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Reprogramming Transcriptional Responses through Functionally-Distinct Classes of Enhancers in Prostate Cancer Cells [ChIP-Seq, Gro-Seq]

GSE27823 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing 30 samples Submitted 2011/05/15 Platform GPL9115
Summary
Mammalian genomes are populated with thousands of transcriptional enhancers that orchestrate cell type-specific gene expression programs; however, the potential that there are pre-established enhancers in different functional classes that permit alternative signal-dependent transcriptional responses has remained unexplored. Here we present evidence that cell lineage-specific factors, such as FoxA1, can simultaneously facilitate and restrict key regulated transcription factors, exemplified by the androgen receptor (AR), acting at structurally- and functionally-distinct classes of pre-established enhancers, thus licensing specific signal-activated responses while restricting others. Consequently, FoxA1 down-regulation, an unfavorable prognostic sign in advanced prostate tumors, causes a massive switch in AR binding from one functional class of enhancers to another, with a parallel switch in levels of enhancer-templated non-coding RNAs (eRNAs) revealed by the global run-on assay (GRO-seq), which documents the dramatic reprogramming of the hormonal response. The molecular basis for this switch lies in the release of FoxA1-mediated restriction of AR binding to the new enhancer class with no apparent nucleosome remodeling, which is required for stimulating their eRNA transcription and/or enhancing enhancer:promoter looping and gene activation. Together, these findings reveal a large repository of pre-determined enhancers in the human genome that can be dynamically tuned to induce their transcription and activation of alternative gene expression programs, which may underlie many sequential gene expression events in development or during disease progression.
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Also filed as BioProject PRJNA141903 and SRA study SRP005967. Searching any of these in the dataset finder brings you back here.

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