HExoSplice

The HExoSplice web interface was designed for predicting the effect of single nucleotide variations (SNVs) on potential splicing regulatory elements (SREs) such as exonic splicing enhancers (ESEs) and silencers (ESSs). This tool is based on the quantitative evaluation of all possible RNA hexamers as potential exonic splicing regulatory sequences (ESRseq) also known as the QUEPASA method, which was developed by Dr Lawrence Chasin’s team (Ke et al, 2011). Users of HExoSplice can enter a sequence of interest and a list of single nucleotide substitutions. HExoSplice will then retrieve the ESRseq scores (Ke et al, 2011) of the hexamers overlapping the positions of the variations, both in the wild-type and in the variant contexts. Next, total ESRseq values are calculated by adding up individual ESRseq scores for each case. Finally, HExoSplice calculates the total ESRseq score change (ΔtESRseq) corresponding to each variant (variant versus wild-type).

If you use this web tool, please cite:

For the web interface

Lefebvre A, Martins A, Labrèche K, Deshaies V, Lahure A, Gaildrat P, and Dauchel H. HExoSplice: a new software based on overlapping hexamer scores for prediction and stratification of exonic variants altering splicing regulation of human genes. European Conference on Computational Biology, Strasbourg, France, 2014. (poster)

For the method

Tubeuf H, Charbonnier C, Soukarieh, O, Blavier O, Lefebvre A, Dauchel H, Frébourg T, Gaildrat P, and Martins A. Large-scale comparative evaluation of user-friendly tools for predicting variant-induced alterations of splicing regulatory elements. Hum Mutat. 2020. Article ID: HUMU24091 Article DOI: 10.1002/humu.24091 Internal Article ID: 16858097

Other useful references related to the QUEPASA method

Tubeuf H, Caputo SM, Sullivan T, Rondeaux J, Krieger S, Caux-Moncoutier V, Hauchard J, Castelain G, Fiévet A, Meulemans L, Révillion F, Léone M, Boutry-Kryza N, Delnatte C, Guillaud-Bataille M, Cleveland L, Reid S, Southon E, Soukarieh O, Drouet A, Di Giacomo D, Vezain M, Bonnet-Dorion F, Bourdon V, Larbre H, Muller D, Pujol P, Vaz F, Audebert-Bellanger S, Colas C, Venat-Bouvet L, Solano AR, Stoppa-Lyonnet D, Houdayer C, Frebourg T, Gaildrat P, Sharan SK, Martins A. Calibration of pathogenicity due to variant-induced leaky splicing defects by using BRCA2 exon 3 as a model/Tub system. Cancer Res. 2020 Jul 8:canres.0895.2020. doi: 10.1158/0008-5472.CAN-20-0895. Online ahead of print. PMID: 32641407

Canson D, Glubb D, Spurdle AB. Variant effect on splicing regulatory elements, branchpoint usage, and pseudoexonization: Strategies to enhance bioinformatic prediction using hereditary cancer genes as exemplars. Hum Mutat. 2020 Jul 5. doi: 10.1002/humu.24074. Online ahead of print. PMID: 32623769 Review.

Meulemans L, Mesman RLS, Caputo SM, Krieger S, Guillaud-Bataille M, Caux-Moncoutier V, Léone M, Boutry-Kryza N, Sokolowska J, Révillion F, Delnatte C, Tubeuf H, Soukarieh O, Bonnet-Dorion F, Guibert V, Bronner M, Bourdon V, Lizard S, Vilquin P, Privat M, Drouet A, Grout C, Calléja FMGR, Golmard L, Vrieling H, Stoppa-Lyonnet D, Houdayer C, Frebourg T, Vreeswijk MPG, Martins A, Gaildrat P. Skipping Nonsense to Maintain Function: The Paradigm of BRCA2 Exon 12. Cancer Res. 2020 Apr 1;80(7):1374-1386. doi: 10.1158/0008-5472.CAN-19-2491. Epub 2020 Feb 11. PMID: 32046981

Grodecká L, Buratti E, Freiberger T. Mutations of Pre-mRNA Splicing Regulatory Elements: Are Predictions Moving Forward to Clinical Diagnostics? Int J Mol Sci. 2017 Jul 31;18(8). pii: E1668. doi: 10.3390/ijms18081668. Review. PubMed PMID: 28758972; PubMed Central PMCID: PMC5578058.

de la Hoya M, Soukarieh O, López-Perolio I, Vega A, Walker LC, van Ierland Y, Baralle D, Santamariña M, Lattimore V, Wijnen J, Whiley P, Blanco A, Raponi M, Hauke J, Wappenschmidt B, Becker A, Hansen TV, Behar R, Investigators K, Niederacher D, Arnold N, Dworniczak B, Steinemann D, Faust U, Rubinstein W, Hulick PJ, Houdayer C, Caputo SM, Castera L, Pesaran T, Chao E, Brewer C, Southey MC, van Asperen CJ, Singer CF, Sullivan J, Poplawski N, Mai P, Peto J, Johnson N, Burwinkel B, Surowy H, Bojesen SE, Flyger H, Lindblom A, Margolin S, Chang-Claude J, Rudolph A, Radice P, Galastri L, Olson JE, Hallberg E, Giles GG, Milne RL, Andrulis IL, Glendon G, Hall P, Czene K, Blows F, Shah M, Wang Q, Dennis J, Michailidou K, McGuffog L, Bolla MK, Antoniou AC, Easton DF, Couch FJ, Tavtigian S, Vreeswijk MP, Parsons M, Meeks HD, Martins A, Goldgar DE, Spurdle AB. Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms. Hum Mol Genet. 2016 Jun 1;25(11):2256-2268. Epub 2016 Mar 23. PubMed PMID: 27008870; PubMed Central PMCID: PMC5081057.

Soukarieh O, Gaildrat P, Hamieh M, Drouet A, Baert-Desurmont S, Frébourg T, Tosi M, Martins A. Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools. PLoS Genet. 2016 Jan 13;12(1):e1005756. doi: 10.1371/journal.pgen.1005756. eCollection 2016 Jan. Erratum in: PLoS Genet. 2016 Apr;12(4):e1005971. PubMed PMID: 26761715

Di Giacomo D, Gaildrat P, Abuli A, Abdat J, Frébourg T, Tosi M, Martins A. Functional Analysis of a Large set of BRCA2 exon 7 Variants Highlights the Predictive Value of Hexamer Scores in Detecting Alterations of Exonic Splicing Regulatory Elements. Hum Mutat. 2013 Nov;34(11):1547-57 PubMed PMID: 23983145

Ke S, Shang S, Kalachikov SM, Morozova I, Yu L, Russo JJ, Ju J, Chasin LA. Quantitative evaluation of all hexamers as exonic splicing elements. Genome Res. 2011 Aug;21(8):1360-74 PubMed PMID:21659425