| Literature DB >> 23810978 |
Nasun Hah1, W Lee Kraus2.
Abstract
Recent rapid advances in next generation sequencing technologies have expanded our understanding of steroid hormone signaling to a genome-wide level. In this review, we discuss the use of a novel genomic approach, global nuclear run-on coupled with massively parallel sequencing (GRO-seq), to explore new facets of the steroid hormone-regulated transcriptome, especially estrogen responses in breast cancer cells. GRO-seq is a high throughput sequencing method adapted from conventional nuclear run-on methodologies, which is used to obtain a map of the position and orientation of all transcriptionally engaged RNA polymerases across the genome with extremely high spatial resolution. GRO-seq, which is an excellent tool for examining transcriptional responses to extracellular stimuli, has been used to comprehensively assay the effects of estrogen signaling on the transcriptome of ERα-positive MCF-7 human breast cancer cells. These studies have revealed new details about estrogen-dependent transcriptional regulation, including effects on transcription by all three RNA polymerases, complex transcriptional dynamics in response to estrogen signaling, and identification novel, unannotated non-coding RNAs. Collectively, these studies have been useful in discerning the molecular logic of the estrogen-regulated mitogenic response.Entities:
Keywords: 17β-estradiol; Breast cancer cells; ChIP; E2; ERBS; ERα; Estrogen; Estrogen receptor; GRO-seq; HMM; Non-coding RNA; Pol (I, II, III); RNA polymerase (I, II, III); SERM; Transcriptome; chromatin immunoprecipitation; eRNA; enhancer RNA; estrogen receptor alpha; estrogen receptor α binding site; global nuclear run-on and sequencing; hidden Markov model lncRNA, long non-coding RNAs; mRNA; messenger RNA; rRNA; ribosomal RNA; selective estrogen-receptor modulator; tRNA; transfer RNA
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Year: 2013 PMID: 23810978 PMCID: PMC3844033 DOI: 10.1016/j.mce.2013.06.021
Source DB: PubMed Journal: Mol Cell Endocrinol ISSN: 0303-7207 Impact factor: 4.102