Designing and making an in-house real-time RT qPCR kit for the detection of SARS-CoV- 2 infection at high sensitivity and low cost

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Aufi, Salah Hashim shaheed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8233598/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The widespread use of accurate real-time RT-PCR tests for community individuals is a critical approach to managing the disease and reducing COVID-19 transmission effectively. In addition, serological ELISA assays are another essential tool for detecting and/or quantifying SARS-CoV-2 IgG and IgM antibodies or for screening for SARS-CoV-2 infection. Objectives The objective of the current study is to develop an in-house multiplex real-time RT-qPCR kit for molecular detection of SARS-CoV-2 N and E genes . Materials and methods A total of 100 samples from the Central Public Health Laboratory were analyzed: 50 tested positive for SARS-CoV-2 RNA and 50 tested negative. Results The in-house multiplex qPCR assay showed a significant association at P value 0.01 between the in-house N gene CT Value and the commercial N gene CT value, but there was no significant association at P value 0.09 between the in-house E gene CT Value and the commercial E gene CT Value. The in-house-designed RT-qPCR-E gene had a sensitivity of 96% and a specificity of 98.11%. The in-house-designed RT-qPCR N gene had a sensitivity of 92.31% and a specificity of 98.11%. Overall, or combined, sensitivity and specificity of the in-house-designed RT qPCR assay were 96.08% and 100.00%, respectively. Conclusions The in-house-designed multiplex real-time RT-qPCR kit was more sensitive than the commercial kit for detecting SARS-CoV-2, and the in-house ELISA kit showed acceptable sensitivity and specificity, given its very low cost. The in-house designed kits were far less expensive than the commercial kits. This study demonstrated a broad range of viral loads, which means some infected individuals with low viral loads might be below the limit of detection of commercial assays. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Coronaviruses are among the most common viruses that may infect humans and cause respiratory disorders. Significant human and animal infections belong to the coronavirus family[1] [2]. Most individuals will get the coronavirus at least once throughout their lives, and it may lead to serious respiratory illnesses, including pneumonia and bronchitis. Alpha, beta, gamma, and delta coronaviruses are the four subgroups of the larger family of single-stranded, enveloped RNA viruses, measuring 120–80 nm in diameter, known as coronaviruses[3]. HCoV-OC43, HCoV-229E, HCoV-NL63, and HCoVHKU1 are four types of coronavirus that are not highly pathogenic and can produce only mild respiratory infection [4]. However, two coronavirus strains—severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV)—were responsible for two separate fatal outbreaks [3]. The new coronavirus has swiftly spread, first causing an outbreak in China and then a pandemic with instances rising in many nations across the globe. [2]. Since China reported the first COVID-19 cases in December 2019, the global pandemic has spread rapidly. Worldwide, there have been over 503 million instances of COVID-19 due to SARS-CoV-2 infection as of April 15, 2022, with over 6.2 million deaths [5]. The World Health Organization officially designated the illness as COVID-19 in February 2020. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was initially known as 2019-nCoV. (the novel coronavirus)[6]. Although global SARS-CoV-2 infections have been contained since January 2022, the number of cases increased by 8% during the first two weeks of March 2022, resulting in 11 million new infections and 43,000 deaths. This brought the total number of confirmed cases to more than 445 million and the total number of deaths to over 6 million worldwide as of March 13, 2022 [6]. To isolate and diagnose the COVID-19 virus, the genome is sequenced using the polymerase chain reaction (PCR) technique. The diagnosis relies on quantitative PCR to detect the coronavirus's DNA [6]. Real-time reverse transcription-polymerase chain reaction enables quick and precise identification of SARS-CoV-2, the first step in controlling COVID-19 (RT–PCR)[7]. There is little question that the adoption of reliable serological testing would improve pandemic management while also lowering costs, workloads, and time spent in national labs and healthcare systems. Computed tomography (CT) radioimaging should be used in addition to RT-PCR for a definitive diagnosis. Before viral RNA could be detected, patients' chest CT images showed a ground-glass appearance, confirming clinical suspicion. Radiographic evidence of lung involvement often precedes positive rRT-PCR findings by 4–6 days[8]. The RBD, S, and N proteins of SARS-CoV-2 are the primary antigens that cause a host immune response and the subsequent production of IgA, IgM, and IgG antibodies. Mucosal immune responses to SARS-CoV-2 are reflected in the titer of secretory IgA. In contrast to IgG, which is indicative of a chronic illness or a prior infection, the presence of IgM suggests the early, acute infectious stage. While IgM and IgG have been observed more often than IgA in relation to SARS-CoV-2 antibodies, the temporal dynamics of these antibodies have been shown to vary somewhat across investigations. There was evidence of IgA and IgM on the 5th day (median) and IgG by the 14th day (study) (median)[9]. The imported commercial kits for the detection of SARS-CoV-2 RNA (real-time RT-qPCR) and serological kits are of limited sensitivity and specificity and are very expensive. Aim of the study The study aims to develop a real-time