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Expression levels of retinoic acid receptor gamma (NR1B3/RARG, encodes RARγ), are commonly reduced in prostate cancer (PCa). Therefore we sought to establish the cellular and gene regulatory consequences of reduced RARγ expression, and determine RARγ regulatory mechanisms.RARGshRNA approaches in non-malignant (RWPE-1 and HPr1-AR) and malignant (LNCaP) prostate models revealed that reducing RARγ levels, rather than adding exogenous retinoid ligand, had the greatest impact on prostate cell viability and gene expression. ChIP-Seq defined the RARγ cistrome which was significantly enriched at active enhancers associated with AR binding sites. Reflecting a significant genomic role for RARγ to regulate androgen signaling, RARγ knockdown in HPr1-AR cells significantly regulated the magnitude of the AR transcriptome. RARγ down-regulation was explained by increased miR-96 in PCa cell and mouse models, and TCGA PCa cohorts. Biochemical approaches confirmed that miR-96 directly regulated RARγ expression and function Capture of the miR-96 targetome by biotin-miR96 identified that RARγ and a number of RARγ interacting co-factors includingTACC1were all targeted by miR-96, and expression of these genes were prominently altered, positively and negatively, in the TCGA-PRAD cohort. Differential gene expression analyses between tumors in the TCGA-PRAD cohort with lower quartile expression levels ofRARGandTACC1and upper quartile miR-96, compared to the reverse, identified a gene network including several RARγ target genes (e.g.SOX15) that significantly associated with worse disease free survival (hazard ratio 2.23, 95% CI 1.58 to 2.88, p=0.015). In summary, miR-96 targets a RARγ network to govern AR signaling, PCa progression and disease outcome.Conflict of interest:The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.FUNDINGLESCacknowledges support, in part, of Roswell Park Comprehensive Cancer Center-University of Pittsburg Cancer Institute Ovarian Cancer Specialized Program of Research Excellence National Institutes of Health [P50CA159981-01A1].MDLacknowledges support of Molecular Pharmacology and Experimental Therapeutics NRSA T32 program [T32CA009072] held at Roswell Park Comprehensive Cancer Center.MJCandDJSacknowledges support in part from the Prostate program of the Department of Defense Congressionally Directed Medical Research Programs [W81XWH-14-1-0608, W81XWH-11-2-0033] and the National Cancer Institute (NCI) grant P30CA016056 involving the use of Roswell Park Comprehensive Cancer Center’s Genomic Shared Resource.MJC, GL, AR, HWandPvdBacknowledges support from the European Union-United States Atlantis Program [P116J090011].MJCandLESCacknowledge support from the National Cancer Institute (NCI) grant P30CA016056 involving the use of OSUCCC The James, CCSG P30CA016058

Song et al. used an allelic reporter approach to show super-enhancers allelic DNA methylation dynamics underlies locus-specific heterogeneity, which functionally impacts transcription and cellular states of mouse embryonic stem cells., NIH (Grants HD045022, 1U19AI131135, 5R01MH104610, and 1R01GM114864)

To define the functions of NCOR1 we developed an integrative analysis that combined ENCODE and NCI-60 data, followed by in vitro validation. NCOR1 and H3K9me3 ChIP-Seq, FAIRE-seq and DNA CpG methylation interactions were related to gene expression using bootstrapping approaches. Most NCOR1 combinations (24/44) were associated with significantly elevated level expression of protein coding genes and only very few combinations related to gene repression. DAVID's biological process annotation revealed that elevated gene expression was uniquely associated with acetylation and ETS binding. A matrix of gene and drug interactions built on NCI-60 data identified that Imatinib significantly targeted the NCOR1 governed transcriptome. Stable knockdown of NCOR1 in K562 cells slowed growth and significantly repressed genes associated with NCOR1 cistrome, again, with the GO terms acetylation and ETS binding, and significantly dampened sensitivity to Imatinib-induced erythroid differentiation. Mining public microarray data revealed that NCOR1-targeted genes were significantly enriched in Imatinib response gene signatures in cell lines and chronic myelogenous leukemia (CML) patients. These approaches integrated cistrome, transcriptome and drug sensitivity relationships to reveal that NCOR1 function is surprisingly most associated with elevated gene expression, and that these targets, both in CML cell lines and patients, associate with sensitivity to Imatinib.

SummaryDuring in vitro differentiation, pluripotent stem cells undergo extensive remodeling of their gene expression profile. While studied extensively at the transcriptome level, much less is known about protein dynamics. Here, we measured mRNA and protein levels of 7459 genes during differentiation of embryonic stem cells (ESCs). This comprehensive data set revealed pervasive discordance between mRNA and protein. The high temporal resolution of the data made it possible to determine protein turnover rates genome-wide by fitting a kinetic model. This model further enabled us to systematically identify dynamic post-transcriptional regulation. Moreover, we linked different modes of regulation to the function of specific gene sets. Finally, we showed that the kinetic model can be applied to singlecell transcriptomics data to predict protein levels in differentiated cell types. In conclusion, our comprehensive data set, easily accessible through a web application, is a valuable resource for the discovery of post-transcriptional regulation in ESC differentiation.