title: Discovering cooperative relationships of chromatin modifications in human T cells based on a proposed closeness measure.
abstract: BACKGROUND
  Eukaryotic transcription is accompanied by combinatorial chromatin modifications that serve as functional epigenetic markers. Composition of chromatin modifications specifies histone codes that regulate the associated gene. Discovering novel chromatin regulatory relationships are of general interest.
  
  
  RESULTS
  Based on the premise that the interaction of chromatin modifications is hypothesized to influence CpG methylation, we present a closeness measure to characterize the regulatory interactions of epigenomic features. The closeness measure is applied to genome-wide CpG methylation and histone modification datasets in human CD4+T cells to select a subset of potential features. To uncover epigenomic and genomic patterns, CpG loci are clustered into nine modules associated with distinct chromatin and genomic signatures based on terms of biological function. We then performed Bayesian network inference to uncover inherent regulatory relationships from the feature selected closeness measure profile and all nine module-specific profiles respectively. The global and module-specific network exhibits topological proximity and modularity. We found that the regulatory patterns of chromatin modifications differ significantly across modules and that distinct patterns are related to specific transcriptional levels and biological function. DNA methylation and genomic features are found to have little regulatory function. The regulatory relationships were partly validated by literature reviews. We also used partial correlation analysis in other cells to verify novel regulatory relationships.
  
  
  CONCLUSIONS
  The interactions among chromatin modifications and genomic elements characterized by a closeness measure help elucidate cooperative patterns of chromatin modification in transcriptional regulation and help decipher complex histone codes.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Lv
authors.forename: Hong
authors.initials: H
authors.lastname: Qiao
authors.forename: Hongbo
authors.initials: H
authors.lastname: Liu
authors.forename: Xueting
authors.initials: X
authors.lastname: Wu
authors.forename: Jiang
authors.initials: J
authors.lastname: Zhu
authors.forename: Jianzhong
authors.initials: J
authors.lastname: Su
authors.forename: Fang
authors.initials: F
authors.lastname: Wang
authors.forename: Ying
authors.initials: Y
authors.lastname: Cui
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002450:Cell Communication; D002843:Chromatin / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods; D018899:CpG Islands; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D006657:Histones / Q000378:metabolism; D006801:Humans; D015233:Models, Statistical; D012984:Software; D013601:T-Lymphocytes / Q000378:metabolism*
chemical_list: D002843:Chromatin; D006657:Histones