Development of a panel of three multiplex allele-specific qRT-PCR assays for quick differentiation of recombinant variants and Omicron subvariants of SARS-CoV-2

Abstract

Quick differentiation of the circulating variants and the emerging recombinant variants of SARS-CoV-2 is essential to monitor their transmission. However, the widely used gene sequencing method is time-consuming and costly when facing the viral recombinant variants, because partial or whole genome sequencing is required. Allele-specific real time RT-PCR (qRT-PCR) represents a quick and cost-effective method in SNP genotyping and has been successfully applied for SARS-CoV-2 variant screening. In the present study, we developed a panel of 3 multiplex allele-specific qRT-PCR assays targeting 12 key differential mutations for quick differentiation of SARS-CoV-2 recombinant variants (XD and XE) and Omicron subvariants (BA.1 and BA.2). Two parallel multiplex qRT-PCR reactions were designed to separately target the protype allele and the mutated allele of the four mutations in each allele-specific qRT-PCR assay. The variation of Cp values (ΔCp) between the two multiplex qRT-PCR reactions was applied for mutation determination. The developed multiplex allele-specific qRT-PCR assays exhibited outstanding analytical sensitivities (with limits of detection [LoDs] of 2.97-27.43 copies per reaction), wide linear detection ranges (10⁷-10⁰ copies per reaction), good amplification efficiencies (82% to 95%), good reproducibility (Coefficient of Variations (CVs) < 5% in both intra-assay and inter-assay tests) and clinical performances (99.5%-100% consistency with Sanger sequencing). The developed multiplex allele-specific qRT-PCR assays in this study provide an alternative tool for quick differentiation of SARS-CoV-2 recombinant variants (XD and XE) and Omicron subvariants (BA.1 and BA.2).

Introduction

The current circulating Omicron variant of SARS-CoV-2 has diverged into at least three subvariants (BA.1, BA.2 and BA.3) (Desingu and Nagarajan, 2022). Dozens of mutations were observed in the Omicron variants, among which at least 6 mutations were unique in the BA.1 subvariant (NSP3: L1266I; NSP6: I189V; Spike: S371L, G446S, T547K, and L981F) (Yu et al., 2022), and at least 6 mutations were unique in the BA.2 subvariant (NSP1: S135R, NSP3: T24I, NSP6: F108L, Spike: A27S, V213G, R408S) (Majumdar and Sarkar, 2022). The BA.2 subvariant is becoming the predominant strain of SARS-CoV-2 by replacing the BA.1 subvariant with a higher transmissibility (Chen and Wei, 2022). It is reported that BA.2 could potentially evade natural and vaccine-induced immunity, rather than BA.1 (Bartsch et al., 2022). The discrepancies in transmissibility and pathogenicity between the BA.1 and BA.2 subvariants make it necessary to conduct differential diagnosis of the Omicron subvariants in COVID-19 patients (Hamill et al., 2021).

Along with the predominant circulation of the Omicron variants, several recombinant variants of SARS-CoV-2 have emerged (He et al., 2022; UK Health Security Agency, 2022; Wertheim et al., 2022). Among the Omicron-recombinant variants (UK Health Security Agency, 2022), the XD variant is from recombination of the Delta variant and the Omicron BA.1 subvariant at the site nt 21643 (numbered as the prototype strain NC_045512.2, the same hereafter) and the site nt 25581; the XE variant is a recombinant variant between the Omicron BA.1 and BA.2 subvariants at the site nt 11537; the XF variant is a recombinant between the Delta variant and the Omicron BA.1 subvariant at the site nt 5386. Besides the Omicron-recombinant variants, Alpha-Epsilon (Wertheim et al., 2022) and Beta-Delta (He et al., 2022) recombinant variants were also reported. Although the pathogenicity and transmissibility of the SARS-CoV-2 recombinant subvariants remain largely undetermined and required further evaluation, previous reports have suggested elevated transmissibility and enhanced pathogenicity of the recombinant coronaviruses (Phillips et al., 1999; Su et al., 2016). Quick differentiation approaches are required to monitor the transmission of SARS-CoV-2 recombinant variants.