RT-qPCR kit for the first Iraqi detection of the SARS-CoV-2 virus using designed primers and probes. Methodology The study aimed to develop a multiplex real-time RT-qPCR kit for in-house molecular detection of the SARS-CoV-2 N and E genes and a COVID-19-specific qualitative serological test based on an indirect ELISA targeting the S1 subunit of SARS-CoV-2 S proteins. Fifty nasopharyngeal swabs were confirmed to be positive for SARS-CoV-2 using the AccuPower® SARS-CoV-2 Multiplex Real-Time RT-PCR Kit, and fifty were confirmed to be negative; in addition, sixty serum specimens were collected from patients who were positive for IgG, of which twenty were from before the pandemic. Samples were collected between January 4 and April 1, 2022. Primers and probes design Primers and TaqMan fluorogenic probes were designed based on conserved regions of the SARS-CoV-2 virus genome. The SARS-CoV-2 virus E gene (165 bp) and N gene were retrieved from GenBank at NCBI ( www.ncbi.nlm.nih.gov ) and Epicov ( https://www.epicov.org ). Then, primers and probes were designed for these genes using the Primer3Plus website ( https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi ) and NCBI ( https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn&BLAST_SPEC=GeoBlast&PAGE_TYPE=BlastSearch ). The Internal control (IC) was the human gene and its primers and probe for MS2 detection; it was used as the IC in the in-house multiplex qPCR-designed kit. Establishment of the standard curve: After calculating the copy number of the E and N genes 52x × 10 8 copies/ml for both genes) In one vial, the standard curve was established using 5 points from 100-fold serial dilutions prepared in TBE buffer. The standard curve generated from the clinical sample in each batch was used to calculate viral load. Results Design and optimization of primers: The optimal concentrations and annealing temperatures for the designed primers for SARS-CoV-2 (E gene, N gene, and RdrP gene) were determined using a single positive sample with five annealing temperatures (46°C, 49°C, 52°C, 55°C, 58°C). Conventional gradient PCR and gel electrophoresis results showed that the optimal primer concentration was 0.1 µM and the optimal annealing temperature was 58°C, as shown in Fig. 1 . Probe optimization Five positive SARS-CoV-2 samples were used to optimize the designed Taq-Man probes, and the results revealed that the optimal probe concentration for the best exponential and linear curves was 0.1 µM, as shown in Fig. 2. Figure (2) (A) and (B) illustrate the log and linear curves of the SARS-CoV-2 positive E gene sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with VIC reporter dye. (C) and (D) illustrate the log and linear curves of the SARS-CoV-2 positive N gene sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with FAM reporter dye. Optimization of the In-house designed multiplex real-time RT qPCR The in-house designed multiplex real-time RT qPCR kit was optimized for the detection of N gene, E gene , and IC MS2, as shown in Fig. 3 . Standardization and efficiency of in-house designed diplex RT qPCR One hundred-fold serial dilutions of a single positive sample, containing the two targets (N and E genes) with viral load 52 × 10 8 copies/ml, were diluted by TBE buffer to 0.52 copies/µl and 2.6 copies per reaction, then multiplex qPCR was conducted using an In-house designed kit in triplicate for each dilution. Figure (4) : In-house qRT-PCR Standard curve. The standard curve of a serial dilution of a single positive sample ranged from 52*1010 copies/ml to 520 copies/ml. The slope value was − 3.4984, R² 0.9807, and efficiency 93.1%. Limit of detection of the In-house designed multiplex qPCR assay This study's results revealed that 520 copies/ml is the limit of detection (LOD) of the SARS-CoV-2 virus Intra -and Inter-assay variability The precision, or repeatability, of the in-house-designed multiplex qPCR assay was established using CT values obtained from testing positive samples in duplicates within each run (intra-assay) and across two different runs (inter-assay). The coefficient of variation (CV%) of E gene for the threshold cycle values ranged between (0% − 7.64%) for inter-assay, with average of high and low CV% equal to 10.56%, and (0-9.75%) for intra-assay, with an average CV% equal to 3.02%, the C T values mean ranged (14.8–33 C T ). For the N gene the coefficient of variation (CV%) for the threshold cycle values ranged between (0–5.07%) for inter-assay, with an average of high and low CV% equal to 9.88%, and (0–8.85%) for intra-assay, with average CV% equal to 2.51%, the C T values means ranged (14.65–33.50 C T ). In-house N and E genes C T Value vs Commercial N and E genes C T Value Pearson’s Correlation Regarding the relationship between the In-house N gene C T Value and the Commercial N gene C T Value, Pearson’s correlation in a sample size of 100 nasopharyngeal swab specimens showed a 95% confidence interval (0.088 to 0.578) and a significant association at P value 0.01, as shown in Fig. 5 . The correlation between In-house E gene CT Value and Commercial E gene CT Value was 95% confidence interval (-0.044 to 0.48), and there was no significant association at P value 0.09, as shown in Fig. 5 . Table 1 shows the C T Values and copy numbers for the RT qPCR in-house-designed kit and the RT qPCR commercial kit. Table 1 C T Value and copy number of RT qPCR In-house designed kit and C T Value of RT qPCR commercial kit. Samples C T Value of In-house E gene Copy number of the In-house E gene C T Value of in-house N gene Copy number of the in-house N gene C T Value Commercial E gene C T Commercial N gene S1 17 20 x 10 8 15.9 41 X 10 8 17.5 17.9 S2 15.8 44 x 10 8 14.8 84 X 10 8 19.9 21.9 S3 14.5 10 x 10 9 14.9 79X 10 8 16 18.8 S4 25.6 79 x 10 