SpliceVault predicts the precise nature of variant-associated mis-splicing

• Published in: Nature genetics Vol. 55; no. 2; pp. 324 - 332
• Main Authors: Dawes, Ruebena, Bournazos, Adam M., Bryen, Samantha J., Bommireddipalli, Shobhana, Marchant, Rhett G., Joshi, Himanshu, Cooper, Sandra T.
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.02.2023; Nature Publishing Group
• Subjects: 45/91; 631/208/2489/1512; 692/308/2056; Agriculture; Alternative Splicing - genetics; Analysis; Animal Genetics and Genomics; Annotations; Base Sequence; Biomedical and Life Sciences; Biomedicine; Cancer Research; Empirical analysis; Gene Function; Gene sequencing; Genomes; Human Genetics; mRNA; Pathogenicity; Pathogens; Retention; RNA Splice Sites - genetics; RNA Splicing - genetics; Sensitivity analysis; Splicing
• ISSN: 1061-4036; 1546-1718; 1546-1718
• DOI: 10.1038/s41588-022-01293-8

Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification. Re-analysis of published RNA-sequencing samples finds that unannotated splicing events predict, with high sensitivity, the activation of exon skipping and cryptic splicing by splice-site variants.