Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes
Abstract
:1. Introduction
2. Results
2.1. Variants Causing Complete Splicing Impairment (Class 3S)
2.2. Variants Causing Incomplete or Uncertain Splicing Impairment (Class 2S)
2.3. Variants Not Interrupting Splicing (Class 1S)
3. Discussion
4. Materials and Methods
4.1. Ethical Approval
4.2. Patients and Germline Genetic Screening
4.3. Criteria for the Variant to Be Included in Functional Characterization by RNAseq
- (1)
- variants located in the consensus 3′ or 5′ss (consensus donor ss (5′ss) is defined as DNA motif spanning from the last three exonic to the first eight intronic nucleotides and acceptor ss (3′ss) spanning from the last twelve intronic till the first two exonic nucleotides) [1]
- (2)
- deep intronic variants,
- (3)
- deep exonic variants,
4.4. RNAseq
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Cartegni, L.; Chew, S.L.; Krainer, A.R. Listening to silence and understanding nonsense: Exonic mutations that affect splicing. Nat. Rev. Genet. 2002, 3, 285–298. [Google Scholar] [CrossRef] [PubMed]
- Scotti, M.M.; Swanson, M.S. RNA mis-splicing in disease. Nat. Rev. Genet. 2016, 17, 19–32. [Google Scholar] [CrossRef] [PubMed]
- Rivas, M.A.; Pirinen, M.; Conrad, D.F.; Lek, M.; Tsang, E.K.; Karczewski, K.J.; Maller, J.B.; Kukurba, K.R.; DeLuca, D.S.; Fromer, M.; et al. Effect of predicted protein-truncating genetic variants on the human transcriptome. Science 2015, 348, 666–669. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Richards, S.; Aziz, N.; Bale, S.; Bick, D.; Das, S.; Gastier-Foster, J.; Grody, W.W.; Hegde, M.; Lyon, E.; Spector, E.; et al. 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. Genet. Med. 2015, 17, 405–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Houdayer, C.; Caux-Moncoutier, V.; Krieger, S.; Barrois, M.; Bonnet, F.; Bourdon, V.; Bronner, M.; Buisson, M.; Coulet, F.; Gaildrat, P.; et al. Guidelines for splicing analysis in molecular diagnosis derived from a set of 327 combined in silico/in vitro studies on BRCA1 and BRCA2 variants. Hum. Mutat. 2012, 33, 1228–1238. [Google Scholar] [CrossRef]
- Yamada, M.; Suzuki, H.; Shiraishi, Y.; Kosaki, K. Effectiveness of integrated interpretation of exome and corresponding transcriptome data for detecting splicing variants of genes associated with autosomal recessive disorders. Mol. Genet. Metab. Rep. 2019, 21, 100531. [Google Scholar] [CrossRef]
- Karam, R.; Conner, B.; LaDuca, H.; McGoldrick, K.; Krempely, K.; Richardson, M.E.; Zimmermann, H.; Gutierrez, S.; Reineke, P.; Hoang, L.; et al. Assessment of Diagnostic Outcomes of RNA Genetic Testing for Hereditary Cancer. JAMA Netw. Open 2019, 2, e1913900. [Google Scholar] [CrossRef] [Green Version]
- Dragoš, V.Š.; Stegel, V.; Blatnik, A.; Klančar, G.; Krajc, M.; Novaković, S. New Approach for Detection of Normal Alternative Splicing Events and Aberrant Spliceogenic Transcripts with Long-Range PCR and Deep RNA Sequencing. Biology 2021, 10, 706. [Google Scholar] [CrossRef]
- Clinical Genome Resource ClinGen Hereditary Breast, Ovarian and Pancreatic Cancer Expert Panel Specifications to the ACMG/AMP Variant Interpretation Guidelines for ATM Version 1.1. Available online: https://clinicalgenome.org/docs/clingen-hereditary-breast-ovarian-and-pancreatic-cancer-expert-panel-specifications-to-the-acmg-amp-variant-interpretation-1.1/ (accessed on 27 June 2021).
