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      The Role of Geography in Human Adaptation

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          Various observations argue for a role of adaptation in recent human evolution, including results from genome-wide studies and analyses of selection signals at candidate genes. Here, we use genome-wide SNP data from the HapMap and CEPH-Human Genome Diversity Panel samples to study the geographic distributions of putatively selected alleles at a range of geographic scales. We find that the average allele frequency divergence is highly predictive of the most extreme F ST values across the whole genome. On a broad scale, the geographic distribution of putatively selected alleles almost invariably conforms to population clusters identified using randomly chosen genetic markers. Given this structure, there are surprisingly few fixed or nearly fixed differences between human populations. Among the nearly fixed differences that do exist, nearly all are due to fixation events that occurred outside of Africa, and most appear in East Asia. These patterns suggest that selection is often weak enough that neutral processes—especially population history, migration, and drift—exert powerful influences over the fate and geographic distribution of selected alleles.

          Author Summary

          Since the beginning of the study of evolution, people have been fascinated by recent human evolution and adaptation. Despite great progress in our understanding of human history, we still know relatively little about the selection pressures and historical factors that have been important over the past 100,000 years. In that time human populations have spread around the world and adapted in a wide variety of ways to the new environments they have encountered. Here, we investigate the genomic signal of these adaptations using a large set of geographically diverse human populations typed at thousands of genetic markers across the genome. We find that patterns at selected loci are predictable from the patterns found at all markers genome-wide. On the basis of this, we argue that selection has been strongly constrained by the historical relationships and gene flow between populations.

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          Most cited references 73

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            Gene flow and the limits to natural selection

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              A note on exact tests of Hardy-Weinberg equilibrium.

              Deviations from Hardy-Weinberg equilibrium (HWE) can indicate inbreeding, population stratification, and even problems in genotyping. In samples of affected individuals, these deviations can also provide evidence for association. Tests of HWE are commonly performed using a simple chi2 goodness-of-fit test. We show that this chi2 test can have inflated type I error rates, even in relatively large samples (e.g., samples of 1,000 individuals that include approximately 100 copies of the minor allele). On the basis of previous work, we describe exact tests of HWE together with efficient computational methods for their implementation. Our methods adequately control type I error in large and small samples and are computationally efficient. They have been implemented in freely available code that will be useful for quality assessment of genotype data and for the detection of genetic association or population stratification in very large data sets.

                Author and article information

                Role: Editor
                PLoS Genet
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                June 2009
                June 2009
                5 June 2009
                : 5
                : 6
                [1 ]Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
                [2 ]Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
                [3 ]HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, United States of America
                [4 ]Department of Genetics, Stanford University, Stanford, California, United States of America
                [5 ]Department of Biological Sciences, Stanford University, Stanford, California, United States of America
                [6 ]Howard Hughes Medical Institute, University of Chicago, Chicago, Illinois, United States of America
                University of Aarhus, Denmark
                Author notes

                Current address: Section of Evolution and Ecology and Center for Population Biology, University of California Davis, Davis, California, United States of America


                Current address: Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America

                Analyzed the data: G. Coop, J. Pickrell, J. Novembre, S. Kudaravalli, J. Pritchard. Contributed reagents/materials/analysis tools: J. Li, D. Absher, R. Myers, L. Cavalli-Sforza, M. Feldman. Wrote the paper: G. Coop, J. Pickrell, J. Novembre, M. Feldman, J. Pritchard. Conceived and designed the project: J. Pickrell, J. Novembre, S. Kudaravalli, J. Pritchard, G. Coop.

                Coop et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 16
                Research Article
                Evolutionary Biology/Genomics
                Evolutionary Biology/Human Evolution
                Genetics and Genomics/Population Genetics



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