Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants

Houdayer, Claude; Caux-Moncoutier, Virginie; Krieger, Sophie; Barrois, Michel; Bonnet, Françoise; Bourdon, Violaine; Bronner, Myriam; Buisson, Monique; Coulet, Florence; Gaildrat, Pascaline; Lefol, Cédrick; Léone, Mélanie; Mazoyer, Sylvie; Muller, Danielle; Remenieras, Audrey; Révillion, Françoise; Rouleau, Etienne; Sokolowska, Joanna; Vert, Jean-Philippe; Lidereau, Rosette; Soubrier, Florent; Sobol, Hagay; Sevenet, Nicolas; Bressac-de Paillerets, Brigitte; Hardouin, Agnès; Tosi, Mario; Sinilnikova, Olga M.; Stoppa-Lyonnet, Dominique

doi:10.1002/humu.22101

Cited by 239BRCA gene mutations in cancerRNA Research and SplicingGenomics and Rare Diseases

Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants

Houdayer, Claude, Caux-Moncoutier, Virginie, Krieger, Sophie, Barrois, Michel, Bonnet, Françoise, Bourdon, Violaine, Bronner, Myriam, Buisson, Monique +20 more·2012·Human Mutation

DOI 10.1002/humu.22101

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Abstract

Assessing the impact of variants of unknown significance (VUS) on splicing is a key issue in molecular diagnosis. This impact can be predicted by in silico tools, but proper evaluation and user guidelines are lacking. To fill this gap, we embarked upon the largest BRCA1 and BRCA2 splice study to date by testing 272 VUSs (327 analyses) within the BRCA splice network of Unicancer. All these VUSs were analyzed by using six tools (splice site prediction by neural network, splice site finder (SSF), MaxEntScan (MES), ESE finder, relative enhancer and silencer classification by unanimous enrichment, and human splicing finder) and the predictions obtained were compared with transcript analysis results. Combining MES and SSF gave 96% sensitivity and 83% specificity for VUSs occurring in the vicinity of consensus splice sites, that is, the surrounding 11 and 14 bases for the 5' and 3' sites, respectively. This study was also an opportunity to define guidelines for transcript analysis along with a tentative classification of splice variants. The guidelines drawn from this large series should be useful for the whole community, particularly in the context of growing sequencing capacities that require robust pipelines for variant interpretation.

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Splice site prediction tools have increased sensitivity (~90-100%) relative to specificity (~60-80%) in predicting splice site abnormalities.
“In general, splice site prediction tools have increased sensitivity (~90-100%) relative to specificity (~60-80%) in predicting splice site abnormalities. 23,24”
From Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (2015) · cites this paper as [23]

Intronic variants inBRCA1andBRCA2that affect RNA splicing can be reliably selected by splice-site prediction programs
Vreeswijk, M. P. G., Kraan, J. N., van der Klift, H. M., Vink, G. R., Cornelisse, C. J., Wijnen, J. T., Bakker, E., van Asperen, C. J., & Devilee, P. (2009) · Human Mutation · doi:10.1002/humu.20811 · Cited by 98 · see citing works

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Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology
Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., Grody, W. W., Hegde, M., Lyon, E., Spector, E., et al. (2015) · Genetics in Medicine · doi:10.1038/gim.2015.30 · Cited by 32,594 · see citing works
“In general, splice site prediction tools have increased sensitivity (~90-100%) relative to specificity (~60-80%) in predicting splice site abnormalities.(23,24) A list of some of the commonly used in-silico tools for splice site variant interpretation is provided in Table 2.”
Background
Pheochromocytoma and paraganglioma: an endocrine society clinical practice guideline
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“To further validate our two best models, we made use of experimentally validated scSNVs from a previous study (22).”
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Self-citation
Exonic Splicing Mutations Are More Prevalent than Currently Estimated and Can Be Predicted by Using In Silico Tools
Soukarieh, O., Gaildrat, P., Hamieh, M., Drouet, A., Baert-Desurmont, S., Frebourg, T., Tosi, M., & Martins, A. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005756 · Cited by 161
Self-citation
Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance
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“Individual tools were deemed to predict altered splicing where the change in splice site score was ≥10% (MES) or ≥5% (NNSplice and SSF).(14,15) An overall prediction of altered splicing was called where two of three Alamut programs agreed.”
BackgroundMethod
In silico tools for splicing defect prediction: a survey from the viewpoint of end users
Jian, X., Boerwinkle, E., & Liu, X. (2014) · Genetics in Medicine · doi:10.1038/gim.2013.176 · Cited by 146 · see citing works
“As a recent example, Houdayer et al. 35 systematically evaluated several in silico prediction tools using 272 variants of unknown significance (VUS) in BRCA1 and BRCA2 genes.”
BackgroundMethod
A High-Throughput Functional Complementation Assay for Classification of BRCA1 Missense Variants
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“For splicing predictions, we recommend using the SSF and MES, both of which have been shown to predict splicing effects with high accuracy.(69-71) PP3, defined as multiple lines of computational evidence supporting a deleterious effect, can be applied for missense variants with a REVEL score .”
Method
Variation Interpretation Predictors: Principles, Types, Performance, and Choice
Niroula, A., & Vihinen, M. (2016) · Human Mutation · doi:10.1002/humu.22987 · Cited by 121 · see citing works
“In another study, the performance of the same six tools was assessed using 272 variations in the BRCA1 and BRCA2 genes [Houdayer et al., 2012].”
Method
Functional Assays for Analysis of Variants of Uncertain Significance inBRCA2
Guidugli, L., Carreira, A., Caputo, S. M., Ehlén, Å., Galli, A., Monteiro, Á. N. A., Neuhausen, S. L., Hansen, T. V. O., Couch, F. J., & Vreeswijk, M. P. G. (2013) · Human Mutation · doi:10.1002/humu.22478 · Cited by 123 · see citing works
“This subject is extensively addressed in a number of recent papers published by the ENIGMA splicing working group [Houdayer et al., 2012; Spurdle et al., 2012; Thomassen et al., 2012].”
