Abstract
Missense variants in ABCA4 constitute ~50% of causal variants in Stargardt disease (STGD1). Their pathogenicity is attributed to their direct effect on protein function, whilst their potential impact on pre-mRNA splicing disruption remains poorly understood. Interestingly, synonymous ABCA4 variants have previously been classified as 'severe' variants based on in silico analyses. Here, we systemically investigated the role of synonymous and missense variants in ABCA4 splicing by combining computational predictions and experimental assays. To identify variants of interest, we used SpliceAI to ascribe defective splice predictions on a dataset of 5579 biallelic STGD1 probands. We selected those variants with predicted delta scores for acceptor/donor gain > 0.20, and no previous reports on their effect on splicing. Fifteen ABCA4 variants were selected, 4 of which were predicted to create a new splice acceptor site and 11 to create a new splice donor site. In addition, three variants of interest with delta scores < 0.20 were included. The variants were introduced in wild-type midigenes that contained 4-12 kb of ABCA4 genomic sequence, which were subsequently expressed in HEK293T cells. By using RT-PCR and Sanger sequencing, we identified splice aberrations for 16 of 18 analyzed variants. SpliceAI correctly predicted the outcomes for 15 out of 18 variants, illustrating its reliability in predicting the impact of coding ABCA4 variants on splicing. Our findings highlight a causal role for coding ABCA4 variants in splicing aberrations, improving the severity assessment of missense and synonymous ABCA4 variants, and guiding to new treatment strategies for STGD1.