5 21.6 10 X 10 7 18.1 24.6 S5 36 96 x 10 2 33.5 48 x 10 3 18.1 19.5 S6 24 22 x 10 6 20.4 22 x 10 7 31.4 32.2 S7 22 81 x 10 6 18 10 x 10 8 18.9 19.1 S8 27 32 x 10 5 23.7 27 x 10 6 28.3 28.7 S9 28 16 x 10 5 26.8 36 x 10 5 23.8 22.9 S10 15 74 x 10 8 15.2 65 x 10 8 26.1 25.9 S11 27 32 x 10 5 25.2 10 x 10 6 18.9 16 S12 35.4 14 x 10 3 30.5 33 x 10 4 22.6 26.3 S13 24 22 x 10 6 20.6 20 x 10 7 34.13 0 S14 22 81 x 10 6 20.6 20 x 10 7 20.1 19 S15 39 13 x 10 2 38 26 x 10 2 18.7 18.8 S16 26.8 36 x 10 5 22.5 58 x 10 6 16.8 16.6 S17 18.5 77 x 10 7 16.6 26 x 10 8 22.81 23.3 S18 28 16 x 10 5 23.9 23 x 10 6 17.2 17.5 S19 19 56 x 10 7 20.6 20 x 10 7 17.6 17.7 S20 20 29 x 10 7 21.6 10 x 10 7 22.6 21.4 S21 0 0 0 0 19.9 16.22 S22 29 88 x 10 4 24.5 16 x 10 6 0 19.9 S23 38 26 x 10 2 35 18 x 10 3 19.6 29.4 S24 28.6 11 x 10 5 23.31 34 x 10 6 26.6 17.8 S25 34.5 25 x 10 3 30.2 40 x 10 4 15.9 29.3 S26 22 81 x 10 6 20 29 x 10 7 27.3 24.9 S27 0 0 0 0 22.8 28.9 S28 21 15 x 10 7 17 20 x 10 8 25 18.4 S29 23 42 x 10 6 23 42 x 10 6 19 22.3 S30 37 50 x 10 2 35 18 x 10 3 21.5 33 S31 32 12 x 10 4 29 88 x10 4 31.4 26.8 S32 26.4 47 x 10 5 22.9 45 x 10 6 25.9 23.9 S33 20 29 x 10 7 18.9 60 x 10 7 25.1 22.3 Ss434 22 81 x 10 6 0 0 27 18.8 S5 24.8 13 x 10 6 30 46 x 10 4 33.6 28.8 S36 16.4 30 x 10 8 21.7 98 x 10 6 31.8 20.6 S37 15.9 41 x 10 8 25 11 x 10 6 17.3 40 S38 26.8 36 x 10 5 18 10 x 10 8 24.4 17 S39 23.4 32 x 10 6 16 39 x 10 8 40 20 S40 20.7 18 x 10 7 27.7 20 x 10 5 20.6 29.6 S41 25 11 x 10 6 23 42 x 10 6 24.9 23.4 S42 20.2 26 x 10 7 22 81 x 10 6 21.1 22 S43 29.5 64 x 10 4 0 0 30 35 S44 26 61 x 10 5 22 81 x 10 6 25.9 25 S45 24 22 x 10 6 30 46 x 10 4 25 33 S46 36 96 x 10 2 34 35 x 10 3 37 33 S47 36 96 x 10 2 36 96 x 10 2 34 35 S48 23 42 x 10 6 27 32 x 10 5 24 28 S49 24 22 x 10 6 26 61 x 10 5 23 26 + 51 negative samples when measured by In-house RT qPCR and Commercial RT qPCR Kits Accuracy, sensitivity, and specificity of the In-House designed RT qPCR assay. The nasopharyngeal swab panels tested positive/negative for the CT value of the N and E genes using a commercial kit, which was used as the gold standard to assess the sensitivity and specificity of the In-house designed real-time RT-qPCR assay. The sensitivity and specificity of the in-house-designed RT-qPCR E gene kit were measured. The assay was perform well with a sensitivity of 96% (95% CI 86.29% to 99.51%) and a specificity of 98.11% (95% CI 89.93% to 99.95%) a 97.96% (95% CI 87.31% to 99.70%) of positive predictive and a 96.30% (95% CI 86.99% to 99.02%) of negative predictive. Finally, the test's accuracy was 97.09% (95% CI 91.72% to 99.40%). The in-house-designed RT-qPCR N gene: Sensitivity and specificity. The assay was perform well with a sensitivity of 92.31% (95% CI 81.46% to 97.86%) and a specificity of 98.11% (95% CI 89.93% to 99.95%) also, it was demonstrated a 97.96% (95% CI 87.31% to 99.70%) of positive predictive and a 92.86% (95% CI 83.52% to 97.09%) of negative predictive. Finally, the test's accuracy was 95.24% (95% CI 89.24% to 98.44%). The overall or combined accuracy, Sensitivity, and Specificity of the in-house designed RT qPCR N gene and E genes . The assay performed well with a sensitivity of 96.08% (95% CI 86.54% to 99.52%) and a specificity of 100.00% (95% CI 93.02% to 100.00%). Also, it demonstrated a 100% positive predictive value and a 96.23% negative predictive value (95% CI 86.76% to 99.00%). Finally, the test's accuracy was 98.04% (95% CI 93.10% to 99.76%). Discussion The primers and TaqMan fluorogenic probes were designed based on conserved regions of the SARS-CoV-2 genome. The SARS-CoV-2 virus E and N genes were retrieved from Genbank by NCBI ( www.ncbi.nlm.nih.gov ) and ( https://www.epicov.org ). The primers and probes for these genes were then designed using the primer3plus website ( https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi ) and NCBI ( https://blast.ncbi.nlm.nih.gov/Blast.cgi\PROGRAM=blastn&BLAST_SPEC=GeoBlast&PAGE_TYPE=BlastSearch ). Conventional gradient PCR reactions were used to check the correct amplification of the desired fragments and to fine-tune the optimal annealing temperature for the designed primers. The optimal annealing temperature for the designed SARS-CoV-2 (E gene and N gene) primers was 58°C; the other annealing temperatures (46°C, 49°C, 52°C, and 55°C) also yielded positive results. Since there is no quantitative molecular detection of SARS-CoV-2 in Iraq, this study aimed to establish an RT quantitative PCR assay for the detection of SARS-CoV-2 viral load. This was achieved by making 100-fold serial dilutions of a single positive sample for the two targets (N and E genes) with viral load 52 × 10^8 copies/ml, which were diluted by TBE buffer to 0.52 copies/µl, 2.6 copies per reaction, then multiplex qPCR was conducted using an in-house designed kit. This assumption also aligns with Myungsun et al. in Korea in 2020, who used SARS-CoV-2 cDNA as a positive control and human-derived HEK-293T cDNA as the human IPC [10]. Actually, preparing an absolute quantitative real-time RT-qPCR has several advantages over the qualitative commercial assays. First, the in-house-prepared kit enables scientists and clinicians to estimate viral load precisely in nasopharyngeal swabs or blood, facilitating decision-making and research. Second, the in-house-prepared kit contains a standard curve for each run, which increases accuracy and repeatability by precisely estimating the variance and performance of the kit in both intra- and inter-assay analyses. During the COVID-19 pandemic, the primary diagnostic priority is identifying the infection, the infectious, and the vulnerable [11]. The limit of detection (LoD) of the SARS-CoV-2 virus was determined using an in-house designed qPCR multiplex with 0.52 copies/l and 2.6 copies