Shpak Max, Lawrence Kadee N, Pool John E
Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA.
Genome Biol Evol. 2025 Apr 30;17(5). doi: 10.1093/gbe/evaf080.
Population branch statistics, which estimate the degree of genetic differentiation along a focal population's lineage, have been used as an alternative to FST-based genome-wide scans for identifying loci associated with local selective sweeps. Beyond the population branch statistic (PBS), the normalized PBSn1 adjusts focal branch length with respect to outgroup branch lengths at the same locus, whereas population branch excess (PBE) incorporates median branch lengths at other loci. PBSn1 and PBE were proposed to be more specific to local selective sweeps as opposed to geographically ubiquitous selection. 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 (approximated) background selection, with local selective sweeps or 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. Particularly when parallel sweeps are introduced, PBSn1 and PBE correctly identify local sweeps among their top outliers more frequently than PBS. Additionally, we evaluate versions of these statistics based on maximal site differentiation within a window, finding that site-based PBE and PBSn1 are particularly effective at identifying local soft sweeps. These results validate the greater specificity of the rescaled branch statistics PBE and PBSn1 to detect population-specific positive selection, supporting their use in genomic studies focused on local adaptation.
群体分支统计用于估计沿目标群体谱系的遗传分化程度，已被用作基于FST的全基因组扫描的替代方法，以识别与局部选择性清除相关的基因座。除了群体分支统计量（PBS），标准化的PBSn1会根据同一基因座上外类群分支长度来调整目标分支长度，而群体分支过剩（PBE）则纳入了其他基因座的中位数分支长度。有人提出，与地理上普遍存在的选择相比，PBSn1和PBE对局部选择性清除更具特异性。然而，分支统计的准确性和统计功效尚未得到系统评估。为此，我们在具有代表性的大群体和小群体中模拟基因组，其中不同比例的位点在遗传漂变或（近似）背景选择、局部选择性清除或地理上平行的选择性清除作用下进化。然后，我们评估通过FST和每个分支统计量将局部选择性清除基因座正确识别为异常值的概率。我们发现，在识别局部清除方面，分支统计始终优于FST。特别是当引入平行清除时，PBSn1和PBE在其顶级异常值中正确识别局部清除的频率比PBS更高。此外，我们评估了基于窗口内最大位点分化的这些统计量版本，发现基于位点的PBE和PBSn1在识别局部软清除方面特别有效。这些结果验证了重新缩放的分支统计量PBE和PBSn1在检测群体特异性正选择方面具有更高的特异性，支持它们在专注于局部适应性的基因组研究中的应用。
