Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.
Emerging Pathogens Institute, University of Florida, Gainesville, FL.
Mol Biol Evol. 2021 Mar 9;38(3):1184-1198. doi: 10.1093/molbev/msaa263.
A number of evolutionary hypotheses can be tested by comparing selective pressures among sets of branches in a phylogenetic tree. When the question of interest is to identify specific sites within genes that may be evolving differently, a common approach is to perform separate analyses on subsets of sequences and compare parameter estimates in a post hoc fashion. This approach is statistically suboptimal and not always applicable. Here, we develop a simple extension of a popular fixed effects likelihood method in the context of codon-based evolutionary phylogenetic maximum likelihood testing, Contrast-FEL. It is suitable for identifying individual alignment sites where any among the K≥2 sets of branches in a phylogenetic tree have detectably different ω ratios, indicative of different selective regimes. Using extensive simulations, we show that Contrast-FEL delivers good power, exceeding 90% for sufficiently large differences, while maintaining tight control over false positive rates, when the model is correctly specified. We conclude by applying Contrast-FEL to data from five previously published studies spanning a diverse range of organisms and focusing on different evolutionary questions.
可以通过比较系统发育树中分支集之间的选择压力来检验许多进化假说。当感兴趣的问题是确定基因内可能以不同方式进化的特定位点时,一种常见的方法是对序列子集进行单独的分析,并以事后的方式比较参数估计。这种方法在统计学上是次优的,并不总是适用。在这里,我们在基于密码子的进化系统发育最大似然检验的背景下,对流行的固定效应似然方法进行了简单的扩展,即 Contrast-FEL。它适用于识别系统发育树中任何 K≥2 个分支的单个对齐位点,这些位点的 ω 比值具有可检测的差异,表明存在不同的选择模式。通过广泛的模拟,我们表明 Contrast-FEL 具有很好的功效,对于足够大的差异,功效超过 90%,而在模型正确指定的情况下,保持对假阳性率的严格控制。最后,我们将 Contrast-FEL 应用于来自五个先前发表的研究的数据,这些研究涵盖了广泛的生物体,并专注于不同的进化问题。