Time-Course Analysis of Direct Reprogramming of Cardiac Cells from Fibroblast

Background: Mammalian heart has limited reprogrammingpotential to repair after embryonic development. Also, adultcardiomyocytes fail to recover during injury and disease.Hence, reprogramming of cardiac cell from different kind ofstem and non-stem cells has a great potential for basic studies,pharmaceutical testes and therapeutic application and canbe carry out as innovative strategies for replacing cardiac cells.Different strategies based on induction with transcription factor,microRNA or chemical cocktails have been developed thatwere induced in different time-point during early stage of reprogramming,from a few days to some weeks. Albeit, regulatoryelements like transcription factor and their involvement pathwaysare not well define. In this study, we have used transcriptomedatasets from three, seven and eighteen days during directconversion of mouse fibroblast into cardiomyocyte to identifythe key transcription factors and correlated signaling pathways.Materials and Methods: In this study, differentially expressedgenes with fold change equal or above ۲ were isolated fromtotal gene expression, using R language program. Then, differentiallyexpressed transcription factors extracted by Enrichronline tools and in-house scripts. Also, Network analysis doneusing Cytoscape plugins to finding hub transcription factors. Finally,signaling pathways were obtained from KEGG and GO.Results: Network Analysis have showed the most importantdifferentially expressed transcription factors in three, seven andeighteen days during early stage of maturation of induced cardiomyocyte.Besides, we have introduced key signaling pathwaysduring this conversion, based on their time point of reprogramming.Conclusion: Our finding could be helpful to achieve regulatoryelements involved in maturation pathway due to their time ofinduction. Also, would be useful in generating of more efficientinduced cardiomyocytes for therapeutic applications.

کلیدواژه ها:

Direct Conversion ، Network Analysis ، Regulatory Factors ، Signaling Pathway ، Transcriptome