Author:
Mentes Anikó,Papp Krisztián,Visontai Dávid,Stéger József,Csabai István,Papp Krisztián,Visontai Dávid,Stéger József,Cochrane Guy,Rahman Nadim,Cummins Carla,Yuan David Yu,Selvakumar Sandeep,Mansurova Milena,O’Cathail Colman,Sokolov Alexey,Thorne Ross,Koopmans Marion,Nieuwenhuijse David,Oude-Munnink Bas,Worp Nathalie,Amid Clara,Csabai István,Medgyes-Horváth Anna,Pipek Orsolya Anna,
Abstract
AbstractDue 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.
Funder
Horizon 2020-BY-COVID
Horizon 2020-VEO
National Research, Development and Innovation Fund of Hungary
Eötvös Loránd University
Publisher
Springer Science and Business Media LLC