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SEPT–GD: A decision tree to prioritise potential RNA splice variants in cardiomyopathy genes for functional splicing assays in diagnostics

•Compared to similar individually tested algorithms, SEPT–GD shows higher sensitivity (91%) and comparable specificity (88%) for both consensus and non-consensus variants.•SGCD c.4-1G > A and CSRP3 c.282-5_285del variants were reclassified as likely pathogenic.•In the minigene assay, all 12 varia...

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Published in:Gene 2023-01, Vol.851, p.146984-146984, Article 146984
Main Authors: Alimohamed, Mohamed Z., Boven, Ludolf G., van Dijk, Krista K., Vos, Yvonne J., Hoedemaekers, Yvonne M., van der Zwaag, Paul A., Sijmons, Rolf H., Jongbloed, Jan D.H., Sikkema-Raddatz, Birgit, Westers, Helga
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Language:English
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Summary:•Compared to similar individually tested algorithms, SEPT–GD shows higher sensitivity (91%) and comparable specificity (88%) for both consensus and non-consensus variants.•SGCD c.4-1G > A and CSRP3 c.282-5_285del variants were reclassified as likely pathogenic.•In the minigene assay, all 12 variants showed results concordant with SEPT-GD predictions.•SEPT–GD outperforms the tools commonly used for RNA splicing prediction and improves prioritisation of variants in cardiomyopathy genes for functional splicing analysis in a diagnostic setting. Splice prediction algorithms currently used in routine DNA diagnostics have limited sensitivity and specificity, therefore many potential splice variants are classified as variants of uncertain significance (VUSs). However, functional assessment of VUSs to test splicing is labour-intensive and time-consuming. We developed a decision tree to prioritise potential splice variants for functional studies and functionally verified the outcome of the decision tree. We built the decision tree, SEPT–GD, by setting thresholds for the splice prediction programs implemented in Alamut. A set of 343 variants with known effects on splicing was used as control for sensitivity and specificity. We tested SEPT–GD using variants from a Dutch cardiomyopathy cohort of 2002 patients that were previously classified as VUS and predicted to have a splice effect according to diagnostic rules. We then selected 12 VUSs ranked by SEPT–GD to functionally verify the predicted effect on splicing using a minigene assay: 10 variants predicted to have a strong effect and 2 with a weak effect. RT-PCR was performed for nine variants. Variant classification was re-evaluated based on the functional test outcome. Compared to similar individually tested algorithms, SEPT–GD shows higher sensitivity (91 %) and comparable specificity (88 %) for both consensus (dinucleotides at the start and end of the intron, GT at the 5′ end and AG at the 3′ end) and non-consensus splice-site variants (excluding middle of exon variants). Using clinical diagnostic criteria, 1295 unique variants in our cardiomyopathy cohort had originally been classified as VUSs, with 57 predicted by Alamut to have an effect on splicing. Using SEPT–GD, we prioritised 31 variants in 40 patients. In the minigene assay, all 12 variants showed results concordant with SEPT-GD predictions. RT-PCR confirmed the minigene results for two variants, TMEM43 c.1000 + 5G > T and TTN c.25922–6 T > G. Based on all
ISSN:0378-1119
1879-0038
DOI:10.1016/j.gene.2022.146984