LDsplit: screening for cis-regulatory motifs stimulating meiotic recombination hotspots by analysis of DNA sequence polymorphisms

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• 作者：Peng Yang (5) (5)
  Min Wu (5) (5)
  Jing Guo (5)
  Chee Keong Kwoh (5)
  Teresa M Przytycka (5)
  Jie Zheng (5) (5)
  
• 关键词：Meiotic recombination hotspots ; Single nucleotide polymorphism (SNP) ; DNA sequence motif ; Genome instability ; Linkage disequilibrium (LD)
• 刊名：BMC Bioinformatics
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：15
• 期：1
• 全文大小：665 KB
• 参考文献：1. Hey J: What’s so hot about recombination hotspots? / PLoS Biol 2004,2(6):e190. CrossRef
  2. McVean G: What drives recombination hotspots to repeat DNA in humans? / Philos Trans R Soc Lond B Biol Sci 2010,365(1544):1213-218. CrossRef
  3. Myers S, Bottolo L, Freeman C, McVean G, Donnelly P: A fine-scale map of recombination rates and hotspots across the human genome. / Science 2005,310(5746):321-24. CrossRef
  4. Myers S, Freeman C, Auton A, Donnelly P, McVean G: A common sequence motif associated with recombination hot spots and genome instability in humans. / Nat Genet 2008,40(9):1124-129. CrossRef
  5. Myers S, Bowden R, Tumian A, Bontrop RE, Freeman C, MacFie TS, McVean G, Donnelly P: Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic recombination. / Science 2010,327(5967):876-79. CrossRef
  6. Baudat F, Buard J, Grey C, Fledel-Alon A, Ober C, Przeworski M, Coop G, de Massy B: PRDM9 is a major determinant of meiotic recombination hotspots in humans and mice. / Science 2010,327(5967):836-40. CrossRef
  7. Parvanov ED, Petkov PM, Paigen K: Prdm9 controls activation of mammalian recombination hotspots. / Science 2010,327(5967):835. CrossRef
  8. Hayashi K, Yoshida K, Matsui Y: A histone H3 methyltransferase controls epigenetic events required for meiotic prophase. / Nature 2005,438(7066):374-78. CrossRef
  9. Brick K, Smagulova F, Khil P, Camerini-Otero RD, Petukhova GV: Genetic recombination is directed away from functional genomics elements in mice. / Nature 2012,485(7400):642-45. CrossRef
  10. Wu M, Kwoh CK, Przytycka TM, Li J, Zheng J: Epigenetic functions enriched in transcription factors binding to mouse recombination hotspots. / Proteome Sci 2012,10(Suppl 1):S11. CrossRef
  11. Wahls WP, Davidson MK: New paradigms for conserved, multifactorial, cis-acting regulation of meiotic recombination. / Nucleic Acids Res 2012,40(10):9983-989. CrossRef
  12. Wu M, Kwoh CK, Przytycka TM, Li J, Zheng J: Integration of Genomic and Epigenomic Features to Predict Meiotic Recombination Hotspots in Human and Mouse. In / Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012). New York, NY, USA: ACM; 2012:297-04. CrossRef
  13. Smagulova F, Gregoretti IV, Brick K, Khil P, Camerini-Otero RD, Petukhova GV: Genome-wide analysis reveals novel molecular features of mouse recombination hotspots. / Nature 2011,472(7343):375-78. CrossRef
  14. Grey C, Barthes P, Chauveau-Le Friec G, Langa F, Baudat F, de Massy B: Mouse PRDM9 DNA-binding specificity determines sites of histone H3 lysine 4 trimethylation for initiation of meiotic recombination. / PLoS Biol 2011,9(10):e1001176. CrossRef
  15. Steiner WW, Davidow PA, Bagshaw AT: Important characteristics of sequence-specific recombination hotspots in Schizosaccharomyces pombe. / Genetics 2011,187(2):385-96. CrossRef
  16. Jeffreys AJ, Neumann R: Reciprocal crossover asymmetry and meiotic drive in a human recombination hot spot. / Nat Genet 2002,31(3):267-71. CrossRef
  17. Jeffreys AJ, Neumann R: Factors influencing recombination frequency and distribution in a human meiotic crossover hotspot. / Hum Mol Genet 2005,14(15):2277-287. CrossRef
  18. Zheng J, Khil PP, Camerini-Otero RD, Przytycka TM: Detecting sequence polymorphisms associated with meiotic recombination hotspots in the human genome. / Genome Biol 2010,11(10):R103. CrossRef
  19. Auton A, McVean G: Recombination rate estimation in the presence of hotspots. / Genome Res 2007,17(8):1219-227. CrossRef
  20. Bailey TL, Elkan C: Fitting a mixture model by expectation maximization to discover motifs in biopolymers. / Proc Int Conf Intell Syst Mol Biol 1994, 2:28-6.
  21. Peng B, Kimmel M: simuPOP: a forward-time population genetics simulation environment. / Bioinformatics 2005,21(18):3686-687. CrossRef
  22. Auton A, Fledel-Alon A, Pfeifer S, Venn O, Segurel L, Street T, Leffler EM, Bowden R, Aneas I, Broxholme J, Humburg P, Iqbal Z, Lunter G, Maller J, Hernandez RD, Melton C, Venkat A, Nobrega MA, Bontrop R, Myers S, Donnelly P, Przeworski M, McVean G: A fine-scale chimpanzee genetic map from population sequencing. / Science 2012,336(6078):193-98. CrossRef
  23. Cho SY, Chung M, Park M, Park S, Lee YS: ZIFIBI: prediction of DNA binding sites for zinc finger proteins. / Biochem Biophys Res Commun 2008,369(3):845-48. CrossRef
  24. Zhang J, Li F, Li J, Zhang MQ, Zhang X: Evidence and characteristics of putative human alpha recombination hotspots. / Hum Mol Genet 2004,13(22):2823-828. CrossRef
  25. Axelsson E, Webster MT, Ratnakumar A, Ponting CP, Lindblad-Toh K: Death of PRDM9 coincides with stabilization of the recombination landscape in the dog genome. / Genome Res 2012,22(1):51-3. CrossRef
  26. Coop G, Myers SR: Live hot, die young: transmission distortion in recombination hotspots. / PLoS Genet 2007,3(3):e35. CrossRef
  27. Boulton A, Myers RS, Redfield RJ: The hotspot conversion paradox and the evolution of meiotic recombination. / Proc Natl Acad Sci U S A 1997,94(15):8058-063. CrossRef
  28. Hellenthal G, Pritchard JK, Stephens M: The effects of genotype-dependent recombination, and transmission asymmetry, on linkage disequilibrium. / Genetics 2006,172(3):2001-005. CrossRef
  29. Yang P, Wu M, Kowh CK, Khil PP, Camerini-Otero RD, Przytycka TM, Zheng J: Predicting DNA sequence motifs of recombination hotspots by integrative visualization and analysis. In / Proceedings of International Symposium on Integrative Bioinformatics. Hangzhou, China; 2012:52-8.
  30. Guo J, Jain R, Yang P, Fan R, Kwoh CK, Zheng J: Reliable and Fast Estimation of Recombination Rates by Convergence Diagnosis and Parallel Markov Chain Monte Carlo. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2014. IEEE Computer Society, http://doi.ieeecomputersociety.org/10.1109/TCBB.2013.133
  31. Katzman S, Capra JA, Haussler D, Pollard KS: Ongoing GC-biased evolution is widespread in the human genome and enriched near recombination hot spots. / Genome Biol Evol 2011, 3:614-26. CrossRef
  32. Wahls WP, Davidson MK: Discrete DNA sites regulate global distribution of meiotic recombination. / Trends Genet 2010,26(5):202-08. CrossRef
  
