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Quantification of genetic components of population differentiation in UK Biobank traits reveals signals of polygenic selection

By Xuanyao Liu, Po-Ru Loh, Luke J. O’Connor, Steven Gazal, Armin Schoech, Robert M. Maier, Nick Patterson, Alkes Price

Posted 27 Jun 2018
bioRxiv DOI: 10.1101/357483

The genetic architecture of most human complex traits is highly polygenic, motivating efforts to detect polygenic selection involving a large number of loci. In contrast to previous work relying on top GWAS loci, we developed a method that uses genome-wide association statistics and linkage disequilibrium patterns to estimate the genome-wide genetic component of population differentiation of a complex trait along a continuous gradient, enabling powerful inference of polygenic selection. We analyzed 43 UK Biobank traits and focused on PC1 and North-South and East-West birth coordinates across 337K unrelated British-ancestry samples, for which our method produced close to unbiased estimates of genetic components of population differentiation and high power to detect polygenic selection in simulations across different trait architectures. For PC1, we identified signals of polygenic selection for height (74.5+-16.7% of 9.3% total correlation with PC1 attributable to genome-wide genetic effects; P = 8.4x10-6) and red hair pigmentation (95.9+-24.7% of total correlation with PC1 attributable to genome-wide genetic effects; P = 1.1x10-4); the bulk of the signal remained when removing genome-wide significant loci, even though red hair pigmentation includes loci of large effect. We also detected polygenic selection for height, systolic blood pressure, BMI and basal metabolic rate along North-South birth coordinate, and height and systolic blood pressure along East-West birth coordinate. Our method detects polygenic selection in modern human populations with very subtle population structure and elucidates the relative contributions of genetic and non-genetic components of trait population differences.

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