While gene sequencing (Sanger sequencing or Next Generation Sequencing) is a commonly applied strategy for viral variant identification (Srivastava et al., 2021), differentiation of massive recombinant variants is time and cost-consuming because of requiring partial or whole viral genome sequencing. Allele-specific real time RT-PCR (qRT-PCR) integrate the advantages of real-time PCR and allele-specific PCR, representing a highly sensitive and time-saving method for SNP genotyping (Gaudet et al., 2009). Allele-specific qRT-PCR has been successfully applied for identification of SARS-CoV-2 mutations, exhibiting a promising potential in differentiation of viral variants (Graber et al., 2021; Wang et al., 2021).

In the present study, we developed a panel of three multiplex allele-specific qRT-PCR assays, targeting 12 key mutations for differentiation of the Omicron BA.1 and BA.2 subvariants and the recombinant XD and XE variants of SARS-CoV-2.

Materials and methods

Ethical statement

The use of desensitized clinical specimens for evaluation of the developed allele-specific qRT-PCR assays was approved by the Ethics Committee of Shanxi University with a project identification code SXULL2022035.

Viral genome sequence analysis and primer/probe design

A total of 1,093,239 genome sequence of SARS-CoV-2 with high quality (< 1% Ns) deposited in GISAID (https://www.gisaid.org) were retrieved. Sequence alignment was performed by using the Muscle algorithm implemented in MEGA v7.0 (Kumar et al., 2016). The key mutations in Omicron BA.1 and BA.2 subvariants (Table 1) were confirmed and viral genomic regions suitable for primer/probe design were selected with the help of Primer Express v3.0 (Applied Biosystems, CA, USA). Primers and probe were designed according to the following principles: choosing regions with GC content of 40-60%; an amplicon of 75-250bp; avoiding regions with secondary structure; avoiding regions with long (> 4) repeats of single bases; avoiding the guanine (G) at the 5’ end of probes; all the selected primers have similar Tm (between 59°C and 61°C) and Tm of the corresponding probes were 5-10°C higher.

Plasmid construction and RNA transcript preparation

The viral NSP1, NSP3, NSP6, and Spike genes were synthesized and separately inserted into a plasmid pEasy-T1 (TransGen Biotech, Beijing, China), linearized by digestion with restriction enzyme for RNA transcript preparation by using the RiboMAX™ Large Scale RNA production System (Promega, WI, USA) according to the manufacturer’s instructions. Concentration of the RNA transcript was measured by using NanoDrop (Thermo Fisher Scientific, MA, USA). Copy number of the transcript was calculated by using the following formula: copy number (copies/ml) = 6.02×10²³ copy/mol × molarity (mol/L)/Molecular Weight (g/mol). The quantified RNA transcript was then 10-fold diluted with RNase-free water as templates for development of the allele-specific qRT-PCR assays.

Formulation and procedures of the developed multiplex allele-specific qRT-PCR assays

Takara Onestep PrimeScript™ III RT-qPCR Mix (Takara, Dalian, China) was used to build the multiplex qRT-PCR assays. Each reaction mix consisted of 10 μl One Step PrimeScript™ III RT-qPCR Mix, 0.4 μl forward primer (10 μM), 0.4 μl reverse primer (10 μM), 0.4 μl probe (5 μM), 2 μl RNA template, supplemented with RNase free water to a final volume of 25 μl (the concentration of each set of primers & probe (0.05 μM to 0.5 μM for each primer, and 0.025 μM to 2.5 μM for each probe) was evaluated in advance to reach an optimal work concentration). Each reaction was run in triplicate with 96-well plates by using a Roche LightCycler 480 (Roche, IN, USA). The thermocycling conditions for each qRT-PCR assay were as follows: 52°C 15 min for reverse transcription, 95°C 10 sec for thermal inactivation of the reverse transcriptase, followed by 45 cycles of 95°C 30 sec and 60°C 1min for PCR amplification (a thermal gradient experiment (58°C-62°C) was performed in advance to reach an optimal work temperature for annealing and extension). Fluorescence acquisition was set at the annealing/extension step of each cycle.

Methodological evaluations of the developed multiplex allele-specific qRT-PCR assays

To determine the analytical sensitivity of the developed allele-specific multiplex qRT-PCR assays, we used the above mentioned in vitro transcribed RNA of the viral genes as templates. The quantified RNA transcript was 2-fold serially diluted from 100 copies/μl to 0.1 copies/μl, and subjected to each of the multiplex allele-specific qRT-PCR assay. Limit of detection (LoD, defined as the minimum detected concentration at 95% probability) for each qRT-PCR assay was determined through the Probit regression analysis implemented in SPSS v22.0 (IBM, IL, USA).