per reaction. Yushen etal. In 2021, in China, they found that the test's true LoD falls between 10 and 1 copies/µL [12]. Other studies confirmed the preliminary LoD by testing 20 replicates of 2-fold dilutions (50 cp/µL, 25 cp/µL, 12.5 cp/µL, 6.25 cp/µL, 3.125 cp/µL, and 1.25 cp/µL)[13]. The study's findings reveal a broad spectrum of viral loads, suggesting that specific infected individuals with viral loads near, within, or even below the limits of detection of many standard assays may remain undiagnosed. As a result, these undetected individuals could potentially transmit the infection to others. The coefficient of variation (CV%) of the E gene for the threshold cycle values ranged between (0% − 7.64%) for inter-assay, with an average of high and low CV% equal to 10.56%, and (0-9.75%) for intra-assay, with an average CV% equal to 3.02%. For N gene, the coefficient of variation (CV%) for the threshold cycle values ranged between (0–5.07%) for inter-assay, with an average of high and low CV% equal to 9.88%, and (0–8.85%) for intra-assay with an average CV% equal to 2.51%, the CT values means ranged (14.65–33.50 CT). As a result, the intra- and inter-assay variability values of the in-house prepared kit are excellent, falling well within the 10% and 15% acceptable ranges, respectively, considered to be within international acceptable ranges [14]. The current study shows that an in-house assay is adequate for the identification of SARS-CoV-2 RNA in clinical samples when compared with the commercial AccuPower® SARS-CoV-2 Multiplex Real-Time RT-PCR Kit. Regarding the relationship between the in-house N gene CT value with a mean of 22 CT and the commercial N gene CT value with a mean of 23 CT, the Pearson’s correlation in sample size 100 nasopharyngeal swap specimens showed a 95% confidence interval (0.088 to 0.578) and a significant association at P value 0.01; this association may be explained by the fact that the in-house designed primers and probe targeting the N gene region target more conserved regions than the commercial primers and probe did. Furthermore, the correlation between the in-house E gene CT value (mean 24.2) and the commercial E gene CT value (mean 23.4) has a 95% confidence interval of -0.044 to 0.48, and there was no significant association at a P value of 0.09. This study is partially superior to the correlation values reported by Dayakar et al. in 2022 in the USA, who found a significant association between the CDC-modified SARS-CoV-2 real-time PCR assay and four commercial assays [15]. A 2021 study by Yushen et al. in China indicated that using the E gene region for primary screening of viral infection, the highly conserved N gene can specifically detect the SARS-CoV-2 virus [12]. The nasopharyngeal swab panels were tested for CT values of the N and E genes, which were positive or negative. The commercial kit was used as the gold standard to assess the sensitivity and specificity of the in-house-designed multiplex RT-qPCR assay. The in-house E gene RT-qPCR assay performed admirably, with a sensitivity of 96% and a specificity of 98.11%; it also demonstrated positive and negative predictive values of 97.96% and 96.30%, respectively. The test's accuracy was 97.09%. The in-house-designed RT-qPCR assay for the N gene also performed well, with a sensitivity of 92.31% and a specificity of 98.11%, and it demonstrated 97.96% positive and 92.86% negative predictive values. The test's accuracy was 95.24%. Accordingly, the overall performance of the in-house-designed multiplex RT-qPCR targeting both N and E genes was 96.08% sensitivity and 100.00% specificity, with 100% positive predictive and 96.23% negative predictive values. Finally, the overall test accuracy was 98.04%. In this study, the high sensitivity of the in-house designed kit came from the optimization procedures used for annealing temperatures on real Iraqi strains of SARS-CoV-2 by using gradient conventional PCR to select the highest yield but still specific annealing temperature for primers, as well as the lengthy optimization steps done for the primers and probes concentrations; moreover, perfect samples collection and processing as well as using efficient RNA extraction protocols might have a role in the production of high sensitivity and specificity. The high specificity of in-house multiplex RT qPCR with no cross-reactivity with common human respiratory viruses came from the primers and probes design tools used in this study; the designed primers and probes were theoretically tested on all SARS-CoV-2 variants from the reference wild-type variant to the Omicron variant by using NCBI and GISAID GenBank and bioinformatics tools. Many RT-PCR kits for detecting the SARS-CoV-2 virus have been developed by laboratories around the world since the outbreak began, each with its own sensitivity and specificity. Yes, in 2022, in Switzerland, Bello-Lemus et al. developed a triplex RT-qPCR assay for identifying SARS-CoV-2 that was 98.3% sensitive, 100% specific, and 99.2% accurate [16]. A different study compared their in-house kit with the commercial Sansure kit, finding that the proposed in-house assay had a sensitivity of 93% and a specificity of 97% [17]. Although the US CDC recommends a set of primers for the N region, these 2019-nCoV N2 primers have been shown to have substantial background cross-reactivity in at least three separate investigations [18]. According to the findings of the current study, the conclusions are: The in-house-designed multiplex real-time RT-qPCR kit was more sensitive than the commercial kit for detecting SARS-CoV-2. The in-house designed kits were far less expensive than the commercial kits. This study demonstrated a broad range of viral loads, which means some infected individuals with low viral