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      Dynamic Analysis of Gene Expression and Genome-wide Transcription Factor Binding during Lineage Specification of Multipotent Progenitors

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          Summary

          We used the paradigmatic GATA-PU.1 axis to explore, at the systems level, dynamic relationships between transcription factor (TF) binding and global gene expression programs as multipotent cells differentiate. We combined global ChIP-seq of GATA1, GATA2, and PU.1 with expression profiling during differentiation to erythroid and neutrophil lineages. Our analysis reveals (1) differential complexity of sequence motifs bound by GATA1, GATA2, and PU.1; (2) the scope and interplay of GATA1 and GATA2 programs within, and during transitions between, different cell compartments, and the extent of their hard-wiring by DNA motifs; (3) the potential to predict gene expression trajectories based on global associations between TF-binding data and target gene expression; and (4) how dynamic modeling of DNA-binding and gene expression data can be used to infer regulatory logic of TF circuitry. This rubric exemplifies the utility of this cross-platform resource for deconvoluting the complexity of transcriptional programs controlling stem/progenitor cell fate in hematopoiesis.

          Highlights

          • Cross-platform resource for TF-network regulation of multipotent blood cell fate

          • DNA motif dependence and changing specificity of GATA factors in lineage choice

          • Modeling-based inference identifies GATA2 repression of PU.1 in multipotent cells

          • Priming, recruitment, and switching modes of GATA interplay during differentiation

          Abstract

          A systems-level resource of the GATA-PU.1 axis provides insight into the dynamics of transcriptional programs during hematopoietic lineage commitment and differentiation.

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          Most cited references41

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          Forcing cells to change lineages.

          The ability to produce stem cells by induced pluripotency (iPS reprogramming) has rekindled an interest in earlier studies showing that transcription factors can directly convert specialized cells from one lineage to another. Lineage reprogramming has become a powerful tool to study cell fate choice during differentiation, akin to inducing mutations for the discovery of gene functions. The lessons learnt provide a rubric for how cells may be manipulated for therapeutic purposes.
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            Bifurcation dynamics in lineage-commitment in bipotent progenitor cells.

            Lineage specification of multipotent progenitor cells is governed by a balance of lineage-affiliated transcription factors, such as GATA1 and PU.1, which regulate the choice between erythroid and myelomonocytic fates. But how ratios of lineage-determining transcription factors stabilize progenitor cells and resolve their indeterminacy to commit them to discrete, mutually exclusive fates remains unexplained. We used a simple model and experimental measurements to analyze the dynamics of a binary fate decision governed by a gene-circuit containing auto-stimulation and cross-inhibition, as embodied by the GATA1-PU.1 paradigm. This circuit generates stable attractors corresponding to erythroid and myelomonocytic fates, as well as an uncommitted metastable state characterized by coexpression of both regulators, explaining the phenomenon of "multilineage priming". GATA1 and PU.1 mRNA and transcriptome dynamics of differentiating progenitor cells confirm that commitment occurs in two stages, as suggested by the model: first, the progenitor state is destabilized in an almost symmetrical bifurcation event, resulting in a poised state at the boundary between the two lineage-specific attractors; second, the cell is driven to the respective, now accessible attractors. This minimal model captures fundamental features of binary cell fate decisions, uniting the concepts of stochastic (selective) and deterministic (instructive) regulation, and hence, may apply to a wider range of binary fate decision points.
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              The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

              Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.
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                Author and article information

                Journal
                Cell Stem Cell
                Cell Stem Cell
                Cell Stem Cell
                Cell Press
                1934-5909
                1875-9777
                05 December 2013
                05 December 2013
                : 13
                : 6
                : 754-768
                Affiliations
                [1 ]Stem Cell Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK
                [2 ]Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
                [3 ]Computational Biology and Biological Physics, Department of Theoretical Physics, Lund University, 223 62 Lund, Sweden
                [4 ]Computational Biology Research Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford OX3 9DS, UK
                [5 ]Cancer Science Institute, National University of Singapore, Singapore 117599
                [6 ]Harvard Stem Cell Institute, Harvard Medical School, Boston, MA 02115, USA
                Author notes
                []Corresponding author t.enver@ 123456cancer.ucl.ac.uk
                [7]

                Present address: Lund Stem Cell Center, Lund University Hospital, Biomedical Centre, 221 84 Lund, Sweden

                [8]

                Present address: National Health Service Blood and Transplant, John Radcliffe Hospital, Nuffield Division of Clinical Laboratory Sciences, University of Oxford, Oxford OX3 9DU, UK

                [9]

                Present address: National Health Service Blood and Transplant, Department of Haematology, University of Cambridge, Cambridge CB2 0PT, UK

                [10]

                These authors contributed equally to this work

                Article
                S1934-5909(13)00403-7
                10.1016/j.stem.2013.09.003
                3878573
                24120743
                5514af7d-6258-445e-8e59-acb9344b58f3
                © 2013 ELL & Excerpta Medica.

                This document may be redistributed and reused, subject to certain conditions.

                History
                : 29 March 2012
                : 6 August 2013
                : 12 September 2013
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