Background
Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?
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“For acceptor sites, the sequential combination of MES and SSF-like (Houdayer et al., 2012) and SSF-like stand-alone reached a performance with the same score of accuracy, 92.65%, but SSF-like showed a highest NPV ( Table 3 ).”
BackgroundMethodInfluential
Rules and tools to predict the splicing effects of exonic and intronic mutations
Ohno, K., Takeda, J.-I., & Masuda, A. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1451 · Cited by 106 · see citing works
“evaluated in silico tools using 272 SNVs in the BRCA1 and BRCA2 genes, and reported that MaxEntScan and PWM best predicted the splicing effects of SNVs at the 50 and 30 ss’s.(109)”
Method
Clinical sequencing: From raw data to diagnosis with lifetime value
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Whole USH2A Gene Sequencing Identifies Several New Deep Intronic Mutations
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“…to create 5′ and 3′ splice sites (from which 36 were recorded in DBASS3 and DBASS5 databases, http://www. dbass.soton.ac.uk/) using thresholds we chose on the basis of the cutoffs defined by Desmet et al. (2009) and Houdayer et al. (2012) to predict disruption of natural 5′ss and 3′ss (Supp.”
Method
Comprehensive annotation of splice junctions supports pervasive alternative splicing at the BRCA1 locus: a report from the ENIGMA consortium.
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BackgroundInfluentialSelf-citation
SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing
Leman, R., Parfait, B., Vidaud, D., Girodon, E., Pacot, L., Gac, G. L., Ka, C., Férec, C., Fichou, Y., Quesnelle, C., et al. (2022) · Human Mutation · doi:10.1002/humu.24491 · Cited by 90 · see citing works
“…(Evidence ‐ based Network for the Interpretation of Germline Mutant Alleles) (Spurdle et al., 2012) products and/or on cell ‐ based minigene splicing assays (Callebaut et al., 2014; Gaildrat et al., 2010; Houdayer et al., 2012; Riant et al., 2013; Sabbagh et al., 2013; Steffensen et al., 2014).”
BackgroundMethodSelf-citation
Germline mutation in the RAD51B gene confers predisposition to breast cancer
Golmard, L., Caux-Moncoutier, V., Davy, G., Ageeli, E. A., Poirot, B., Tirapo, C., Michaux, D., Barbaroux, C., d'Enghien, C. D., Nicolas, A., et al. (2013) · BMC Cancer · doi:10.1186/1471-2407-13-484 · Cited by 88 · see citing works
“All variants detected on DNA were tested by in silico splicing effect prediction according to a previously published pipeline [30]: a greater than 15% decrease of the MaxEntScan score for donor/acceptor splice sites and a greater than 5% decrease of the SpliceSiteFinder-like score for donor/acceptor splice sites were…”
MethodSelf-citation
Diagnostic Interpretation of Genetic Studies in Patients with Primary Immunodeficiency Diseases: A Working Group Report of the Primary Immunodeficiency Diseases Committee of the American Academy of Allergy, Asthma, and Immunology.
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“In order to compare SPiCE with our former guidelines, the BRCA1/2 validation set was assayed as previously described (7).”
BackgroundMethodInfluentialSelf-citation
Splicing analysis for exonic and intronic mismatch repair gene variants associated with Lynch syndrome confirms high concordance between minigene assays and patient RNA analyses
van der Klift, H. M., Jansen, A. M., van der Steenstraten, N., Bik, E., Tops, C., Devilee, P., & Wijnen, J. (2015) · Molecular Genetics & Genomic Medicine · doi:10.1002/mgg3.145 · Cited by 81
“0 for four of the variants, in keeping with the poor specificity previously associated with this prediction tool (Houdayer et al. 2012).”
BackgroundResultInfluential
A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity
Shamsani, J., Kazakoff, S., Armean, I., McLaren, W., Parsons, M., Thompson, B., O'Mara, T., Hunt, S., Waddell, N., & Spurdle, A. (2018) · Bioinform. · doi:10.1093/bioinformatics/bty960 · Cited by 78 · see citing works
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“(SSF-like), per prior demonstrations of high sensitivity and specificity for these tools and thresholds.(25,26) Gain of a splice site was predicted by the splicing module of Alamut (Interactive Biosoftware, Rouen, France) when two or more algorithms met the”
Method
BRCA2 Deep Intronic Mutation Causing Activation of a Cryptic Exon: Opening toward a New Preventive Therapeutic Strategy
Anczuków, O., Buisson, M., Léoné, M., Coutanson, C., Lasset, C., Calender, A., Sinilnikova, O., & Mazoyer, S. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-1100 · Cited by 75
“Genomic DNA from Family A index case was amplified with intron 12 primers: 50-TGATGCCATTACCGATCAGA-30 (c.6937þ348-c.6937þ367) and 50- GGGAATCCAAGCTGTCAAAA-30 (c.6937þ742-c.6937þ 761); the resulting 414-nt fragment containing the cryptic exon was sequenced.”
BackgroundInfluentialSelf-citation
Landscape of pathogenic variations in a panel of 34 genes and cancer risk estimation from 5131 HBOC families
Castéra, L., Harter, V., Muller, E., Krieger, S., Goardon, N., Ricou, A., Rousselin, A., Paimparay, G., Legros, A., Bruet, O., et al. (2018) · Genetics in Medicine · doi:10.1038/s41436-018-0005-9 · Cited by 73 · see citing works
Self-citation
Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches
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“Because these variants have little or only partial aberrant effects on splicing (Table S3), 26,27 they were included in the functional study.”
