似然法及其在甲型流感病毒中的应用

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摘要

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution toward a given residue at individual positions of a protein alignment—directional evolution of protein sequences (DEPS). DEPS can identify both the target residue and sites evolving toward it, help detect selective sweeps and frequency-dependent selection—scenarios that confound most existing tests for selection, and achieve good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype), and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies and document known functional correlates, such as immune escape or host adaptation.
机译:我们开发了基于模型的系统发生最大似然测试,以证明在蛋白质比对的各个位置朝着给定残基的优先取代的证据-蛋白质序列的定向进化(DEPS)。 DEPS可以识别目标残留物和向其进化的位点,帮助检测选择性扫描和与频率相关的选择,这些场景使大多数现有的选择测试混淆了,并在模拟数据上获得了良好的功效和准确性。我们将DEPS应用于代表禽流感(H5N1血清型)和人类宿主(H3N2血清型)的甲型流感病毒不同基因组区域的比对,并在H5N1和H3N2 IAV的5/8基因组片段中鉴定了多个方向进化的位点。我们提出了基于残基频率的时间分布和方向已知演变为5个组的简单描述性分类,并记录了已知的功能相关性,例如免疫逃逸或宿主适应性。

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