Linear detection range and amplification efficiency of the multiplex allele-specific qRT-PCR assay were determined by using 10-fold serially diluted RNA transcript of the viral genes as templates. Fitting curves generating from the quantity of RNA transcripts and the corresponding Cp values were applied for determination of the linear detection ranges of the qRT-PCR assays. Correlation coefficient (R²) in the fitting curve (ranging from 0-1, with the value closer to 1 suggesting higher linearity) was applied for evaluation of the detection linearity, with the threshold for good linearity being defined as R² > 0.99. Amplification efficiencies of the qRT-PCR assays were evaluated by calculating the slope of the fitting curve, and defined as 10 ^(-1/slope)-1. The value of amplification efficiency was ranged from 0 to 1, with a value closer to 1 indicating a higher amplification efficiency.

Reproducibility of the multiplex allele-specific qRT-PCR assays were evaluated by using the parameter “Coefficient of Variation (CV)”, which was calculated by the standard deviation of a Cp value for an RNA dilution divided by the men Cp values for all replicates of the same RNA dilution. Intra-assay and inter-assay reproducibility were assessed by the results of three replicates in one run and the results of three runs in three days, respectively.

Specificity of the multiplex allele-specific qRT-PCR assays were evaluated by checking possible cross-reactivity between the developed qRT-PCR assays and the nucleic acids from common respiratory viruses (including coronaviruses (NL63, OC43 and 229E), influenza viruses (A and B), parainfluenza viruses (types 1-4), and respiratory syncytial virus) and respiratory bacteria (including Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus and Pseudomonas aeruginosa).

Clinical performance of the developed multiplex allele-specific qRT-PCR assays

To further evaluate the performance of the developed multiplex allele-specific qRT-PCR assays, we conducted assay validation with a total of 105 nasopharyngeal swabs. SARS-CoV-2 nucleic acid detection was performed by using a previously reported assay (Liu et al., 2020; Xiao et al., 2021), and confirmed by Sanger sequencing. A volume of 20 μl RNA was extracted from 200 μl of each nasopharyngeal swab containing viral transport medium by using the Trizol RNA extraction method (Rio et al., 2010). Assay validation was performed by using 2 μl of the extracted RNA as template for each 20 μl qRT-PCR reaction system.

Statistical analysis

All qRT-PCR experiments were performed in triplicate, and data are expressed as mean ± s.d. (the standard deviation). Fitting curves between the quantity of RNA transcript and the corresponding Cp values were generated by using Excel^® Microsoft^® 365. The amplification efficiency of a qRT-PCR assay was defined as 10 ^(-1/slope)-1, whereas “slope” represents the slope of the fitting curve. R² of the fitting curve was applied for description of the correlation coefficient between the quantity of RNA transcripts and the corresponding Cp values. The LoDs of the developed qRT-PCR assays were determined by using the Probit regression analysis module implemented in SPSS 22.0 at the 95% probability level. The kappa index evaluating the agreement between results of Sanger sequencing and the developed qRT-PCR assay was calculated by using the Kappa and the McNemar crosstab statistics implemented in SPSS 22.0.

Results

Description and result interpretation of the developed multiplex allele-specific qRT-PCR assays

A panel of 3 multiplex allele-specific qRT-PCR assays targeting 12 key mutations (Figure 1A) were developed for differentiation of the SARS-CoV-2 XD and XE recombinant variants and the Omicron BA.1 and BA.2 subvariants (Table 1). Each assay contained two parallel reactions targeting the prototype allele and the corresponding mutated allele of each mutation, respectively. Each reaction contained 4 TaqMan hydrolysis probes targeting 4 mutations, labeled with 5’-FAM-BHQ1-3’, 5’-VIC-BHQ1-3’, 5’-CY3-BHQ2-3’, and 5’-CY5-BHQ2-3’, respectively. The Forward primer was designed to be allele specific, with one additional mutation at the 3’ terminus to amplify the mismatch effect. The variation of Cp values (ΔCp) between the two parallel reactions induced by primer-target mismatch was employed to differentiate the prototype allele and the mutated allele (Figure 1B). A mutation was determined to occur if the Cp value in the mutated allele targeting reaction was smaller than that in the prototype allele targeting reaction. The threshold was set as ΔCp > 2 according to the performance of all the three developed assays. If ΔCp ≤ 2, a repeated test is required to confirm the result. Viral variant was identified according to the obtained unique mutation patterns of the Omicron subvariants and recombinant variants of SARS-CoV-2 (Figure 1C).

Figure 1

Analytical sensitivities of the developed multiplex allele-specific qRT-PCR assays

The analytical sensitivities of the developed qRT-PCR assays were represented with limit of detection (LoD), defined as the minimum detected template concentration at 95% probability (calculated through the Probit regression analysis). Using a 2-fold serially diluted in vitro transcribed RNA (from 200 to 0.1 copies per reaction) as templates, the LoDs for the prototype allele targeting reactions of the developed multiplex allele-specific qRT-PCR assays were determined to be 3.06-27.43 copies per reaction (Table 2, Figure 2), while the LoDs for the mutated allele targeting reactions were 2.97-23.65 copies per reaction (Table 2, Figure 3). These results suggested outstanding analytical sensitivities of the developed multiplex allele specific qRT-PCR assays.

Figure 2

Figure 3

Linear detection ranges and amplification efficiencies of the developed multiplex allele-specific qRT-PCR assays

Linear detection range serves as a key indicator of qRT-PCR performance, which is defined as the span of signal intensities that display a linear relationship between quantity of RNA transcript and corresponding Cp values. By using a 10-fold diluted in vitro transcribed RNA as templates, the linear detection ranges of the developed multiplex allele-specific qRT-PCR assays were determined with the parameter Coefficient of Correlation (R², ranging from 0-1, the value closer to 1 represents stronger correlation). In the prototype allele targeting reactions (Table 2), the linear detection ranges were 10⁷-10^-1 copies per reaction (R² > 0.99) for the alleles of A27S (Spike), G446S (Spike), T547K (Spike), L981F (Spike), T24I (NSP3), and L1266I (NSP3), while the other prototype allele targeting reactions exhibited linear detection ranges of 10⁷-10⁰ copies per reaction (R² > 0.99). Meanwhile, all the mutated allele targeting reactions exhibited linear detection ranges of 10⁷-10^-1 copies per reaction (Table 2).

Amplification efficiency, defined as ratio of the actual amplicon number to the theoretical amplicon number from the same original template, with an efficiency value of 100% representing two copies of amplicon generated from one available template. We tested the amplification efficiencies of the developed assays by using the 10-fold diluted in vitro transcribed RNA as templates. The amplification curves of the prototype template (Figure 4) and the mutated template (Figure 5) exhibited approximately equal interval, indicating good amplification efficiencies of the developed assays. We further calculated the amplification efficiencies by using the formula: amplification efficiency = 10 ^(-1/slope) -1, in which the slope was from the fitting curve between the quantity of RNA transcript and the corresponding Cp values. The amplification efficiencies were ranged from 85% to 95% for the prototype allele targeting reactions, and ranged from 82% to 93% for the mutated allele targeting reactions (Table 2). These results demonstrated wide linear detection ranges and good amplification efficiencies of the developed multiplex allele-specific qRT-PCR assays for differentiation of SARS-CoV-2 recombinant variants (XD and XE) and the Omicron subvariants (BA.1 and BA.2).

Figure 4

Figure 5

Reproducibility and specificities of the developed multiplex allele-specific qRT-PCR assays

The intra-assay and inter-assay reproducibility of the developed qRT-PCR assays were separately assessed by using Coefficient of Variation (CV) between quantity of RNA template and the corresponding Cp values in triplicate repeated tests. For the intra-assay reproducibility (Table 3), the CVs were 0.04-3.32 in the prototype allele targeting reactions and were 0.04-2.66 in the mutated allele targeting reactions. For the inter-assay reproducibility (Table 4), the CVs were 0.32-4.68 in the prototype allele targeting reactions and were 0.46-4.26 in the mutated allele targeting reactions. These results suggested good intra- and inter-assay reproducibility (with Coefficient of Variation less than 5%) of the developed multiplex allele-specific qRT-PCR assays for differentiation of SARS-CoV-2 recombinant variants and the Omicron BA.1 and BA.2 subvariants.

No cross-reaction was observed between the developed qRT-PCR assays and other coronavirus (including NL63, OC43 and 229E), influenza viruses, parainfluenza viruses, respiratory syncytial virus, and common respiratory bacteria (Figure 6), suggesting good specificity of the developed multiplex allele-specific qRT-PCR assays.

