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SpliceVault predicts the precise nature of variant-associated mis-splicing

Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most...

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Autores principales: Dawes, Ruebena, Bournazos, Adam M., Bryen, Samantha J., Bommireddipalli, Shobhana, Marchant, Rhett G., Joshi, Himanshu, Cooper, Sandra T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925382/
https://www.ncbi.nlm.nih.gov/pubmed/36747048
http://dx.doi.org/10.1038/s41588-022-01293-8
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author Dawes, Ruebena
Bournazos, Adam M.
Bryen, Samantha J.
Bommireddipalli, Shobhana
Marchant, Rhett G.
Joshi, Himanshu
Cooper, Sandra T.
author_facet Dawes, Ruebena
Bournazos, Adam M.
Bryen, Samantha J.
Bommireddipalli, Shobhana
Marchant, Rhett G.
Joshi, Himanshu
Cooper, Sandra T.
author_sort Dawes, Ruebena
collection PubMed
description Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification.
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spelling pubmed-99253822023-02-15 SpliceVault predicts the precise nature of variant-associated mis-splicing Dawes, Ruebena Bournazos, Adam M. Bryen, Samantha J. Bommireddipalli, Shobhana Marchant, Rhett G. Joshi, Himanshu Cooper, Sandra T. Nat Genet Analysis Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification. Nature Publishing Group US 2023-02-06 2023 /pmc/articles/PMC9925382/ /pubmed/36747048 http://dx.doi.org/10.1038/s41588-022-01293-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Analysis
Dawes, Ruebena
Bournazos, Adam M.
Bryen, Samantha J.
Bommireddipalli, Shobhana
Marchant, Rhett G.
Joshi, Himanshu
Cooper, Sandra T.
SpliceVault predicts the precise nature of variant-associated mis-splicing
title SpliceVault predicts the precise nature of variant-associated mis-splicing
title_full SpliceVault predicts the precise nature of variant-associated mis-splicing
title_fullStr SpliceVault predicts the precise nature of variant-associated mis-splicing
title_full_unstemmed SpliceVault predicts the precise nature of variant-associated mis-splicing
title_short SpliceVault predicts the precise nature of variant-associated mis-splicing
title_sort splicevault predicts the precise nature of variant-associated mis-splicing
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925382/
https://www.ncbi.nlm.nih.gov/pubmed/36747048
http://dx.doi.org/10.1038/s41588-022-01293-8
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