title: Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.
abstract: BACKGROUND
  The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired.
  
  
  RESULTS
  In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks.
  
  
  CONCLUSIONS
  The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with recombination hotspots. The trans-regulators predicted by our pipeline are enriched with epigenetic functions (e.g., histone modifications), demonstrating the epigenetic regulatory mechanisms of recombination hotspots. The identified protein complexes also provide us with candidates to further investigate the molecular machineries for recombination hotspots. Moreover, the experimental data and results are available on our web site http://www.ntu.edu.sg/home/zhengjie/data/RecombinationHotspot/NetPipe/.
authors.forename: Min
authors.initials: M
authors.lastname: Wu
authors.forename: Chee-Keong
authors.initials: CK
authors.lastname: Kwoh
authors.forename: Xiaoli
authors.initials: X
authors.lastname: Li
authors.forename: Jie
authors.initials: J
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005656:Fungal Proteins / Q000235:genetics* / Q000378:metabolism*; D005786:Gene Expression Regulation; D063990:Gene Ontology; D006801:Humans; D008540:Meiosis / Q000235:genetics*; D051379:Mice; D016017:Odds Ratio; D025941:Protein Interaction Mapping; D011995:Recombination, Genetic; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D015003:Yeasts / Q000166:cytology* / Q000235:genetics / Q000378:metabolism
chemical_list: D005656:Fungal Proteins