Abstract
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.
【초록키워드】 SARS-CoV-2, Mutation, Variation, variant, diagnostic, omicron, RT-PCR, PCR, Accuracy, dataset, Analysis, Neutral, strain, Efficiency, PCR efficiency, overlapping, gold standard, primer sets, genomic variation, primer, approach, susceptible, SARS-CoV-2 viral, Sample, primer set, target region, anticipated, the SARS-CoV-2 genome, 【제목키워드】 Mutation, Region, SARS-CoV-2 PCR, identification, primer,