Global transcription network incorporating distal regulator binding reveals selective cooperation of cancer drivers and risk genes.

ABSTRACT: Global network modeling of distal regulatory interactions is essential in understanding the overall architecture of gene expression programs. Here, we developed a Bayesian probabilistic model and computational method for global causal network construction with breast cancer as a model. Whereas physical regulator binding was well supported by gene expression causality in general, distal elements in intragenic regions or loci distant from the target gene exhibited particularly strong functional effects. Modeling the action of long-range enhancers was critical in recovering true biological interactions with increased coverage and specificity overall and unraveling regulatory complexity underlying tumor subclasses and drug responses in particular. Transcriptional cancer drivers and risk genes

SUBMITTER: Kim K 

PROVIDER: S-EPMC4499150 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature