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

Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.
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髓系祖细胞的分层分化由转录因子网络编码。

DOI:
10.1371/journal.pone.0022649
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发表时间:
2011
期刊:
影响因子:
3.7
通讯作者:
Theis FJ
Theis FJ
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Krumsiek J;Marr C;Schroeder T;Theis FJ

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造血是干细胞生物学的理想模型系统,具有先进的实验通道。关于核心转录因子相互作用的系统观点对于理解分化机制和动力学非常重要。在这份手稿中,我们构建了一个布尔网络来模拟骨髓分化,特别是从常见的骨髓祖细胞到巨核细胞、红细胞、粒细胞和单核细胞。通过解释造血文献并将实验证据转化为布尔规则,我们在所得的 11 因子调控网络上实现了二元动力学。我们的网络包含有趣的功能模块和相互对立的对的串联。我们模型的状态空间是一个分层的非循环图,代表了骨髓分化的原理。我们观察到我们的模型的稳态与两项不同研究的微阵列表达谱之间非常一致。此外,网络拓扑的扰动可以在计算机中正确再现报告的敲除表型。我们预测以前未表征的调节相互作用和分化过程的改变,并列出重编程策略。
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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