loads might be below the LOD of many commonly used assays. A library of SARS-CoV-2 recombinant S1 subunits was prepared in competent bacteria and can be used at any time for various purposes (e.g., diagnostic tool development and research). The in-house anti-SARS-CoV-2 human IgG-ELISA was sensitive and specific for detecting IgG antibodies in individuals exposed to SARS-CoV-2. Declarations Ethics approval and consent to participate . The Institutional Review Board approved the study. Board (IRB) of Al-Nahrain University, College of Medicine, Baghdad, Iraq. Approval Number: 2020/983. Approval Date: January 10, 2021. Consent for publication Not applicable. Competing interests The author declares no conflicts of interest. Funding This study did not receive any external funding. Author Contribution Abdul-Sattar AL-Saeedi led the project, designed the study, and supervised its implementation. Ahmed Sahib Abdulamir developed the research plan and provided oversight. Iman M. Aufi assisted with laboratory work, while Salah Hashim Shaheed contributed to primer and probe design and performed computational analysis. Acknowledgment The author expresses gratitude to the technical staff and laboratory teams for their help and support in carrying out this research. 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Thomsson, O., et al., Validation of an enzyme-linked immunosorbent assay developed for measuring cortisol concentration in human saliva and serum for its applicability to analyze cortisol in pig saliva. Acta Veterinaria Scandinavica, 2014. 56 (1): p. 1–5. Seetha, D., A. Ravikumar, and R.R. Nair, Comparative performance of CDC-modified SARS-CoV-2 real-time PCR assay with four different commercial assays: laboratory-based study. Comparative Clinical Pathology, 2022: p. 1–9. Bello-Lemus, Y., et al., Comparative Analysis of In-House RT-qPCR Detection of SARS-CoV-2 for Resource-Constrained Settings. Diagnostics, 2022. 12 (11): p. 2883. Sarkar, S.L., et al., Development and validation of cost-effective one-step multiplex RT-PCR assay for detecting the SARS-CoV-2 infection using SYBR Green melting curve analysis. Scientific reports, 2022. 12 (1): p. 1–13. Vogels, C.B., et al., Analytical sensitivity and efficiency comparisons of SARS-CoV-2 RT–qPCR primer–probe sets. Nature microbiology, 2020. 5 (10): p. 1299–1305. Additional Declarations No competing interests reported. Supplementary Files photo20251208213412.jpg Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8233598","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":557649453,"identity":"48b6a218-94e6-4248-9af7-f09292fa3d9d","order_by":0,"name":"Abdul-Sattar AL-Saeedi","email":"data:image/png;base64,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","orcid":"","institution":"University of Karbala","correspondingAuthor":true,"prefix":"","firstName":"Abdul-Sattar","middleName":"","lastName":"AL-Saeedi","suffix":""},{"id":557649462,"identity":"38ab8beb-4a51-438a-a0aa-4b12ae4d8602","order_by":1,"name":"Ahmed Sahib Abdulamir","email":"","orcid":"","institution":"Al-Nahrain University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"Sahib","lastName":"Abdulamir","suffix":""},{"id":557649470,"identity":"1fc5417b-ac67-438a-91e8-affbcfba92c9","order_by":2,"name":"Iman M. Aufi","email":"","orcid":"","institution":"Central Public Health Laboratory","correspondingAuthor":false,"prefix":"","firstName":"Iman","middleName":"M.","lastName":"Aufi","suffix":""},{"id":557649476,"identity":"42e99826-b1bb-4374-a32e-30217f9fd02a","order_by":3,"name":"Salah Hashim shaheed","email":"","orcid":"","institution":"University of Karbala","correspondingAuthor":false,"prefix":"","firstName":"Salah","middleName":"Hashim","lastName":"shaheed","suffix":""}],"badges":[],"createdAt":"2025-11-29 00:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8233598/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8233598/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97865920,"identity":"9034f5be-910a-4199-856d-5e694408f762","added_by":"auto","created_at":"2025-12-10 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09:27:53","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":80296,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/db97c10ba1122ab73e15c241.html"},{"id":97865911,"identity":"f28e0f95-cc0d-4ed7-862c-e822fc76a05a","added_by":"auto","created_at":"2025-12-10 09:27:53","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":310115,"visible":true,"origin":"","legend":"\u003cp\u003eSARS CoV-2\u0026nbsp; primers optimization, the ladder was 100-1000 bp, SARS CoV-2\u0026nbsp;\u0026nbsp; amplicons were for \u003cem\u003eE gene\u003c/em\u003e 123bp, N gene 147 bp and\u0026nbsp; RdrP gene 172bp,\u0026nbsp; at agarose 1% (w/v) with 75 V through 60 mins.58\u003csup\u003e0\u003c/sup\u003ec was chosen as the annealing temperature.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/811334527c3c17eb61764bcf.jpeg"},{"id":97899329,"identity":"b8c6b328-e828-41da-bc89-26a55458b567","added_by":"auto","created_at":"2025-12-10 15:43:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":326207,"visible":true,"origin":"","legend":"\u003cp\u003e(A) and (B) illustrate the log and linear curves of the SARS-CoV-2 positive E gene sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with VIC reporter dye. (C) and (D) illustrate the log and linear curves of the SARS-CoV-2 positive \u003cem\u003eN gene\u003c/em\u003e sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with FAM reporter dye.