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Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2017,6,6]]},"abstract":"<jats:p>\n                    Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte\u2013erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (\n                    <jats:italic>Nfe2<\/jats:italic>\n                    ) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (\n                    <jats:italic>Cbfa2t3h<\/jats:italic>\n                    ) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships.\n                  <\/jats:p>","DOI":"10.1073\/pnas.1610609114","type":"journal-article","created":{"date-parts":[[2017,6,5]],"date-time":"2017-06-05T20:50:17Z","timestamp":1496695817000},"page":"5822-5829","update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":102,"title":["Reconstructing blood stem cell regulatory network models from single-cell molecular profiles"],"prefix":"10.1073","volume":"114","author":[{"given":"Fiona K.","family":"Hamey","sequence":"first","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonia","family":"Nestorowa","sequence":"additional","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah J.","family":"Kinston","sequence":"additional","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David G.","family":"Kent","sequence":"additional","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicola K.","family":"Wilson","sequence":"additional","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6302-5705","authenticated-orcid":false,"given":"Berthold","family":"G\u00f6ttgens","sequence":"additional","affiliation":[{"name":"Department of Haematology, Wellcome Trust\u2013Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2017,6,5]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"crossref","first-page":"338","DOI":"10.2353\/ajpath.2006.060312","article-title":"Hematopoietic stem cells: The paradigmatic tissue-specific stem cell","volume":"169","author":"Bryder D","year":"2006","unstructured":"D Bryder, DJ Rossi, IL Weissman, Hematopoietic stem cells: The paradigmatic tissue-specific stem cell. Am J Pathol 169, 338\u2013346 (2006).","journal-title":"Am J Pathol"},{"key":"e_1_3_4_2_2","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1016\/j.stem.2015.04.004","article-title":"Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations","volume":"16","author":"Wilson NK","year":"2015","unstructured":"NK Wilson, , Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations. Cell Stem Cell 16, 712\u2013724 (2015).","journal-title":"Cell Stem Cell"},{"key":"e_1_3_4_3_2","doi-asserted-by":"crossref","first-page":"1663","DOI":"10.1016\/j.cell.2015.11.013","article-title":"Transcriptional heterogeneity and lineage commitment in myeloid progenitors","volume":"163","author":"Paul F","year":"2015","unstructured":"F Paul, , Transcriptional heterogeneity and lineage commitment in myeloid progenitors. Cell 163, 1663\u20131677 (2015).","journal-title":"Cell"},{"key":"e_1_3_4_4_2","doi-asserted-by":"crossref","first-page":"4052","DOI":"10.1002\/1873-3468.12231","article-title":"Advancing haematopoietic stem and progenitor cell biology through single cell profiling","volume":"590","author":"Hamey FK","year":"2016","unstructured":"FK Hamey, S Nestorowa, NK Wilson, B Gottgens, Advancing haematopoietic stem and progenitor cell biology through single cell profiling. FEBS Lett 590, 4052\u20134067 (2016).","journal-title":"FEBS Lett"},{"key":"e_1_3_4_5_2","volume-title":"Genomic Control Process: Development and Evolution","author":"Peter I","year":"2015","unstructured":"I Peter, EH Davidson Genomic Control Process: Development and Evolution (Academic, 2nd Ed, New York, 2015).","edition":"2"},{"key":"e_1_3_4_6_2","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1038\/ncb2709","article-title":"Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis","volume":"15","author":"Moignard V","year":"2013","unstructured":"V Moignard, , Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. 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Cell 157, 714\u2013725 (2014).","journal-title":"Cell"},{"key":"e_1_3_4_22_2","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1038\/nbt.2859","article-title":"The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells","volume":"32","author":"Trapnell C","year":"2014","unstructured":"C Trapnell, , The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32, 381\u2013386 (2014).","journal-title":"Nat Biotechnol"},{"key":"e_1_3_4_23_2","doi-asserted-by":"crossref","first-page":"i80","DOI":"10.1093\/bioinformatics\/btt243","article-title":"Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model","volume":"29","author":"Bonzanni N","year":"2013","unstructured":"N Bonzanni, , Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model. 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