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Identification of intronic sequences promoting natural skipping of ABCA4 exon 15 using long-read transcriptomics and midigene assays

Stargardt disease is an inherited retinal disease that leads to progressive loss of vision, and is caused by biallelic variants in the ABCA4 gene. A significant proportion of ABCA4 variants of variable penetrance affect pre-mRNA splicing. Previously, we observed the exclusion of certain ABCA4 exons into the final transcript in the absence of any disease-causing variants. In this study, we explored this phenomenon that we coined natural exon skipping (NES) for the entire ABCA4 transcript, using targeted RT-PCR analysis as well as long-read transcriptome sequencing of control retina samples. For the most abundant NES event, which is skipping of ABCA4 exon 15, overlapping ABCA4 deletion constructs were employed to identify responsible cis-regulatory sequence motifs. Subsequently, antisense oligonucleotides (AONs) were designed and tested to reverse NES and restore fully-spliced ABCA4 mRNA. We identified intronic regions on each side of exon 15 that, when deleted, increased the inclusion of exon 15 in the final transcripts. Interestingly, these motifs appear to work in a synergistic manner. Further fine-mapping of these regions revealed several cis-regulatory motifs that may be responsible for inducing NES, on each side of the exon. AONs targeting these motifs unfortunately did not decrease the skipping of exon 15. In conclusion, we discovered an intriguing phenomenon that, in the absence of disease-causing variants, results in the skipping of one or more exons in the ABCA4 transcript. These NES events appear to be regulated by cis-regulatory motifs within the flanking introns. This work captured the extend of NES throughout ABCA4 transcript and the role of cis-regulatory motifs in pre-mRNA splicing.. The use of AONs targeting cis-regulatory motifs is an innovative strategy for splicing modulation, suitable for complementing future variant-specific splicing modulation therapies in ABCA4 retinopathies.

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Dataset ID Description Technology Samples
EGAD50000000100 Sequel IIe 2
EGAD50000000101 Sequel II 4