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Establishing the stem cell state: insights from regulatory network analysis of blood stem cell development

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Abstract Transcription factors (TFs) have long been recognized as powerful regulators of cell‐type identity and differentiation. As TFs function as constituents of regulatory networks, identification and functional characterization of key interactions within these wider networks will be required to understand how TFs exert their powerful biological functions. The formation of blood cells (hematopoiesis) represents a widely used model system for the study of cellular differentiation. Moreover, specific TFs or groups of TFs have been identified to control the various cell fate choices that must be made when blood stem cells differentiate into more than a dozen distinct mature blood lineages. Because of the relative ease of accessibility, the hematopoietic system represents an attractive experimental system for the development of regulatory network models. Here, we review the modeling efforts carried out to date, which have already provided new insights into the molecular control of blood cell development. We also explore potential areas of future study such as the need for new high‐throughput technologies and a focus on studying dynamic cellular systems. Many leukemias arise as the result of mutations that cause transcriptional dysregulation, thus suggesting that a better understanding of transcriptional control mechanisms in hematopoiesis is of substantial biomedical relevance. Moreover, lessons learned from regulatory network analysis in the hematopoietic system are likely to inform research on less experimentally tractable tissues. WIREs Syst Biol Med 2012. doi: 10.1002/wsbm.1163 This article is categorized under: Biological Mechanisms > Cell Fates

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Transcription factor (TF) action through regulatory elements. (a) A representative gene locus is composed of a promoter region (II) as well as distal cis‐regulatory elements (I and III). On the basis of the cell state, multiple TFs can bind in different combinations to the different regulatory regions resulting in distinct regulatory states. For example, TF A binds only the regulatory region I in state 1. In state 2, TF A binds the regulatory region I, and it also forms a complex with TF E to bind the regulatory region III. (b) The gene regulatory network is identical for all blood cell types, but the specific configuration of a given network varies depending on the cell state. Lines with dots represent direct binding of two proteins, and arrows represent regulation of gene expression. Transparent TFs and lines indicate inactive parts and nontransparent TFs and lines active interactions within the given network state.

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Modeling transcriptional regulatory core circuits in hematopoiesis. (a) The cross‐antagonism between Gata1 and PU.1 in the erythroid–myeloid lineage decision. While Gata1 expression determines the development of erythroid and megakaryocytic cells, PU.1 expression specifies the development of monocytes. (b) The HSC triad is composed of Fli1, Gata2, and Scl, and these transcription factors are connected via cross‐regulatory and auto‐regulatory interactions through regulatory elements within their gene loci. (c) A gene‐regulatory network model for B‐cell versus macrophage development. Arrows indicate activation of gene expression and barred lines describe gene repression. Blue represents the network state with high levels of PU.1, green with low levels of PU.1. Dashed lines indicate interactions that still have to be defined on a molecular basis.

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Selection of network motifs commonly found in mammalian gene regulatory networks. Circles represent genes, which are connected by arrows signifying activation and bar‐ended lines signifying repression. Of note, the multi‐input motif represents a subset of the dense‐overlapping‐region motif. The reader is kindly referred to a number of expert articles14,61 for more detailed information.

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Schematic view of adult hematopoiesis. All mature blood cells emerge from a hematopoietic stem cell (HSC). HSCs differentiate into multipotent progenitors (MPPs) that lose the potential of long‐term self‐renewal. The MPPs give rise to common lymphoid progenitors (CLP) and common myeloid progenitors CMP. CMPs further differentiate into all mature blood cells of the myeloid lineage including erythrocytes, megakaryocytes, mast cells, macrophages and granulocytes, whereas CLPs differentiate into T, B, and natural killer cells.

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