18
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      PRDM16 binds MED1 and controls chromatin architecture to determine a brown fat transcriptional program

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Harms et al. reveal that PRDM16 binding is highly enriched at a broad set of brown fat-selective genes. PRDM16 physically binds to MED1, a component of the Mediator complex, and recruits it to superenhancers at brown fat-selective genes. PRDM16 deficiency in BAT reduces MED1 binding at PRDM16 target sites and causes a fundamental change in chromatin architecture at key brown fat-selective genes.

          Abstract

          PR (PRD1–BF1–RIZ1 homologous) domain-containing 16 (PRDM16) drives a brown fat differentiation program, but the mechanisms by which PRDM16 activates brown fat-selective genes have been unclear. Through chromatin immunoprecipitation (ChIP) followed by deep sequencing (ChIP-seq) analyses in brown adipose tissue (BAT), we reveal that PRDM16 binding is highly enriched at a broad set of brown fat-selective genes. Importantly, we found that PRDM16 physically binds to MED1, a component of the Mediator complex, and recruits it to superenhancers at brown fat-selective genes. PRDM16 deficiency in BAT reduces MED1 binding at PRDM16 target sites and causes a fundamental change in chromatin architecture at key brown fat-selective genes. Together, these data indicate that PRDM16 controls chromatin architecture and superenhancer activity in BAT.

          Related collections

          Most cited references36

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          BEDTools: a flexible suite of utilities for comparing genomic features

          Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              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.
                Bookmark

                Author and article information

                Journal
                Genes Dev
                Genes Dev
                genesdev
                genesdev
                GAD
                Genes & Development
                Cold Spring Harbor Laboratory Press
                0890-9369
                1549-5477
                1 February 2015
                : 29
                : 3
                : 298-307
                Affiliations
                [1 ]Institute for Diabetes, Obesity, and Metabolism,
                [2 ]Department of Cell and Developmental Biology,
                [3 ]Genetics Department, Smilow Center for Translational Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
                Author notes
                [4]

                These authors contributed equally to this work.

                Article
                8711660 RA
                10.1101/gad.252734.114
                4318146
                25644604
                440a0309-d1ce-4be1-9074-da4fd3219f13
                © 2015 Harms et al.; Published by Cold Spring Harbor Laboratory Press

                This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genesdev.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 17 September 2014
                : 10 December 2014
                Page count
                Pages: 10
                Funding
                Funded by: National Institute of General Medical Sciences/National Institutes of Health
                Award ID: DP2OD007288
                Funded by: National Institutes of Health
                Award ID: R21DK098769
                Funded by: National Institute of Diabetes and Digestive and Kidney Diseases
                Award ID: R01 DK49780
                Categories
                Research Paper

                prdm16,prdm3,med1,mediator,brown adipose tissue,ucp1
                prdm16, prdm3, med1, mediator, brown adipose tissue, ucp1

                Comments

                Comment on this article