Background
Functional characterization of BRCA1 gene variants by mini-gene splicing assay
Steffensen, A. Y., Dandanell, M., Jønson, L., Ejlertsen, B., Gerdes, A., Nielsen, F., & Hansen, T. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.40 · Cited by 71 · see citing works
Comparison of mRNA Splicing Assay Protocols across Multiple Laboratories: Recommendations for Best Practice in Standardized Clinical Testing
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“…and extension time were controlled, all sites detected the fulllength transcript and the predominant alternative transcripts, suggesting that high-abundance aberrant transcripts will be detectable regardless of assay protocol, which is consistent with the conclusions of Houdayer et al. (12 ).”
Self-citation
A Standardized DNA Variant Scoring System for Pathogenicity Assessments in Mendelian Disorders
Karbassi, I., Maston, G. A., Love, A., Divincenzo, C., Braastad, C. D., Elzinga, C. D., Bright, A. R., Previte, D., Zhang, K., Rowland, C., et al. (2015) · Human Mutation · doi:10.1002/humu.22918 · Cited by 66 · see citing works
“Splicing prediction scores at least 15% lower than the wild-type score [Houdayer et al., 2012] and a consensus among three or more prediction tools [Hellen, 2009] were used to assess the variant’s effect on known splice sites.”
Method
EMQN best practice guidelines for genetic testing in dystrophinopathies
Fratter, C., Dalgleish, R., Allen, S., Santos, R., Abbs, S., Tuffery-Giraud, S., & Ferlini, A. (2020) · European Journal of Human Genetics · doi:10.1038/s41431-020-0643-7 · Cited by 64 · see citing works
Functional classification of DNA variants by hybrid minigenes: Identification of 30 spliceogenic variants of BRCA2 exons 17 and 18
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“Thus, DNA variants: c.7806-9T > G (exon 17 skipping+ex17-del69+ivs16-ins8) [35], c.7975A > G (partial exon 17 skipping) [36], c.7976G > A and c.7976G > C (total exon 17 skipping) [37,38], c.7988A > T (partial exon 18 skipping) [38], c.7992A > T (partial exon 18 disruption; [+] creation.”
Adding In Silico Assessment of Potential Splice Aberration to the Integrated Evaluation of BRCA Gene Unclassified Variants
Vallée, M., DiSera, T., Nix, D. A., Paquette, A., Parsons, M., Bell, R., Hoffman, A., Hogervorst, F., Goldgar, D., Spurdle, A., et al. (2016) · Human Mutation · doi:10.1002/humu.22973 · Cited by 61 · see citing works
“From their dataset of sequence variants’ effects on splicing, Houdayer et al. (2012) were able to perform receiver operating characteristic (ROC) analyses on several splice junction analysis programs; they found that MES was the single best performing program, with an area under the ROC curve of…”
MethodResultInfluential
Experimental Assessment of Splicing Variants Using Expression Minigenes and Comparison with In Silico Predictions
Sharma, N., Sosnay, P., Ramalho, A., Douville, C., Franca, A. L., Gottschalk, L. B., Park, J., Lee, M., Vecchio-Pagán, B., Raraigh, K., et al. (2014) · Human Mutation · doi:10.1002/humu.22624 · Cited by 61 · see citing works
“The discrepancies between experimental results and in silico predictions in this study support the recommendation that use of a single prediction model is not sufficient, as recommended for the BRCA1 and the BRCA2 genes [Spurdle et al., 2008; Acedo et al., 2012; Houdayer et al., 2012].”
MethodResultInfluential
CCM molecular screening in a diagnosis context: novel unclassified variants leading to abnormal splicing and importance of large deletions
Riant, F., Cécillon, M., Saugier-Veber, P., & Tournier-Lasserve, E. (2013) · Neurogenetics · doi:10.1007/s10048-013-0362-0 · Cited by 61
“proposed an analysis pipeline to check the unknown variants with a cutoff ratio of 15 % for MaxEntScan and 5 % for Splice Site finder like [23].”
Method
Beyond DNA: An Integrated and Functional Approach for Classifying Germline Variants in Breast Cancer Genes
Pesaran, T., Karam, R., Huether, R., Li, S., Farber-Katz, S., Chamberlin, A., Chong, H., LaDuca, H., & Elliott, A. (2016) · International Journal of Breast Cancer · doi:10.1155/2016/2469523 · Cited by 60 · see citing works
“In general, these in silico tools are more sensitive (∼90–100%) than being specific (∼60–80%) when predicting the impact of a variant on splicing [21, 22].”
Comparative In Vitro and In Silico Analyses of Variants in Splicing Regions of BRCA1 and BRCA2 Genes and Characterization of Novel Pathogenic Mutations
Colombo, M., Vecchi, G. D., Caleca, L., Foglia, C., Ripamonti, C., Ficarazzi, F., Barile, M., Varesco, L., Peissel, B., Manoukian, S., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057173 · Cited by 59 · see citing works
“However, in some instances, different mRNA transcript patterns have been reported in association with the same mutation by diverse studies [18,22].”
Result
Functional Classification of BRCA2 DNA Variants by Splicing Assays in a Large Minigene with 9 Exons
Acedo, A., Hernández-Moro, C., Curiel-García, Á., Díez-Gómez, B., & Velasco, E. (2015) · Human Mutation · doi:10.1002/humu.22725 · Cited by 58 · see citing works
“Also, variant c.8486A>G, in the same position that c.8486A>T tested by us (Table 2), was reported to have the same outcome (exon 19 skipping) [Houdayer et al., 2012].”