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/f12d25448b5eccea14635488.png"},{"id":97865916,"identity":"bb171744-cc3c-415e-b299-0631aef04a1f","added_by":"auto","created_at":"2025-12-10 09:27:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":199123,"visible":true,"origin":"","legend":"\u003cp\u003eA: Single positive (RNA) eluents sample for SARS-CoV-2 with contents of two target \u003cem\u003eE and N genes was\u003c/em\u003e mixed with human eluent DNA and ROX dye (Normalization stain), then amplified simultaneously by an In-house designed multiplex real-time RT qPCR. B; NC (negative control) of in-house designed multiplex real-time RT for SARS-CoV-2, IC curve generated only.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/640cde1941909ea6c0ac1883.png"},{"id":97900505,"identity":"a5ed19bc-8fae-4796-8aee-a8ee8cad144c","added_by":"auto","created_at":"2025-12-10 15:45:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":106805,"visible":true,"origin":"","legend":"\u003cp\u003eIn-house qRT-PCR Standard curve. The standard curve of a serial dilution of a single positive sample ranged from 52*1010 copies/ml to 520 copies/ml. The slope value was -3.4984, R² 0.9807, and efficiency 93.1%.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/4b7ef26457bf9ac70af068a6.png"},{"id":97898675,"identity":"15c98b4c-37b5-4e5e-aeef-e88ed9e15bd4","added_by":"auto","created_at":"2025-12-10 15:39:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":510722,"visible":true,"origin":"","legend":"\u003cp\u003eA; In-house N gene CT Value vs Commercial N gene CT Value Pearson’s Correlation. B: In-house E gene C\u003csub\u003eT\u003c/sub\u003e Value vs Commercial E gene C\u003csub\u003eT\u003c/sub\u003e Value Pearson’s Correlation.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/0766527040f25d97087b5ac4.png"},{"id":100373652,"identity":"cd41e538-4d8e-40e7-b488-cc43f13a9ef0","added_by":"auto","created_at":"2026-01-16 08:16:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2587368,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/fd8e97cc-ef4b-485b-b19e-eca4241e6e6c.pdf"},{"id":97900847,"identity":"677f1438-4f7f-464c-b497-57cdee170497","added_by":"auto","created_at":"2025-12-10 15:46:00","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":33597,"visible":true,"origin":"","legend":"","description":"","filename":"photo20251208213412.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8233598/v1/4386699932ed3d9cd0f44d35.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Designing and making an in-house real-time RT qPCR kit for the detection of SARS-CoV- 2 infection at high sensitivity and low cost","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronaviruses are among the most common viruses that may infect humans and cause respiratory disorders. Significant human and animal infections belong to the coronavirus family[1] [2]. Most individuals will get the coronavirus at least once throughout their lives, and it may lead to serious respiratory illnesses, including pneumonia and bronchitis. Alpha, beta, gamma, and delta coronaviruses are the four subgroups of the larger family of single-stranded, enveloped RNA viruses, measuring 120\u0026ndash;80 nm in diameter, known as coronaviruses[3]. HCoV-OC43, HCoV-229E, HCoV-NL63, and HCoVHKU1 are four types of coronavirus that are not highly pathogenic and can produce only mild respiratory infection [4]. However, two coronavirus strains\u0026mdash;severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV)\u0026mdash;were responsible for two separate fatal outbreaks [3].\u003c/p\u003e\u003cp\u003eThe new coronavirus has swiftly spread, first causing an outbreak in China and then a pandemic with instances rising in many nations across the globe. [2]. Since China reported the first COVID-19 cases in December 2019, the global pandemic has spread rapidly. Worldwide, there have been over 503\u0026nbsp;million instances of COVID-19 due to SARS-CoV-2 infection as of April 15, 2022, with over 6.2\u0026nbsp;million deaths [5]. The World Health Organization officially designated the illness as COVID-19 in February 2020. COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was initially known as 2019-nCoV. (the novel coronavirus)[6]. Although global SARS-CoV-2 infections have been contained since January 2022, the number of cases increased by 8% during the first two weeks of March 2022, resulting in 11\u0026nbsp;million new infections and 43,000 deaths. This brought the total number of confirmed cases to more than 445\u0026nbsp;million and the total number of deaths to over 6\u0026nbsp;million worldwide as of March 13, 2022 [6].\u003c/p\u003e\u003cp\u003eTo isolate and diagnose the COVID-19 virus, the genome is sequenced using the polymerase chain reaction (PCR) technique. The diagnosis relies on quantitative PCR to detect the coronavirus's DNA [6]. Real-time reverse transcription-polymerase chain reaction enables quick and precise identification of SARS-CoV-2, the first step in controlling COVID-19 (RT\u0026ndash;PCR)[7]. There is little question that the adoption of reliable serological testing would improve pandemic management while also lowering costs, workloads, and time spent in national labs and healthcare systems. Computed tomography (CT) radioimaging should be used in addition to RT-PCR for a definitive diagnosis. Before viral RNA could be detected, patients' chest CT images showed a ground-glass appearance, confirming clinical suspicion. Radiographic evidence of lung involvement often precedes positive rRT-PCR findings by 4\u0026ndash;6 days[8].\u003c/p\u003e\u003cp\u003eThe RBD, S, and N proteins of SARS-CoV-2 are the primary antigens that cause a host immune response and the subsequent production of IgA, IgM, and IgG antibodies. Mucosal immune responses to SARS-CoV-2 are reflected in the titer of secretory IgA. In contrast to IgG, which is indicative of a chronic illness or a prior infection, the presence of IgM suggests the early, acute infectious stage. While IgM and IgG have been observed more often than IgA in relation to SARS-CoV-2 antibodies, the temporal dynamics of these antibodies have been shown to vary somewhat across investigations. There was evidence of IgA and IgM on the 5th day (median) and IgG by the 14th day (study) (median)[9]. The imported commercial kits for the detection of SARS-CoV-2 RNA (real-time RT-qPCR) and serological kits are of limited sensitivity and specificity and are very expensive.