Literature DB >> 16510432

Allele dropout in PCR-based diagnosis of Wilson disease: mechanisms and solutions.

Ching-Wan Lam1, Chloe M Mak.   

Abstract

BACKGROUND: We investigated the mechanisms leading to allele dropout-the nonamplification of 1 of the alleles-in PCR-based diagnosis of Wilson disease (WD).
METHODS: We extracted genomic DNA from blood samples from 6 WD patients (P1-P6) with allele dropouts detected in a previous study of WD in a Hong Kong Chinese population. We amplified the ATP7B gene by PCR and performed direct DNA sequencing of all exons of the ATP7B gene. To support the proposed mechanism of allele dropout, we used proofreading DNA polymerase, primer design avoiding single-nucleotide polymorphism sites, and duplex PCR.
RESULTS: Patients P1-P4 were all apparently homozygous for a known disease-causing mutation, c.2975C > T (p.P992L) in exon 13. Patient P5 was apparently homozygous for a novel mutation, c.2524G > A, and patient P6 was apparently homozygous for another known mutation, c.522_523insA (p.K175K-fs). In all cases, we determined that the patients were actually heterozygous for these mutations.
CONCLUSION: Our results confirm that allele dropout is the mechanism causing apparent homozygosity of heterozygous mutations in these WD patients.

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Year:  2006        PMID: 16510432     DOI: 10.1373/clinchem.2005.060491

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  6 in total

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Journal:  Urol Res       Date:  2008-11-04

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Journal:  J Hum Genet       Date:  2017-04-06       Impact factor: 3.172

4.  Interpretation of Autosomal Recessive Kidney Diseases With "Presumed Homozygous" Pathogenic Variants Should Consider Technical Pitfalls.

Authors:  Haiyue Deng; Yanqin Zhang; Yong Yao; Huijie Xiao; Baige Su; Ke Xu; Na Guan; Jie Ding; Fang Wang
Journal:  Front Pediatr       Date:  2020-04-17       Impact factor: 3.418

5.  The validation and clinical implementation of BRCAplus: a comprehensive high-risk breast cancer diagnostic assay.

Authors:  Hansook Kim Chong; Tao Wang; Hsiao-Mei Lu; Sara Seidler; Hong Lu; Steven Keiles; Elizabeth C Chao; A J Stuenkel; Xiang Li; Aaron M Elliott
Journal:  PLoS One       Date:  2014-05-15       Impact factor: 3.240

6.  Analysis of amplicon-based NGS data from neurological disease gene panels: a new method for allele drop-out management.

Authors:  Susanna Zucca; Margherita Villaraggia; Stella Gagliardi; Gaetano Salvatore Grieco; Marialuisa Valente; Cristina Cereda; Paolo Magni
Journal:  BMC Bioinformatics       Date:  2016-11-08       Impact factor: 3.169

  6 in total

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