RT-PCR genotyping outperforms whole-genome sequencing in speedy and accurate COVID-19 variant tracking

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In a recent study published in Lancet Microberesearchers compare the potential of real-time reverse transcriptase-polymerase chain reaction (RT-PCR) genotyping assays with whole-genome sequencing (WGS) for high-throughput, accurate, and timely surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants.

Study: RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study, Image Credit: tilialucida / Shutterstock.com Study: RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study, Image Credit: tilialucida / Shutterstock.com

Background

The genome of SARS-CoV-2 mutated rapidly over time, giving rise to several variants of concern (VOCs), which, in turn, continuously changed the epidemiological trajectory of the coronavirus disease 2019 (COVID-19) globally.

WGS remains the gold standard to identify and genetically characterize SARS-CoV-2 variants; however, this approach was less effective in initiating a rapid public health response, given its one to two weeks turnaround time and other technical, logistical, and financial limitations. 

To date, the potential for high-throughput SARS-CoV-2 variant surveillance has been under-investigated. In fact, most previous studies only focused on developing and using surveillance efforts in specific population groups.  

RT-PCR genotyping assays for population-level SARS-CoV-2 surveillance could complement WGS by offering increased scalability at a lower cost, higher accuracy, and rapid rate.

About the study

In the present study, researchers developed decision algorithms to monitor and evaluate genotyping in the United Kingdom Health Security Agency (UKHSA) Second Generation Surveillance System (SGSS).

A total of 115,934 SARS-CoV-2-positive samples between March and September 2021 were analyzed, 2,674 of which met the criteria to become a part of an RT-PCR genotyping assay panel. Three measures of variant assignment accuracy and their associated 95% confidence intervals (CIs) were assessed for all samples to evaluate changes over time. 

The first measure was sensitivity, which reflected the proportion of samples with WGS-identified variants, which was also correctly classified by the decision algorithm. The second measure was specificity, defined as the proportion of samples that WGS did not classify as a variant but classified by the decision algorithm.

The third and final measure was a positive predictive value [PPV], which reflected the proportion of samples for which WGS confirmed the decision algorithm classification. The speed of results, cost, and increased capacity for RT-PCR testing as compared to WGS were also determined. 

To assess the timeliness of variant surveillance, the researchers calculated the time between the sample collection date of the RT-PCR-positive sample and the availability of genotyping and WGS results for paired variant results. This data was presented as mean (SD) and median (IQR) time lags and stratified by week to explore changes in timeliness.

Study findings

RT-PCR genotyping assays allowed for the timely and improved characterization of SARS-CoV-2 transmission patterns and risk factors. These assays were associated with a high degree of accuracy, being less resource-intensive than WGS, shorter turnaround times, and higher flexibility to adapt.

April decision algorithm had sensitivities and PPVs of 0·99, 1, and 0.91 (95% CI) for the SARS-CoV-2 Alpha, Beta, and Gamma variants, respectively, with specificities of 0.97, 1.00, and 1.00, respectively, for variant assignment.

The subsequent decision algorithm remained accurate for variant assignment, with sensitivities of 0.91, 0.98, and 0.93 for the Beta, Delta, and Gamma viral variants, respectively. These variants were associated with PPVs of 0.83, 1.00, and 0.78, respectively, and specificities of 1.00, 0.96, and 1.00, respectively. 

During the emergence of new variants, these tests helped front-line health protection professionals to quickly link cases to each other and specific premises, thereby facilitating prompt public health action to prevent further transmission. Genotyping assays also rapidly highlighted the travel cases causing importation, ultimately facilitating the Delta VOC's dominance. 

Delta case rates doubled every 4.5 days in some UK regions during the study period. Genotyping assays not only helped with the rapid identification of variants but allowed for a timelier assessment of their infectivity, transmissibility, and severity than WGS. 

RT-PCR genotyping assays reported probable variant assignment on an average of three days after the sample collection date as compared to nine days taken by WGS. Furthermore, the flexibility of RT-PCR genotyping assays enabled a nine-times rise in the samples tested from 5,000 to 45,000.

Importantly, maximizing the benefits of a genotyping approach requires effectively prioritizing which samples would benefit most from variant assignment.

Conclusions

RT-PCR genotyping assays demonstrated the potential for high-throughput surveillance of SARS-CoV-2 variants to complement WGS, especially when variants are not rapidly changing. Given their higher speed, flexibility, and relatively low cost, these assays could guide variant-specific disease modeling and differential management of cases according to variants globally. This screening approach could also inform public health action and policy, including travel restrictions and the time of vaccination delivery programs.

Journal reference:
  • Bray, N., Sopwith, W., Edmunds, M., et al. (2024). RT-PCR genotyping assays to identify SARS-CoV-2 variants in England in 2021: a design and retrospective evaluation study. Lancet Microbe. doi:10.1016/ S2666-5247(23)00320-8
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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