Endogenous Network Reveals the Landscape of Liver Lineage Differentiation

Abstract

Revealing the molecular regulation mechanism of cell fate decision is of great significance for understanding stem cell differentiation and tissue homeostasis. In this paper, a coarse-grained endogenous network for endodermal liver differentiation is constructed, which is composed of five transcription factors and their interaction was collected from the accumulated biological knowledge. The stable states and transition states with biological significance are obtained from the dynamics of the network, by which previously unobserved cell states during the differentiation of liver cells were predicted. In addition, the landscape of the liver cell differentiation is also predicted from the computing results. This landscape not only contains the classical endoderm liver cell differentiation roadmap; but also predicts more complex differentiation paths. This study shows that the construction of the dynamic model of the endogenous network is an effective tool for more in-depth research in the mechanism of liver cell differentiation and explain the genesis of liver diseases