Data from: Detection of human adaptation during the past 2000 years

Field, Yair, Stanford University

Boyle, Evan A., Stanford University

Telis, Natalie, Stanford University

Gao, Ziyue, Stanford University

Gaulton, Kyle J., Stanford University

Golan, David, Stanford University

Yengo, Loic, University of Lille

Rocheleau, Ghislain, University of Lille

Froguel, Philippe, University of Lille

McCarthy, Mark I., Oxford Centre for Diabetes, Endocrinology and Metabolism

Pritchard, Jonathan K., Stanford University

Published Oct 03, 2017 on Dryad. https://doi.org/10.5061/dryad.kd58f

Cite this dataset

Field, Yair et al. (2017). Data from: Detection of human adaptation during the past 2000 years [Dataset]. Dryad. https://doi.org/10.5061/dryad.kd58f

Abstract

Detection of recent natural selection is a challenging problem in population genetics. Here we introduce the Singleton Density Score (SDS), a method to infer very recent changes in allele frequencies from contemporary genome sequences. Applied to data from the UK10K Project, SDS reflects allele frequency changes in the ancestors of modern Britons during the past ~2,000-3,000 years. We see strong signals of selection at lactase and the MHC, and in favor of blond hair and blue eyes. For polygenic adaptation we find that recent selection for increased height has driven allele frequency shifts across most of the genome. Moreover, we identify shifts associated with other complex traits, suggesting that polygenic adaptation has played a pervasive role in shaping genotypic and phenotypic variation in modern humans.

Usage notes

SDS_UK10K_n3195_release_Sep_19_2016.tab

Singleton Density Score (SDS) computed for autosomal SNPs with let least 5% minor allele frequency over a set of 3,195 individuals from the UK10K project. This is a gzipped tab-delimited file and the first row is a column header. Columns correspond to: (1) chromosome; (2) genomic position (hg19); (3) SNP id (rsid); (4) ancestral allele; (5) derived allele; (6) derived allele frequency; (7) SDS. See our manuscript for further description of the SDS method as well as the data quality control and SNP filtering.