Genome-wide Identification and Analysis of Splicing QTLs in Multiple Sclerosis by RNA-Seq Data

Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions in the central nervous system. Recently, the dysregulation of alternative splicing (AS) in brain has been found to significantly influence the progression of MS. Moreover, previous studies demonstrated that many MS-related variants in genome act as the important regulation factors of AS events and contribute to the pathogenesis of MS. However, by far, no genome-wide research about the effect of genomic variants on AS events in MS has been reported. Here, we first implemented a strategy to obtain genomic variant genotype and AS isoform average percent spliced-in (PSI) values from RNA-seq data of 142 individuals (51 MS patients and 91 controls). Then, combing the two sets of data, we performed a cis-splicing quantitative trait loci (sQTLs) analysis to identify the cis-acting loci and the affected differential AS events in MS, and further explored the characteristics of these cis-sQTLs. Finally, the weighted gene coexpression network and gene set enrichment analyses were used to investigate gene interaction pattern and functions of the affected AS events in MS. In total, we identified 5,835 variants affecting 672 differential AS events. The cis-sQTLs tend to be distributed in proximity of gene transcription initiation site, and the intronic variants of them are more capable of regulating AS events. The retained intron AS events are more susceptible to influence of genome variants, and their functions are involved in protein kinase and phosphorylation modification. In summary, these findings provide an insight into the mechanism of MS.