Focusing on human haplotype diversity in numerous individual genomes demonstrates an evolutional feature of each locus

The application of current genome-wide sequencing techniques on human populations helps elucidate the considerable gene flow among genus Homo, which includes modern and archaic humans. Gene flow among current human populations has been studied using frequencies of single nucleotide polymorphisms. Unlike single nucleotide polymorphism frequency data, haplotype data are suitable for identifying and tracing rare evolutionary events. Haplotype data can also conveniently detect genomic location and estimate molecular function that may be a target of selection. We analyzed eight loci of the human genome using the same procedure for each locus to infer human haplotype diversity and reevaluate past explanations of the evolutionary mechanisms that affected these loci. These loci have been recognized by separate studies because of their unusual gene genealogy and geographic distributions that are inconsistent with the recent out-of-Africa model. For each locus, we constructed genealogies for haplotypes using sequence data of the 1000 Genomes Project. Then, we performed S* analysis to estimate distinct gene flow events other than out-of-Africa events. Furthermore, we also estimated unevenness of selective pressure between haplotypes by Extended Haplotype Homozygosity analysis. Based on the patterns of results obtained by this combination of analyses, we classified the examined loci without using a specific population model. This simple method helped clarify evolutionary events for each locus, including rare evolutionary events such as introgression, incomplete lineage sorting, selection, and haplotype recombination that may be hard to discriminate from each other.

当前全基因组测序技术在人类群体中的应用，有助于阐明人属（包括现代人类和古代人类）之间广泛的基因流。利用单核苷酸多态性频率，人们对当代人类群体间的基因流展开了研究。与单核苷酸多态性频率数据不同，单倍型数据适用于识别和追溯罕见的进化事件。单倍型数据还能便捷地检测基因组位置，并评估可能成为选择目标的分子功能。我们采用相同流程对人类基因组的8个基因座进行分析，以推断人类单倍型多样性，并重新评估以往对影响这些基因座的进化机制的解释。由于这些基因座具有异常的基因谱系，且其地理分布与近期的 “走出非洲” 模型相悖，因而在各项独立研究中受到关注。对于每个基因座，我们利用千人基因组计划的序列数据构建单倍型谱系。随后，我们进行S* 分析，以估算除 “走出非洲” 事件之外的独特基因流事件。此外，我们还通过扩展单倍型纯合性分析，评估单倍型之间选择压力的不均衡性。基于这一系列分析所得结果的模式，我们在不使用特定群体模型的情况下，对所检测的基因座进行分类。这种简单的方法有助于厘清每个基因座的进化事件，包括诸如基因渗入、不完全谱系分选、选择以及单倍型重组等可能难以相互区分的罕见进化事件。