Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
    
    
        
    
    
        
        PLoS ONE 6:e22649 (2011)
    
    
    
      
      
	
	    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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        Publication type
        Article: Journal article
    
 
    
        Document type
        Scientific Article
    
 
    
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        Keywords
        hematopoietic stem-cells; lineage-commitment; factor gata-1; c/ebp-alpha; mice lacking; regulatory networks; logical analysis; mouse embryos; fetal liver; factor eklf
    
 
    
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        Language
        english
    
 
    
        Publication Year
        2011
    
 
    
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        HGF-reported in Year
        2011
    
 
    
    
        ISSN (print) / ISBN
        1932-6203
    
 
    
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	    Volume: 6,  
	    Issue: 8,  
	    Pages: ,  
	    Article Number: e22649 
	    Supplement: ,  
	
    
 
    
        
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            Publisher
            Public Library of Science (PLoS)
        
 
        
            Publishing Place
            Lawrence, Kan.
        
 
	
        
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        Reviewing status
        Peer reviewed
    
 
     
    
        POF-Topic(s)
        30505 - New Technologies for Biomedical Discoveries
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
    
 
    
        Research field(s)
        Enabling and Novel Technologies
Stem Cell and Neuroscience
    
 
    
        PSP Element(s)
        G-503700-004
G-501200-001
    
 
    
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        Erfassungsdatum
        2011-11-07