ArticleScientific reports2024
Rapid detection of the SARS-CoV-2 omicron variants based on high-resolution melting curve analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- The virology of Omicron: pathophysiology, immune regulation, and clinical impact of SARS-CoV-2 sub variants.Virology journal · 2025Review
- Next-Generation Nucleic Acid-Based Diagnostics for Viral Pathogens: Lessons Learned from the SARS-CoV-2 Pandemic.Microorganisms · 2025Review
- The Detection and Differentiation of Pigeon Adenovirus Types 1 and 2 via a High-Resolution Melting Curve Platform.Microorganisms · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
With the continuous spread of the SARS-CoV-2 globally, viral mutations have accumulated. As a result, SARS-CoV-2 became more contagious, and has a higher risk of immune escape and reinfection. To identify variants and have an awareness of the prevalence of these variants, this study selected four segments containing mutations on the S gene of the SARS-CoV-2. Then a rapid and convenient variants detection method was established using high-resolution melting(HRM) analysis combined with nested polymerase chain reaction(PCR). The total detection process takes about 5 h. Through comprehensive analysis of the results from the four reaction systems, the identification of seven important Omicron variants(BA.2, BA.2.75, BA.5.2, BF.7, BQ.1, XBB.1 and XBB.2) can be achieved, with significant differentiation in the melting curves of each variant group. The method established in this study was used to genotype positive specimens in COVID-19 nucleic acid testing, the overall concordance rate compared to whole genome sequencing results was 88.9%, and the positive concordance rate of each sublineage was greater than 80% and the negative concordance rate was greater than 94.4%. The detection of clinical specimens has demonstrated that the HRM analysis established in this study is an effective, rapid and convenient variant identification method, which can be used for monitoring SARS-CoV-2 variants and has important value in addressing public health issues caused by the ongoing mutations of the SARS-CoV-2.
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