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Publications

Journal Article Research Support, Non-U.S. Gov't Epublish 42 citations

PubMed: 30770838 DOI: 10.1038/s41598-019-38581-z

Cost-effective and robust genotyping using double-mismatch allele-specific quantitative PCR.

Sci Rep 9(1):2150

Authors: Steve Lefever, Ali Rihani, Joni Van der Meulen, Filip Pattyn, Tom Van Maerken, Jo Van Dorpe, Jan Hellemans, Jo Vandesompele

Affiliations

  • Center for Medical Genetics Ghent, Ghent University, Ghent, 9000, Belgium.
  • Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, 9000, Belgium.
  • Bioinformatics Institute Ghent (BIG), Ghent University, Ghent, 9000, Belgium.
  • Center for Medical Genetics Ghent, Ghent University, Ghent, 9000, Belgium.
  • Karolinska Institute, Stockholm, SE-171 77, Sweden.
  • Ontoforce, Ghent, 9000, Belgium.
  • Cancer Research Institute Ghent (CRIG), Ghent University, Ghent, 9000, Belgium.
  • Department of Pathology, University Hospital Ghent, Ghent, 9000, Belgium.
  • Biogazelle, Zwijnaarde, 9052, Belgium.
  • Bioinformatics Institute Ghent (BIG), Ghent University, Ghent, 9000, Belgium.

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.

MeSH

Polymerase Chain Reaction, Alleles, Natural Science Disciplines, Mutation

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