Figure 6

Clinical performance of the developed multiplex allele-specific qRT-PCR assays

A total of 105 clinical specimens were used to evaluate the clinical performance of the developed assays, which were tested for SARS-CoV-2 by a previously reported assay and confirmed by Sanger sequencing. Of the 105 clinical specimens (Table 5), 12 were Omicron BA.1 positive, 2 were Omicron BA.2 positive, 1 was variant XD positive, and 1 was variant XE positive by the developed assays, whereas 13 were Omicron BA.1 positive, 2 were Omicron BA.2 positive, 1 was variant XD positive, and 1 was variant XE positive by Sanger sequencing. Thus, the sensitivities of the developed assays against Sanger sequencing to detect the Omicron subvariants BA.1, BA.2 and the recombinant variants XD and XE were 92%, 100%, 100%, and 100%, respectively. The specificities of all the developed assays against Sanger sequencing to detect the Omicron subvariants BA.1, BA.2 and the recombinant variants XD and XE were 100%. The consistencies for the Omicron subvariants BA.1, BA.2 and the recombinant variants XD and XE between the developed assays and Sanger sequencing were 99.5% (Kappa=0.955, P>0.05), 100% (Kappa=1.000, P>0.05), 100% (Kappa=1.000, P>0.05), and 100% (Kappa=1.000, P>0.05), respectively. These results suggested good clinical performance of the developed multiplex allele-specific qRT-PCR assays.

Discussion

The desprepant transmissibility among Omicron subvariants and potential impacts of the recombinant variants of SARS-CoV-2 call for quick viral variant screening method to effectively monitor the viral transmission. Allele-specific qRT-PCR is an easy-to-perform and wide applicable method in SNP screening, representing a potential basic technology for developing viral variant screening assay. In the present study, we developed a panel of 3 multiplex allele-specific qRT-PCR assays targeting 12 key viral mutations for differentiation of SARS-CoV-2 recombinant variants (XD and XE) and the Omicron subvariants (BA.1 and BA.2).

Several technologies have been applied for screening of viral mutations. Sanger sequencing is one of the reliable methods to detect the rapidly emerging SARS-CoV-2 variants by providing a detailed view of mutations (Wang et al., 2021). Nevertheless, Sanger sequencing is time-consuming, a longer turnaround time to deal with, requiring expensive sequencer. Droplet digital RT-PCR also has been applied for screening of SARS-CoV-2 variants with the advantages of sensitive absolute quantification (Perchetti et al., 2021), but requiring costly apparatus. Next generation sequencing (NGS) based whole-genome sequencing (WGS) represents a promising strategy in searching viral mutations by providing a more comprehensive view of the viral genomic variations (Bull et al., 2020). However, the NGS based WGS costs higher and requires professional skills, making it hard for wide application especially in the developing areas. When facing the task of SARS-CoV-2 recombinant variant identification, the limitations of the above-mentioned technologies are multiplied, because multiple genomic regions are required to reach a clear conclusion.

qRT-PCR represents a promising approach in viral mutation screening with the advantages of time and cost effective, easy to manage, and wide applicable (Corman et al., 2020). qRT-PCR based short-amplicon high-resolution melting analysis (SA-HRM) was applied for SARS-CoV-2 variant screening, allowing cost-effective genotyping of single-nucleotide differences by the differential melting pattern of a short double-stranded DNA molecule (Diaz-Garcia et al., 2021) While SA-HRM is less specific and less robust than TaqMan assays, its results should be confirmed by TaqMan assays or DNA sequencing, making the overall processes time-consuming and costly.

Allele-specific qRT-PCR method provides a potential strategy in screening viral mutations, which has been widely used for SNP screening (Gaudet et al., 2009; Ngai et al., 2010; Cuenca et al., 2013). Although several allele-specific qRT-PCR assays have been developed for detecting SARS-CoV-2 variants either from clinical specimens (Borsova et al., 2021) or from waste water (Graber et al., 2021), a comprehensive assay covering the current circulating Omicron subvariants and the recent emerged recombinant variants of SARS-CoV-2 is lacking. To meet this demand, we developed and analytically validated a panel of 3 multiplex allele-specific qRT-PCR assays for differentiation of SARS-CoV-2 recombinant variants XD and XE, and the Omicron subvariants BA.1 and BA.2. The developed assays exhibited better or comparable analytical sensitivities with the previously reported allele-specific qRT-PCR assays for SARS-CoV-2 variants (Borsova et al., 2021; Wang et al., 2021; Garson et al., 2022). Based on the achievements of previous reports in detecting SNPs of West Nile virus (Worwa et al., 2014), genetic lineage of the infectious bursal disease virus (Tomas et al., 2017), recombination of infectious laryngotracheitis virus (Loncoman et al., 2017), and the developed assays for detecting SARS-CoV-2 Omicron subvariants and recombinant variants in the present study, we reached a conclusion that allele-specific qRT-PCR could be generalized as a methodology for quick differentiation of viral sublineages and recombination events.

