Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups1,2,3. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.
We thank the Biological Resource Center at the Fondation Jean Dausset – CEPH for preparing HGDP–CEPH diversity panel DNA samples, and S. Chanock and A. Hutchinson for assistance with the DNAs. This work was supported in part by NIH grants, by a postdoctoral fellowship from the University of Michigan Center for Genetics in Health and Medicine, by grants from the Alfred P. Sloan Foundation and the Burroughs Wellcome Fund, by the National Center for Minority Health and Health Disparities, and by the Intramural Program of the National Institute on Aging. The study used the Biowulf Linux cluster at the National Institutes of Health (http://biowulf.nih.gov).
Author Contributions N.A.R. and A.B.S. wish to be regarded as joint last authors.
This file contains extensive Supplementary Information with Supplementary Notes, Supplementary Data, Supplementary Tables S1-S17, Supplementary Figures S1-S30 with Legends and additional references.