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Detecting Recent Positive Selection with a Single Locus Test Bipartitioning the Coalescent Tree

机译:使用单个轨迹测试对合并树进行二分法检测最近的正选择

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摘要

Many population genomic studies have been conducted in the past to search for traces of recent events of positive selection. These traces, however, can be obscured by temporal variation of population size or other demographic factors. To reduce the confounding impact of demography, the coalescent tree topology has been used as an additional source of information for detecting recent positive selection in a population or a species. Based on the branching pattern at the root, we partition the hypothetical coalescent tree, inferred from a sequence sample, into two subtrees. The reasoning is that positive selection could impose a strong impact on branch length in one of the two subtrees while demography has the same effect on average on both subtrees. Thus, positive selection should be detectable by comparing statistics calculated for the two subtrees. Simulations demonstrate that the proposed test based on these principles has high power to detect recent positive selection even when DNA polymorphism data from only one locus is available, and that it is robust to the confounding effect of demography. One feature is that all components in the summary statistics (Du) can be computed analytically. Moreover, misinference of derived and ancestral alleles is seen to have only a limited effect on the test, and it therefore avoids a notorious problem when searching for traces of recent positive selection.
机译:过去已经进行了许多种群基因组学研究,以寻找正选择最近事件的痕迹。但是,人口规模或其他人口因素随时间变化会掩盖这些痕迹。为了减少人口统计学的混杂影响,已将合并树形拓扑用作检测种群或物种中最近的阳性选择的附加信息源。基于根的分支模式,我们将从序列样本推断出的假设合并树划分为两个子树。原因是正选择可能会对两个子树之一的分支长度产生很大影响,而人口统计学对两个子树的平均影响相同。因此,应该通过比较为两个子树计算的统计数据来检测肯定选择。仿真表明,基于这些原理的拟议测试即使在仅来自一个基因座的DNA多态性数据可用的情况下,也具有检测最近的阳性选择的强大能力,并且对人口统计学的混杂效应具有鲁棒性。一个功能是摘要统计(Du)中的所有组件都可以进行分析计算。而且,派生的和祖先的等位基因的错误推断被认为对测试仅具有有限的影响,因此,当寻找最近的阳性选择的痕迹时,它避免了一个臭名昭著的问题。

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