Literature DB >> 26945717

The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification.

Eric Bertolino1, John Reinitz2.   

Abstract

C/EBPα plays an instructive role in the macrophage-neutrophil cell-fate decision and its expression is necessary for neutrophil development. How Cebpa itself is regulated in the myeloid lineage is not known. We decoded the cis-regulatory logic of Cebpa, and two other myeloid transcription factors, Egr1 and Egr2, using a combined experimental-computational approach. With a reporter design capable of detecting both distal enhancers and silencers, we analyzed 46 putative cis-regulatory modules (CRMs) in cells representing myeloid progenitors, and derived early macrophages or neutrophils. In addition to novel enhancers, this analysis revealed a surprisingly large number of silencers. We determined the regulatory roles of 15 potential transcriptional regulators by testing 32,768 alternative sequence-based transcriptional models against CRM activity data. This comprehensive analysis allowed us to infer the cis-regulatory logic for most of the CRMs. Silencer-mediated repression of Cebpa was found to be effected mainly by TFs expressed in non-myeloid lineages, highlighting a previously unappreciated contribution of long-distance silencing to hematopoietic lineage resolution. The repression of Cebpa by multiple factors expressed in alternative lineages suggests that hematopoietic genes are organized into densely interconnected repressive networks instead of hierarchies of mutually repressive pairs of pivotal TFs. More generally, our results demonstrate that de novo cis-regulatory dissection is feasible on a large scale with the aid of transcriptional modeling. Current address: Department of Biology, University of North Dakota, 10 Cornell Street, Stop 9019, Grand Forks, ND 58202-9019, USA.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cell fate; Gene regulation; Hematopoiesis; Silencers; Transcriptional modeling

Mesh:

Substances:

Year:  2016        PMID: 26945717      PMCID: PMC4878123          DOI: 10.1016/j.ydbio.2016.02.030

Source DB:  PubMed          Journal:  Dev Biol        ISSN: 0012-1606            Impact factor:   3.582


  117 in total

1.  C/EBPalpha binds and activates the PU.1 distal enhancer to induce monocyte lineage commitment.

Authors:  Christine Yeamans; Dehua Wang; Ido Paz-Priel; Bruce E Torbett; Daniel G Tenen; Alan D Friedman
Journal:  Blood       Date:  2007-08-01       Impact factor: 22.113

2.  Transcriptomic profiling identifies a PU.1 regulatory network in macrophages.

Authors:  Karin Weigelt; Monika Lichtinger; Michael Rehli; Thomas Langmann
Journal:  Biochem Biophys Res Commun       Date:  2009-01-22       Impact factor: 3.575

Review 3.  Gene regulatory networks directing myeloid and lymphoid cell fates within the immune system.

Authors:  Peter Laslo; Jagan M R Pongubala; David W Lancki; Harinder Singh
Journal:  Semin Immunol       Date:  2008-09-03       Impact factor: 11.130

4.  Expression of the leukemia oncogene Lmo2 is controlled by an array of tissue-specific elements dispersed over 100 kb and bound by Tal1/Lmo2, Ets, and Gata factors.

Authors:  Josette-Renée Landry; Nicolas Bonadies; Sarah Kinston; Kathy Knezevic; Nicola K Wilson; S Helen Oram; Mary Janes; Sandie Piltz; Michelle Hammett; Jacinta Carter; Tina Hamilton; Ian J Donaldson; Georges Lacaud; Jonathan Frampton; George Follows; Valerie Kouskoff; Berthold Göttgens
Journal:  Blood       Date:  2009-01-26       Impact factor: 22.113

5.  Transcription factor EBF restricts alternative lineage options and promotes B cell fate commitment independently of Pax5.