Background
Streamlined ion torrent PGM-based diagnostics: BRCA1 and BRCA2 genes as a model
Tarabeux, J., Zeitouni, B., Moncoutier, V., Tenreiro, H., Abidallah, K., Lair, S., Legoix-né, P., Leroy, Q., Rouleau, E., Golmard, L., et al. (2013) · European Journal of Human Genetics · doi:10.1038/ejhg.2013.181 · Cited by 58 · see citing works
Self-citation
Interpretable prioritization of splice variants in diagnostic next-generation sequencing
Danis, D., Jacobsen, J. O. B., Carmody, L., Gargano, M. A., McMurry, J., Hegde, A., Haendel, M., Valentini, G., Smedley, D., & Robinson, P. N. (2021) · bioRxiv · doi:10.1101/2021.01.28.428499 · Cited by 57
“Suggestive evidence exists that non-canonical SAVs might be a more common cause of Mendelian disease than is commonly appreciated.(9,19,21).”
Background
Detecting splicing patterns in genes involved in hereditary breast and ovarian cancer
Davy, G., Rousselin, A., Goardon, N., Castéra, L., Harter, V., Legros, A., Muller, E., Fouillet, R., Brault, B., Smirnova, A., et al. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.116 · Cited by 54
Self-citation
Naturally occurring BRCA2 alternative mRNA splicing events in clinically relevant samples
Fackenthal, J., Yoshimatsu, T., Zhang, B.-F., de Garibay, G. R., Colombo, M., Vecchi, G. D., Ayoub, S. C., Lal, K., Olopade, O., Vega, A., et al. (2016) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2015-103570 · Cited by 54 · see citing works
Self-citation
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
Giacomo, D. D., Gaildrat, P., Abulí, A., Abdat, J., Frebourg, T., Tosi, M., & Martins, A. (2013) · Human Mutation · doi:10.1002/humu.22428 · Cited by 52 · see citing works
“It is currently accepted that the most useful programs in molecular diagnostic settings are those devoted to predicting alterations in consensus splice sites, as it has been shown for multiple disease-associated BRCA1 and BRCA2 variants [Houdayer et al., 2012; Spurdle et al., 2008; Thery et al., 2011; Vreeswijk et al.…”
BackgroundInfluentialSelf-citation
Contribution of germline deleterious variants in the RAD51 paralogs to breast and ovarian cancers
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Evaluation of Bioinformatic Programmes for the Analysis of Variants within Splice Site Consensus Regions
Tang, R., Prosser, D., & Love, D. (2016) · Adv. Bioinformatics · doi:10.1155/2016/5614058 · Cited by 51 · see citing works
GREM 1 and POLE variants in hereditary colorectal cancer syndromes
Rohlin, A., Eiengård, F., Lundstam, U., Zagoras, T., Nilsson, S., Edsjö, A., Pedersen, J., Svensson, J., Skullman, S., Karlsson, B., et al. (2015) · Genes, Chromosomes and Cancer · doi:10.1002/gcc.22314 · Cited by 51
“…prediction of variants was performed with SpliceSiteFinder-like, MaxEntScan, NNSPLICE, GeneSplicer and Human Splicefinder (Reese et al., 1997; Zhang, 1998; Pertea et al., 2001; Fairbrother et al., 2002; Cartegni et al., 2003; Yeo and Burge, 2004; Desmet et al., 2009; Houdayer et al., 2012).”
Method
Analysis of PALB2 Gene in BRCA1/BRCA2 Negative Spanish Hereditary Breast/Ovarian Cancer Families with Pancreatic Cancer Cases
Blanco, A., de la Hoya, M., Osorio, A., Díez, O., Miramar, M., Infante, M., Martı́nez-Bouzas, C., Torres, A., Lasa, A., Llort, G., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067538 · Cited by 51 · see citing works
“Recently published guidelines for splicing analysis [39] indicate that only variants located in the consensus sites described by Cartegni et al [40], 11 bases for the 59 site (from the 3 last exonic to the 8 first intronic bases) and 14 bases for the 39 site (from the 12 last intronic to the first 2 exonic bases), wou…”
Frequent mutations of RetNet genes in eoHM: Further confirmation in 325 probands and comparison with late‐onset high myopia based on exome sequencing
Zhou, L., Xiao, X.-S., Li, S.-Q., Jia, X.-Y., & Zhang, Q.-J. (2018) · Experimental Eye Research · doi:10.1016/j.exer.2018.02.007 · Cited by 50 · see citing works
A survey of the clinicopathological and molecular characteristics of patients with suspected Lynch syndrome in Latin America
Rossi, B., Palmero, E., López-Kostner, F., Sarroca, C., Vaccaro, C., Spirandelli, F., Ashton-Prolla, P., Rodriguez, Y., Galvão, H. D. C. R., Reis, R., et al. (2017) · BMC Cancer · doi:10.1186/s12885-017-3599-4 · Cited by 48
“For stratification purposes, negative alterations of reference splice sites were deemed important when MaxEntScan scores showed ≥15% decrease relative to corresponding wild-type splice sites [57].”
BackgroundMethod
Variation benchmark datasets: update, criteria, quality and applications
Sarkar, A., Yang, Y., & Vihinen, M. (2019) · bioRxiv · doi:10.1093/database/baz117 · Cited by 47 · see citing works
“Experimental BRCA1 and BRCA2 13, 15, 33, 38, 35, 73 1, 1, 1, 1, 1, 1 (98)”
Cancer Variant Interpretation Group UK (CanVIG-UK): an exemplar national subspecialty multidisciplinary network
Garrett, A., Callaway, A., Durkie, M., Çubuk, C., Alikian, M., Burghel, G., Robinson, R., Izatt, L., Talukdar, S., Side, L., et al. (2020) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2019-106759 · Cited by 45 · see citing works
Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort
Li, H.-Y., LaDuca, H., Pesaran, T., Chao, E. C., Dolinsky, J. S., Parsons, M., Spurdle, A., Polley, E., Shimelis, H., Hart, S., et al. (2019) · Genetics in Medicine · doi:10.1038/s41436-019-0729-1 · Cited by 45 · see citing works
Genotype–phenotype correlations for COL4A3–COL4A5 variants resulting in Gly substitutions in Alport syndrome
Gibson, J., Huang, M., Dabrera, M. S. C., Shukla, K., Rothe, H., Hilbert, P., Deltas, C., Storey, H., Lipska-Ziętkiewicz, B., Chan, M., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-06525-9 · Cited by 44 · see citing works
CI-SpliceAI—Improving machine learning predictions of disease causing splicing variants using curated alternative splice sites
Strauch, Y., Lord, J., Niranjan, M., & Baralle, D. (2022) · PLoS ONE · doi:10.1371/journal.pone.0269159 · Cited by 43 · see citing works
Performance Evaluation of SpliceAI for the Prediction of Splicing of NF1 Variants
Ha, C., Kim, J.-W., & Jang, J.-H. (2021) · Genes · doi:10.3390/genes12091308 · Cited by 42 · see citing works
“In contrast, 5% was used for NNSplice and SSF and 2% was used for Human Splicing Finder [18,31,33,34].”
