Abstract

For a wide range of diseases, SNPs in the genome are the underlying mechanism of dysfunction. Therefore, targeted detection of these variations is of high importance for early diagnosis and (familial) screenings. While allele-specific PCR has been around for many years, its adoption for SNP genotyping or somatic mutation detection has been hampered by its low discriminating power and high costs. To tackle this, we developed a cost-effective qPCR based method, able to detect SNPs in a robust and specific manner. This study describes how to combine the basic principles of allele-specific PCR (the combination of a wild type and variant primer) with the straightforward readout of DNA-binding dye based qPCR technology. To enhance the robustness and discriminating power, an artificial mismatch in the allele-specific primer was introduced. The resulting method, called double-mismatch allele-specific qPCR (DMAS-qPCR), was successfully validated using 12 SNPs and 15 clinically relevant somatic mutations on 48 cancer cell lines. It is easy to use, does not require labeled probes and is characterized by high analytical sensitivity and specificity. DMAS-qPCR comes with a complimentary online assay design tool, available for the whole scientific community, enabling researchers to design custom assays and implement those as a diagnostic test.

Details

Title
Cost-effective and robust genotyping using double-mismatch allele-specific quantitative PCR
Author
Lefever, Steve 1   VIAFID ORCID Logo  ; Rihani, Ali 2   VIAFID ORCID Logo  ; Van der Meulen Joni 3 ; Pattyn Filip 4   VIAFID ORCID Logo  ; Tom, Van Maerken 5 ; Van Dorpe Jo 6 ; Hellemans, Jan 7 ; Vandesompele Jo 8   VIAFID ORCID Logo 

 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Cancer Research Institute Ghent (CRIG), Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Bioinformatics Institute Ghent (BIG), Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798) 
 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Karolinska Institute, Stockholm, Sweden (GRID:grid.4714.6) (ISNI:0000 0004 1937 0626) 
 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798) 
 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ontoforce, Ghent, Belgium (GRID:grid.5342.0) 
 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Cancer Research Institute Ghent (CRIG), Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798) 
 University Hospital Ghent, Department of Pathology, Ghent, Belgium (GRID:grid.410566.0) (ISNI:0000 0004 0626 3303) 
 Biogazelle, Zwijnaarde, Belgium (GRID:grid.410566.0) 
 Ghent University, Center for Medical Genetics Ghent, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Biogazelle, Zwijnaarde, Belgium (GRID:grid.5342.0); Ghent University, Cancer Research Institute Ghent (CRIG), Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798); Ghent University, Bioinformatics Institute Ghent (BIG), Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2181777006
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.