期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2017
卷号：114
期号：25
页码：E4914-E4923
DOI：10.1073/pnas.1704553114
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：The rapid increase of genome-wide datasets on gene expression, chromatin states, and transcription factor (TF) binding locations offers an exciting opportunity to interpret the information encoded in genomes and epigenomes. This task can be challenging as it requires joint modeling of context-specific activation of cis -regulatory elements (REs) and the effects on transcription of associated regulatory factors. To meet this challenge, we propose a statistical approach based on paired expression and chromatin accessibility (PECA) data across diverse cellular contexts. In our approach, we model ( i ) the localization to REs of chromatin regulators (CRs) based on their interaction with sequence-specific TFs, ( ii ) the activation of REs due to CRs that are localized to them, and ( iii ) the effect of TFs bound to activated REs on the transcription of target genes (TGs). The transcriptional regulatory network inferred by PECA provides a detailed view of how trans - and cis -regulatory elements work together to affect gene expression in a context-specific manner. We illustrate the feasibility of this approach by analyzing paired expression and accessibility data from the mouse Encyclopedia of DNA Elements (ENCODE) and explore various applications of the resulting model.
