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Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.

PLoS ONE 6:e22649 (2011)
Verlagsversion Volltext DOI PMC
Open Access Gold
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Hematopoiesis is an ideal model system for stem cell biology with advanced experimental access. A systems view on the interactions of core transcription factors is important for understanding differentiation mechanisms and dynamics. In this manuscript, we construct a Boolean network to model myeloid differentiation, specifically from common myeloid progenitors to megakaryocytes, erythrocytes, granulocytes and monocytes. By interpreting the hematopoietic literature and translating experimental evidence into Boolean rules, we implement binary dynamics on the resulting 11-factor regulatory network. Our network contains interesting functional modules and a concatenation of mutual antagonistic pairs. The state space of our model is a hierarchical, acyclic graph, typifying the principles of myeloid differentiation. We observe excellent agreement between the steady states of our model and microarray expression profiles of two different studies. Moreover, perturbations of the network topology correctly reproduce reported knockout phenotypes in silico. We predict previously uncharacterized regulatory interactions and alterations of the differentiation process, and line out reprogramming strategies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter hematopoietic stem-cells; lineage-commitment; factor gata-1; c/ebp-alpha; mice lacking; regulatory networks; logical analysis; mouse embryos; fetal liver; factor eklf
Sprache englisch
Veröffentlichungsjahr 2011
HGF-Berichtsjahr 2011
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 6, Heft: 8, Seiten: , Artikelnummer: e22649 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort Lawrence, Kan.
Begutachtungsstatus Peer reviewed
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
Forschungsfeld(er) Enabling and Novel Technologies
Stem Cell and Neuroscience
PSP-Element(e) G-503700-004
G-501200-001
PubMed ID 21853041
Scopus ID 80051505603
Erfassungsdatum 2011-11-07