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Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort

Raphael Leman 1, 2 Pascaline Gaildrat 2 Gerald L. Gac 3 Chandran Ka 3 Yann Fichou 3 Marie-Pierre Audrezet 3 Virginie Caux-Moncoutier 4, 5, 6 Sandrine M. Caputo 7 Nadia Boutry-Kryza 8 Melanie Leone 8 Sylvie Mazoyer 9 Francoise Bonnet-Dorion 10 Nicolas Sevenet 11 Marine Guillaud-Bataille 12 Etienne Rouleau 7 Brigitte Bressac-de Paillerets 13 Barbara Wappenschmidt 14 Maria Rossing 15 Danielle Muller 16 Violaine Bourdon 17 Francoise Revillon 18 Michael T. Parsons 19 Antoine Rousselin 20 Gregoire Davy 21 Gaia Castelain 2 Laurent Castera 1, 2 Joanna Sokolowska 22, 23 Florence Coulet 24 Capucine Delnatte 25 Claude Ferec 3, 26, 27 Amanda B. Spurdle 19 Alexandra Martins 2 Sophie Krieger 1, 2 Claude Houdayer 7, 5
13 Génétique (Biologie pathologie)
Département de biologie et pathologie médicales [Gustave Roussy]
Abstract : Variant interpretation is the key issue in molecular diagnosis. Spliceogenic variants exemplify this issue as each nucleotide variant can be deleterious via disruption or creation of splice site consensus sequences. Consequently, reliable in silico prediction of variant spliceogenicity would be a major improvement. Thanks to an international effort, a set of 395 variants studied at the mRNA level and occurring in 5' and 3' consensus regions (defined as the 11 and 14 bases surrounding the exon/intron junction, respectively) was collected for 11 different genes, including BRCA1, BRCA2, CFTR and RHD, and used to train and validate a new prediction protocol named Splicing Prediction in Consensus Elements (SPiCE). SPiCE combines in silico predictions fromSpliceSiteFinder-like and MaxEntScan and uses logistic regression to define optimal decision thresholds. It revealed an unprecedented sensitivity and specificity of 99.5 and 95.2%, respectively, and the impact on splicing was correctly predicted for 98.8% of variants. We therefore propose SPiCE as the new tool for predicting variant spliceogenicity. It could be easily implemented in any diagnostic laboratory as a routine decision making tool to help geneticists to face the deluge of variants in the next-generation sequencing era. SPiCE is accessible at (https://sourceforge.net/projects/spicev2-1/).
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Raphael Leman, Pascaline Gaildrat, Gerald L. Gac, Chandran Ka, Yann Fichou, et al.. Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort. Nucleic Acids Research, Oxford University Press, 2018, 46 (15), pp.7913-7923. ⟨10.1093/nar/gky372⟩. ⟨hal-01910334⟩

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