As a potential shortcoming of the developed assays in this study, the unobserved or subsequent appearing mutations in the targeting area of the primers and probes could affect the performance of the assays by increasing the uncontrolled mismatch. To overcome this shortcoming, we select the unique mutations of the SARS-CoV-2 recombinant variants and the Omicron subvariants that are far away from the other existed viral mutations. Nevertheless, further evaluation is required to assess the potential influence of future mutations occurred in the targeting area of the primers and probes of the developed assay. Another potential shortcoming of the developed assays is possible disturbance of result interpretation by the intra-/inter- assay Cp variation between the prototype allele targeting reaction and the mutated allele targeting reaction. Because all the intra- or inter- assay Cp variations were no more than 5% (Tables 3, 4) (that is to say, the highest variation of Cp ≤ 35×5% =1.75), we thus set the threshold as ΔCp > 2 to avoid results misinterpretation induced by intra-/inter-assay Cp variations.

In summary, a panel of 3 multiplex allele-specific qRT-PCR assays was developed for differentiation of SARS-CoV-2 recombinant variants and the Omicron subvariants. The developed assays exhibited outstanding analytical sensitivities (LoDs: 2.97-27.43 copies per reaction), wide linear detections ranges (from 10⁷ copies per reaction to 10⁰ copies per reaction), good amplification efficiencies (82% to 95%), good reproducibility (CVs < 5% in both intra-assay and inter-assay tests), and good specificity (not cross-reacted with other common respiratory viruses and bacteria). The developed assays provide an alternative tool for quick differentiation of SARS-CoV-2 recombinant variants XD and XE, and the Omicron BA.1 and BA.2 subvariants.

Funding

This study has been funded by the Key R & D project of Shanxi Province (202102130501001 to JL, 202003D31005/GZ to CW, 202003D31003/GZ to JL).

Acknowledgments

We thank Prof. Eric Leroy from University of Montpellier and Prof. Eric Westhof from University of Strasbourg for their valuable suggestions on the conception and design of the study, and critical comments on the draft of the manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

• 1

  BartschY.CizmeciD.KangJ.GaoH.ShiW.ChandrashekarA. (2022). BA.2 evasion of vaccine induced binding and functional non-neutralizing antibodies. medRxiv. doi: 10.1101/2022.02.25.22271511

  • CrossRef
  • Google Scholar

• 2

  BorsovaK.PaulE. D.KovacovaV.RadvanszkaM.HajduR.CabanovaV.et al. (2021). Surveillance of SARS-CoV-2 lineage B.1.1.7 in Slovakia using a novel, multiplexed RT-qPCR assay. Sci. Rep.11 (1), 20494. doi: 10.1038/s41598-021-99661-7

  • CrossRef
  • Google Scholar

• 3

  BullR. A.AdikariT. N.FergusonJ. M.HammondJ. M.StevanovskiI.BeukersA. G.et al. (2020). Analytical validity of nanopore sequencing for rapid SARS-CoV-2 genome analysis. Nat. Commun.11 (1), 6272. doi: 10.1038/s41467-020-20075-6

  • CrossRef
  • Google Scholar

• 4

  ChenJ.WeiG. W. (2022). Omicron BA.2 (B.1.1.529.2): High potential to becoming the next dominating variant. J. Phys. Chem. Lett.13 (17), 3480–3489. doi: 10.1021/acs.jpclett.2c00469

  • CrossRef
  • Google Scholar

• 5

  CormanV. M.LandtO.KaiserM.MolenkampR.MeijerA.ChuD. K.et al. (2020). Detection of 2019 novel coronavirus, (2019-nCoV) by real-time RT-PCR. Euro Surveill25 (3), 2000045. doi: 10.2807/1560-7917.ES.2020.25.3.2000045

