Identification of mutations in SARS-CoV-2 PCR primer regions

Anikó Mentes*, Krisztián Papp, VEO Technical Working Group, Dávid Visontai, József Stéger, István Csabai, Krisztián Papp, Dávid Visontai, József Stéger, Guy Cochrane, Nadim Rahman, Carla Cummins, David Yu Yuan, Sandeep Selvakumar, Milena Mansurova, Colman O’Cathail, Alexey Sokolov, Ross Thorne, Marion Koopmans, David NieuwenhuijseBas Oude-Munnink, Nathalie Worp, Clara Amid, István Csabai, Anna Medgyes-Horváth, Orsolya Anna Pipek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
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Due to the constantly increasing number of mutations in the SARS-CoV-2 genome, concerns have emerged over the possibility of decreased diagnostic accuracy of reverse transcription-polymerase chain reaction (RT-PCR), the gold standard diagnostic test for SARS-CoV-2. We propose an analysis pipeline to discover genomic variations overlapping the target regions of commonly used PCR primer sets. We provide the list of these mutations in a publicly available format based on a dataset of more than 1.2 million SARS-CoV-2 samples. Our approach distinguishes among mutations possibly having a damaging impact on PCR efficiency and ones anticipated to be neutral in this sense. Samples are categorized as “prone to misclassification” vs. “likely to be correctly detected” by a given PCR primer set based on the estimated effect of mutations present. Samples susceptible to misclassification are generally present at a daily rate of 2% or lower, although particular primer sets seem to have compromised performance when detecting Omicron samples. As different variant strains may temporarily gain dominance in the worldwide SARS-CoV-2 viral population, the efficiency of a particular PCR primer set may change over time, therefore constant monitoring of variations in primer target regions is highly recommended.

Original languageEnglish
Article number18651
JournalScientific Reports
Issue number1
Publication statusPublished - 4 Nov 2022

Bibliographical note

Open access funding provided by Eötvös Loránd University.

Publisher Copyright: © 2022, The Author(s).


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