title: Comparative annotation of functional regions in the human genome using epigenomic data.
abstract: Epigenetic regulation is dynamic and cell-type dependent. The recently available epigenomic data in multiple cell types provide an unprecedented opportunity for a comparative study of epigenetic landscape. We developed a machine-learning method called ChroModule to annotate the epigenetic states in eight ENCyclopedia Of DNA Elements cell types. The trained model successfully captured the characteristic histone-modification patterns associated with regulatory elements, such as promoters and enhancers, and showed superior performance on identifying enhancers compared with the state-of-art methods. In addition, given the fixed number of epigenetic states in the model, ChroModule allows straightforward illustration of epigenetic variability in multiple cell types. Using this feature, we found that invariable and variable epigenetic states across cell types correspond to housekeeping functions and stimulus response, respectively. Especially, we observed that enhancers, but not the other regulatory elements, dictate cell specificity, as similar cell types share common enhancers, and cell-type-specific enhancers are often bound by transcription factors playing critical roles in that cell type. More interestingly, we found some genomic regions are dormant in cell type but primed to become active in other cell types. These observations highlight the usefulness of ChroModule in comparative analysis and interpretation of multiple epigenomes.
authors.affiliation: Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0359, USA.
authors.forename: Kyoung-Jae
authors.initials: KJ
authors.lastname: Won
authors.forename: Xian
authors.initials: X
authors.lastname: Zhang
authors.forename: Tao
authors.initials: T
authors.lastname: Wang
authors.forename: Bo
authors.initials: B
authors.lastname: Ding
authors.forename: Debasish
authors.initials: D
authors.lastname: Raha
authors.forename: Michael
authors.initials: M
authors.lastname: Snyder
authors.forename: Bing
authors.initials: B
authors.lastname: Ren
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
mesh_terms: D001185:Artificial Intelligence; D001665:Binding Sites; D004742:Enhancer Elements, Genetic; D044127:Epigenesis, Genetic; D015894:Genome, Human; D006801:Humans; D058977:Molecular Sequence Annotation; D011401:Promoter Regions, Genetic; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors