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Cardiogenetics
  • Cardiogenetics is published by MDPI from Volume 10 Issue 2 (2020). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with PAGEPress.
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  • Open Access

5 June 2012

Combined Use of In Silico and In Vitro Splicing Assays for Interpretation of Genomic Variants of Unknown Significance in Cardiomyopathies and Channelopathies

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1
Laboratoire de Cardiogénétique moléculaire, CBPE– Hospices Civils de Lyon, Bron
2
EA4612, Université Claude Bernard Lyon 1, Lyon
3
Laboratoire de Génétique Moléculaire, CHU, Hôtel-Dieu, Nantes
4
Centre de Biotechnologie Cellulaire, CBPE– Hospices Civils de Lyon, Bron

Abstract

The identification of molecular anomalies in patients with inherited arrhythmias or cardiomyopathies is a multi challenge due to: i) the number of genes involved; ii) the number of polymorphisms and the fact that most mutations are private; and iii) the variable degree of penetrance which complicates family segregation study. Consequently, a number of unclassified variants (UV) are found in patients’ DNA and some (outside the canonical GT/AG) may affect splicing. Mutational screening on the most prevalent genes involved in arrythmias syndromes or in cardiomyopathies was performed on a cohort made up of 740 unrelated French index probands. To identify splice variants among the identified UVs, a combination of available in silico and in vitro tools were used since transcript is not available. Using this approach, 10 previously identified UVs were reclassified as disease-causing mutations and, more precisely, as haploinsufficiency mutations rather than dominant-negative mutations. Most of them (7 of 10) were observed in MYBPC3. Our study highlighted the importance of the combined use of in silico and in vitro splicing assays to improve the prediction of the functional impact of identified genetic variants. The primary challenge now, with new sequencing technologies, is to distinguish between background polymorphisms and pathogenic mutations. Since splice site mutations can account for almost 50% of disease-causing mutations, recognizing them from among other variations is essential.

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