Open AccessSynergistic Transcriptional and Post-Transcriptional Regulation of ESC Characteristics by Core Pluripotency Transcription Factors in Protein-Protein Interaction Networks
Author(s) -
Leijie Li,
Liangcai Zhang,
Guiyou Liu,
Rennan Feng,
Yongshuai Jiang,
Lei Yang,
Shihua Zhang,
Mingzhi Liao,
Jinlian Hua
Publication year - 2014
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0105180
Subject(s) - transcription factor , transcription (linguistics) , transcriptional regulation , microbiology and biotechnology , regulation of gene expression , protein–protein interaction , biology , computational biology , chemistry , genetics , gene , linguistics , philosophy
The molecular mechanism that maintains the pluripotency of embryonic stem cells (ESCs) is not well understood but may be reflected in complex biological networks. However, there have been few studies on the effects of transcriptional and post-transcriptional regulation during the development of ESCs from the perspective of computational systems biology. In this study, we analyzed the topological properties of the “core” pluripotency transcription factors (TFs) OCT4, SOX2 and NANOG in protein-protein interaction networks (PPINs). Further, we identified synergistic interactions between these TFs and microRNAs (miRNAs) in PPINs during ESC development. Results show that there were significant differences in centrality characters between TF-targets and non-TF-targets in PPINs. We also found that there was consistent regulation of multiple “core” pluripotency TFs. Based on the analysis of shortest path length, we found that the module properties were not only within the targets regulated by common or multiple “core” pluripotency TFs but also between the groups of targets regulated by different TFs. Finally, we identified synergistic regulation of these TFs and miRNAs. In summary, the synergistic effects of “core” pluripotency TFs and miRNAs were analyzed using computational methods in both human and mouse PPINs.