Genome-wide analysis revealed the dysregulation of RNA binding protein-correlated alternative splicing events in myocardial ischemia reperfusion injury

Abstract

Background: Myocardial ischemia reperfusion injury (MIRI), the tissue damage which is caused by the returning of blood supply to tissue after a period of ischemia, greatly reduces the therapeutic effect of treatment of myocardial infarction. But the underlying functional mechanisms of MIRI are still unclear.

Methods: We constructed mouse models of MIRI, extracted injured and healthy myocardial tissues, and performed transcriptome sequencing experiments (RNA-seq) to systematically investigate the dysregulated transcriptome of MIRI, especially the alternative splicing (AS) regulation and RNA binding proteins (RBPs). Selected RBPs and MIRI-associated AS events were then validated by RT-qPCR experiments.

Results: The differentially expressed gene (DEG) analyses indicated that transcriptome profiles were changed by MIRI and that DEGs' enriched functions were consistent with MIRI's dysregulated pathways. Furthermore, the AS profile was synergistically regulated and showed clear differences between the mouse model and the healthy samples. The exon skipping events significantly increased in MIRI model samples, while the opposite cassette exon events significantly decreased. According to the functional analysis, regulated alternative splicing genes (RASGs) were enriched in protein transport, cell division /cell cycle, RNA splicing, and endocytosis pathways, which were associated with the development of MIRI. Meanwhile, 493 differentially expressed RBPs (DE RBPs) were detected, most of which were correlated with the changed ratios of AS events. In addition, nine DE RBP genes were validated, including Eif5, Pdia6, Tagln2, Vasp, Zfp36l2, Grsf1, Idh2, Ndrg2, and Uqcrc1. These nine DE RBPs were correlated with RASGs enriched in translation process, cell growth and division, and endocytosis pathways, highly consistent with the functions of all RASGs. Finally, we validated the AS ratio changes of five regulated alternative splicing events (RASEs) derived from important regulatory genes, including Mtmr3, Cdc42, Cd47, Fbln2, Vegfa, and Fhl2.

Conclusion: Our study emphasized the critical roles of the dysregulated AS profiles in MIRI development, investigated the potential functions of MIRI-associated RASGs, and identified regulatory RBPs involved in AS regulation. We propose that the identified RASEs and RBPs could serve as important regulators and potential therapeutic targets in MIRI treatment in the future.

Keywords: Alternative splicing; Correlation network; MIRI; RNA binding protein; RNA-seq.

Fig. 1

The AS analysis of cardiac tissues in MIRI. (A) PCA based on ratio values of all RASEs’ different expression levels. (B) Bar plot showing the RASEs. (C) Hierarchical clustering heatmap of the RASEs based on ratio values. (D) Scatter plot shows the top ten GO BP results of the RASGs. (E) Scatter plot shows the top ten KEGG pathways of the RASGs. (F) Bar plot shows the statistical differences and expression patterns of some important genes’ RASEs from RT-qPCR and RNA-seq validation. The Y-axis represent the AS ratio between model event and alternative event. Mean ± SEM is represented by error bars. Student’s t-test; *** P-value < 0.001, ** P-value < 0.01, * P-value < 0.05

Fig. 2

Analysis of the differential expression of RBPs in MIRI. (A) The overlapped genes between DEGs and RBPs are shown in venn diagram. (B) The expression levels of the DE RBPs are shown in hierarchical clustering heatmap. (C) The scatter plot shows the top ten GO BP results of the DE RBPs. (D) The scatter plot shows the top ten KEGG pathways of the DE RBPs. (E) Bar plot shows the statistical differences and expression patterns of the DEGs of some critical RBPs. Mean ± SEM is represented by error bars. Student’s t-test; *** P-value < 0.001; **** P-value < 0.0001

Fig. 3

Correlation network between DE RBPs and RASGs associated with MIRI. (A) The network plot showing the RASG co-expressing with the ten RBPs. The enriched GO pathways for RASGs were shown in the right panel. (B) Scatter plot shows the top ten GO BP results of the co-expressed RASGs. (C) Scatter plot shows the top ten KEGG pathways of the co-expressed RASEs. (D) Bar plot shows the statistical differences and expression patterns of some important genes’ RASEs from RT-qPCR and RNA-seq validation. Mean ± SEM is represented by error bars. Student’s t-test; *** P-value < 0.001, ** P-value < 0.01, * P-value < 0.05