Investigating Alzheimer's Disease-Associated Genes Using Differential Splicing Frequency Analysis

Accurately quantifying the expression of individual isoforms remains a formidable challenge, especially in contexts like neurodegenerative diseases and cancers, which are noted for their high isoform diversity. The first contribution of the present study is the development of a new method, named differential splicing frequency analysis (DSFA), which enables more sensitive capture of the alternative splicing information in RNA-seq data. DSFA quantifies the expression levels of splicing junctions, rather than those of genes, isoforms or exons. Application of DSFA to the analysis of Alzheimer's disease (AD)-associated genes resulted in the identification of APP/58417N and APP/52804N as differentially expressed splicing junctions in human and mouse, respectively. Observed in a considerable portion of the re-analyzed RNA-seq datasets, the splicing frequencies of APP/58417N and APP/52804N were significantly decreased in AD groups. Such reductions in splicing frequencies lead to decreased production of secretory APP proteins, potentially playing a critical role in AD onset or progression. The present study has proposed over-expression of U1 snRNA as an effective method for modulating the splicing frequencies of splicing junctions, thereby rapidly establishing cellular or animal AD models. Therefore, the present study has provided new methods, preliminary results, and valuable insights, advancing the understanding of the functions of U1 snRNA and the roles of alternative splicing in its associated diseases.