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      A New Approach for Using Genome Scans to Detect Recent Positive Selection in the Human Genome

      research-article
      1 , * , 2 , 1
      PLoS Biology
      Public Library of Science

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          Abstract

          Genome-wide scanning for signals of recent positive selection is essential for a comprehensive and systematic understanding of human adaptation. Here, we present a genomic survey of recent local selective sweeps, especially aimed at those nearly or recently completed. A novel approach was developed for such signals, based on contrasting the extended haplotype homozygosity (EHH) profiles between populations. We applied this method to the genome single nucleotide polymorphism (SNP) data of both the International HapMap Project and Perlegen Sciences, and detected widespread signals of recent local selection across the genome, consisting of both complete and partial sweeps. A challenging problem of genomic scans of recent positive selection is to clearly distinguish selection from neutral effects, given the high sensitivity of the test statistics to departures from neutral demographic assumptions and the lack of a single, accurate neutral model of human history. We therefore developed a new procedure that is robust across a wide range of demographic and ascertainment models, one that indicates that certain portions of the genome clearly depart from neutrality. Simulations of positive selection showed that our tests have high power towards strong selection sweeps that have undergone fixation. Gene ontology analysis of the candidate regions revealed several new functional groups that might help explain some important interpopulation differences in phenotypic traits.

          Author Summary

          The evolution of new functions and adaptation to new environments occurs by positive selection, whereby beneficial mutations increase in frequency and eventually become fixed in a population. Detecting such selection in humans is crucial for understanding the importance of past genetic adaptations and their role in contemporary common diseases. Methods have already been developed for detecting the signature of positive selection in large, genome-scale datasets (such as the “HapMap”). Positive selection is expected to more rapidly increase the frequency of an allele, and hence, the length of the haplotype (extent of DNA segment) associated with the selected allele, relative to those that are not under selection. Such methods compare haplotype lengths within a single population. Here, we introduce a new method that compares the lengths of haplotypes associated with the same allele in different populations. We demonstrate that our method has greater power to detect selective sweeps that are fixed or nearly so, and we construct a statistical framework that shows that our method reliably detects positive selection. We applied our method to the HapMap data and identified approximately 500 candidate regions in the human genome that show a signature of recent positive selection. Further targeted studies of these regions should reveal important genetic adaptations in our past.

          Abstract

          The authors present a novel genome-scan approach for detecting local positive selection. The approach is designed to detect selective events that have resulted in complete or near-complete fixation of a beneficial allele.

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          Most cited references32

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          Molecular signatures of natural selection.

          There is an increasing interest in detecting genes, or genomic regions, that have been targeted by natural selection. The interest stems from a basic desire to learn more about evolutionary processes in humans and other organisms, and from the realization that inferences regarding selection may provide important functional information. This review provides a nonmathematical description of the issues involved in detecting selection from DNA sequences and SNP data and is intended for readers who are not familiar with population genetic theory. Particular attention is placed on issues relating to the analysis of large-scale genomic data sets.
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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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              A high-resolution recombination map of the human genome.

              Determination of recombination rates across the human genome has been constrained by the limited resolution and accuracy of existing genetic maps and the draft genome sequence. We have genotyped 5,136 microsatellite markers for 146 families, with a total of 1,257 meiotic events, to build a high-resolution genetic map meant to: (i) improve the genetic order of polymorphic markers; (ii) improve the precision of estimates of genetic distances; (iii) correct portions of the sequence assembly and SNP map of the human genome; and (iv) build a map of recombination rates. Recombination rates are significantly correlated with both cytogenetic structures (staining intensity of G bands) and sequence (GC content, CpG motifs and poly(A)/poly(T) stretches). Maternal and paternal chromosomes show many differences in locations of recombination maxima. We detected systematic differences in recombination rates between mothers and between gametes from the same mother, suggesting that there is some underlying component determined by both genetic and environmental factors that affects maternal recombination rates.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                pbio
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                July 2007
                19 June 2007
                : 5
                : 7
                : e171
                Affiliations
                [1 ] Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
                [2 ] Department of Ecology and Evolutionary Biology, University of California Irvine, Irvine, California, United States of America
                University of Dublin, Ireland
                Author notes
                * To whom correspondence should be addressed. E-mail: tang@ 123456eva.mpg.de
                Article
                06-PLBI-RA-1819R1 plbi-05-07-06
                10.1371/journal.pbio.0050171
                1892573
                17579516
                5cdafe24-32d6-420b-a06f-513cddc85fe1
                Copyright: © 2007 Tang 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.
                History
                : 28 September 2006
                : 20 April 2007
                Page count
                Pages: 16
                Categories
                Research Article
                Computational Biology
                Evolutionary Biology
                Genetics and Genomics
                Homo (Human)
                Custom metadata
                Tang K, Thornton KR, Stoneking M (2007) A new approach for using genome scans to detect recent positive selection in the human genome. PLoS Biol 5(7): e171. doi: 10.1371/journal.pbio.0050171

                Life sciences
                Life sciences

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