1. Center for Computational Medicine and Biology,
2. Department of Human Genetics,
3. Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
4. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892, USA
5. Department of Molecular Neuroscience and Reta Lila Weston Institute of Neurological Studies, Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK
6. Department of Neurology, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, Taipei 10591, Taiwan
7. Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
8. Center for Neurosciences and Cell Biology, Faculty of Medicine, University of Coimbra, 3004-504 Coimbra, Portugal
9. University of Oxford, Department of Clinical Neurology, John Radcliffe Hospital, Oxford OX3 9DU, UK
10. Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892, USA
11. Unidad de Genética Molecular, Departamento de Genómica y Proteómica, Instituto de Biomedicina de Valencia-CSIC, 46010, Valencia, Spain
12. Fondation Jean Dausset – Centre d'Étude du Polymorphisme Humain (CEPH), 27 rue Juliette Dodu, 75010 Paris, France
13. Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia 22908, USA
14. These authors contributed equally to this work.

Correspondence to: Noah A. Rosenberg^1,2,3Andrew B. Singleton^4,13 Correspondence and requests for materials should be addressed to N.A.R. (Email: rnoah@umich.edu) or A.B.S. (Email: singleta@mail.nih.gov).

Abstract

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 groups^{1, 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.

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