Deciphering the impact of coding and non-coding SCN1A gene variants on RNA splicing

Variants that disrupt normal pre-mRNA splicing are increasingly being recognized as a major cause of monogenic disorders. The SCN1A gene, a key epilepsy gene that is linked to various epilepsy phenotypes, is no exception. Approximately 10% of all reported variants in the SCN1A gene are designated as splicing variants, with many located outside of the canonical donor and acceptor splice sites, and most have not been functionally investigated. However, given its restricted expression pattern, functional analysis of splicing variants in the SCN1A gene could not be routinely performed. In this study, we conducted a comprehensive analysis of all reported SCN1A variants and their potential to impact SCN1A splicing and conclude that splicing variants are substantially misannotated and under-represented. We created a splicing reporter system consisting of 18 splicing vectors covering all 26 protein-coding exons with different genomic contexts and several promoters of varying strengths in order to reproduce the wild-type splicing pattern of the SCN1A gene, revealing cis-regulatory elements essential for proper recognition of SCN1A exons. Functional analysis of 95 SCN1A variants was carried out, including all 68 intronic variants reported in the literature, located outside of the splice sites canonical dinucleotides; 21 exonic variants of different classes (synonymous, missense, nonsense and in-frame deletion) and six variants observed in patients with epilepsy. Interestingly, almost 20% of tested intronic variants had no influence on SCN1A splicing, despite being reported as causative in the literature. Moreover, we confirmed that the majority of predicted exonic variants affect splicing unravelling their true molecular mechanism. We used functional data to perform genotype-phenotype correlation, revealing distinct distribution patterns for missense and splice-affecting 'missense' variants and observed no difference in the phenotype severity of variants leading to in-frame and out-of-frame isoforms, indicating that the Nav1.1 protein is highly intolerant to structural variations. Our work demonstrates the importance of functional analysis in proper variant annotation and provides a tool for high-throughput delineation of splice-affecting variants in SCN1A in a whole-gene manner.