Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing

Abstract

Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature <i>MAPT</i> mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the B^act complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced <i>MAPT</i> gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of <i>MAPT</i>. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants.