Meta-Analysis of Transcriptome Regulation During Induction to Cardiac Myocyte Fate From Mouse and Human Fibroblasts
| Autor: | Shima, Rastegar-Pouyani, Niusha, Khazaei, Ping, Wee, Moein, Yaqubi, Abdulshakour, Mohammadnia |
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| Rok vydání: | 2016 |
| Předmět: |
Heart Diseases
Transcription Genetic Gene Expression Profiling Computational Biology Fibroblasts Cellular Reprogramming Mice Phenotype Gene Expression Regulation Cell Transdifferentiation Databases Genetic Animals Humans Cell Lineage Gene Regulatory Networks Myocytes Cardiac Protein Interaction Maps Transcriptome Oligonucleotide Array Sequence Analysis Signal Transduction Transcription Factors |
| Zdroj: | Journal of cellular physiology. 232(8) |
| ISSN: | 1097-4652 |
| Popis: | Ectopic expression of a defined set of transcription factors (TFs) can directly convert fibroblasts into a cardiac myocyte cell fate. Beside inefficiency in generating induced cardiomyocytes (iCMs), the molecular mechanisms that regulate this process remained to be well defined. The main purpose of this study was to provide better insight on the transcriptome regulation and to introduce a new strategy for candidating TFs for the transdifferentiation process. Eight mouse and three human high quality microarray data sets were analyzed to find differentially expressed genes (DEGs), which we integrated with TF-binding sites and protein-protein interactions to construct gene regulatory and protein-protein interaction networks. Topological and biological analyses of constructed gene networks revealed the main regulators and most affected biological processes. The DEGs could be categorized into two distinct groups, first, up-regulated genes that are mainly involved in cardiac-specific processes and second, down-regulated genes that are mainly involved in fibroblast-specific functions. Gata4, Mef2a, Tbx5, Tead4 TFs were identified as main regulators of cardiac-specific gene expression program; and Trp53, E2f1, Myc, Sfpi1, Lmo2, and Meis1 were identified as TFs which mainly regulate the expression of fibroblast-specific genes. Furthermore, we compared gene expression profiles and identified TFs between mouse and human to find the similarities and differences. In summary, our strategy of meta-analyzing the data of high-throughput techniques by computational approaches, besides revealing the mechanisms involved in the regulation of the gene expression program, also suggests a new approach for increasing the efficiency of the direct reprogramming of fibroblasts into iCMs. J. Cell. Physiol. 232: 2053-2062, 2017. © 2016 Wiley Periodicals, Inc. |
| Databáze: | OpenAIRE |
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