Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.

ABSTRACT: Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network. The GO analyses revealed the distinct biological function associated with each of three embedded modules. The survival analysis showed the genes in each module were able to render a significant survival correlation in breast cancer patient cohorts. In summary, our Bayesian statistical model

SUBMITTER: Tang B 

PROVIDER: S-EPMC3500769 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature