title: Discriminative identification of transcriptional responses of promoters and enhancers after stimulus.
abstract: Promoters and enhancers regulate the initiation of gene expression and maintenance of expression levels in spatial and temporal manner. Recent findings stemming from the Cap Analysis of Gene Expression (CAGE) demonstrate that promoters and enhancers, based on their expression profiles after stimulus, belong to different transcription response subclasses. One of the most promising biological features that might explain the difference in transcriptional response between subclasses is the local chromatin environment. We introduce a novel computational framework, PEDAL, for distinguishing effectively transcriptional profiles of promoters and enhancers using solely histone modification marks, chromatin accessibility and binding sites of transcription factors and co-activators. A case study on data from MCF-7 cell-line reveals that PEDAL can identify successfully the transcription response subclasses of promoters and enhancers from two different stimulations. Moreover, we report subsets of input markers that discriminate with minimized classification error MCF-7 promoter and enhancer transcription response subclasses. Our work provides a general computational approach for identifying effectively cell-specific and stimulation-specific promoter and enhancer transcriptional profiles, and thus, contributes to improve our understanding of transcriptional activation in human.
authors: Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.|The Institute of Cancer Research (ICR), London, SW7 3RP, UK.
authors: Dimitrios
authors: D
authors: Kleftogiannis
authors: Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
authors: Panos
authors: P
authors: Kalnis
authors: RIKEN Center for Life Science Technologies (Division of Genomic Technologies) (CLST (DGT)), Yokohama, Kanagawa 230-0045, Japan.
authors: Erik
authors: E
authors: Arner
authors: Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
authors: Vladimir B
authors: VB
authors: Bajic
mesh_terms: D000465:Algorithms; D002843:Chromatin / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D004742:Enhancer Elements, Genetic; D004815:Epidermal Growth Factor / Q000494:pharmacology; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation / Q000187:drug effects; D006801:Humans; D061986:MCF-7 Cells; D011401:Promoter Regions, Genetic; D011485:Protein Binding; D014157:Transcription Factors; D014158:Transcription, Genetic; D015533:Transcriptional Activation; D057188:Workflow
chemical_list: D002843:Chromatin; D014157:Transcription Factors; D004815:Epidermal Growth Factor