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Transcription Factors in Regulatory and Protein Subnetworks during Generation of Neural Stem Cells and Neurons from Direct Reprogramming of Non-fibroblastic Cell Sources.

Authors :
Omrani MR
Yaqubi M
Mohammadnia A
Source :
Neuroscience [Neuroscience] 2018 Jun 01; Vol. 380, pp. 63-77. Date of Electronic Publication: 2018 Apr 11.
Publication Year :
2018

Abstract

Direct reprogramming of non-fibroblastic cells to the neuronal cell types including induced neurons (iNs) and induced neural stem cells (iNSCs) has provided an alternative approach for the direct reprogramming of fibroblasts to those cells. However, to increase the efficiency of the reprogramming process the underlying mechanisms should be clarified. In the current study, we analyzed the gene expression profiles of five different cellular conversions to understand the most significant molecular mechanisms and transcription factors (TFs) underlying each conversion. For each conversion, we found the list of differentially expressed genes (DEGs) and the list of differentially expressed TFs (DE-TFs) which regulate expression of DEGs. Moreover, we constructed gene regulatory networks based on the TF-binding sites' data and found the most central regulators and the most active part of the networks. Furthermore, protein complexes were identified from constructed protein-protein interaction networks for DE-TFs. Finally, we proposed a list of main regulators for each conversion; for example, in the direct conversion of epithelial-like cells (ECs) to iNSCs, combination of centrality with active modules or protein complex analyses highlighted the role of POU3F2, BACH1, AR, PBX1, SOX2 and NANOG genes in this conversion. To the best of our knowledge, this study is the first one that analyzed the direct conversion of non-fibroblastic cells toward iNs and iNSCs and we believe that the expression manipulation of identified genes may increase efficiency of these processes.<br /> (Copyright © 2018. Published by Elsevier Ltd.)

Details

Language :
English
ISSN :
1873-7544
Volume :
380
Database :
MEDLINE
Journal :
Neuroscience
Publication Type :
Academic Journal
Accession number :
29653196
Full Text :
https://doi.org/10.1016/j.neuroscience.2018.03.033