title: Modeling co-occupancy of transcription factors using chromatin features.
abstract: Regulation of gene expression requires both transcription factor (TFs) and epigenetic modifications, and interplays between the two types of factors have been discovered. However study of relationships between chromatin features and TF-TF co-occupancy remains limited. Here, we revealed the relationship by first illustrating distinct profile patterns of chromatin features related to different binding events, including single TF binding and TF-TF co-occupancy of 71 TFs from five human cell lines. We further implemented statistical analyses to demonstrate the relationship by accurately predicting co-occupancy genome-widely using chromatin features including DNase I hypersensitivity, 11 histone modifications (HMs) and GC content. Remarkably, our results showed that the combination of chromatin features enables accurate predictions across the five cells. For individual chromatin features, DNase I enables high and consistent predictions. H3K27ac, H3K4me 2, H3K4me3 and H3K9ac are more reliable predictors than other HMs. Although the combination of 11 HMs achieves accurate predictions, their predictive ability varies considerably when a model obtained from one cell is applied to others, indicating relationship between HMs and TF-TF co-occupancy is cell type dependent. GC content is not a reliable predictor, but the addition of GC content to any other features enhances their predictive ability. Together, our results elucidate a strong relationship between TF-TF co-occupancy and chromatin features.
authors.affiliation: Center for Bioinformatics and Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
authors.forename: Liang
authors.initials: L
authors.lastname: Liu
authors.affiliation: Center for Bioinformatics and Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
authors.forename: Weiling
authors.initials: W
authors.lastname: Zhao
authors.affiliation: Center for Bioinformatics and Systems Biology, Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA xizhou@wakehealth.edu.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D001482:Base Composition; D001665:Binding Sites; D045744:Cell Line, Tumor; D002843:Chromatin / Q000737:chemistry* / Q000378:metabolism; D047369:Chromatin Immunoprecipitation; D003850:Deoxyribonuclease I / Q000235:genetics / Q000378:metabolism*; D044127:Epigenesis, Genetic; D015894:Genome, Human; D006657:Histones / Q000235:genetics / Q000378:metabolism*; D006801:Humans; D008957:Models, Genetic; D009928:Organ Specificity; D011401:Promoter Regions, Genetic; D011485:Protein Binding; D011499:Protein Processing, Post-Translational; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism*
chemical_list: D002843:Chromatin; D006657:Histones; D014157:Transcription Factors; D003850:Deoxyribonuclease I