  • CrossRef
  • Google Scholar

• 6

  CuencaJ.AlezaP.NavarroL.OllitraultP. (2013). Assignment of SNP allelic configuration in polyploids using competitive allele-specific PCR: application to citrus triploid progeny. Ann. Bot.111 (4), 731–742. doi: 10.1093/aob/mct032

  • CrossRef
  • Google Scholar

• 7

  DesinguP. A.NagarajanK. (2022). Omicron BA.2 lineage spreads in clusters and is concentrated in Denmark. J. Med. Virol.94 (6), 2360–2364. doi: 10.1002/jmv.27659

  • CrossRef
  • Google Scholar

• 8

  Diaz-GarciaH.Guzman-OrtizA. L.Angeles-FlorianoT.Parra-OrtegaI.Lopez-MartinezB.Martinez-SaucedoM.et al. (2021). Genotyping of the major SARS-CoV-2 clade by short-amplicon high-resolution melting (SA-HRM) analysis. Genes (Basel)12 (4), 531. doi: 10.3390/genes12040531

  • CrossRef
  • Google Scholar

• 9

  GarsonJ. A.BadruS.ParkerE.TedderR. S.McClureM. O. (2022). Highly sensitive and specific detection of the SARS-CoV-2 delta variant by double-mismatch allele-specific real time reverse transcription PCR. J. Clin. Virol.146, 105049. doi: 10.1016/j.jcv.2021.105049

  • CrossRef
  • Google Scholar

• 10

  GaudetM.FaraA. G.BeritognoloI.SabattiM. (2009). Allele-specific PCR in SNP genotyping. Methods Mol. Biol.578, 415–424. doi: 10.1007/978-1-60327-411-1_26

  • CrossRef
  • Google Scholar

• 11

  GraberT. E.MercierE.BhatnagarK.FuzzenM.D'AoustP. M.HoangH. D.et al. (2021). Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy. Water Res.205, 117681. doi: 10.1016/j.watres.2021.117681

  • CrossRef
  • Google Scholar

• 12

  HamillV.NollL.LuN.TsuiW. N. T.PorterE. P.GrayM.et al. (2021). Molecular detection of SARS-CoV-2 strains and differentiation of delta variant strains. Transbound Emerg. Dis. doi: 10.1111/tbed.14443

  • CrossRef
  • Google Scholar

• 13

  HeY.MaW.DangS.ChenL.ZhangR.MeiS.et al. (2022). Possible recombination between two variants of concern in a COVID-19 patient. Emerg. Microbes Infect.11 (1), 552–555. doi: 10.1080/22221751.2022.2032375

  • CrossRef
  • Google Scholar

• 14

  KumarS.StecherG.TamuraK. (2016). MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol. Biol. Evol.33 (7), 1870–1874. doi: 10.1093/molbev/msw054

  • CrossRef
  • Google Scholar

• 15

  LiuY.WangY.WangX.XiaoY.ChenL.GuoL.et al. (2020). Development of two TaqMan real-time reverse transcription-PCR assays for the detection of severe acute respiratory syndrome coronavirus-2. Biosaf Health2 (4), 232–237. doi: 10.1016/j.bsheal.2020.07.009

  • CrossRef
  • Google Scholar

• 16

  LoncomanC. A.HartleyC. A.CoppoM. J.VazP. K.Diaz-MendezA.BrowningG. F.et al. (2017). Development and application of a TaqMan single nucleotide polymorphism genotyping assay to study infectious laryngotracheitis virus recombination in the natural host. PloS One12 (3), e0174590. doi: 10.1371/journal.pone.0174590

  • CrossRef
  • Google Scholar

• 17

  MajumdarS.SarkarR. (2022). Mutational and phylogenetic analyses of the two lineages of the omicron variant. J. Med. Virol.94 (5), 1777–1779. doi: 10.1002/jmv.27558

  • CrossRef
  • Google Scholar

• 18

  NgaiK. L.LamW. Y.LeeN.LeungT. F.HuiD. S.ChanP. K. (2010). Allele-specific conventional reverse-transcription polymerase chain reaction as a screening assay for discriminating influenza a H1N1 (H275Y) oseltamivir-resistant and wild-type viruses. J. Med. Virol.82 (8), 1295–1298. doi: 10.1002/jmv.21783

