biostudies-literatureBencun MDeutsche ForschungsgemeinschaftKlaus Tschira Foundation391https://www.ebi.ac.uk/biostudies/studies/S-EPMC8962266biostudies-literatureUnknown10(2)Cardiovascular disease is still the leading cause of morbidity and mortality worldwide. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a valuable widespread in vitro model to study cardiac disease. Herein, we employ the hiPSC-CM model to identify novel miRNA-mRNA interaction partners during cardiac differentiation and β-adrenergic stress. Whole transcriptome and small RNA sequencing data were combined to identify novel miRNA-mRNA interactions. Briefly, mRNA and miRNA expression profiles were integrated with miRNA target predictions to identify significant statistical dependencies between a miRNA and its candidate target set. We show by experimental validation that our approach discriminates true from false miRNA target predictions. Thereby, we identifiedBiomedicinesNew Tricks with Old Dogs: Computational Identification and Experimental Validation of New miRNA-mRNA Regulation in hiPSC-CMs.PMC896226600.219.20131501/8-2Dieterich CBritto-Borges TEschenbach JBencun MfalseNew Tricks with Old Dogs: Computational Identification and Experimental Validation of New miRNA-mRNA Regulation in hiPSC-CMs.Cardiovascular disease is still the leading cause of morbidity and mortality worldwide. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a valuable widespread in vitro model to study cardiac disease. Herein, we employ the hiPSC-CM model to identify novel miRNA-mRNA interaction partners during cardiac differentiation and β-adrenergic stress. Whole transcriptome and small RNA sequencing data were combined to identify novel miRNA-mRNA interactions. Briefly, mRNA and miRNA expression profiles were integrated with miRNA target predictions to identify significant statistical dependencies between a miRNA and its candidate target set. We show by experimental validation that our approach discriminates true from false miRNA target predictions. Thereby, we identified2022-01-01T00:00:00Z2022 Feb2026-04-08T17:52:25.027Z2025-04-04T23:15:30.323ZS-EPMC89622663520360010.3390/biomedicines10020391