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAim of the study\u003c/strong\u003e\u003cp\u003eThe study aims to develop a real-time RT-qPCR kit for the first Iraqi detection of the SARS-CoV-2 virus using designed primers and probes.\u003c/p\u003e\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThe study aimed to develop a multiplex real-time RT-qPCR kit for in-house molecular detection of the SARS-CoV-2 N and E genes and a COVID-19-specific qualitative serological test based on an indirect ELISA targeting the S1 subunit of SARS-CoV-2 S proteins. Fifty nasopharyngeal swabs were confirmed to be positive for SARS-CoV-2 using the AccuPower\u0026reg; SARS-CoV-2 Multiplex Real-Time RT-PCR Kit, and fifty were confirmed to be negative; in addition, sixty serum specimens were collected from patients who were positive for IgG, of which twenty were from before the pandemic. Samples were collected between January 4 and April 1, 2022.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePrimers and probes design\u003c/h2\u003e\u003cp\u003ePrimers and TaqMan fluorogenic probes were designed based on conserved regions of the SARS-CoV-2 virus genome. The SARS-CoV-2 virus \u003cem\u003eE gene\u003c/em\u003e (165 bp) and N gene were retrieved from GenBank at NCBI (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.ncbi.nlm.nih.gov\" target=\"_blank\"\u003ewww.ncbi.nlm.nih.gov\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Epicov (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.epicov.org\u003c/span\u003e\u003cspan address=\"https://www.epicov.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Then, primers and probes were designed for these genes using the Primer3Plus website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and NCBI (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn\u0026amp;BLAST_SPEC=GeoBlast\u0026amp;PAGE_TYPE=BlastSearch\u003c/span\u003e\u003cspan address=\"https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn\u0026amp;BLAST_SPEC=GeoBlast\u0026amp;PAGE_TYPE=BlastSearch\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Internal control (IC) was the human gene and its primers and probe for MS2 detection; it was used as the IC in the in-house multiplex qPCR-designed kit.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEstablishment of the standard curve:\u003c/h3\u003e\n\u003cp\u003eAfter calculating the copy number of the E and N genes 52x \u0026times; 10\u003csup\u003e8\u003c/sup\u003e copies/ml for both genes) In one vial, the standard curve was established using 5 points from 100-fold serial dilutions prepared in TBE buffer. The standard curve generated from the clinical sample in each batch was used to calculate viral load.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eDesign and optimization of primers:\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe optimal concentrations and annealing temperatures for the designed primers for SARS-CoV-2 (E gene, N gene, and RdrP gene) were determined using a single positive sample with five annealing temperatures (46\u0026deg;C, 49\u0026deg;C, 52\u0026deg;C, 55\u0026deg;C, 58\u0026deg;C). Conventional gradient PCR and gel electrophoresis results showed that the optimal primer concentration was 0.1 \u0026micro;M and the optimal annealing temperature was 58\u0026deg;C, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProbe optimization\u003c/h3\u003e\n\u003cp\u003eFive positive SARS-CoV-2 samples were used to optimize the designed Taq-Man probes, and the results revealed that the optimal probe concentration for the best exponential and linear curves was 0.1 \u0026micro;M, as shown in Fig.\u0026nbsp;2.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure (2) (A) and (B) illustrate the log and linear curves of the SARS-CoV-2 positive E gene sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with VIC reporter dye. (C) and (D) illustrate the log and linear curves of the SARS-CoV-2 positive \u003cem\u003eN gene\u003c/em\u003e sample, respectively, that were formed through real-time RT-qPCR by designed primers and Taqman probes labeled with FAM reporter dye.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eOptimization of the In-house designed multiplex real-time RT qPCR\u003c/h2\u003e\u003cp\u003eThe in-house designed multiplex real-time RT qPCR kit was optimized for the detection of \u003cem\u003eN gene, E gene\u003c/em\u003e, and IC MS2, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStandardization and efficiency of in-house designed diplex RT qPCR\u003c/h3\u003e\n\u003cp\u003eOne hundred-fold serial dilutions of a single positive sample, containing the two targets (N and E genes) with viral load 52 \u0026times; 10\u003csup\u003e8\u003c/sup\u003e copies/ml, were diluted by TBE buffer to 0.52 copies/\u0026micro;l and 2.6 copies per reaction, then multiplex qPCR was conducted using an In-house designed kit in triplicate for each dilution.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure (4)\u003c/b\u003e: In-house qRT-PCR Standard curve. The standard curve of a serial dilution of a single positive sample ranged from 52*1010 copies/ml to 520 copies/ml. The slope value was \u0026minus;\u0026thinsp;3.4984, R\u0026sup2; 0.9807, and efficiency 93.1%.