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      Long Range Linkage Disequilibrium across the Human Genome

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      PLoS ONE
      Public Library of Science

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          Abstract

          Long-range linkage disequilibria (LRLD) between sites that are widely separated on chromosomes may suggest that population admixture, epistatic selection, or other evolutionary forces are at work. We quantified patterns of LRLD on a chromosome-wide level in the YRI population of the HapMap dataset of single nucleotide polymorphisms (SNPs). We calculated the disequilibrium between all pairs of SNPs on each chromosome (a total of >2×10 11 values) and evaluated significance of overall disequilibrium using randomization. The results show an excess of associations between pairs of distant sites (separated by >0.25 cM) on all of the 22 autosomes. We discuss possible explanations for this observation.

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          The fine-scale structure of recombination rate variation in the human genome.

          The nature and scale of recombination rate variation are largely unknown for most species. In humans, pedigree analysis has documented variation at the chromosomal level, and sperm studies have identified specific hotspots in which crossing-over events cluster. To address whether this picture is representative of the genome as a whole, we have developed and validated a method for estimating recombination rates from patterns of genetic variation. From extensive single-nucleotide polymorphism surveys in European and African populations, we find evidence for extreme local rate variation spanning four orders in magnitude, in which 50% of all recombination events take place in less than 10% of the sequence. We demonstrate that recombination hotspots are a ubiquitous feature of the human genome, occurring on average every 200 kilobases or less, but recombination occurs preferentially outside genes.
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            A worldwide survey of haplotype variation and linkage disequilibrium in the human genome.

            Recent genomic surveys have produced high-resolution haplotype information, but only in a small number of human populations. We report haplotype structure across 12 Mb of DNA sequence in 927 individuals representing 52 populations. The geographic distribution of haplotypes reflects human history, with a loss of haplotype diversity as distance increases from Africa. Although the extent of linkage disequilibrium (LD) varies markedly across populations, considerable sharing of haplotype structure exists, and inferred recombination hotspot locations generally match across groups. The four samples in the International HapMap Project contain the majority of common haplotypes found in most populations: averaging across populations, 83% of common 20-kb haplotypes in a population are also common in the most similar HapMap sample. Consequently, although the portability of tag SNPs based on the HapMap is reduced in low-LD Africans, the HapMap will be helpful for the design of genome-wide association mapping studies in nearly all human populations.
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              Measures of human population structure show heterogeneity among genomic regions.

              Estimates of genetic population structure (F(ST)) were constructed from all autosomes in two large SNP data sets. The Perlegen data set contains genotypes on approximately 1 million SNPs segregating in all three samples of Americans of African, Asian, and European descent; and the Phase I HapMap data set contains genotypes on approximately 0.6 million SNPs segregating in all four samples from specific Caucasian, Chinese, Japanese, and Yoruba populations. Substantial heterogeneity of F(ST) values was found between segments within chromosomes, although there was similarity between the two data sets. There was also substantial heterogeneity among population-specific F(ST) values, with the relative sizes of these values often changing along each chromosome. Population-structure estimates are often used as indicators of natural selection, but the analyses presented here show that individual-marker estimates are too variable to be useful. There is inherent variation in these statistics because of variation in genealogy even among neutral loci, and values at pairs of loci are correlated to an extent that reflects the linkage disequilibrium between them. Furthermore, it may be that the best indications of selection will come from population-specific F(ST) values rather than the usually reported population-average values.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                12 December 2013
                : 8
                : 12
                : e80754
                Affiliations
                [1]Department of Integrative Biology, University of Texas, Austin, Texas, United States of America
                University of Lausanne, Switzerland
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MK. Performed the experiments: EK MR. Analyzed the data: EK MR MK. Contributed reagents/materials/analysis tools: EK MR. Wrote the paper: EK MK.

                [¤]

                Current address: Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America

                Article
                PONE-D-13-32235
                10.1371/journal.pone.0080754
                3861250
                24349013
                a8392b36-8ba1-4324-a511-8f7d149ecdc6
                Copyright @ 2013

                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.

                History
                : 2 August 2013
                : 17 October 2013
                Page count
                Pages: 10
                Funding
                Funding was from N.S.F. grant DEB-0819901 ( www.nsf.gov) and the Miller Institute for Basic Research in Science (millerinstitute.berkeley.edu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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