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

PLoS ONE 6:e22649 (2011)
Publishers Version DOI PMC
Open Access Gold
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as soon as is submitted to ZB.
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
Keywords hematopoietic stem-cells; lineage-commitment; factor gata-1; c/ebp-alpha; mice lacking; regulatory networks; logical analysis; mouse embryos; fetal liver; factor eklf
Reviewing status