Discriminative identification of transcriptional responses of promoters and enhancers after stimulus
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computational Bioscience Research Center (CBRC)
Computer Science Program
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/622038
MetadataShow full item record
AbstractPromoters 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.
CitationKleftogiannis D, Kalnis P, Arner E, Bajic VB (2016) Discriminative identification of transcriptional responses of promoters and enhancers after stimulus. Nucleic Acids Research: gkw1015. Available: http://dx.doi.org/10.1093/nar/gkw1015.
SponsorsKing Abdullah University of Science and Technology (KAUST); Research Grant from MEXT [to the RIKEN Center for Life Science Technologies]. Funding for open access charge: King Abdullah University of Science and Technology (KAUST).
PublisherOxford University Press (OUP)
JournalNucleic Acids Research
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/ ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact firstname.lastname@example.org