• 作者单位：Peng Yang (5) (5)
  Min Wu (5) (5)
  Jing Guo (5)
  Chee Keong Kwoh (5)
  Teresa M Przytycka (5)
  Jie Zheng (5) (5)
  
  5. Genome Institute of Singapore, A*STAR, Biopolis, Singapore, 138672, Singapore
  
• ISSN：1471-2105

文摘

Background As a fundamental genomic element, meiotic recombination hotspot plays important roles in life sciences. Thus uncovering its regulatory mechanisms has broad impact on biomedical research. Despite the recent identification of the zinc finger protein PRDM9 and its 13-mer binding motif as major regulators for meiotic recombination hotspots, other regulators remain to be discovered. Existing methods for finding DNA sequence motifs of recombination hotspots often rely on the enrichment of co-localizations between hotspots and short DNA patterns, which ignore the cross-individual variation of recombination rates and sequence polymorphisms in the population. Our objective in this paper is to capture signals encoded in genetic variations for the discovery of recombination-associated DNA motifs. Results Recently, an algorithm called “LDsplit-has been designed to detect the association between single nucleotide polymorphisms (SNPs) and proximal meiotic recombination hotspots. The association is measured by the difference of population recombination rates at a hotspot between two alleles of a candidate SNP. Here we present an open source software tool of LDsplit, with integrative data visualization for recombination hotspots and their proximal SNPs. Applying LDsplit on SNPs inside an established 7-mer motif bound by PRDM9 we observed that SNP alleles preserving the original motif tend to have higher recombination rates than the opposite alleles that disrupt the motif. Running on SNP windows around hotspots each containing an occurrence of the 7-mer motif, LDsplit is able to guide the established motif finding algorithm of MEME to recover the 7-mer motif. In contrast, without LDsplit the 7-mer motif could not be identified. Conclusions LDsplit is a software tool for the discovery of cis-regulatory DNA sequence motifs stimulating meiotic recombination hotspots by screening and narrowing down to hotspot associated SNPs. It is the first computational method that utilizes the genetic variation of recombination hotspots among individuals, opening a new avenue for motif finding. Tested on an established motif and simulated datasets, LDsplit shows promise to discover novel DNA motifs for meiotic recombination hotspots.