Tijssen, MR, Cvejic, A, Joshi, A, Hannah, RL, Ferreira, R, Forrai, A et al.. Genome-wide analysis of simultaneous GATA1/2, RUNX1, FLI1, and SCL binding in megakaryocytes identifies hematopoietic regulators. Dev Cell 20: 597-609

Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK.
Developmental Cell (Impact Factor: 9.71). 05/2011; 20(5):597-609. DOI: 10.1016/j.devcel.2011.04.008
Source: PubMed


Hematopoietic differentiation critically depends on combinations of transcriptional regulators controlling the development of individual lineages. Here, we report the genome-wide binding sites for the five key hematopoietic transcription factors--GATA1, GATA2, RUNX1, FLI1, and TAL1/SCL--in primary human megakaryocytes. Statistical analysis of the 17,263 regions bound by at least one factor demonstrated that simultaneous binding by all five factors was the most enriched pattern and often occurred near known hematopoietic regulators. Eight genes not previously appreciated to function in hematopoiesis that were bound by all five factors were shown to be essential for thrombocyte and/or erythroid development in zebrafish. Moreover, one of these genes encoding the PDZK1IP1 protein shared transcriptional enhancer elements with the blood stem cell regulator TAL1/SCL. Multifactor ChIP-Seq analysis in primary human cells coupled with a high-throughput in vivo perturbation screen therefore offers a powerful strategy to identify essential regulators of complex mammalian differentiation processes.

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    • "This prediction can now be evaluated comprehensively and quantitatively in mouse cell models. Recent studies from our laboratory, as part of the Mouse ENCODE Project (The Mouse ENCODE Consortium et al. 2014), and others have used chromatin immunoprecipitation (ChIP) followed by secondgeneration sequencing (ChIP-seq) (Johnson et al. 2007; Robertson et al. 2007) and related methods to map DNA segments occupied by TAL1 and other TFs across the genomes of multiple human and mouse hematopoietic cells of different lineages and at progressive stages of maturation (Cheng et al. 2009; Wilson et al. 2009, 2010; Kassouf et al. 2010; Soler et al. 2010; Palii et al. 2011; Tijssen et al. 2011; Wu et al. 2011; Dore et al. 2012; Kowalczyk et al. 2012; Xu et al. 2012; Pimkin et al. 2014). To gain further insights into the functions carried out by TAL1 in each cell type, we integrated these maps of TAL1 occupancy to establish its patterns of cell lineage– specific and maturational stage–specific occupancy and correlated these with gene expression. "
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    ABSTRACT: We used mouse ENCODE data along with complementary data from other laboratories to study the dynamics of occupancy and the role in gene regulation of the transcription factor TAL1, a critical regulator of hematopoiesis, at multiple stages of hematopoietic differentiation. We combined ChIP-seq and RNA-seq data in six mouse cell types representing a progression from multilineage precursors to differentiated erythroblasts and megakaryocytes. We found that sites of occupancy shift dramatically during commitment to the erythroid lineage, vary further during terminal maturation, and are strongly associated with changes in gene expression. In multilineage progenitors, the likely target genes are enriched for hematopoietic growth and functions associated with the mature cells of specific daughter lineages (such as megakaryocytes). In contrast, target genes in erythroblasts are specifically enriched for red cell functions. Furthermore, shifts in TAL1 occupancy during erythroid differentiation are associated with gene repression (dissociation) and induction (co-occupancy with GATA1). Based on both enrichment for transcription factor binding site motifs and co-occupancy determined by ChIP-seq, recruitment by GATA transcription factors appears to be a stronger determinant of TAL1 binding to chromatin than the canonical E-box binding site motif. Studies of additional proteins lead to the model that TAL1 regulates expression after being directed to a distinct subset of genomic binding sites in each cell type via its association with different complexes containing master regulators such as GATA2, ERG, and RUNX1 in multilineage cells and the lineage-specific master regulator GATA1 in erythroblasts.
    Genome Research 10/2014; 24(12). DOI:10.1101/gr.164830.113 · 14.63 Impact Factor
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    • "Runx3 occupies thousands of genomic loci in resting and IL-2-activated CD8-TC and NKC, reflecting a common property of many TFs, including the other two RUNX family members Runx1 [15,52] and Runx2 [53]. About 80% of Runx3-bound genes in CD8-TC overlapped those in NKC. "
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    ABSTRACT: The transcription factor Runx3 is highly expressed in CD8(+) T and NK cytotoxic lymphocytes and is required for their effective activation and proliferation but molecular insights into the transcription program regulated by Runx3 in these cells are still missing. Using Runx3-ChIP-seq and transcriptome analysis of wild type vs. Runx3(-/-) primary cells we have now identified Runx3-regulated genes in the two cell types at both resting and IL-2-activated states. Runx3-bound genomic regions in both cell types were distantly located relative to gene transcription start sites and were enriched for RUNX and ETS motifs. Bound genomic regions significantly overlapped T-bet and p300-bound enhancer regions in Runx3-expressing Th1 helper cells. Compared to resting cells, IL-2-activated CD8(+) T and NK cells contain three times more Runx3-regulated genes that are common to both cell types. Functional annotation of shared CD8(+) T and NK Runx3-regulated genes revealed enrichment for immune-associated terms including lymphocyte activation, proliferation, cytotoxicity, migration and cytokine production, highlighting the role of Runx3 in CD8(+) T and NK activated cells.
    PLoS ONE 11/2013; 8(11):e80467. DOI:10.1371/journal.pone.0080467 · 3.23 Impact Factor
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    • "This view also permits easy visualization of comparative binding profiles at these or other regions in primary megakaryocytes (12) and AML cells (20). The gene expression view (Supplementary Figure S2C) to the right shows RUNX1 expression across HSCs, multi-potent progenitors (MPP), common myeloid progenitors (CMP), granulocyte–monocyte progenitors (GMP) or megakaryocyte–erythroid progenitor (MEP) fractions as well as in AML leukaemic stem cells (LSC; Lin-/CD34+/38-/CD90-), AML leukaemic progenitor cells (Lin-/34+/38+) and AML blasts (Lin-/34-) (14), megakaryocytes and AML cells. "
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    ABSTRACT: The BloodChIP database (http://www.med.unsw.edu.au/CRCWeb.nsf/page/BloodChIP) supports exploration and visualization of combinatorial transcription factor (TF) binding at a particular locus in human CD34-positive and other normal and leukaemic cells or retrieval of target gene sets for user-defined combinations of TFs across one or more cell types. Increasing numbers of genome-wide TF binding profiles are being added to public repositories, and this trend is likely to continue. For the power of these data sets to be fully harnessed by experimental scientists, there is a need for these data to be placed in context and easily accessible for downstream applications. To this end, we have built a user-friendly database that has at its core the genome-wide binding profiles of seven key haematopoietic TFs in human stem/progenitor cells. These binding profiles are compared with binding profiles in normal differentiated and leukaemic cells. We have integrated these TF binding profiles with chromatin marks and expression data in normal and leukaemic cell fractions. All queries can be exported into external sites to construct TF-gene and protein-protein networks and to evaluate the association of genes with cellular processes and tissue expression.
    Nucleic Acids Research 10/2013; 42(Database issue). DOI:10.1093/nar/gkt1036 · 9.11 Impact Factor
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