Literature DB >> 16096109

Recombination hotspots as a point process.

Maria De Iorio1, Eric de Silva, Michael P H Stumpf.   

Abstract

The variation of the recombination rate along chromosomal DNA is one of the important determinants of the patterns of linkage disequilibrium. A number of inferential methods have been developed which estimate the recombination rate and its variation from population genetic data. The majority of these methods are based on modelling the genealogical process underlying a sample of DNA sequences and thus explicitly include a model of the demographic process. Here we propose a different inferential procedure based on a previously introduced framework where recombination is modelled as a point process along a DNA sequence. The approach infers regions containing putative hotspots based on the inferred minimum number of recombination events; it thus depends only indirectly on the underlying population demography. A Poisson point process model with local rates is then used to infer patterns of recombination rate estimation in a fully Bayesian framework. We illustrate this new approach by applying it to several population genetic datasets, including a region with an experimentally confirmed recombination hotspot.

Mesh:

Year:  2005        PMID: 16096109      PMCID: PMC1569526          DOI: 10.1098/rstb.2005.1690

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  18 in total

Review 1.  Linkage disequilibrium: what history has to tell us.

Authors:  Magnus Nordborg; Simon Tavaré
Journal:  Trends Genet       Date:  2002-02       Impact factor: 11.639

2.  A coalescent-based method for detecting and estimating recombination from gene sequences.

Authors:  Gil McVean; Philip Awadalla; Paul Fearnhead
Journal:  Genetics       Date:  2002-03       Impact factor: 4.562

3.  Bounds on the minimum number of recombination events in a sample history.

Authors:  Simon R Myers; Robert C Griffiths
Journal:  Genetics       Date:  2003-01       Impact factor: 4.562

4.  A coalescent model of recombination hotspots.

Authors:  Carsten Wiuf; David Posada
Journal:  Genetics       Date:  2003-05       Impact factor: 4.562

Review 5.  Estimating recombination rates from population-genetic data.

Authors:  Michael P H Stumpf; Gilean A T McVean
Journal:  Nat Rev Genet       Date:  2003-12       Impact factor: 53.242

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

Authors:  Na Li; Matthew Stephens
Journal:  Genetics       Date:  2003-12       Impact factor: 4.562

7.  Simulating haplotype blocks in the human genome.

Authors:  David Posada; Carsten Wiuf
Journal:  Bioinformatics       Date:  2003-01-22       Impact factor: 6.937

8.  Haplotype diversity and SNP frequency dependence in the description of genetic variation.

Authors:  Michael P H Stumpf
Journal:  Eur J Hum Genet       Date:  2004-06       Impact factor: 4.246

9.  Statistical properties of the number of recombination events in the history of a sample of DNA sequences.

Authors:  R R Hudson; N L Kaplan
Journal:  Genetics       Date:  1985-09       Impact factor: 4.562

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

Authors:  Gilean A T McVean; Simon R Myers; Sarah Hunt; Panos Deloukas; David R Bentley; Peter Donnelly
Journal:  Science       Date:  2004-04-23       Impact factor: 47.728

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  4 in total

1.  Introduction: genetic variation and human health.

Authors:  M P H Stumpf; D B Goldstein; N W Wood
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-08-29       Impact factor: 6.237

2.  Population genomic inference of recombination rates and hotspots.

Authors:  Ying Wang; Bruce Rannala
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-02       Impact factor: 11.205

3.  Cloning of the papaya chromoplast-specific lycopene beta-cyclase, CpCYC-b, controlling fruit flesh color reveals conserved microsynteny and a recombination hot spot.

Authors:  Andrea L Blas; Ray Ming; Zhiyong Liu; Olivia J Veatch; Robert E Paull; Paul H Moore; Qingyi Yu
Journal:  Plant Physiol       Date:  2010-02-24       Impact factor: 8.340

4.  Methodology and software to detect viral integration site hot-spots.

Authors:  Angela P Presson; Namshin Kim; Yan Xiaofei; Irvin Sy Chen; Sanggu Kim
Journal:  BMC Bioinformatics       Date:  2011-09-14       Impact factor: 3.169

  4 in total

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