Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98018
Title: NetPipe : a network-based pipeline for discovery of genes and protein complexes regulating meiotic recombination hotspots
Authors: Wu, Min
Kwoh, Chee Keong
Zheng, Jie
Li, Xiaoli
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Wu, M., Kwoh, C. K., Zheng, J., & Li, X. (2012). NetPipe: a network-based pipeline for discovery of genes and protein complexes regulating meiotic recombination hotspots. Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '12, 20-27.
Abstract: 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" in mammalian genomes. 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 also 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, discovery of other regulators of recombination hotspots becomes a current challenge. Meanwhile, recombination is a complex process unlikely to be regulated by individual proteins. Rather, multiple proteins need to act in concert as a molecular machinery to carry out the process accurately and stably. As such, the extension of the prediction of individual proteins to protein complexes is also highly desired. In this paper, we propose a network-based pipeline named NetPipe to identify protein complexes associated with meiotic recombination hotspots. Previously, we associated proteins with recombination hotspots using the binding information between these proteins and hotspots. Here, we exploited protein-protein interaction (PPI) data to prioritize many more other proteins without such binding information. Furthermore, we detected protein complexes conserved between human and mouse that are associated with hotspots. Evaluation results show that the top genes ranked in PPI networks have significant relations to recombination related GO terms. In addition, individual genes in the multi-protein complexes detected by NetPipe are enriched with epigenetic functions, providing more insights into the epigenetic regulatory mechanisms of recombination hotspots.
URI: https://hdl.handle.net/10356/98018
http://hdl.handle.net/10220/11911
DOI: 10.1145/2382936.2382939
Rights: © 2012 ACM. This is the author created version of a work that has been peer reviewed and accepted for publication by Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '12, ACM. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1145/2382936.2382939].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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