Hypertrophic cardiomyopathies (HCM) are inherited cardiac diseases with an autosomal dominant transmission, among which MYBPC3 is the main causal gene responsible for haplo-insufficiency. RNA splicing variants in MYBPC3 appears to be a prevalent cause of HCM, however RNA analysis is not developed for these diseases because of cardiac tissue unavailability. Thus, these variants are often classified as Variant of Unknown Significance (VUS) and can’t be use for clinical purposes.

We aim to propose an optimized enrichment method to detect splicing aberrations in MYBPC3 cDNA causing cardiomyopathies from blood cells mRNA.

We selected 26 variants (16 intronics and 10 exonics) detected on DNA sequencing and predicted to affect splicing (SpliceAI, SPiP). polyA+RNA purified from venous blood cells (PAXGene®) of variant carriers was retro-transcribed, captured with optimized design (KAPA HyperCap®) and sequenced on NextSeq550. A specific bio-informatic pipeline was developed to automatically detect splicing events.

The gene MYBPC3 was very well covered and interpretable (RPM∼6809, mean depth∼2947X). We detect a splice aberration for 19/26 (73%) of cases, consistent with their respective predictive score, among which 6 (32%) creates a novel junction; 8 (42%) modifies the proportional usage of annotated junctions and 5 (26%) leads to the retention of the entire intron. Then, we perform bio-informatic screening that was able to detect all pathogenic events, including intron retention even when no abnormal junction is associated.

Targeted mRNA sequencing from blood cells allows functional identification of splice variants with the perspective to helps for splice variant classification, thus improving the yield of molecular diagnostic in cardiomyopathy patients. This method could also be used for screening, even as first approach, thanks to a specific bio-informatic pipeline and be expanded to other cardiomyopathy genes.