Fraction of Informative Recombinations: A Heuristic Approach to Analyze Recombination Rates
Author(s) -
J-F Lefebvre,
Damian Labuda
Publication year - 2008
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1534/genetics.107.082255
Subject(s) - recombination , biology , genetics , population , heuristic , sequence (biology) , evolutionary biology , algorithm , statistics , gene , mathematics , computer science , artificial intelligence , demography , sociology
In this article we present a new heuristic approach (informative recombinations, InfRec) to analyze recombination density at the sequence level. InfRec is intuitive and easy and combines previously developed methods that (i) resolve genotypes into haplotypes, (ii) estimate the minimum number of recombinations, and (iii) evaluate the fraction of informative recombinations. We tested this approach in its sliding-window version on 117 genes from the SeattleSNPs program, resequenced in 24 African-Americans (AAs) and 23 European-Americans (EAs). We obtained population recombination rate estimates (rho(obs)) of 0.85 and 0.37 kb(-1) in AAs and EAs, respectively. Coalescence simulations indicated that these values account for both the recombinations and the gene conversions in the history of the sample. The intensity of rho(obs) varied considerably along the sequence, revealing the presence of recombination hotspots. Overall, we observed approximately 80% of recombinations in one-third and approximately 50% in only 10% of the sequence. InfRec performance, tested on published simulated and additional experimental data sets, was similar to that of other hotspot detection methods. Fast, intuitive, and visual, InfRec is not constrained by sample size limitations. It facilitates understanding data and provides a simple and flexible tool to analyze recombination intensity along the sequence.
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