BackgroundMethod
Genetic profiles of cervical tumors by high‐throughput sequencing for personalized medical care
Müller, E., Brault, B., Holmes, A. M., Legros, A., Jeannot, E., Campitelli, M., Rousselin, A., Goardon, N., Frébourg, T., Krieger, S., et al. (2015) · Cancer Medicine · doi:10.1002/cam4.492 · Cited by 40 · see citing works
“Variants were retrieved from CanDiD database according to five criteria: (1) the variant was found on a list of preferred transcripts; (2) the variant was in targeted zones; (3) the variant was within the coding sequence or ±10 bp within the intronic sequences; (4) the variant was in a canonical splicing mutation site…”
MethodSelf-citation
Evaluation of a 5‐Tier Scheme Proposed for Classification of Sequence Variants Using Bioinformatic and Splicing Assay Data: Inter‐Reviewer Variability and Promotion of Minimum Reporting Guidelines
Walker, L., Whiley, P., Houdayer, C., Hansen, T. V. O., Vega, A., Santamariña, M., Blanco, A., Fachal, L., Southey, M., Lafferty, A., et al. (2013) · Human Mutation · doi:10.1002/humu.22388 · Cited by 40 · see citing works
“, 2009], and guidelines for the utilization of commonly used bioinformatic tools were recently proposed based on a large-scale assessment of 272 unclassified variants in the BRCA1/BRCA2 genes using in silico and transcript analyses [Houdayer et al., 2012].”
MethodSelf-citation
Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants
Leman, R., Tubeuf, H., Raad, S., Tournier, I., Derambure, C., Lanos, R., Gaildrat, P., Castelain, G., Hauchard, J., Killian, A., et al. (2019) · BMC Genomics · doi:10.1186/s12864-020-6484-5 · Cited by 39 · see citing works
Self-citation
Genetics of movement disorders in the next‐generation sequencing era
Olgiati, S., Quadri, M., & Bonifati, V. (2016) · Movement Disorders · doi:10.1002/mds.26521 · Cited by 40 · see citing works
Protein haploinsufficiency drivers identify MYBPC3 variants that cause hypertrophic cardiomyopathy
Suay-Corredera, C., Pricolo, M., Herrero-Galán, E., Velázquez-Carreras, D., Sánchez-Ortiz, D., García-Giustiniani, D., Delgado, J., Galano-Frutos, J., García-Cebollada, H., Vilches, S., et al. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100854 · Cited by 38 · see citing works
“Positive hits result in at least two tools predicting >10% decrease (for native sites) or increase (for new sites) in the splicing score, in agreement with published guidelines (73).”
Result
Mass-array screening of frequent mutations in cancers reveals RB1 alterations in aggressive adrenocortical carcinomas.
Ragazzon, B., Libé, R., Assié, G., Tissier, F., Barreau, O., Houdayer, C., Perlemoine, K., Audebourg, A., Clauser, E., René-Corail, F., et al. (2014) · European Journal of Endocrinology · doi:10.1530/eje-13-0778 · Cited by 37 · see citing works
Self-citation
Large‐scale comparative evaluation of user‐friendly tools for predicting variant‐induced alterations of splicing regulatory elements
Tubeuf, H., Charbonnier, C., Soukarieh, O., Blavier, A., Lefebvre, A., Dauchel, H., Frebourg, T., Gaildrat, P., & Martins, A. (2020) · Human Mutation · doi:10.1002/humu.24091 · Cited by 35 · see citing works
“Like, and SPiCE) were evaluated in other studies (Houdayer et al., 2012; Leman et al., 2018; Moles ‐ Fernández et al., 2018).”
BackgroundMethodInfluentialSelf-citation
Mis‐splicing in breast cancer: identification of pathogenic BRCA2 variants by systematic minigene assays
Fraile-Bethencourt, E., Valenzuela-Palomo, A., Díez-Gómez, B., Goina, E., Acedo, A., Buratti, E., & Velasco, E. (2019) · Journal of Pathology · doi:10.1002/path.5268 · Cited by 35 · see citing works
Leveraging splice-affecting variant predictors and a minigene validation system to identify Mendelian disease-causing variants amongst exon-captured variants of uncertain significance
Soens, Z. T., Branch, J., Wu, S., Yuan, Z., Li, Y.-M., Li, H., Wang, K.-Q., Xu, M.-C., Rajan, L., Motta, F., et al. (2017) · Human Mutation · doi:10.1002/humu.23294 · Cited by 35 · see citing works
“The eight scores were also chosen based on recommendations of performance drawn from 11 different publications that utilized, reported on, or compared the performance of these tools (Colombo et al., 2013; Houdayer et al., 2012;Hunt, Simhadri, Iandoli, Sauna,&Kimchi-Sarfaty, 2014; Jian et al., 2014; Jian, Boerwinkle, &…”
Method
Targeted RNA‐seq successfully identifies normal and pathogenic splicing events in breast/ovarian cancer susceptibility and Lynch syndrome genes
Brandão, R., Mensaert, K., López-Perolio, I., Tserpelis, D., Xenakis, M., Lattimore, V., Walker, L., Kvist, A., Vega, A., Gutiérrez-Enríquez, S., et al. (2019) · International Journal of Cancer · doi:10.1002/ijc.32114 · Cited by 34 · see citing works
“In the targeted RNA-seq on LCLs we obtained an average of 18,868 reads [9389-33,956], whereas it was 347 [118–484] for non-targeted LCLs, 134 [44–226] for normal breast tissue and 10 [2-16] for normal fimbria tissue.”
