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Detecting sequence polymorphisms associated with meiotic recombination hotspots in the human genome

Jie Zheng1, Pavel P Khil2, R Daniel Camerini-Otero2* and Teresa M Przytycka1*

Author Affiliations

1 Computational Biology Branch, NCBI, NLM, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA

2 Genetics and Biochemistry Branch, NIDDK, National Institutes of Health, 5 Memorial Drive, Bethesda, Maryland 20892, USA

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Genome Biology 2010, 11:R103  doi:10.1186/gb-2010-11-10-r103

Published: 20 October 2010



Meiotic recombination events tend to cluster into narrow spans of a few kilobases long, called recombination hotspots. Such hotspots are not conserved between human and chimpanzee and vary between different human ethnic groups. At the same time, recombination hotspots are heritable. Previous studies showed instances where differences in recombination rate could be associated with sequence polymorphisms.


In this work we developed a novel computational approach, LDsplit, to perform a large-scale association study of recombination hotspots with genetic polymorphisms. LDsplit was able to correctly predict the association between the FG11 SNP and the DNA2 hotspot observed by sperm typing. Extensive simulation demonstrated the accuracy of LDsplit under various conditions. Applying LDsplit to human chromosome 6, we found that for a significant fraction of hotspots, there is an association between variations in intensity of historical recombination and sequence polymorphisms. From flanking regions of the SNPs output by LDsplit we identified a conserved 11-mer motif GGNGGNAGGGG, whose complement partially matches 13-mer CCNCCNTNNCCNC, a critical motif for the regulation of recombination hotspots.


Our result suggests that computational approaches based on historical recombination events are likely to be more powerful than previously anticipated. The putative associations we identified may be a promising step toward uncovering the mechanisms of recombination hotspots.