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

      Interactions between lineage‐associated transcription factors govern haematopoietic progenitor states

      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

          Recent advances in molecular profiling provide descriptive datasets of complex differentiation landscapes including the haematopoietic system, but the molecular mechanisms defining progenitor states and lineage choice remain ill‐defined. Here, we employed a cellular model of murine multipotent haematopoietic progenitors (Hoxb8‐ FL) to knock out 39 transcription factors ( TFs) followed by RNA‐Seq analysis, to functionally define a regulatory network of 16,992 regulator/target gene links. Focussed analysis of the subnetworks regulated by the B‐lymphoid TF Ebf1 and T‐lymphoid TF Gata3 revealed a surprising role in common activation of an early myeloid programme. Moreover, Gata3‐mediated repression of Pax5 emerges as a mechanism to prevent precocious B‐lymphoid differentiation, while Hox‐mediated activation of Meis1 suppresses myeloid differentiation. To aid interpretation of large transcriptomics datasets, we also report a new method that visualises likely transitions that a progenitor will undergo following regulatory network perturbations. Taken together, this study reveals how molecular network wiring helps to establish a multipotent progenitor state, with experimental approaches and analysis tools applicable to dissecting a broad range of both normal and perturbed cellular differentiation landscapes.

          Abstract

          Functional definition of a transcription factor network reveals regulatory interdependencies during early blood development.

          Related collections

          Most cited references 104

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

          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
            Bookmark
            • 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

              An Integrated Encyclopedia of DNA Elements in the Human Genome

              Summary The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure, and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall the project provides new insights into the organization and regulation of our genes and genome, and an expansive resource of functional annotations for biomedical research.
                Bookmark

                Author and article information

                Contributors
                bg200@cam.ac.uk
                Journal
                EMBO J
                EMBO J
                10.1002/(ISSN)1460-2075
                EMBJ
                embojnl
                The EMBO Journal
                John Wiley and Sons Inc. (Hoboken )
                0261-4189
                1460-2075
                26 October 2020
                15 December 2020
                26 October 2020
                : 39
                : 24 ( doiID: 10.1002/embj.v39.24 )
                Affiliations
                [ 1 ] Wellcome–MRC Cambridge Stem Cell Institute Department of Haematology Jeffrey Cheah Biomedical Centre University of Cambridge Cambridge UK
                [ 2 ] Department of Cellular and Molecular Immunology Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany
                [ 3 ] International Max Planck Research School for Molecular and Cellular Biology Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany
                Author notes
                [*] [* ]Corresponding author. Tel: +44 1223 336829; E‐mail: bg200@ 123456cam.ac.uk
                Article
                EMBJ2020104983
                10.15252/embj.2020104983
                7737608
                33103827
                c41904dd-4c89-4fa6-ba59-43789339c3a6
                © 2020 The Authors Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 14, Tables: 0, Pages: 23, Words: 17805
                Product
                Funding
                Funded by: HHS|National Institutes of Health (NIH)
                Award ID: NIDDK DK106766
                Funded by: Wellcome Trust (WT)
                Award ID: 206328/Z/17/Z
                Funded by: Blood Cancer UK , open-funder-registry 10.13039/501100015570;
                Award ID: 18002
                Funded by: Cancer Research UK (CRUK)
                Award ID: C1163/A21762
                Funded by: UKRI|Medical Research Council (MRC)
                Award ID: MR/S036113/1
                Funded by: Cancer Research UK (CRUK)
                Award ID: C49940/A25117
                Funded by: Wellcome Trust (WT)
                Award ID: 203151/Z/16/Z
                Funded by: UKRI|Medical Research Council (MRC)
                Award ID: 203151/Z/16/Z
                Categories
                Article
                Articles
                Custom metadata
                2.0
                15 December 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.5 mode:remove_FC converted:15.12.2020

                Comments

                Comment on this article