PDF(Pubmed)
Abstract：
The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.
摘要：
从群体基因组数据中检测选择性扫描通常依赖于以下前提:所讨论的有益突变在采样时间附近已经固定。正如前面已经表明的那样，检测选择性扫描的能力强烈依赖于自固定以来的时间以及选择的强度。情况自然是如此强烈，最近的扫荡留下了最强烈的签名。然而,生物学现实是有益的突变以一定的速度进入人群，部分确定扫描事件之间的平均等待时间，从而确定其年龄分布。因此，一个重要的问题仍然是关于检测复发性选择性扫描的能力，当它们通过现实的突变率建模并作为健身效应（DFE）的现实分布的一部分时，而不是单身，最近，在纯中性背景上的孤立事件，这是更常见的建模方法。在这里，我们使用时间前向模拟来研究常用扫描统计信息的性能，在包含净化和背景选择的更现实的进化基线模型的背景下，人口规模变化，突变和重组率异质性。结果表明这些过程的重要相互作用，在解释选择扫描时需要谨慎；特别是，在大部分评估的参数空间中，假阳性率超过真阳性率，和选择性扫描通常是不可检测的，除非选择的强度是非常强的。