- Fortuno, C.; Lee, K.; Olivier, M.; Pesaran, T.; Mai, P.L.; de Andrade, K.C.; Attardi, L.D.; Crowley, S.; Evans, D.G.; Feng, B.-J.; et al. Specifications of the ACMG/AMP variant interpretation guidelines for germline TP53 variants. Hum. Mutat. 2021, 42, 223–236. [Google Scholar] [CrossRef]
- Brandão, R.D.; Mensaert, K.; López-Perolio, I.; Tserpelis, D.; Xenakis, M.; Lattimore, V.; Walker, L.C.; Kvist, A.; Vega, A.; Gutiérrez-Enríquez, S.; et al. Targeted RNA-seq successfully identifies normal and pathogenic splicing events in breast/ovarian cancer susceptibility and Lynch syndrome genes. Int. J. Cancer 2019, 145, 401–414. [Google Scholar] [CrossRef] [Green Version]
- Smith, A.; Moran, A.; Boyd, M.C.; Bulman, M.; Shenton, A.; Smith, L.; Iddenden, R.; Woodward, E.R.; Lalloo, F.; Maher, E.R.; et al. Phenocopies in BRCA1 and BRCA2 families: Evidence for modifier genes and implications for screening. J. Med. Genet. 2007, 44, 10–15. [Google Scholar] [CrossRef] [Green Version]
- Buckingham, L.; Mitchell, R.; Maienschein-Cline, M.; Green, S.; Hu, V.H.; Cobleigh, M.; Rotmensch, J.; Burgess, K.; Usha, L. Somatic variants of potential clinical significance in the tumors of BRCA phenocopies. Hered. Cancer Clin. Pract. 2019, 17, 21. [Google Scholar] [CrossRef] [PubMed]
- Nix, P.; Mundt, E.; Manley, S.; Coffee, B.; Roa, B. Functional RNA Studies Are a Useful Tool in Variant Classification but Must Be Used With Caution: A Case Study of One BRCA2 Variant. JCO Precis. Oncol. 2020, 4, 730–735. [Google Scholar] [CrossRef] [PubMed]
- Feliubadaló, L.; Moles-Fernández, A.; Santamariña-Pena, M.; Sánchez, A.T.; López-Novo, A.; Porras, L.M.; Blanco, A.; Capellá, G.; de la Hoya, M.; Molina, I.J.; et al. A Collaborative Effort to Define Classification Criteria for ATM Variants in Hereditary Cancer Patients. Clin. Chem. 2021, 67, 518–533. [Google Scholar] [CrossRef] [PubMed]
- Garrett, A.; Durkie, M.; Callaway, A.; Burghel, G.J.; Robinson, R.; Drummond, J.; Torr, B.; Cubuk, C.; Berry, I.R.; Wallace, A.J.; et al. Combining evidence for and against pathogenicity for variants in cancer susceptibility genes: CanVIG-UK consensus recommendations. J. Med. Genet. 2021, 58, 297–304. [Google Scholar] [CrossRef]
- Piotrowski, A.; Xie, J.; Liu, Y.F.; Poplawski, A.B.; Gomes, A.R.; Madanecki, P.; Fu, C.; Crowley, M.R.; Crossman, D.K.; Armstrong, L.; et al. Germline loss-of-function mutations in LZTR1 predispose to an inherited disorder of multiple schwannomas. Nat. Genet. 2013, 46, 182–187. [Google Scholar] [CrossRef]
- Sutton, I.J.; Last, J.I.K.; Ritchie, S.J.; Harrington, H.J.; Byrd, P.J.; Taylor, A.M.R. Adult-onset ataxia telangiectasia due to ATM 5762ins137 mutation homozygosity. Ann. Neurol. 2004, 55, 891–895. [Google Scholar] [CrossRef]
- Hu, C.; Hart, S.N.; Gnanaolivu, R.; Huang, H.; Lee, K.Y.; Na, J.; Gao, C.; Lilyquist, J.; Yadav, S.; Boddicker, N.J.; et al. A Population-Based Study of Genes Previously Implicated in Breast Cancer. N. Engl. J. Med. 2021, 384, 440–451. [Google Scholar] [CrossRef]