  • CrossRef
  • Google Scholar

• 19

  PerchettiG. A.ZhuH.MillsM. G.ShresthaL.WagnerC.BakhashS. M.et al. (2021). Specific allelic discrimination of N501Y and other SARS-CoV-2 mutations by ddPCR detects B.1.1.7 lineage in Washington state. J. Med. Virol.93 (10), 5931–5941. doi: 10.1002/jmv.27155

  • CrossRef
  • Google Scholar

• 20

  PhillipsJ. J.ChuaM. M.LaviE.WeissS. R. (1999). Pathogenesis of chimeric MHV4/MHV-A59 recombinant viruses: The murine coronavirus spike protein is a major determinant of neurovirulence. J. Virol.73 (9), 7752–7760. doi: 10.1128/JVI.73.9.7752-7760.1999

  • CrossRef
  • Google Scholar

• 21

  RioD. C.AresM.Jr.HannonG. J.NilsenT. W. (2010). Purification of RNA using TRIzol (TRI reagent). Cold Spring Harb. Protoc.(6), pdb.prot5439. doi: 10.1101/pdb.prot5439

  • CrossRef
  • Google Scholar

• 22

  SrivastavaS.BanuS.SinghP.SowpatiD. T.MishraR. K. (2021). SARS-CoV-2 genomics: An Indian perspective on sequencing viral variants. J. Biosci.46 (1), 22. doi: 10.1007/s12038-021-00145-7

  • CrossRef
  • Google Scholar

• 23

  SuS.WongG.ShiW.LiuJ.LaiA. C. K.ZhouJ.et al. (2016). Epidemiology, genetic recombination, and pathogenesis of coronaviruses. Trends Microbiol.24 (6), 490–502. doi: 10.1016/j.tim.2016.03.003

  • CrossRef
  • Google Scholar

• 24

  TomasG.HernandezM.MarandinoA.TecheraC.GreccoS.HernandezD.et al. (2017). Development of an RT-qPCR assay for the specific detection of a distinct genetic lineage of the infectious bursal disease virus. Avian Pathol.46 (2), 150–156. doi: 10.1080/03079457.2016.1228827

  • CrossRef
  • Google Scholar

• 25

  UK_Health_Security_Agency (2022) Technical briefing 39. SARS-CoV-2 variants of concern and variants under investigation in England. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1063424/Tech-Briefing-39-25March2022_FINAL.pdf.

  • Google Scholar

• 26

  WangH.MillerJ. A.VergheseM.SibaiM.SolisD.MfuhK. O.et al. (2021). Multiplex SARS-CoV-2 genotyping reverse transcriptase PCR for population-level variant screening and epidemiologic surveillance. J. Clin. Microbiol.59 (8), e0085921. doi: 10.1128/jcm.00859-21

  • CrossRef
  • Google Scholar

• 27

  WertheimJ. O.WangJ. C.LeelawongM.MartinD. P.HavensJ. L.ChowdhuryM. A.et al. (2022). Detection of SARS-CoV-2 intra-host recombination during superinfection with alpha and epsilon variants in new York city. Nat. Commun.13 (1), 3645. doi: 10.1038/s41467-022-31247-x

  • CrossRef
  • Google Scholar

• 28

  WorwaG.AndradeC. C.ThiemannT. C.ParkB.MaharajP. D.AnishchenkoM.et al. (2014). Allele-specific qRT-PCR demonstrates superior detection of single nucleotide polymorphisms as genetic markers for West Nile virus compared to Luminex(R) and quantitative sequencing. J. Virol. Methods195, 76–85. doi: 10.1016/j.jviromet.2013.09.014

  • CrossRef
  • Google Scholar

• 29

  XiaoY.LiZ.WangX.WangY.WangY.WangG.et al. (2021). Comparison of three TaqMan real-time reverse transcription-PCR assays in detecting SARS-CoV-2. J. Virol. Methods288, 114030. doi: 10.1016/j.jviromet.2020.114030

  • CrossRef
  • Google Scholar

• 30

  YuJ.CollierA. Y.RoweM.MardasF.VenturaJ. D.WanH.et al. (2022). Neutralization of the SARS-CoV-2 omicron BA.1 and BA.2 variants. N Engl. J. Med. 386, 1579–1580. doi: 10.1056/NEJMc2201849

  • CrossRef
  • Google Scholar