Myocardial infarction (MI) is a leading cause of death worldwide. Although some targets associated with MI are extensively studied, their dynamic characteristics of gene expressions during the disease progression haven’t been fully elucidated yet.

In this study, we aim to measure the dynamic regulation of gene expression during ischemia-reperfusion (IR) in mouse heart, infer gene regulatory networks and decipher the main hubs linking cellular processes.

8–12 weeks old C57BL/6 mice are anesthetized, undergone IR and sacrificed at different times (8 animals per time point) of the IR sequence. RNA-seq data from controls, ischemic and non-ischemic myocardium are analyzed, clustered and functionally characterized.

RNA-seq data normalized as fragments per kilobase per million analyzed by PCA implemented in R software, are not clustered based on their temporal profiles. We hypothesized that analyzing the data directly by PCA disqualified it as a method for temporal analysis of gene expression. We thus shifted to analyzing raw counts data by DESeq2. 975, 446 and 3878 genes are significantly induced by thoracotomy, anesthesia, remote and IR specific effect respectively. These genes are further analyzed by WGCNA analysis splitting them into modules. These modules are then studied separately by gene ontology (GO) so that molecular functions, biological processes and cellular components involved in MI progression are clarified.

This kinetical study not only provides comprehensive framework and transcriptional resource in the myocardium during MI, but also sheds new light on the importance of taking thoracotomy effect and the different analytical methods into account.