- Dorling, L.; Carvalho, S.; Allen, J.; González-Neira, A.; Luccarini, C.; Wahlström, C.; Pooley, K.A.; Parsons, M.T.; Fortuno, C.; Wang, Q.; et al. Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women. N. Engl. J. Med. 2021, 384, 428–439. [Google Scholar]
- Nieminen, T.T.; Pavicic, W.; Porkka, N.; Kankainen, M.; Järvinen, H.J.; Lepistö, A.; Peltomäki, P. Pseudoexons provide a mechanism for allele-specific expression of APC in familial adenomatous polyposis. Oncotarget 2016, 7, 70685–70698. [Google Scholar] [CrossRef] [Green Version]
- Castro-Vega, L.J.; Buffet, A.; De Cubas, A.A.; Cascón, A.; Menara, M.; Khalifa, E.; Amar, L.; Azriel, S.; Bourdeau, I.; Chabre, O.; et al. Germline mutations in FH confer predisposition to malignant pheochromocytomas and paragangliomas. Hum. Mol. Genet. 2014, 23, 2440–2446. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Plon, S.E.; Eccles, D.M.; Easton, D.; Foulkes, W.D.; Genuardi, M.; Greenblatt, M.S.; Hogervorst, F.B.L.; Hoogerbrugge, N.; Spurdle, A.B.; Tavtigian, S.V.; et al. Sequence variant classification and reporting: Recommendations for improving the interpretation of cancer susceptibility genetic test results. Hum. Mutat. 2008, 29, 1282–1291. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Morak, M.; Schaefer, K.; Steinke-Lange, V.; Koehler, U.; Keinath, S.; Massdorf, T.; Mauracher, B.; Rahner, N.; Bailey, J.; Kling, C.; et al. Full-length transcript amplification and sequencing as universal method to test mRNA integrity and biallelic expression in mismatch repair genes. Eur. J. Hum. Genet. 2019, 27, 1808–1820. [Google Scholar] [CrossRef] [PubMed]
- Landrum, M.J.; Lee, J.M.; Benson, M.; Brown, G.R.; Chao, C.; Chitipiralla, S.; Gu, B.; Hart, J.; Hoffman, D.; Jang, W.; et al. ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018, 46, D1062–D1067. [Google Scholar] [CrossRef] [Green Version]
- Pagenstecher, C.; Wehner, M.; Friedl, W.; Rahner, N.; Aretz, S.; Friedrichs, N.; Sengteller, M.; Henn, W.; Buettner, R.; Propping, P.; et al. Aberrant splicing in MLH1 and MSH2 due to exonic and intronic variants. Hum. Genet. 2006, 119, 9–22. [Google Scholar] [CrossRef]
- Thompson, B.A.; Walters, R.; Parsons, M.T.; Dumenil, T.; Drost, M.; Tiersma, Y.; Lindor, N.M.; Tavtigian, S.V.; de Wind, N.; Spurdle, A.B.; et al. Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation. Front. Genet. 2020, 11, 798. [Google Scholar] [CrossRef]
- Tubeuf, H.; Caputo, S.M.; Sullivan, T.; Rondeaux, J.; Krieger, S.; Caux-Moncoutier, V.; Hauchard, J.; Castelain, G.; Fiévet, A.; Meulemans, L.; et al. Calibration of Pathogenicity Due to Variant-Induced Leaky Splicing Defects by Using BRCA2 Exon 3 as a Model System. Cancer Res. 2020, 80, 3593–3605. [Google Scholar] [CrossRef]
- Høberg-Vetti, H.; Ognedal, E.; Buisson, A.; Vamre, T.B.A.; Ariansen, S.; Hoover, J.M.; Eide, G.E.; Houge, G.; Fiskerstrand, T.; Haukanes, B.I.; et al. The intronic BRCA1 c.5407-25T>A variant causing partly skipping of exon 23—a likely pathogenic variant with reduced penetrance? Eur. J. Hum. Genet. 2020, 28, 1078–1086. [Google Scholar] [CrossRef]
- Desmond, A.; Kurian, A.W.; Gabree, M.; Mills, M.A.; Anderson, M.J.; Kobayashi, Y.; Horick, N.; Yang, S.; Shannon, K.M.; Tung, N.; et al. Clinical Actionability of Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Risk Assessment. JAMA Oncol. 2015, 1, 943–951. [Google Scholar] [CrossRef]
- Kotler, E.; Shani, O.; Goldfeld, G.; Lotan-Pompan, M.; Tarcic, O.; Gershoni, A.; Hopf, T.A.; Marks, D.S.; Oren, M.; Segal, E. A Systematic p53 Mutation Library Links Differential Functional Impact to Cancer Mutation Pattern and Evolutionary Conservation. Mol. Cell 2018, 71, 178–190.e8. [Google Scholar] [CrossRef] [Green Version]
- Findlay, G.M.; Daza, R.M.; Martin, B.; Zhang, M.D.; Leith, A.P.; Gasperini, M.; Janizek, J.D.; Huang, X.; Starita, L.M.; Shendure, J. Accurate classification of BRCA1 variants with saturation genome editing. Nature 2018, 562, 217–222. [Google Scholar] [CrossRef] [PubMed]
- Wai, H.A.; Lord, J.; Lyon, M.; Gunning, A.; Kelly, H.; Cibin, P.; Seaby, E.G.; Spiers-Fitzgerald, K.; Lye, J.; Ellard, S.; et al. Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance. Genet. Med. 2020, 22, 1005–1014. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Setrajcic Dragos, V.; Blatnik, A.; Klancar, G.; Stegel, V.; Krajc, M.; Blatnik, O.; Novakovic, S. Two Novel NF1 Pathogenic Variants Causing the Creation of a New Splice Site in Patients With Neurofibromatosis Type I. Front. Genet. 2019, 10, 762. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Klančar, G.; Blatnik, A.; Šetrajčič Dragoš, V.; Vogrič, V.; Stegel, V.; Blatnik, O.; Drev, P.; Gazič, B.; Krajc, M.; Novaković, S. A Novel Germline MLH1 In-Frame Deletion in a Slovenian Lynch Syndrome Family Associated with Uncommon Isolated PMS2 Loss in Tumor Tissue. Genes 2020, 11, 325. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Krivokuca, A.; Dragos, V.S.; Stamatovic, L.; Blatnik, A.; Boljevic, I.; Stegel, V.; Rakobradovic, J.; Skerl, P.; Jovandic, S.; Krajc, M.; et al. Novel BRCA1 splice-site mutation in ovarian cancer patients of Slavic origin. Fam. Cancer 2018, 17, 179–185. [Google Scholar] [CrossRef]
- Jaganathan, K.; Kyriazopoulou Panagiotopoulou, S.; McRae, J.F.; Darbandi, S.F.; Knowles, D.; Li, Y.I.; Kosmicki, J.A.; Arbelaez, J.; Cui, W.; Schwartz, G.B.; et al. Predicting Splicing from Primary Sequence with Deep Learning. Cell 2019, 176, 535–548.e24. [Google Scholar] [CrossRef] [Green Version]
- Leman, R.; Gaildrat, P.; Le Gac, G.; Ka, C.; Fichou, Y.; Audrezet, M.-P.; Caux-Moncoutier, V.; Caputo, S.M.; Boutry-Kryza, N.; Léone, M.; 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 Res. 2018, 46, 7913–7923. [Google Scholar] [CrossRef] [Green Version]
- Thomassen, M.; Blanco, A.; Montagna, M.; Hansen, T.V.O.O.; Pedersen, I.S.; Gutiérrez-Enríquez, S.; Menéndez, M.; Fachal, L.; Santamariña, M.; Steffensen, A.Y.; et al. Characterization of BRCA1 and BRCA2 splicing variants: A collaborative report by ENIGMA consortium members. Breast Cancer Res. Treat. 2012, 132, 1009–1023. [Google Scholar] [CrossRef]
- Santos, C.; Peixoto, A.; Rocha, P.; Pinto, P.; Bizarro, S.; Pinheiro, M.; Pinto, C.; Henrique, R.; Teixeira, M.R. Pathogenicity Evaluation of BRCA1 and BRCA2 Unclassified Variants Identified in Portuguese Breast/Ovarian Cancer Families. J. Mol. Diagn. 2014, 16, 324–334. [Google Scholar] [CrossRef]
- Dobin, A.; Gingeras, T.R. Mapping RNA-seq Reads with STAR. Curr. Protoc. Bioinform. 2015, 51, 11.14.1–11.14.19. [Google Scholar] [CrossRef] [Green Version]
- Davy, G.; Rousselin, A.; Goardon, N.; Castéra, L.; Harter, V.; Legros, A.; Muller, E.; Fouillet, R.; Brault, B.; Smirnova, A.S.; et al. Detecting splicing patterns in genes involved in hereditary breast and ovarian cancer. Eur. J. Hum. Genet. 2017, 25, 1147–1154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
cDNA Variant | Variant Type | Splicing Event Description | Effect on mRNA Splicing | Predicted Protein Change | % Aberrant Transcript Carrier | mean % Aberrant Transcript Controls (N = 5) | Splicing Classification [5] | ACMG/AMP Evidences | ACMG/AMP Classification after RNAseq |
---|---|---|---|---|---|---|---|---|---|
APC:c.1408+743_1408+745delinsACG intronic | DI | ▼10A ▼10B | r.1408_1409ins1408+647_1408+744 r.1408_1409ins1408+602_1408+744 | p.(Gly471Serfs*60) p.(Gly470Alafs*13) | 27% 0.3% | ND ND | 2S | PM2, PP3, PS3-m, PP4 | 4-LP |
ATM:c.172G>T missense | DE | Δ3qA Δ3qB | r.171_185del r.171_195del r.172g>u | p.(Trp57*) p.(Trp57Cysfs*14) p.(Asp58Tyr) | 41.4% 1.3% 8% | ND ND ND | 2S | PM2-supp, PP3, PS3-m | 3-VUS |
ATM:c.5763-1056G>A intronic | DI | ▼38A ▼38B | r.5762_5763ins5762+985_5763-1055 r.5762_5763ins5762+1002_5763-1055 | p.(Arg1921Serfs*6) p.(Arg1921Serfs*12) | 20.8% 1.6% | ND ND | 2S | PM2-supp, PP3, PS3-m | 3-VUS |
ATM:c.7816A>G missense | DE | Δ53 | r.7789_7927del r.7816a>g | p.(Asp2597Lysfs*3) p.(Ile2606Val) | 3% 43% | 0.7% ND | 2S | PP3 | 3-VUS |
FH:c.1237-11C>G intronic | 3′ss | ▼8p | r.1236_1237ins1237-1_1237-10 | p.(Ile413Serfs*5) | 40% | ND | 2S | PM2, PP3, PS3-m, PP4 | 4-LP |
LZTR1:c.1942G>T missense | 5′ss | Δ16q Δ16 | r.1831_1942del r.1786_1942del r.1942g>u | p.(Val611Alafs*4) p.(Glu596Alafs*4) p.(Gly648Cys) | 36% 2% ND | ND ND ND | 3S | PM2, PP3, PS3, PP4 | 4-LP |
MSH6:c.3646+5G>A intronic | 5′ss | Δ7 | r.3557_3646del | p.(Glu1187_Gly1216del) | 6.8% | ND | 2S | PM2, PP3, PM4 | 3-VUS |
PALB2:c.2379C>T synonymous | DE | Δ5q | r.2378_2514del r.2379c>u | p.(Gly793Aspfs*2) p.(Gly793=) | 1.7%; 0.3% 44%; 50% | ND ND | 2S | BS3-SA, BS1, PP3 | 2-LB |
PALB2:c.3495G>A synonymous | DE | / | no aberrant transcript detected r.3495g>a | / p.(Ser1165=) | ND 48% | ND ND | 1S | BS3-SA, BS1 PP3 | 2-LB |
RAD51C:c.1027-3C>G intronic | 3′ss | Δ9pA Δ9pB Δ9pC | r.1027_1032del r.1027_1078del r.1027_1081del | p.(Pro343_Gln344del) p.(Pro343Lysfs*4) p.(Pro343Valfs*3) | 10.5% 4.9% 0.04% | 0.16% ND ND | 2S | PM2, PP3, PS3-m | 3-VUS |
RAD51C:c.779G>A missense | DE | / | no aberrant transcript detected r.779g>a | / p.(Arg260Gln) | ND 45% | ND ND | 1S | PM2, PP3 | 3-VUS |
TP53:c.74+23C>T intronic | DI | ▼2q | r.74_75ins74+1_74+21 | p.(Leu26*) | 1.1% and 1.7% | ND | 2S | BS3-SA | 2-LB |
Patient Number | cDNA Variant | Personal History of Tumors (Age at Diagnosis) | Family History of Tumors (Age at Diagnosis) | Another Pathogenic Variant Detected in a Patient. |
---|---|---|---|---|
1 | APC:c.1408+743_1408+745delinsACG | CP (51) | RC (79) | - |
2 | ATM:c.5763-1056G>A | Bil BC (61) | GC (60); UC (52) | - |
3 | ATM:c.7816A>G | BC (41) | - | BRCA2:c.4139_4140dup p.(Lys1381Leufs*8) |
4 | ATM:c.7816A>G | Bil BC (49,52) | - | - |
5 | ATM:c.172G>T | MM (53), BC (68) | 3 NHL (49,76,80); 2 MM (51,79), BC (84); GCT (16) | - |
6 | FH:c.1237-11C>G | L (37) | BC (53), MM (52) | - |
7 | MSH6:c.3646+5G>A | BC (37) | - | - |
8 | PALB2:c.2379C>T | BC (78) | BC (41); GC (82) | - |
9 | PALB2:c.2379C>T | BC (46) | BC (42) | CHEK2:c.444+1G>A p.? |
10 | PALB2:c.3495G>A | BC (59) | 2 BC (37,40); LaC (58) | - |
11 | RAD51C:c.1027-3C>G | OC (49) | - | - |
12 | RAD51C:c.1027-3C>G | OC (74) | NHL (46), NSCLC (54) | - |
13 | RAD51C:c.779G>A | BC (43) | BC (41), OC (41) | BRCA1:c.3718C>T p.(Gln1240*) |
14 | TP53:c.74+23C>T | MBC (42), NSCLC (61) | SCLC (60), LiC (59); CRC (54), GC (75), PrC (72); CC (46), LaC (57) | - |
15 | TP53:c.74+23C>T | BC (49) | 2 BC (64,84); PrC (70) | - |
16 | LZTR1:c.1942G>T | SCH (54) | NA | - |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dragoš, V.Š.; Strojnik, K.; Klančar, G.; Škerl, P.; Stegel, V.; Blatnik, A.; Banjac, M.; Krajc, M.; Novaković, S. Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes. Int. J. Mol. Sci. 2022, 23, 7446. https://doi.org/10.3390/ijms23137446
Dragoš VŠ, Strojnik K, Klančar G, Škerl P, Stegel V, Blatnik A, Banjac M, Krajc M, Novaković S. Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes. International Journal of Molecular Sciences. 2022; 23(13):7446. https://doi.org/10.3390/ijms23137446
Chicago/Turabian StyleDragoš, Vita Šetrajčič, Ksenija Strojnik, Gašper Klančar, Petra Škerl, Vida Stegel, Ana Blatnik, Marta Banjac, Mateja Krajc, and Srdjan Novaković. 2022. "Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes" International Journal of Molecular Sciences 23, no. 13: 7446. https://doi.org/10.3390/ijms23137446
APA StyleDragoš, V. Š., Strojnik, K., Klančar, G., Škerl, P., Stegel, V., Blatnik, A., Banjac, M., Krajc, M., & Novaković, S. (2022). Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes. International Journal of Molecular Sciences, 23(13), 7446. https://doi.org/10.3390/ijms23137446