BackgroundResult
Alternative mRNA splicing can attenuate the pathogenicity of presumed loss-of-function variants in BRCA2
Mesman, R. L. S., Calléja, F., de la Hoya, M., Devilee, P., van Asperen, C. V., Vrieling, H., & Vreeswijk, M. (2020) · Genetics in Medicine · doi:10.1038/s41436-020-0814-5 · Cited by 33 · see citing works
About 1% of the breast and ovarian Spanish families testing negative for BRCA1 and BRCA2 are carriers of RAD51D pathogenic variants
Gutiérrez-Enríquez, S., Bonache, S., de Garibay, G. R., Osorio, A., Santamariña, M., Cajal, T. R. Y., Esteban-Cardeñosa, E. M., Tenés, A., Yanowsky, K., Barroso, A., et al. (2014) · International Journal of Cancer · doi:10.1002/ijc.28540 · Cited by 33 · see citing works
Spanish Guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia
Palomo, L., Ibáñez, M., Abáigar, M., Vázquez, I., Álvarez, S., Cabezón, M., Tazón‐Vega, B., Rapado, I., Fuster‐Tormo, F., Cervera, J., et al. (2019) · British Journal of Haematology · doi:10.1111/bjh.16175 · Cited by 42 · see citing works
“In silico tools have also been developed to evaluate the consequence of splicing variants related to the creation or loss of splice sites at the exonic or intronic regions (Thusberg et al, 2011; Houdayer et al, 2012).”
Method
A Classification Model Relative to Splicing for Variants of Unknown Clinical Significance: Application to the CFTR Gene
Raynal, C., Baux, D., Thèze, C., Bareil, C., Taulan, M., Roux, A., Claustres, M., Tuffery-Giraud, S., & Georges, M. D. (2013) · Human Mutation · doi:10.1002/humu.22291 · Cited by 32 · see citing works
“They were shown to act as efﬁcient ﬁlters [Houdayer et al., 2012; Vreeswijk et al., 2009], however their performance could be improved as they generate some false positive or false negative predictions [Le Guedard-Mereuze et al., 2010; Thery et al., 2011].”
BackgroundMethod
In silico methods for predicting functional synonymous variants
Lin, B. C., Katneni, U., Jankowska, K. I., Meyer, D., & Kimchi‐Sarfaty, C. (2023) · Genome biology · doi:10.1186/s13059-023-02966-1 · Cited by 40 · see citing works
“Use of a combination of tools predicting both SSs and SREs and employing different algorithms is recommended to overcome potential deficiencies of a single tool and is expected to improve predictive values [12, 132, 133].”
Method
Variant effect on splicing regulatory elements, branchpoint usage, and pseudoexonization: Strategies to enhance bioinformatic prediction using hereditary cancer genes as exemplars
Canson, D. M., Glubb, D. M., & Spurdle, A. B. (2020) · Human Mutation · doi:10.1002/humu.24074 · Cited by 35 · see citing works
“ACTIVE EXONIC SREs: BRCA1/2 AS EXEMPLARS It has been recommended that a precise and detailed map of active SREs be established for each gene of interest in order for SRE prediction to be useful in clinical diagnostics (Houdayer et al., 2012).”
BackgroundMethod
Mutations of Pre-mRNA Splicing Regulatory Elements: Are Predictions Moving Forward to Clinical Diagnostics?
Grodecká, L., Buratti, E., & Freiberger, T. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18081668 · Cited by 37 · see citing works
“[17], as this recommended a particular (specific) re-classification of class 3 variants (or variants of unknown significance) into three other classes (1S, 2S, 3S).”
BackgroundInfluential
High-frequency actionable pathogenic exome variants in an average-risk cohortPreprint
Rego, S., Dagan-Rosenfeld, O., Zhou, W., Sailani, M., Limcaoco, P., Colbert, E., Avina, M., Wheeler, J., Craig, C. M., Salins, D., et al. (2018) · Cold Spring Harbor molecular case studies · doi:10.1101/mcs.a003178 · Cited by 30 · see citing works
“Splice site predictors are only slightly more accurate (Vreeswijk et al. 2008; Houdayer et al. 2012).”
Background
mRNA analysis identifies deep intronic variants causing Alport syndrome and overcomes the problem of negative results of exome sequencing
Wang, X.-Y., Zhang, Y.-Q., Ding, J., & Wang, F. (2021) · Scientific Reports · doi:10.1038/s41598-021-97414-0 · Cited by 29 · see citing works
Functional Categorization of BRCA1 Variants of Uncertain Clinical Significance in Homologous Recombination Repair Complementation Assays
Bouwman, P., van der Heijden, I., van der Gulden, H., de Bruijn, R., Braspenning, M. E., Moghadasi, S., Wessels, L., Segers, K., Badoer, C., Vandernoot, I., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-0255 · Cited by 29 · see citing works
A Deep Intronic Variant in LDLR in Familial Hypercholesterolemia: Time to Widen the Scope?
