PDF(Pubmed)
Abstract：
Population branch statistics, which estimate the branch lengths of focal populations with respect to two outgroups, have been used as an alternative to FST-based genome-wide scans for identifying loci associated with local selective sweeps. In addition to the original population branch statistic (PBS), there are subsequently proposed branch rescalings: normalized population branch statistic (PBSn1), which adjusts focal branch length with respect to outgroup branch lengths at the same locus, and population branch excess (PBE), which also incorporates median branch lengths at other loci. PBSn1 and PBE have been proposed to be less sensitive to allele frequency divergence generated by background selection or geographically ubiquitous positive selection rather than local selective sweeps. However, the accuracy and statistical power of branch statistics have not been systematically assessed. To do so, we simulate genomes in representative large and small populations with varying proportions of sites evolving under genetic drift or background selection (approximated using variable Ne), local selective sweeps, and geographically parallel selective sweeps. We then assess the probability that local selective sweep loci are correctly identified as outliers by FST and by each of the branch statistics. We find that branch statistics consistently outperform FST at identifying local sweeps. When background selection and/or parallel sweeps are introduced, PBSn1 and especially PBE correctly identify local sweeps among their top outliers at a higher frequency than PBS. These results validate the greater specificity of rescaled branch statistics such as PBE to detect population-specific positive selection, supporting their use in genomic studies focused on local adaptation.
摘要：
人口科统计，估计焦点人群相对于两个外组的分支长度，已被用作基于FST的全基因组扫描的替代方法，用于识别与局部选择性扫描相关的基因座。除了原始人口分支统计(PBS)之外，随后提出了分支重新划分：归一化人口分支统计量(PBSn1)，相对于同一基因座上的外组分支长度调整焦点分支长度，和人口分支过剩(PBE)，其中还包括其他基因座的中位分支长度。已提出PBSn1和PBE对由背景选择或地理上普遍存在的正选择而不是局部选择性扫描产生的等位基因频率差异较不敏感。然而,部门统计数据的准确性和统计能力尚未得到系统评估。要做到这一点，我们模拟具有代表性的大型和小型群体的基因组，在遗传漂移或背景选择（使用变量Ne近似）下进化的不同比例的位点，本地选择性扫描，和地理上平行的选择性扫描。然后，我们通过FST和每个分支统计量评估将局部选择性扫描基因座正确识别为异常值的概率。我们发现，在识别本地扫描时，分支统计信息的表现始终优于FST。当引入背景选择和/或并行扫描时，PBSn1和特别是PBE以高于PBS的频率正确地识别其顶部异常值中的局部扫描。这些结果验证了重新缩放的分支统计数据（如PBE）的更大特异性，以检测特定人群的阳性选择。支持它们在侧重于局部适应的基因组研究中的使用。
■人口分支统计被广泛用于全基因组扫描，以识别与局部适应相关的基因座。这项研究发现，在广泛的人口统计学参数和进化模型下，分支统计在识别局部选择性扫描方面比FST更准确。它还表明，某些分支统计数据提高了将局部适应与其他自然选择模型区分开来的能力。
■人口分支统计被广泛用于全基因组扫描，以识别与局部适应相关的基因座。这项研究发现，在广泛的人口统计学参数和进化模型下，分支统计在识别局部选择性扫描方面比FST更准确。它还表明，某些分支统计数据提高了将局部适应与其他自然选择模型区分开来的能力。
