Mohammadreza Omrani - National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran These authors contributed equally to this work
Moein Yaqubi - National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran These authors contributed equally to this work
Abdulshakour Mohammadnia - National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran These authors contributed equally to this work
Hossein Fallahi - Department of Biology, School of Science, Razi University, Kermanshah, Iran Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran

Reprogramming of fibroblast to induced pluripotent stem cells (iPSCs) using over expression of transcription factors (TFs) provide alternative source for stem cells in addition to embryonic stem cells (ESCs) in regenerative medicine. Most of the TFs involve in regulation of gene expression during conversion of fibroblast to iPSCs are unknown. We use microarray data to construct gene regulatory network and investigate roles of TFs during reprogramming.Method: Microarray expression data for reprogramming of fibroblast into iPSCs obtained from the GEO server by GSE32598accession number. Normalization and detection of differentially expressed (DE) genes and annotation of DE genes conducted in Felxarray. TFs binding sites and protein-protein interactions obtained from ChEA and BioGRID databases respectively. Cytoscape was used for network visualization and construction. Degree and closeness are centrality parameterswere used to dissecting regulatory network using CentiScaPe plugin in cytoscape.Result: Comparison of microarray data of mouse fibroblast and iPSCs shows 2,743 DE genes during reprogramming. Generegulatory network constructed from expression data, potentially TFs binding sites, and valid protein-protein interactions.ChIP enrichment analysis reveals 57 TFs as potentially regulators of 2,436 out of 2,743 DE genes. Search for valid proteinproteininteractions for these TFs show 309 interactions for 185 DE genes. Collectively, our best constructed gene regulatory network accommodates 2,458 nodes and 17,179 interactions. Based on degree and closeness parameters, NANOG, POU5F1, SUZ12, MYC, KLF4, SOX2, MTF2, ASH2L, TRIM28 and TET1 are most important TFs during reprogramming of mouse fibroblast into iPSCs. Conclusion: Constructing of gene regulatory network and investigating the roles of TFs sheds light on the reprogramming mechanism.

Fibroblast, Microarray, Regulatory network, Reprogramming, Transcription factor