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Biology subjects

Minana, B.

Publications and source records attributed to Minana, B..

3 recordsLinked to original sources

A splice-switching antisense oligonucleotide approach for pediatric genetic epilepsies

Summary ParagraphVariants in ion channel genes are common causes of pediatric epilepsy, often leading to intractable seizures, developmental delay and other comorbidities, which increases risk of death. Pathogenic variants in the SCN8A gene, which encodes a voltage-gated sodium channel critical for action potential generation in the brain, account for [~]1% of genetic epilepsies. The voltage sensor in SCN8A domain 1 is encoded by one of two developmentally-regulated mutually exclusive alternative exons, 5N and 5A. We observe that variants in these exons are more likely to cause infantile spasms, a severe seizure type, than variants elsewhere in SCN8A, and that some pathogenic variants affect exon 5 splicing, impacting patient phenotype. Molecular and evolutionary analyses implicate the exon sequences of these and other voltage-gated ion channel alternative exons in splicing regulation. We identified antisense oligonucleotides (ASOs) that shift splicing of SCN8A exon 5N to 5A or vice versa. These ASOs normalize neuronal activity in patient-derived iPSC neurons, and reduce seizures and motor impairment and extend lifespan in a new exon 5N mutant mouse model. Our results demonstrate that splice-switching ASOs can effectively reduce the expression of pathogenic isoforms and rescue both seizure and non-seizure phenotypes. Similar approaches should be applicable to pediatric genetic epilepsies caused by mutations in other ion channel alternative exons.

neuroscience↗

Deep indel mutagenesis reveals the regulatory and modulatory architecture of alternative exon splicing

Altered splicing is a frequent mechanism by which genetic variants cause disease and antisense oligonucleotides (AONs) that target pre-mRNA splicing have been approved as therapeutics for multiple pathologies including patient-customized treatments for rare diseases. However, the regulatory architecture of human exons remains poorly understood and AON discovery is currently slow and expensive, limiting the wider adoption of the approach. Here we show that that systematic deletion scans -which can be made experimentally at very low cost - provide an efficient strategy to chart the regulatory landscape of human exons and to rapidly identify effective splicing-modulating oligonucleotides in a fully quantitative manner. Our results suggest a mechanism for the evolutionary origins of unusually short microexons and the repression of transmembrane domain-encoding exons, and reveal a checkerboard architecture of sequential enhancers and silencers in a model alternative exon. Accurate prediction of the effects of deletions using deep learning provides a resource, DANGO, that maps the splicing regulatory landscape of all human exons and predicts effective splicing-altering antisense oligonucleotides genome-wide.

genetics↗

Mutations primarily alter the inclusion of alternatively spliced exons

Genetic analyses and systematic mutagenesis have revealed that synonymous, non-synonymous and intronic mutations frequently alter the inclusion levels of alternatively spliced exons, consistent with the concept that altered splicing might be a common mechanism by which mutations cause disease. However, most exons expressed in any cell are highly-included in mature mRNAs. Here, by performing deep mutagenesis of highly-included exons and by analysing the association between genome sequence variation and exon inclusion across the transcriptome, we report that mutations only very rarely alter the inclusion of highly-included exons. This is true for both exonic and intronic mutations as well as for perturbations in trans. Therefore, mutations that affect splicing are not evenly distributed across primary transcripts but are focussed in and around alternatively spliced exons with intermediate inclusion levels. These results provide a resource for prioritising synonymous and other variants as disease-causing mutations.

genomics↗