Galinsky Kevin J, Loh Po-Ru, Mallick Swapan, Patterson Nick J, Price Alkes L
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
Am J Hum Genet. 2016 Nov 3;99(5):1130-1139. doi: 10.1016/j.ajhg.2016.09.014. Epub 2016 Oct 20.
Analyzing genetic differences between closely related populations can be a powerful way to detect recent adaptation. The very large sample size of the UK Biobank is ideal for using population differentiation to detect selection and enables an analysis of the UK population structure at fine resolution. In this study, analyses of 113,851 UK Biobank samples showed that population structure in the UK is dominated by five principal components (PCs) spanning six clusters: Northern Ireland, Scotland, northern England, southern England, and two Welsh clusters. Analyses of ancient Eurasians revealed that populations in the northern UK have higher levels of Steppe ancestry and that UK population structure cannot be explained as a simple mixture of Celts and Saxons. A scan for unusual population differentiation along the top PCs identified a genome-wide-significant signal of selection at the coding variant rs601338 in FUT2 (p = 9.16 × 10). In addition, by combining evidence of unusual differentiation within the UK with evidence from ancient Eurasians, we identified genome-wide-significant (p = 5 × 10) signals of recent selection at two additional loci: CYP1A2-CSK and F12. We detected strong associations between diastolic blood pressure in the UK Biobank and both the variants with selection signals at CYP1A2-CSK (p = 1.10 × 10) and the variants with ancient Eurasian selection signals at the ATXN2-SH2B3 locus (p = 8.00 × 10), implicating recent adaptation related to blood pressure.
分析亲缘关系密切的群体之间的基因差异,可能是检测近期适应性的有效方法。英国生物银行非常大的样本量,非常适合利用群体分化来检测自然选择,并且能够对英国的群体结构进行高分辨率分析。在本研究中,对113851份英国生物银行样本的分析表明,英国的群体结构主要由跨越六个集群的五个主成分(PC)主导:北爱尔兰、苏格兰、英格兰北部、英格兰南部以及两个威尔士集群。对古代欧亚人群的分析表明,英国北部人群具有更高水平的草原血统,而且英国的群体结构不能简单地解释为凯尔特人(Celts)和撒克逊人(Saxons)的混合。沿着主成分顶部对异常群体分化进行扫描,在FUT2基因的编码变体rs601338处,发现了全基因组显著的选择信号(p = 9.16×10)。此外,通过将英国境内异常分化的证据与古代欧亚人群的证据相结合,我们在另外两个基因座上,确定了全基因组显著(p = 5×10)的近期选择信号:CYP1A2-CSK和F12。我们在英国生物银行中检测到舒张压与CYP1A2-CSK基因座上具有选择信号的变体(p = 1.10×10)以及ATXN2-SH2B3基因座上具有古代欧亚人群选择信号的变体(p = 8.00×10)之间存在强关联,这表明近期存在与血压相关的适应性变化。