Authors:  Jagan M R Pongubala; Daniel L Northrup; David W Lancki; Kay L Medina; Thomas Treiber; Eric Bertolino; Matthew Thomas; Rudolf Grosschedl; David Allman; Harinder Singh
Journal:  Nat Immunol       Date:  2008-01-06       Impact factor: 25.606

6.  Predicting expression patterns from regulatory sequence in Drosophila segmentation.

Authors:  Eran Segal; Tali Raveh-Sadka; Mark Schroeder; Ulrich Unnerstall; Ulrike Gaul
Journal:  Nature       Date:  2008-01-02       Impact factor: 49.962

7.  Endoglin expression in blood and endothelium is differentially regulated by modular assembly of the Ets/Gata hemangioblast code.

Authors:  John E Pimanda; Wan Y I Chan; Nicola K Wilson; Aileen M Smith; Sarah Kinston; Kathy Knezevic; Mary E Janes; Josette-Renée Landry; Anja Kolb-Kokocinski; Jonathan Frampton; David Tannahill; Katrin Ottersbach; George A Follows; Georges Lacaud; Valerie Kouskoff; Berthold Göttgens
Journal:  Blood       Date:  2008-09-19       Impact factor: 22.113

8.  GATA-2 regulates granulocyte-macrophage progenitor cell function.

Authors:  Neil P Rodrigues; Ashleigh S Boyd; Cristina Fugazza; Gillian E May; Yanping Guo; Alex J Tipping; David T Scadden; Paresh Vyas; Tariq Enver
Journal:  Blood       Date:  2008-10-07       Impact factor: 22.113

9.  Regulation of B cell fate commitment and immunoglobulin heavy-chain gene rearrangements by Ikaros.

Authors:  Damien Reynaud; Ignacio A Demarco; Karen L Reddy; Hilde Schjerven; Eric Bertolino; Zhengshan Chen; Stephen T Smale; Susan Winandy; Harinder Singh
Journal:  Nat Immunol       Date:  2008-06-22       Impact factor: 25.606

10.  Global mapping of protein-DNA interactions in vivo by digital genomic footprinting.

Authors:  Jay R Hesselberth; Xiaoyu Chen; Zhihong Zhang; Peter J Sabo; Richard Sandstrom; Alex P Reynolds; Robert E Thurman; Shane Neph; Michael S Kuehn; William S Noble; Stanley Fields; John A Stamatoyannopoulos
Journal:  Nat Methods       Date:  2009-03-22       Impact factor: 28.547

View more
  7 in total

1.  A sequence level model of an intact locus predicts the location and function of nonadditive enhancers.

Authors:  Kenneth A Barr; John Reinitz
Journal:  PLoS One       Date:  2017-07-17       Impact factor: 3.240

2.  The regulatory control of Cebpa enhancers and silencers in the myeloid and red-blood cell lineages.

Authors:  Andrea Repele; Shawn Krueger; Tapas Bhattacharyya; Michelle Y Tuineau
Journal:  PLoS One       Date:  2019-06-10       Impact factor: 3.240

3.  Robust Normalization of Luciferase Reporter Data.

Authors:  Andrea Repele
Journal:  Methods Protoc       Date:  2019-07-25

4.  Data-driven modeling predicts gene regulatory network dynamics during the differentiation of multipotential hematopoietic progenitors.

Authors:  Joanna E Handzlik
Journal:  PLoS Comput Biol       Date:  2022-01-14       Impact factor: 4.475

5.  EBF1 primes B-lymphoid enhancers and limits the myeloid bias in murine multipotent progenitors.

Authors:  Iwo Kucinski; Ward Deboutte; Marta Derecka; Aurelie Lenaerts; Pierre Cauchy; Thomas Manke; Berthold Göttgens; Rudolf Grosschedl
Journal:  J Exp Med       Date:  2022-09-01       Impact factor: 17.579

6.  Fully interpretable deep learning model of transcriptional control.

Authors:  Yi Liu; Kenneth Barr; John Reinitz
Journal:  Bioinformatics       Date:  2020-07-01       Impact factor: 6.937

7.  Analyzing a putative enhancer of optic disc morphology.

Authors:  Vladimir Babenko; Roman Babenko; Yuri Orlov
Journal:  BMC Genet       Date:  2020-10-22       Impact factor: 2.797

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.