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      Identifying Selected Regions from Heterozygosity and Divergence Using a Light-Coverage Genomic Dataset from Two Human Populations

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          Abstract

          When a selective sweep occurs in the chromosomal region around a target gene in two populations that have recently separated, it produces three dramatic genomic consequences: 1) decreased multi-locus heterozygosity in the region; 2) elevated or diminished genetic divergence (F ST) of multiple polymorphic variants adjacent to the selected locus between the divergent populations, due to the alternative fixation of alleles; and 3) a consequent regional increase in the variance of F ST (S 2F ST) for the same clustered variants, due to the increased alternative fixation of alleles in the loci surrounding the selection target. In the first part of our study, to search for potential targets of directional selection, we developed and validated a resampling-based computational approach; we then scanned an array of 31 different-sized moving windows of SNP variants (5–65 SNPs) across the human genome in a set of European and African American population samples with 183,997 SNP loci after correcting for the recombination rate variation. The analysis revealed 180 regions of recent selection with very strong evidence in either population or both. In the second part of our study, we compared the newly discovered putative regions to those sites previously postulated in the literature, using methods based on inspecting patterns of linkage disequilibrium, population divergence and other methodologies. The newly found regions were cross-validated with those found in nine other studies that have searched for selection signals. Our study was replicated especially well in those regions confirmed by three or more studies. These validated regions were independently verified, using a combination of different methods and different databases in other studies, and should include fewer false positives. The main strength of our analysis method compared to others is that it does not require dense genotyping and therefore can be used with data from population-based genome SNP scans from smaller studies of humans or other species.

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          Most cited references33

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          The hitch-hiking effect of a favourable gene.

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            The genetical structure of populations.

            S. Wright (1951)
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              Genomic scans for selective sweeps using SNP data.

              Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2008
                5 March 2008
                : 3
                : 3
                : e1712
                Affiliations
                [1 ]Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland, United States of America
                [2 ]Basic Research Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland, United States of America
                [3 ]Applied Biosystems, Foster City, California, United States of America
                Indiana University, United States of America
                Author notes

                Conceived and designed the experiments: SO MS TO. Performed the experiments: TO KZ. Analyzed the data: TO KZ. Contributed reagents/materials/analysis tools: TO FD DG. Wrote the paper: SO MS TO.

                Article
                07-PONE-RA-01482R2
                10.1371/journal.pone.0001712
                2248624
                18320033
                531e1b01-6d60-4f5d-99f4-ca4547ebed8f
                This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
                History
                : 8 June 2007
                : 30 January 2008
                Page count
                Pages: 15
                Categories
                Research Article
                Evolutionary Biology
                Genetics and Genomics
                Evolutionary Biology/Genomics
                Genetics and Genomics/Comparative Genomics
                Genetics and Genomics/Population Genetics
                Evolutionary Biology/Human Evolution

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                Uncategorized

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