Searching for cardioprotective microRNA families by bioinformatics analysis of cross-species transcriptomic datasets

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Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This study was supported by the National Research, Development and Innovation Office of Hungary (NKFIA; NVKP-16-1-2016-0017 National Heart Program) and the Thematic Excellence Programme (2020-4.1.1.-TKP2020) of the Ministry for Innovation and Technology in Hungary, within the framework of the Therapeutic Development and Molecular Biology thematic programmes of the Semmelweis University. Introduction There is a growing body of evidence that changes in cardiac microRNA expression pattern plays an important role in cardioprotective cellular signaling. Purpose Our aim was to identify evolutionarily conserved cardioprotective microRNA (protectomiR) families with a high probability of translation into human clinical practice. Methods Global cardiac microRNA expression profiles were measured in both a rat and a porcine model of myocardial infarction with or without ischemic preconditioning and postconditioning by microarray and high-throughput polymerase chain reaction, respectively. A software developed by our team was used to identify cross-species microRNA families (i.e. microRNAs with identic seed sequence) with cardioprotective expression patterns. By selecting experimentally validated human target genes from the miRTarBase database we built a microRNA family-target interaction network by the miRNAtarget.com software. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the selected target genes. Results Due to potential patenting, microRNAs and microRNA families were anonymized. We identified 7 microRNA families, showing cardioprotective expression pattern. Based on the analysis of the microRNA family-target network, expression change of the target hubs were predicted to be consistent with previously described changes in pathways with high relevance in cardioprotection (e.g. positive regulation of TGF-beta, HIF-1, PI3K-Akt signaling pathways). Conclusion By an unbiased transcriptomics and bioinformatics based approach we successfully identified microRNA families with robust cross-species protectomiR expression pattern and targets involved in well-established cardioprotective pathways. These cardioprotective microRNA families are of high translational value for human clinical application.

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