Congenital heart disease (CHD) is the most serious congenital defect in newborns with higher mortality. Alternative splicing (AS) plays an essential role in numerous heart diseases. However, our understanding of the link between mRNA splicing and CHD in humans is limited. Here, we try to investigate the genome-wide AS events in CHD using bioinformatics methods. We collected available RNA-seq datasets of CHD-induced pluripotent stem cell-cardiomyocytes (iPSC-CMs) (including single ventricle disease [SVD] and tetralogy of Fallot [TOF]) and non-CHD from the Gene Expression Omnibus database. Then, we unprecedentedly performed AS profiles in CHD-iPSC-CMs and non-CHD-iPSC-CMs. The rMAPS was used to generate RNA-maps for the analysis of RNA-binding proteins’ (RBPs) binding sites. We used StringTie to identify and quantify the transcripts from aligned RNA-Seq reads. A quantification matrix was generated with respect to different groups by extracting the transcripts per million values from StringTie outputs. Then, this matrix was used for correlation analysis between the expression level of RBP and AS level. Finally, we validated our AS results using RNA-seq data from CHD and non-CHD patient tissue samples. We identified CHD-related AS events using CHD-iPSC-CMs and CHD samples from patients. The results showed that functional enrichment of abnormal AS in SVD and TOF was transcription factor-related. Using rMAPS, RNA-binding proteins which regulated these AS were also determined, and RBP-AS regulatory network was constructed. Overall, we identified abnormal AS in CHD-iPSC-CMs and CHD samples from patients. We predicted AS regulators in SVD and TOF, respectively. At last, we concluded that AS played a key role in the pathogenesis of CHD.
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