ArticleGenes & genomics2022
Identification of conserved regions from 230,163 SARS-CoV-2 genomes and their use in diagnostic PCR primer design.
Article in Genes & genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Molecular pathogenesis, global epidemiological trends, and treatment strategies for pteropine orthoreoviruses: a narrative review.Emerging microbes & infections · 2026Review
- Simultaneous detection of respiratory virus RNA on environmental surfaces in a university setting by a sensitive Surface 3-Step PCR platform.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs the rapidly evolving characteristic of SARS-CoV-2 could result in false negative diagnosis, the use of as much sequence data as possible is key to the identification of conserved viral sequences. However, multiple alignment of massive genome sequences is computationally intensive.
objectiveTo extract conserved sequences from SARS-CoV-2 genomes for the design of diagnostic PCR primers using a bioinformatics approach that can handle massive genomic sequences efficiently.
methodsA total of 230,163 full-length viral genomes were retrieved from the NCBI SARS-CoV-2 Resources and GISAID EpiCoV database. This number was reduced to 14.11% following removal of 5'-/3'-untranslated regions and sequence dereplication. Fast, reference-based, multiple sequence alignments identified conserved sequences and specific primer sets were designed against these regions using a conventional tool. Primer sets chosen among the candidates were evaluated by in silico PCR and RT-qPCR.
resultsOut of 17 conserved sequences (totaling 4.3 kb), two primer sets targeting the nsp2 and ORF3a genes were picked that exhibited > 99.9% in silico amplification coverage against the original dataset (230,163 genomes) when a 5% mismatch between the primers and target was allowed. In addition, the primer sets successfully detected nine SARS-CoV-2 variant RNA samples (Alpha, Beta, Gamma, Delta, Epsilon, Zeta, Eta, Iota, and Kappa) in experimental RT-qPCR validations.
conclusionIn addition to the RdRp, E, N, and S genes that are targeted commonly, our approach can be used to identify novel primer targets in SARS-CoV-2 and should be a priority strategy in the event of novel SARS-CoV-2 variants or other pandemic outbreaks.
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