Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12918-014-0107-1
DC FieldValue
dc.titleFinding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast
dc.contributor.authorWu, M
dc.contributor.authorKwoh, C.-K
dc.contributor.authorLi, X
dc.contributor.authorZheng, J
dc.date.accessioned2020-10-28T07:01:00Z
dc.date.available2020-10-28T07:01:00Z
dc.date.issued2014
dc.identifier.citationWu, M, Kwoh, C.-K, Li, X, Zheng, J (2014). Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast. BMC Systems Biology 8 (1) : 107. ScholarBank@NUS Repository. https://doi.org/10.1186/s12918-014-0107-1
dc.identifier.issn17520509
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/181744
dc.description.abstractBackground: 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/. © 2014 Wu et al.; licensee BioMed Central Ltd.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.subjectfungal protein
dc.subjectalgorithm
dc.subjectanimal
dc.subjectbiology
dc.subjectcytology
dc.subjectgene expression regulation
dc.subjectgene ontology
dc.subjectgenetic recombination
dc.subjectgenetics
dc.subjecthuman
dc.subjectmeiosis
dc.subjectmetabolism
dc.subjectmouse
dc.subjectprocedures
dc.subjectprotein analysis
dc.subjectregulatory sequence
dc.subjectrisk
dc.subjectyeast
dc.subjectAlgorithms
dc.subjectAnimals
dc.subjectComputational Biology
dc.subjectFungal Proteins
dc.subjectGene Expression Regulation
dc.subjectGene Ontology
dc.subjectHumans
dc.subjectMeiosis
dc.subjectMice
dc.subjectOdds Ratio
dc.subjectProtein Interaction Mapping
dc.subjectRecombination, Genetic
dc.subjectRegulatory Sequences, Nucleic Acid
dc.subjectYeasts
dc.typeArticle
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1186/s12918-014-0107-1
dc.description.sourcetitleBMC Systems Biology
dc.description.volume8
dc.description.issue1
dc.description.page107
Appears in Collections:Staff Publications
Elements

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_s12918-014-0107-1.pdf840.33 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons