A novel system-level approach using RNA-sequencing data identifies miR-30-5p and miR-142a-5p as key regulators of apoptosis in myocardial infarction

Abstract This study identified microRNAs involved in myocardial infarction (MI) through a novel system-level approach using RNA sequencing data in an MI mouse model. This approach involved the extraction of DEGs and DEmiRs from RNA-seq data in sham and MI samples and the subsequent selection of two...

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Autores principales: Jin Ock Kim, Jei Hyoung Park, Taeyong Kim, Seong Eui Hong, Ji Young Lee, Kyoung Jin Nho, Chunghee Cho, Yong Sook Kim, Wan Seok Kang, Youngkeun Ahn, Do Han Kim
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/87f602c9a40c4a7f8e59fe82557b8e0d
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Sumario:Abstract This study identified microRNAs involved in myocardial infarction (MI) through a novel system-level approach using RNA sequencing data in an MI mouse model. This approach involved the extraction of DEGs and DEmiRs from RNA-seq data in sham and MI samples and the subsequent selection of two miRNAs: miR-30-5p (family) and miR-142a-5p, which were downregulated and upregulated in MI, respectively. Gene Set Enrichment Analysis (GSEA) using the predicted targets of the two miRNAs suggested that apoptosis is an essential gene ontology (GO)-associated term. In vitro functional assays using neonatal rat ventricular myocytes (NRVMs) demonstrated that miR-30-5p is anti-apoptotic and miR-142a-5p is pro-apoptotic. Luciferase assays showed that the apoptotic genes, Picalm and Skil, and the anti-apoptotic genes, Ghr and Kitl, are direct targets of miR-30-5p and miR-142a-5p, respectively. siRNA studies verified the results of the luciferase assays for target validation. The results of the system-level high throughput approach identified a pair of functionally antagonistic miRNAs and their targets in MI. This study provides an in-depth analysis of the role of miRNAs in the pathogenesis of MI which could lead to the development of therapeutic tools. The system-level approach could be used to identify miRNAs involved in variety of other diseases.