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      Computational Promoter Modeling Identifies the Modes of Transcriptional Regulation in Hematopoietic Stem Cells

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          Abstract

          Extrinsic and intrinsic regulators are responsible for the tight control of hematopoietic stem cells (HSCs), which differentiate into all blood cell lineages. To understand the fundamental basis of HSC biology, we focused on differentially expressed genes (DEGs) in long-term and short-term HSCs, which are closely related in terms of cell development but substantially differ in their stem cell capacity. To analyze the transcriptional regulation of the DEGs identified in the novel transcriptome profiles obtained by our RNA-seq analysis, we developed a computational method to model the linear relationship between gene expression and the features of putative regulatory elements. The transcriptional regulation modes characterized here suggest the importance of transcription factors (TFs) that are expressed at steady state or at low levels. Remarkably, we found that 24 differentially expressed TFs targeting 21 putative TF-binding sites contributed significantly to transcriptional regulation. These TFs tended to be modulated by other nondifferentially expressed TFs, suggesting that HSCs can achieve flexible and rapid responses via the control of nondifferentially expressed TFs through a highly complex regulatory network. Our novel transcriptome profiles and new method are powerful tools for studying the mechanistic basis of cell fate decisions.

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          Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

          Alex Shalek, Rahul Satija, Xian Adiconis … (2013)
          Recent molecular studies have revealed that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels, and phenotypic output 1–5 , with important functional consequences 4,5 . Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs 1,2 or proteins 5,6 simultaneously because genomic profiling methods 3 could not be applied to single cells until very recently 7–10 . Here, we use single-cell RNA-Seq to investigate heterogeneity in the response of bone marrow derived dendritic cells (BMDCs) to lipopolysaccharide (LPS). We find extensive, and previously unobserved, bimodal variation in mRNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization (RNA-FISH) for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.
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            Clonal analysis unveils self-renewing lineage-restricted progenitors generated directly from hematopoietic stem cells.

            Ryo Yamamoto, Yohei Morita, Jun Ooehara … (2013)
            Consensus holds that hematopoietic stem cells (HSCs) give rise to multipotent progenitors (MPPs) of reduced self-renewal potential and that MPPs eventually produce lineage-committed progenitor cells in a stepwise manner. Using a single-cell transplantation system and marker mice, we unexpectedly found myeloid-restricted progenitors with long-term repopulating activity (MyRPs), which are lineage-committed to megakaryocytes, megakaryocyte-erythroid cells, or common myeloid cells (MkRPs, MERPs, or CMRPs, respectively) in the phenotypically defined HSC compartment together with HSCs. Paired daughter cell assays combined with transplantation revealed that HSCs can give rise to HSCs via symmetric division or directly differentiate into MyRPs via asymmetric division (yielding HSC-MkRP or HSC-CMRP pairs). These myeloid bypass pathways could be essential for fast responses to ablation stress. Our results show that loss of self-renewal and stepwise progression through specific differentiation stages are not essential for lineage commitment of HSCs and suggest a revised model of hematopoietic differentiation. Copyright © 2013 Elsevier Inc. All rights reserved.
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              TRANSFAC: an integrated system for gene expression regulation.

              E. Wingender, X. Chen, R Hehl … (2000)
              TRANSFAC is a database on transcription factors, their genomic binding sites and DNA-binding profiles (http://transfac.gbf.de/TRANSFAC/). Its content has been enhanced, in particular by information about training sequences used for the construction of nucleotide matrices as well as by data on plant sites and factors. Moreover, TRANSFAC has been extended by two new modules: PathoDB provides data on pathologically relevant mutations in regulatory regions and transcription factor genes, whereas S/MARt DB compiles features of scaffold/matrix attached regions (S/MARs) and the proteins binding to them. Additionally, the databases TRANSPATH, about signal transduction, and CYTOMER, about organs and cell types, have been extended and are increasingly integrated with the TRANSFAC data sources.
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                Author and article information

                Contributors
                Connie J. Eaves: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2014
                Publication date (Electronic): 7 April 2014
                Volume: 9
                Issue: 4
                Electronic Location Identifier: e93853
                Affiliations
                [1 ]Human Genome Center, the Institute of Medical Science, the University of Tokyo, Tokyo, Japan
                [2 ]Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan
                B.C. Cancer Agency, Canada
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SJP KN. Performed the experiments: TU YS MY. Analyzed the data: SJP MSA. Contributed reagents/materials/analysis tools: TU SJP. Wrote the paper: SJP.

                Article
                Publisher ID: PONE-D-13-53146
                DOI: 10.1371/journal.pone.0093853
                PMC ID: 3977923
                PubMed ID: 24710559
                SO-VID: 078ce766-7226-41e2-9572-ac9f01c79df7
                Copyright statement: Copyright @ 2014
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 18 December 2013
                Date accepted : 7 March 2014
                Page count
                Pages: 15
                Funding
                This work was supported by Research on Applying Health Technology, Health and Labour Sciences by the Ministry of Health, Labour and Welfare, Japan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Cell Biology
                Subject: Cellular Types
                Subject: Animal Cells
                Subject: Stem Cells
                Subject: Hematopoietic Stem Cells
                Subject: Molecular Cell Biology
                Subject: Computational Biology
                Subject: Genome Analysis
                Subject: Transcriptome Analysis
                Subject: Developmental Biology
                Subject: Cell Differentiation
                Subject: Genetics
                Subject: Gene Expression
                Subject: Gene Regulation
                Subject: Genomics
                Subject: Systems Biology
                Subject: Computer and Information Sciences
                Subject: Network Analysis
                Subject: Regulatory Networks
                Subject: Medicine and Health Sciences
                Subject: Hematology
                Subject: Hematopoiesis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Probability Theory
                Subject: Random Variables
                Subject: Stochastic Processes
                Subject: Statistics (Mathematics)
                Subject: Contingency Tables
                Subject: Statistical Methods

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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