Splice Junction Analysis

Introduction of Splice Junction Analysis

In higher eukaryotes, the precursor mRNA (pre-mRNA) of some genes produces different mRNA splicing isoforms through different splicing methods ( selecting different splicing sites), and this process is called alternative splicing. Alternative splicing allows a gene to produce multiple different transcripts. These transcripts have their own specific expression and function in different tissues at different stages of cell or individual differentiation and development. This greatly enriches the types and quantities of coding RNA and non-coding RNA, thereby increasing the complexity of the transcriptome and proteome. Most genes with protein-coding capabilities can be regulated by alternative splicing, resulting in a variety of protein subtypes with different functions. Abnormal alternative splicing is also widely involved in a variety of diseases, such as cancer. Therefore, exploring alternative splicing events is crucial for further understanding the functions of different transcripts in organisms.

Studies have shown that 35% of human genetic diseases may be caused by alternative splicing of RNA, such as retinitis pigmentosa and spinal muscular atrophy. With the development of artificial intelligence, methods such as deep learning combined with Bayesian hypothesis testing have been used in RNA alternative splicing analysis, which effectively improves the accuracy of RNA-seq quantitative differential splicing. Accurately identifying and analyzing the splice site through splice junctions analysis is of great significance for the treatment of related diseases and drug development.

• DARTS Analysis
• SpliceAI Based Analysis