Aims
This study aimed to address inconsistencies in
Conclusions
This study reveals both shared and distinct transcriptomic responses in the MI and H9C2 models, highlighting the importance of model selection for studying myocardial ischaemia and hypoxia.
Methods
RNA sequencing was used to analyse DEGs in MI rat tissues and H9C2 cells exposed to hypoxia for 24 h. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to identify key biological processes and pathways. Weighted correlation network analysis [weighted gene co-expression network analysis (WGCNA)] was used to construct gene co-expression networks, and hub genes were compared with published MI datasets [Gene Expression Omnibus (GEO)] for target identification.
Results
GO analysis revealed enrichment of immune inflammation and mitochondrial respiration processes among 5139 DEGs in MI tissues and 2531 in H9C2 cells. KEGG analysis identified 537 overlapping genes associated with metabolism and oxidative stress pathways. Cross-analyses using the published GSE35088 and GSE47495 datasets identified 40 and 16 overlapping genes, respectively, with nine genes overlapping across all datasets and our models. WGCNA identified a key module in the MI model enriched for mRNA processing and protein binding. GO analysis revealed enrichment of mRNA processing, protein binding and mitochondrial respiratory chain complex I assembly in MI and H9C2 MH models. Five relevant hub genes were identified via a cross-analysis between the 92 hub genes that showed a common expression trend in both models. Conclusions: This study reveals both shared and distinct transcriptomic responses in the MI and H9C2 models, highlighting the importance of model selection for studying myocardial ischaemia and hypoxia.