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

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...

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Autores principales:	Jan Krumsiek, Carsten Marr, Timm Schroeder, Fabian J Theis
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/944146055e3b4ec4b2fd7bdd7efb2555
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spelling	oai:doaj.org-article:944146055e3b4ec4b2fd7bdd7efb25552021-11-18T06:48:22ZHierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.1932-620310.1371/journal.pone.0022649https://doaj.org/article/944146055e3b4ec4b2fd7bdd7efb25552011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21853041/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Hematopoiesis 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.Jan KrumsiekCarsten MarrTimm SchroederFabian J TheisPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 8, p e22649 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jan Krumsiek Carsten Marr Timm Schroeder Fabian J Theis Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
description	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.
format	article
author	Jan Krumsiek Carsten Marr Timm Schroeder Fabian J Theis
author_facet	Jan Krumsiek Carsten Marr Timm Schroeder Fabian J Theis
author_sort	Jan Krumsiek
title	Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
title_short	Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
title_full	Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
title_fullStr	Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
title_full_unstemmed	Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
title_sort	hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/944146055e3b4ec4b2fd7bdd7efb2555
work_keys_str_mv	AT jankrumsiek hierarchicaldifferentiationofmyeloidprogenitorsisencodedinthetranscriptionfactornetwork AT carstenmarr hierarchicaldifferentiationofmyeloidprogenitorsisencodedinthetranscriptionfactornetwork AT timmschroeder hierarchicaldifferentiationofmyeloidprogenitorsisencodedinthetranscriptionfactornetwork AT fabianjtheis hierarchicaldifferentiationofmyeloidprogenitorsisencodedinthetranscriptionfactornetwork
_version_	1718424366476165120

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

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