A universally observed feature of meiotic recombination is a highly non-uniform distribution of meiotic crossovers across the genome. Although it has become evident that hotspots of recombination are relatively unstable in evolution, the magnitude of the variation of recombination profiles on a genome-wide scale is unknown. To study the underlying mechanisms responsible for the birth, life and death of recombination hotspots we decided to estimate the genome-wide variation in profiles of recombination. This has become possible due to the recent confluence of two major developments: improvements in the computational approaches to calculate genome-wide recombination profiles from linkage disequilibrium data and the availability of a very dense catalog of genetic markers (single nucleotide polymorphisms, SNPs) in human beings (phase I of the HapMap, 106 SNPs). As the HapMap is the major resource being used for Genome-Wide Association Studies (GWAS) knowing how well historic recombination is reflected in recombination in current individuals is important in assessing the strength of these associations. Recently, we have computed historic recombination maps for several populations. We have shown that although for a given population we find only about 60% of present-day recombination (crossovers) at recombination hotspots (roughly equivalent to the edges of haplotype blocks) in the historical computed map, nearly all crossovers in present-day individuals are predicted by including computed hotspots from several populations (Khil and Camerini-Otero (2010) PLoS Genetics 6, 1). We have hypothesized that this reflects the existence of a universal human recombinome. In the last two years we have been able to generate a genome-wide map for hotspots for double-strand breaks in mouse meiosis by using Solexa/Illumina ChIP-Seq for Dmc1 and Rad51 foci, both of which mark these sites (all in collaboration with the laboratory of Galina Petukhova at the Department of Biochemistry and Molecular Biology at the Uniformed Services University of Health Sciences). Depending on the level of statistical significance as many as 40,000 of these hotspots can be enumerated and a large majority of both Rad51 and Dmc1 sites are identical. About 10,000 of these hotspots have a high degree of statistical significance. Compared to the LD recombination that has an accuracy of about 5 KB, our physical recombination map, has an accuracy of about 200 bp. This is the first, and to date only, high-resolution genome-wide map of recombination hotspots in a multicellular organism. Using such a map has allowed to identify novel structural features for recombination hotspots. For example, we determined that recombination hotspots share a centrally distributed consensus motif (in the vast majority of hotspots), possess a nucleotide skew that changes polarity at the center of the hotspots, and have both a calculated and experimental preference to be occupied by a nucleosome. Finally, we find that the vast majority of recombination hotspots in mice are associated with testis-specific H3K4 trimethylation that do not overlap transcription start sites even though these sites are well-known to be marked by H3K4 trimethylation. Thus, H3K4 trimethylation per se is not a sufficient mark for directing the meiotic double-strand break machinery. Recently, we developed a novel method that is a variant of chromatin immunoprecipitation followed by sequencing (ChIP-seq)single-stranded DNA sequencing (SSDS)- that specifically detects protein-bound single-stranded DNA. SSDS consists of a new sequencing library preparation procedure for the enrichment of fragments originating from ssDNA that creates a signature sequence that is computationally identified after high-throughput sequencing. We have used this novel method to show that the product of the highly polymorphic and rapidly evolving gene Prdm9 not only determines the positions of practically all hotspots but also actively sequesters recombination away from functional genomic elements, such as promoters and enhancers, in mice. Currently we are mapping recombination hotspots in the human genome.

Project Start
Project End
Budget Start
Budget End
Support Year
6
Fiscal Year
2012
Total Cost
$1,048,202
Indirect Cost
City
State
Country
Zip Code
Davies, Benjamin; Hatton, Edouard; Altemose, Nicolas et al. (2016) Re-engineering the zinc fingers of PRDM9 reverses hybrid sterility in mice. Nature 530:171-6
Smagulova, Fatima; Brick, Kevin; Pu, Yongmei et al. (2016) Erratum: The evolutionary turnover of recombination hot spots contributes to speciation in mice. Genes Dev 30:871
Smagulova, Fatima; Brick, Kevin; Pu, Yongmei et al. (2016) The evolutionary turnover of recombination hot spots contributes to speciation in mice. Genes Dev 30:266-80
Fayer, Shawn; Yu, Qi; Kim, Joongbaek et al. (2016) Robertsonian translocations modify genomic distribution of γH2AFX and H3.3 in mouse germ cells. Mamm Genome 27:225-36
Pratto, Florencia; Brick, Kevin; Khil, Pavel et al. (2014) DNA recombination. Recombination initiation maps of individual human genomes. Science 346:1256442
Smagulova, Fatima; Brick, Kevin; Pu, Yongmei et al. (2013) Suppression of genetic recombination in the pseudoautosomal region and at subtelomeres in mice with a hypomorphic Spo11 allele. BMC Genomics 14:493
Khil, Pavel P; Smagulova, Fatima; Brick, Kevin M et al. (2012) Sensitive mapping of recombination hotspots using sequencing-based detection of ssDNA. Genome Res 22:957-65
Brick, Kevin; Smagulova, Fatima; Khil, Pavel et al. (2012) Genetic recombination is directed away from functional genomic elements in mice. Nature 485:642-5
Smagulova, Fatima; Gregoretti, Ivan V; Brick, Kevin et al. (2011) Genome-wide analysis reveals novel molecular features of mouse recombination hotspots. Nature 472:375-8
Khil, Pavel P; Camerini-Otero, R Daniel (2010) Genetic crossovers are predicted accurately by the computed human recombination map. PLoS Genet 6:e1000831

Showing the most recent 10 out of 12 publications