Nature Genetics
36, 700 - 706 (2004)
Published online: 6 June 2004; | doi:10.1038/ng1376
Evidence for substantial fine-scale variation in recombination rates across the human genomeDana C Crawford1, Tushar Bhangale2, Na Li3, 4, Garrett Hellenthal3, Mark J Rieder1, Deborah A Nickerson1, 2
& Matthew Stephens31
Department of Genome Sciences, University of Washington, Box 354322, Seattle, Washington 98195, USA. 2
Department of Bioengineering, University of Washington, Box 354322, Seattle, Washington 98195, USA. 3
Department of Statistics, University of Washington, Box 354322, Seattle, Washington 98195, USA. 4
Present address: Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455, USA.
Correspondence should be addressed to stephens@stat.washington.eduCharacterizing fine-scale variation in human recombination rates is important, both to deepen understanding of the recombination process1 and to aid the design of disease association studies2,
3. Current genetic maps show that rates vary on a megabase scale, but studying finer-scale variation using pedigrees is difficult. Sperm-typing experiments4,
5,
6 have characterized regions where crossovers cluster into 1−2-kb hot spots, but technical difficulties limit the number of studies7. An alternative is to use population variation to infer fine-scale characteristics of the recombination process. Several surveys8,
9,
10 reported 'block-like' patterns of diversity, which may reflect fine-scale recombination rate variation11,
12,
13, but limitations of available methods made this impossible to assess. Here, we applied a new statistical method, which overcomes these limitations, to infer patterns of fine-scale recombination rate variation in 74 genes. We found extensive rate variation both within and among genes. In particular, recombination hot spots are a common feature of the human genome: 47% (35 of 74) of genes showed substantive evidence for a hot spot, and many more showed evidence for some rate variation. No primary sequence characteristics are consistently associated with precise hot-spot location, although G+C content and nucleotide diversity are correlated with local recombination rate.
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