Reeskamp, L., Hartgers, M. L., Peter, J., Dallinga-Thie, G., Zuurbier, L., Defesche, J., Grefhorst, A., & Hovingh, G. (2018) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.118.002385 · Cited by 29 · see citing works
Quantitative Analysis of BRCA1 and BRCA2 Germline Splicing Variants Using a Novel RNA-Massively Parallel Sequencing Assay
Farber-Katz, S., Hsuan, V., Wu, S.-T., Landrith, T. A., Vuong, H., Xu, D.-D., Li, B., Hoo, J., Lam, S., Nashed, S., et al. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00286 · Cited by 29 · see citing works
“A specific challenge is the large percentage of VUS in the BRCA1 and BRCA2 genes predicted to affect splicing by in silico tools, but lack RNA evidence (26).”
Background
Splicing analysis of 14 BRCA1 missense variants classifies nine variants as pathogenic
Ahlborn, L. B., Dandanell, M., Steffensen, A. Y., Jønson, L., Nielsen, F., & Hansen, T. (2015) · Breast Cancer Research and Treatment · doi:10.1007/s10549-015-3313-7 · Cited by 29
“Asp1778Asn variant are in agreement with recent splicing data using RNA from patient blood samples [27].”
Background
Implementation of next-generation sequencing for molecular diagnosis of hereditary breast and ovarian cancer highlights its genetic heterogeneity
Pinto, P., Paulo, P., Santos, C., Rocha, P., Pinto, C., Veiga, I., Pinheiro, M., Peixoto, A., & Teixeira, M. (2016) · Breast Cancer Research and Treatment · doi:10.1007/s10549-016-3948-z · Cited by 28 · see citing works
“Although these tools cannot be used for classification of variants per se, they are useful for prioritization of VUS for further segregation and functional studies [23, 46].”
MethodResult
Combined Computational–Experimental Analyses of CFTR Exon Strength Uncover Predictability of Exon‐Skipping Level
Aissat, A., de Becdelièvre, A., Golmard, L., Vasseur, C., Costa, C., Chaoui, A., Martin, N., Costes, B., Goossens, M., Girodon, E., et al. (2013) · Human Mutation · doi:10.1002/humu.22300 · Cited by 28 · see citing works
“These observations also emphasize the necessity of using a minigene approach to adjust in silico analysis [Houdayer et al., 2012].”
Method
Splicing in the pathogenesis, diagnosis and treatment of ciliopathies.
Wheway, G., Lord, J., & Baralle, D. (2019) · Biochimica et Biophysica Acta. Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194433 · Cited by 27 · see citing works
Extensive Alternative Splicing of KIR Transcripts
Bruijnesteijn, J., van der Wiel, M. V. D., de Groot, N., Otting, N., de Vos-Rouweler, A. J. M., Lardy, N., de Groot, N. D., & Bontrop, R. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.02846 · Cited by 27 · see citing works
Alport syndrome cold cases: Missing mutations identified by exome sequencing and functional analysis
Chiereghin, C., Robusto, M., Mastrangelo, A., Castorina, P., Montini, G., Giani, M., Duga, S., Asselta, R., & Soldà, G. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178630 · Cited by 27
Clinical and molecular characterization of cystinuria in a French cohort: relevance of assessing large‐scale rearrangements and splicing variants
Gaildrat, P., Lebbah, S., Tebani, A., Sudrié-Arnaud, B., Tostivint, I., Bollée, G., Tubeuf, H., Charles, T., Bertholet-Thomas, A., Goldenberg, A., et al. (2017) · Molecular Genetics & Genomic Medicine · doi:10.1002/mgg3.294 · Cited by 27 · see citing works
“These data confirm the good performance of this type of bioinformatics prediction, as previously shown, in particular for large datasets of BRCA1 and BRCA2 variants (Houdayer et al. 2012).”
ResultSelf-citation
Capillary Electrophoresis Analysis of Conventional Splicing Assays: IARC Analytical and Clinical Classification of 31 BRCA2 Genetic Variants
de Garibay, G. R., Acedo, A., García-Casado, Z., Gutiérrez-Enríquez, S., Tosar, A., Romero, A., Garre, P., Llort, G., Thomassen, M., Díez, O., et al. (2014) · Human Mutation · doi:10.1002/humu.22456 · Cited by 27
“Undoubtedly, in silico analyses might provide high-accuracy predictions, but they do not detect all splicing defects, especially in variants located outside the 5′ and 3′ consensus sites (Houdayer et al., 2012).”
Background
Criteria of the German Consortium for Hereditary Breast and Ovarian Cancer for the Classification of Germline Sequence Variants in Risk Genes for Hereditary Breast and Ovarian Cancer
Wappenschmidt, B., Hauke, J., Faust, U., Niederacher, D., Wiesmüller, L., Schmidt, G., Groß, E., Gehrig, A., Sutter, C., Ramser, J., et al. (2020) · Geburtshilfe und Frauenheilkunde · doi:10.1055/a-1110-0909 · Cited by 26 · see citing works
RNA splicing analysis in genomic medicine.
Wai, H., Douglas, A., & Baralle, D. (2019) · International Journal of Biochemistry and Cell Biology · doi:10.1016/j.biocel.2018.12.009 · Cited by 26 · see citing works
Combination of Whole Genome Sequencing, Linkage, and Functional Studies Implicates a Missense Mutation in Titin as a Cause of Autosomal Dominant Cardiomyopathy With Features of Left Ventricular Noncompaction
Hastings, R., de Villiers, C. P., Hooper, C., Ormondroyd, L., Pagnamenta, A., Lise, S., Salatino, S., Knight, S., Taylor, J. C., Thomson, K., et al. (2016) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.116.001431 · Cited by 26 · see citing works
Russian Association of Endocrinologists clinical practice guidelines for diagnosis and treatment of pheochromocytoma and paraganglioma
Mel'nichenko, G., Troshina, E., Bel'tsevich, D., Kuznetsov, N. S., & Yukina, M. (2015) · Endocrine Surgery · doi:10.14341/serg2015315-33 · Cited by 26 · see citing works
Comparison of In Silico Tools for Splice-Altering Variant Prediction Using Established Spliceogenic Variants: An End-User's Point of View
Jang, W., Park, J., Chae, H., & Kim, M. (2022) · International Journal of Genomics · doi:10.1155/2022/5265686 · Cited by 25 · see citing works
“22, and performed better than the combined analysis of MES/SSF [19].”
