Role of Splicing Regulatory Elements and In Silico Tools Usage in the Identification of Deep Intronic Splicing Variants in Hereditary Breast/Ovarian Cancer Genes.
Alejandro Moles-Fernández,Joanna Domènech-Vivó,Anna Tenés,Judith Balmaña,Orland Diez,Sara Gutiérrez-Enríquez +5 more
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TLDR
Wang et al. as mentioned in this paper assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs).Abstract:
The contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.read more
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Journal ArticleDOI
Human Splicing Finder: an online bioinformatics tool to predict splicing signals
François Olivier Desmet,Dalil Hamroun,Marine Lalande,Gwenaëlle Collod-Béroud,Mireille Claustres,Christophe Béroud +5 more
TL;DR: Human Splicing Finder is designed, a tool to predict the effects of mutations on splicing signals or to identify splicing motifs in any human sequence, and it is shown that the mutation effect was correctly predicted in almost all cases.
Journal ArticleDOI
RNA splice junctions of different classes of eukaryotes: sequence statistics and functional implications in gene expression.
TL;DR: A striking similarity among the rare splice junctions which do not contain AG at the 3' splice site or GT at the 5'splice site indicates the existence of special mechanisms to recognize them, and that these unique signals may be involved in crucial gene-regulation events and in differentiation.
Journal ArticleDOI
Listening to silence and understanding nonsense: exonic mutations that affect splicing
TL;DR: As the splicing mechanisms that depend on exonic signals are elucidated, new therapeutic approaches to treating certain genetic diseases can begin to be explored.
Journal ArticleDOI
Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals.
Gene W. Yeo,Christopher B. Burge +1 more
TL;DR: The best models out-perform previous probabilistic models in the discrimination of human 5' and 3' splice sites from decoys and mechanistically motivated ways of comparing models are discussed.
Journal ArticleDOI
Predicting Splicing from Primary Sequence with Deep Learning.
Kishore Jaganathan,Sofia Kyriazopoulou Panagiotopoulou,Jeremy F. McRae,Siavash Fazel Darbandi,David A. Knowles,Yang I. Li,Jack A. Kosmicki,Jack A. Kosmicki,Juan Arbelaez,Wenwu Cui,Grace Schwartz,Eric D. Chow,Efstathios Kanterakis,Hong Gao,Amirali Kia,Serafim Batzoglou,Stephen Sanders,Kyle Kai-How Farh +17 more
TL;DR: A deep neural network is described that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing.