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      Splice Site Variants in the KCNQ1 and SCN5A Genes: Transcript Analysis as a Tool in Supporting Pathogenicity

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          Abstract

          Background

          Approximately 75% of clinically definite long QT syndrome (LQTS) cases are caused by mutations in the KCNQ1, KCNH2 and SCN5A genes. Of these mutations, a small proportion (3.2-9.2%) are predicted to affect splicing. These mutations present a particular challenge in ascribing pathogenicity.

          Methods

          Here we report an analysis of the transcriptional consequences of two mutations, one in the KCNQ1 gene (c.781_782delinsTC) and one in the SCN5A gene (c.2437-5C>A), which are predicted to affect splicing. We isolated RNA from lymphocytes and used a directed PCR amplification strategy of cDNA to show mis-spliced transcripts in mutation-positive patients.

          Results

          The loss of an exon in each mis-spliced transcript had no deduced effect on the translational reading frame. The clinical phenotype corresponded closely with genotypic status in family members carrying the KCNQ1 splice variant, but not in family members with the SCN5A splice variant. These results are put in the context of a literature review, where only 20% of all splice variants reported in the KCNQ1, KCNH2 and SCN5A gene entries in the HGMDPro 2015.4 database have been evaluated using transcriptional assays.

          Conclusions

          Prediction programmes play a strong role in most diagnostic laboratories in classifying variants located at splice sites; however, transcriptional analysis should be considered critical to confirm mis-splicing. Critically, this study shows that genuine mis- splicing may not always imply clinical significance, and genotype/phenotype cosegregation remains important even when mis-splicing is confirmed.

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          Most cited references10

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          SCN5A mutations associated with an inherited cardiac arrhythmia, long QT syndrome.

          Long QT syndrome (LQT) is an inherited disorder that causes sudden death from cardiac arrhythmias, specifically torsade de pointes and ventricular fibrillation. We previously mapped three LQT loci: LQT1 on chromosome 11p15.5, LQT2 on 7q35-36, and LQT3 on 3p21-24. Here we report genetic linkage between LQT3 and polymorphisms within SCN5A, the cardiac sodium channel gene. Single strand conformation polymorphism and DNA sequence analyses reveal identical intragenic deletions of SCN5A in affected members of two unrelated LQT families. The deleted sequences reside in a region that is important for channel inactivation. These data suggest that mutations in SCN5A cause chromosome 3-linked LQT and indicate a likely cellular mechanism for this disorder.
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            Splicing in action: assessing disease causing sequence changes.

            Variations in new splicing regulatory elements are difficult to identify exclusively by sequence inspection and may result in deleterious effects on precursor (pre) mRNA splicing. These mutations can result in either complete skipping of the exon, retention of the intron, or the introduction of a new splice site within an exon or intron. Sometimes mutations that do not disrupt or create a splice site activate pre-existing pseudo splice sites, consistent with the proposal that introns contain splicing inhibitory sequences. These variants can also affect the fine balance of isoforms produced by alternatively spliced exons and in consequence cause disease. Available genomic pathology data reveal that we are still partly ignorant of the basic mechanisms that underlie the pre-mRNA splicing process. The fact that human pathology can provide pointers to new modulatory elements of splicing should be exploited.
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              Spectrum and prevalence of mutations from the first 2,500 consecutive unrelated patients referred for the FAMILION long QT syndrome genetic test.

              Long QT syndrome (LQTS) is a potentially lethal, highly treatable cardiac channelopathy for which genetic testing has matured from discovery to translation and now clinical implementation. Here we examine the spectrum and prevalence of mutations found in the first 2,500 unrelated cases referred for the FAMILION LQTS clinical genetic test. Retrospective analysis of the first 2,500 cases (1,515 female patients, average age at testing 23 +/- 17 years, range 0 to 90 years) scanned for mutations in 5 of the LQTS-susceptibility genes: KCNQ1 (LQT1), KCNH2 (LQT2), SCN5A (LQT3), KCNE1 (LQT5), and KCNE2 (LQT6). Overall, 903 referral cases (36%) hosted a possible LQTS-causing mutation that was absent in >2,600 reference alleles; 821 (91%) of the mutation-positive cases had single genotypes, whereas the remaining 82 patients (9%) had >1 mutation in > or =1 gene, including 52 cases that were compound heterozygous with mutations in >1 gene. Of the 562 distinct mutations, 394 (70%) were missense, 428 (76%) were seen once, and 336 (60%) are novel, including 92 of 199 in KCNQ1, 159 of 226 in KCNH2, and 70 of 110 in SCN5A. This cohort increases the publicly available compendium of putative LQTS-associated mutations by >50%, and approximately one-third of the most recently detected mutations continue to be novel. Although control population data suggest that the great majority of these mutations are pathogenic, expert interpretation of genetic test results will remain critical for effective clinical use of LQTS genetic test results.
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                Author and article information

                Journal
                J Clin Med Res
                J Clin Med Res
                Elmer Press
                Journal of Clinical Medicine Research
                Elmer Press
                1918-3003
                1918-3011
                August 2017
                1 July 2017
                : 9
                : 8
                : 709-718
                Affiliations
                [a ]Diagnostic Genetics, LabPlus, Auckland City Hospital, Auckland, New Zealand
                [b ]Department of Cardiology, Waikato Hospital, Hamilton, New Zealand
                [c ]Cardiac Inherited Disease Group, Auckland City Hospital, Auckland, New Zealand
                [d ]Green Lane Paediatric and Congenital Cardiac Services, Starship Children’s Hospital, Auckland, New Zealand
                Author notes
                [e ]Corresponding Author: Donald R. Love, Diagnostic Genetics, LabPlus, PO Box 110031, Auckland City Hospital, Auckland 1148, New Zealand. Email: donaldl@ 123456adhb.govt.nz
                Article
                10.14740/jocmr2894w
                5505308
                28725320
                f6955385-1cc2-45b2-ab2f-0fcb6b8bdda0
                Copyright 2017, Leong et al.

                This article is distributed under the terms of the Creative Commons Attribution Non-Commercial 4.0 International License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 December 2016
                : 22 May 2017
                Categories
                Short Communication

                Medicine
                long qt syndrome,splicing,transcript analysis,in silico analysis
                Medicine
                long qt syndrome, splicing, transcript analysis, in silico analysis

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