BackgroundMethodInfluential
Empirical prediction of variant-activated cryptic splice donors using population-based RNA-Seq data
Dawes, R., Joshi, H., & Cooper, S. T. (2022) · Nature Communications · doi:10.1038/s41467-022-29271-y · Cited by 24 · see citing works
Splicing predictions, minigene analyses, and ACMG‐AMP clinical classification of 42 germline PALB2 splice‐site variants
Valenzuela-Palomo, A., Bueno-Martínez, E., Sanoguera-Miralles, L., Lorca, V., Fraile-Bethencourt, E., Esteban-Sánchez, A., Gómez-Barrero, S., Carvalho, S., Allen, J., García-Álvarez, A., et al. (2021) · Journal of Pathology · doi:10.1002/path.5839 · Cited by 24 · see citing works
“[26 – 28]; (3) creation of de novo alternative splice sites (cut-off ≥ 3.0); (4) regardless of MES predictions, variants at other conserved positions of the acceptor (Y 11 NCAG j G) and donor (MAG j GTRAGT) consensussequences,suchaspyrimidinetopurinechanges…”
BackgroundInfluential
Urine‐derived podocytes‐lineage cells: A promising tool for precision medicine in Alport Syndrome
Daga, S., Baldassarri, M., Rizzo, C. L., Fallerini, C., Imperatore, V., Longo, I., Frullanti, E., Landucci, E., Massella, L., Pecoraro, C., et al. (2018) · Human Mutation · doi:10.1002/humu.23364 · Cited by 24
Minigene‐based splicing analysis and ACMG/AMP‐based tentative classification of 56 ATM variants
Bueno-Martínez, E., Sanoguera-Miralles, L., Valenzuela-Palomo, A., Esteban-Sánchez, A., Lorca, V., Llinares-Burguet, I., Allen, J., García-Álvarez, A., Pérez-Segura, P., Durán, M., et al. (2022) · Journal of Pathology · doi:10.1002/path.5979 · Cited by 23 · see citing works
“We selected likely spliceogenic variants based on: (i) ≥20% decrease of MES scores [21,22], (ii) creation of putative de novo sites (MES cutoff ≥3.”
Method
Pathogenic neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq
Koster, R., Brandão, R., Tserpelis, D., van Roozendaal, C. V., van Oosterhoud, C. V., Claes, K. B., Paulussen, A., Sinnema, M., Vreeburg, M., van der Schoot, V., et al. (2021) · npj Genomic Medicine · doi:10.1038/s41525-021-00258-w · Cited by 23 · see citing works
HRness in Breast and Ovarian Cancers
dos Santos, E. S., Lallemand, F., Petitalot, A., Caputo, S., & Rouleau, E. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21113850 · Cited by 23 · see citing works
Self-citation
BRCA1-No Matter How You Splice It
Li, D., Harlan-Williams, L. M., Kumaraswamy, E., & Jensen, R. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-3190 · Cited by 23 · see citing works

Authors: Houdayer, C., Caux-Moncoutier, V., Krieger, S., Barrois, M., Bonnet, F., Bourdon, V., Bronner, M., Buisson, M., Coulet, F., Gaildrat, P., Lefol, C., Léone, M., Mazoyer, S., Muller, D., Remenieras, A., Révillion, F., Rouleau, E., Sokolowska, J., Vert, J.-P., Lidereau, R., Soubrier, F., Sobol, H., Sevenet, N., Bressac-de Paillerets, B., Hardouin, A., Tosi, M., Sinilnikova, O. M., & Stoppa-Lyonnet, D.
Affiliations: Sorbonne Paris Cité (FR)
Centre François Baclesse (FR)
Institut Gustave Roussy (FR)
Inserm (FR)
Institut Paoli-Calmettes (FR)
Centre Hospitalier Régional et Universitaire de Nancy (FR)
Lyon 1 Université (FR)
Assistance Publique – Hôpitaux de Paris (FR)
Hôpital René Huguenin (FR)
Institut Strauss (FR)
Corresponding author: Houdayer, Claude
ORCID: Houdayer, Claude
Krieger, Sophie
Bourdon, Violaine
Bronner, Myriam
Coulet, Florence
Gaildrat, Pascaline
Mazoyer, Sylvie
Vert, Jean-Philippe
Soubrier, Florent
Sobol, Hagay
Venue: Human Mutation
Publisher: Hindawi Limited
Published: 2012-05-11
Volume: 33
Issue: 8
Pages: 1228-1238
ISSN: 1059-7794 (ISSN-L)
DOI: 10.1002/humu.22101
OpenAlex: W1975196485
Cited by: 239
References: 0
Citations by year: 2026: 3 · 2025: 5 · 2024: 11 · 2023: 6 · 2022: 25 · 2021: 27 · 2020: 22 · 2019: 23 · 2018: 27 · 2017: 23 · 2016: 14 · 2015: 22 · 2014: 11 · 2013: 17 · 2012: 3
FWCI: 10.21
Type: journal article
Language: en
Open access: closed
Licence: doi.wiley.com/10.1002/tdm_license_1.1 (tdm, 1208 d)
Locations: Human Mutation (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › BRCA gene mutations in cancer
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Keywords: BRCA1, BRCA2, variants of uncertain significance, splicing, splice site prediction, in silico tools, transcript analysis, variant interpretation, molecular diagnosis
MeSH terms: Exons, Female, Humans, RNA Splicing, BRCA1 Protein, BRCA2 Protein, Pathology, Molecular

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Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants

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