Literature DB >> 18617692

Confounding between recombination and selection, and the Ped/Pop method for detecting selection.

Paul F O'Reilly1, Ewan Birney, David J Balding.   

Abstract

In recent years, there have been major developments of population genetics methods to estimate both rates of recombination and levels of natural selection. However, genomic variants subject to positive selection are likely to have arisen recently and, consequently, had less opportunity to be affected by recombination. Thus, the two processes have an intimately related impact on genetic variation, and inference of either may be vulnerable to confounding by the other. We illustrate here that even modest levels of positive selection can substantially reduce population-based recombination rate estimates. We also show that genome-wide scans to detect loci under recent selection in humans have tended to highlight loci in regions of low recombination, suggesting that confounding by recombination rate may have reduced the power of these studies. Motivated by these findings, we introduce a new genome-wide approach for detecting selection, based on the ratio of pedigree-based to population-based estimates of recombination rate. Simulations suggest that our "Ped/Pop" method, which is designed to capture completed sweeps, has good power to discriminate between neutral and adaptive evolution. Unusually for a multimarker method, our approach performs well in regions of high recombination and also has good power for many generations after the fixation of an advantageous variant. We apply the method to human HapMap and Perlegen data sets, finding confirmation of reported candidates as well as identifying new loci that may have undergone recent intense selection.

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Year:  2008        PMID: 18617692      PMCID: PMC2493435          DOI: 10.1101/gr.067181.107

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  50 in total

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Journal:  Nature       Date:  2001-05-31       Impact factor: 49.962

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Journal:  Nature       Date:  2002-10-09       Impact factor: 49.962

5.  Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data.

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Journal:  Genetics       Date:  2003-12       Impact factor: 4.562

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Authors:  Michael Bamshad; Stephen P Wooding
Journal:  Nat Rev Genet       Date:  2003-02       Impact factor: 53.242

7.  Genetic signatures of strong recent positive selection at the lactase gene.

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8.  SelSim: a program to simulate population genetic data with natural selection and recombination.

Authors:  Chris C A Spencer; Graham Coop
Journal:  Bioinformatics       Date:  2004-07-22       Impact factor: 6.937

9.  High-resolution sperm typing of meiotic recombination in the mouse MHC Ebeta gene.

Authors:  C L Yauk; P R J Bois; A J Jeffreys
Journal:  EMBO J       Date:  2003-03-17       Impact factor: 11.598

10.  Reciprocal crossover asymmetry and meiotic drive in a human recombination hot spot.

Authors:  Alec J Jeffreys; Rita Neumann
Journal:  Nat Genet       Date:  2002-06-24       Impact factor: 38.330

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  35 in total

1.  Fine-scale recombination rate differences between sexes, populations and individuals.

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Journal:  Nature       Date:  2010-10-28       Impact factor: 49.962

Review 2.  Population genetic inference from genomic sequence variation.

Authors:  John E Pool; Ines Hellmann; Jeffrey D Jensen; Rasmus Nielsen
Journal:  Genome Res       Date:  2010-01-12       Impact factor: 9.043

3.  Population differentiation as a test for selective sweeps.

Authors:  Hua Chen; Nick Patterson; David Reich
Journal:  Genome Res       Date:  2010-01-19       Impact factor: 9.043

4.  Recombination rates in admixed individuals identified by ancestry-based inference.

Authors:  Daniel Wegmann; Darren E Kessner; Krishna R Veeramah; Rasika A Mathias; Dan L Nicolae; Lisa R Yanek; Yan V Sun; Dara G Torgerson; Nicholas Rafaels; Thomas Mosley; Lewis C Becker; Ingo Ruczinski; Terri H Beaty; Sharon L R Kardia; Deborah A Meyers; Kathleen C Barnes; Diane M Becker; Nelson B Freimer; John Novembre
Journal:  Nat Genet       Date:  2011-07-20       Impact factor: 38.330

5.  Admixture provides new insights into recombination.

Authors:  Paul F O'Reilly; David J Balding
Journal:  Nat Genet       Date:  2011-08-29       Impact factor: 38.330

6.  The effect of genomic inversions on estimation of population genetic parameters from SNP data.

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7.  Refining the Use of Linkage Disequilibrium as a Robust Signature of Selective Sweeps.

Authors:  Guy S Jacobs; Tim J Sluckin; Toomas Kivisild
Journal:  Genetics       Date:  2016-08       Impact factor: 4.562

8.  Identifying and Classifying Shared Selective Sweeps from Multilocus Data.

Authors:  Alexandre M Harris; Michael DeGiorgio
Journal:  Genetics       Date:  2020-03-09       Impact factor: 4.562

9.  Human population differentiation is strongly correlated with local recombination rate.

Authors:  Alon Keinan; David Reich
Journal:  PLoS Genet       Date:  2010-03-26       Impact factor: 5.917

10.  Human and non-human primate genomes share hotspots of positive selection.

Authors:  David Enard; Frantz Depaulis; Hugues Roest Crollius
Journal:  PLoS Genet       Date:  2010-02-05       Impact factor: 5.917

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