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      Epigenetic disruption of the RARγ complex impairs its function to bookmark AR enhancer interactions required for enzalutamide sensitivity in prostate cancer

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          Abstract

          Lineage plasticity in advanced prostate cancer (PCa) involves a corruption of differentiation programs, often regulated by the androgen receptor (AR). This study explores an under-explored cistromic mechanism: how type II nuclear receptors like RARγ may affect AR control of prodifferentiation transcriptional programs. The components of the RARγ complex are dynamic in PCa cell models and enriched for miR-96 targets, partly due to m6A-marked miR-96 recognition elements. Restoration of TACC1 and RARγ, both miR-96 repressed targets, in 22Rv1 cells augmented the AR cistrome, particularly in active enhancers and super-enhancers. In 22Rv1 cells the RARγ complex was enriched for bookmarking components, and created nucleosome-free chromatin enriched for H3K27ac, and profoundly enhanced the dihydrotestosterone (DHT)-dependent AR cistrome in G2/M cells and are all indicative of bookmarking functions. The RARγ-dependent and DHT-regulated AR cistrome-transcriptome relationships were significantly strengthened, notably in Active Enhancers, associated with AR-dependent luminal differentiation transcriptional programs. Interestingly RARγ-dependent AR cistromes significantly overlapped with ONECUT2, but the comparative transcriptional analyses supported an antagonistic function between RARγ and ONECUT2. Finally, the footprint of these data was detected in advanced tumors. For example, the miR-96 targetome and RARγ/ONECUT2 antagonized genes were significantly similar to AR signaling inhibitor-induced alternative lineages and metastatic tumors. Partial correlation analyses revealed RARγ CoAs identified by RIME, including SSRP1, significantly strengthened the correlations between AR and RARγ-TACC1-dependent DHT-regulated target genes in SU2C advanced PCa, and differentially-expressed genes between tumors with high RARγ and low ONECUT2 expression compared to the reverse was significantly associated with elevated AR score. In summary, the RARγ complex, selectively targeted by miR-96 functions as an enhancer re-programmer by bookmarking chromatin in G 2/M cells to sustain and restrict AR transcriptional competency required for programs such as luminal differentiation, and antagonizing ONECUT2.

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          Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities.

          Genome-scale studies have revealed extensive, cell type-specific colocalization of transcription factors, but the mechanisms underlying this phenomenon remain poorly understood. Here, we demonstrate in macrophages and B cells that collaborative interactions of the common factor PU.1 with small sets of macrophage- or B cell lineage-determining transcription factors establish cell-specific binding sites that are associated with the majority of promoter-distal H3K4me1-marked genomic regions. PU.1 binding initiates nucleosome remodeling, followed by H3K4 monomethylation at large numbers of genomic regions associated with both broadly and specifically expressed genes. These locations serve as beacons for additional factors, exemplified by liver X receptors, which drive both cell-specific gene expression and signal-dependent responses. Together with analyses of transcription factor binding and H3K4me1 patterns in other cell types, these studies suggest that simple combinations of lineage-determining transcription factors can specify the genomic sites ultimately responsible for both cell identity and cell type-specific responses to diverse signaling inputs. Copyright 2010 Elsevier Inc. All rights reserved.
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            Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference

            We introduce Salmon, a method for quantifying transcript abundance from RNA-seq reads that is accurate and fast. Salmon is the first transcriptome-wide quantifier to correct for fragment GC content bias, which we demonstrate substantially improves the accuracy of abundance estimates and the reliability of subsequent differential expression analysis. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure.
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              Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons.

              Methylation of the N(6) position of adenosine (m(6)A) is a posttranscriptional modification of RNA with poorly understood prevalence and physiological relevance. The recent discovery that FTO, an obesity risk gene, encodes an m(6)A demethylase implicates m(6)A as an important regulator of physiological processes. Here, we present a method for transcriptome-wide m(6)A localization, which combines m(6)A-specific methylated RNA immunoprecipitation with next-generation sequencing (MeRIP-Seq). We use this method to identify mRNAs of 7,676 mammalian genes that contain m(6)A, indicating that m(6)A is a common base modification of mRNA. The m(6)A modification exhibits tissue-specific regulation and is markedly increased throughout brain development. We find that m(6)A sites are enriched near stop codons and in 3' UTRs, and we uncover an association between m(6)A residues and microRNA-binding sites within 3' UTRs. These findings provide a resource for identifying transcripts that are substrates for adenosine methylation and reveal insights into the epigenetic regulation of the mammalian transcriptome. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                bioRxiv
                BIORXIV
                bioRxiv
                Cold Spring Harbor Laboratory
                19 December 2023
                : 2023.12.15.571947
                Affiliations
                [1 ]Division of Pharmaceutics and Pharmacology, The Ohio State University, Columbus, OH 43210
                [2 ]Division of Cancer Biology, Cedars Sinai Cancer
                [3 ]Board of Governors Innovation Center, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048
                [4 ]Division of Cancer Therapeutics, Cedars Sinai Cancer, Departments of Urology and Biomedical Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048
                [5 ]Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY 14263
                [6 ]Institute of Metabolism and Systems Research (IMSR), and Centre of Endocrinology, Diabetes and Metabolism (CEDAM), University of Birmingham, Birmingham, UK
                [7 ]Department of Cancer Prevention and Control, Cedars-Sinai Medical Center, Los Angeles, CA 90048
                Author notes
                [a]

                Current address: Department of Cancer Biology, College of Medicine, University of Cincinnati, Cincinnati OH 45267

                [b]

                Current address: Medpace Inc, 5375 Medpace Way, Cincinnati, OH 45227

                [c]

                Current address: Division of Cancer Biology and Inflammatory Disorder, CSIR-Indian Institute of Chemical Biology, 4, Kolkata 700032, India

                [d]

                Current address:

                [e]

                Current address: Abigail Wexner Research Institute at Nationwide Children’s Hospital, 575 Children’s Crossroad, Columbus, OH 43215

                [f]

                Current address: Department of Animal Husbandry and Veterinary Services, Karnataka, India.

                [*]

                These authors contributed equally

                Authors’ contributions

                SAW undertook IMPACT-Seq, m6A-Seq, RIME, CUT&RUN, ATAC-Seq, RNA-Seq and cell biology; SS undertook cell biology; HT contributed to bioinformatic analyses; JSG contributed to ATAC-Seq and cell biology; MDL undertook GIGGLE analyses; SAW and MJC jointly conceived of the study design; MJC oversaw the implementation of the study and undertook all other bioinformatic analyses and generated tables and figures and led manuscript preparation.

                [* ]Correspondence: moray.campbell@ 123456cshs.org
                Article
                10.1101/2023.12.15.571947
                10760102
                38168185
                45c8a2f4-c26d-4f82-a8d8-9b43fbaad645

                This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

                History
                Funding
                Funded by: National Institute of Health Cancer Center
                Award ID: P30CA016058
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