In Silico Assessment of the Impact of 2019 Novel Coronavirus Genomic Variation on the Efficiency of Published Real-Time Quantitative Polymerase Chain Reaction Detection Assays
The outbreak of coronavirus disease 2019 (COVID-19), caused by the 2019 novel coronavirus (2019-nCoV), emerged in Wuhan, China, in December 2019. This outbreak has since evolved into a global public health crisis. Real-time quantitative polymerase chain reaction (RT-qPCR) has been widely recommended as an effective method for pathogen detection and has played a crucial role in the prevention and control of the ongoing pandemic. Numerous research institutions have released their primer sets for RT-qPCR to detect 2019-nCoV. However, the efficiency of RT-qPCR can be significantly reduced if variant sites are located within the primer regions, potentially leading to false-negative results. This could have unpredictable consequences for patient diagnosis and the overall management of the outbreak. Therefore, a comprehensive investigation into the genomic variation of 2019-nCoV is essential to evaluate the effectiveness of the currently available RT-qPCR methods.
To address this issue, an in silico analysis was conducted using 77 publicly available full-length genome sequences of 2019-nCoV obtained from the GISAID database. These sequences were aligned using MAFFT version 7.450, a multiple sequence alignment software known for its performance and usability. The analysis identified a total of 85 variant sites, all of which were single nucleotide variants. Among these, seven variant sites were shared by two 2019-nCoV sequences, and nine were found in three or more sequences. This level of genomic variation underscores the importance of assessing the potential impact on RT-qPCR detection assays.
The study investigated 13 RT-qPCR primer sets designed by eight different institutions. These primer sets target various genes of 2019-nCoV, including ORF1ab, Spike (S), Envelope (E), and Nucleocapsid (N). The analysis revealed that the reverse primers of primer sets 3 and 6 had one mismatch against all of the released 2019-nCoV sequences. Furthermore, three specific variant sites (positions 28291, 28688, and 29200 on the reference genome IVDC-HB-01) were found to be located within the regions of the forward primers of primer sets 7 and 9, and the probe of primer set 8, respectively. These variants were identified in the sequences BetaCoV/Shenzhen/SZTH-003/2020, BetaCoV/Shandong/IVDC-SD-001/2020jEPI_ISL_408482, and BetaCoV/Chongqing/YC01/2020jEPI_ISL_408478. The presence of these variants in the primer or probe regions could potentially reduce the efficiency of RT-qPCR detection. Notably, variations in the probe region of primer set 8 are expected to have a particularly negative impact on detection efficiency, based on previous research.
The findings suggest that the use of any of the five RT-qPCR primer sets mentioned above (primer sets 3, 6, 7, 8, and 9) could lead to false-negative results when detecting 2019-nCoV. Among these, two primer sets have mismatches, and three contain genome variants that have emerged during the outbreak. It is particularly noteworthy that the three primer sets containing variants are all located on the N gene. This highlights the need for careful consideration when selecting primer targets, with more conservative regions such as the nsp12 (RdRp) gene being preferable choices. Although the use of multiple targets in RT-qPCR protocols can help mitigate the risk of false-negative results caused by genome variation, a thorough performance evaluation of the currently used primers is still necessary. Additionally, continuous surveillance of genome variants and their effects on RT-qPCR assays is crucial throughout the duration of the outbreak.
The study emphasizes the importance of ongoing genomic surveillance to ensure the reliability of diagnostic methods during a rapidly evolving pandemic. The identification of variant sites within primer and probe regions underscores the need for periodic updates to RT-qPCR assays to maintain their effectiveness. The findings also highlight the potential for false-negative results due to genomic variation, which could have significant implications for patient diagnosis and outbreak control.
In conclusion, the in silico assessment of 2019-nCoV genomic variation provides valuable insights into the potential impact on RT-qPCR detection assays. The identification of variant sites within primer and probe regions highlights the need for careful primer selection and continuous genomic surveillance. The findings underscore the importance of updating RT-qPCR assays to account for emerging variants and ensuring the reliability of diagnostic methods during a rapidly evolving pandemic. By addressing these challenges, the scientific community can enhance the accuracy of 2019-nCoV detection and contribute to more effective outbreak control measures.
doi.org/10.1097/CM9.0000000000000817
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