\u003c/p\u003e\n\u003ch3\u003eLimit of detection of the In-house designed multiplex qPCR assay\u003c/h3\u003e\n\u003cp\u003eThis study's results revealed that 520 copies/ml is the limit of detection (LOD) of the SARS-CoV-2 virus\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eIntra -and Inter-assay variability\u003c/h2\u003e\u003cp\u003eThe precision, or repeatability, of the in-house-designed multiplex qPCR assay was established using CT values obtained from testing positive samples in duplicates within each run (intra-assay) and across two different runs (inter-assay). The coefficient of variation (CV%) of \u003cem\u003eE gene\u003c/em\u003e for the threshold cycle values ranged between (0% \u0026minus;\u0026thinsp;7.64%) for inter-assay, with average of high and low CV% equal to 10.56%, and (0-9.75%) for intra-assay, with an average CV% equal to 3.02%, the C\u003csub\u003eT\u003c/sub\u003e values mean ranged (14.8\u0026ndash;33 C\u003csub\u003eT\u003c/sub\u003e). For the \u003cem\u003eN gene\u003c/em\u003e the coefficient of variation (CV%) for the threshold cycle values ranged between (0\u0026ndash;5.07%) for inter-assay, with an average of high and low CV% equal to 9.88%, and (0\u0026ndash;8.85%) for intra-assay, with average CV% equal to 2.51%, the C\u003csub\u003eT\u003c/sub\u003e values means ranged (14.65\u0026ndash;33.50 C\u003csub\u003eT\u003c/sub\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn-house N and E genes C\u003c/b\u003e\u003csub\u003e\u003cb\u003eT\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eValue vs Commercial N and E genes C\u003c/b\u003e\u003csub\u003e\u003cb\u003eT\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eValue Pearson\u0026rsquo;s Correlation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRegarding the relationship between the In-house N gene C\u003csub\u003eT\u003c/sub\u003e Value and the Commercial N gene C\u003csub\u003eT\u003c/sub\u003e Value, Pearson\u0026rsquo;s correlation in a sample size of 100 nasopharyngeal swab specimens showed a 95% confidence interval (0.088 to 0.578) and a significant association at P value 0.01, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The correlation between In-house E gene CT Value and Commercial E gene CT Value was 95% confidence interval (-0.044 to 0.48), and there was no significant association at P value 0.09, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the C\u003csub\u003eT\u003c/sub\u003e Values and copy numbers for the RT qPCR in-house-designed kit and the RT qPCR commercial kit.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eC\u003csub\u003eT\u003c/sub\u003e Value and copy number of RT qPCR In-house designed kit and C\u003csub\u003eT\u003c/sub\u003e Value of RT qPCR commercial kit.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSamples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u003csub\u003eT\u003c/sub\u003e Value of In-house E gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCopy number of the In-house E gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003eT\u003c/sub\u003e Value of in-house N gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCopy number of \u0026nbsp;the in-house N gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eC\u003csub\u003eT\u003c/sub\u003e Value Commercial E gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eC\u003csub\u003eT\u003c/sub\u003e Commercial N gene\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41 X 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84 X 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e21.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 x 10\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79X 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 X 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e32.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e21.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e88 x10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSs434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e98 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39 x 10\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 x 10\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 x 10\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35 x 10\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e96 x 10\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 x 10\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61 x 10\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e+\u0026thinsp;51 negative samples when measured by In-house RT qPCR and Commercial RT qPCR Kits\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAccuracy, sensitivity, and specificity of the In-House designed RT qPCR assay.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe nasopharyngeal swab panels tested positive/negative for the CT value of the N and E genes using a commercial kit, which was used as the gold standard to assess the sensitivity and specificity of the In-house designed real-time RT-qPCR assay. The sensitivity and specificity of the in-house-designed RT-qPCR E gene kit were measured. The assay was perform well with a sensitivity of 96% (95% CI 86.29% to 99.51%) and a specificity of 98.11% (95% CI 89.93% to 99.95%) a 97.96% (95% CI 87.31% to 99.70%) of positive predictive and a 96.30% (95% CI 86.99% to 99.02%) of negative predictive. Finally, the test's accuracy was 97.09% (95% CI 91.72% to 99.40%).\u003c/p\u003e\u003cp\u003eThe in-house-designed RT-qPCR N gene: Sensitivity and specificity. The assay was perform well with a sensitivity of 92.31% (95% CI 81.46% to 97.86%) and a specificity of 98.11% (95% CI 89.93% to 99.95%) also, it was demonstrated a 97.96% (95% CI 87.31% to 99.70%) of positive predictive and a 92.86% (95% CI 83.52% to 97.09%) of negative predictive. Finally, the test's accuracy was 95.24% (95% CI 89.24% to 98.44%).\u003c/p\u003e\u003cp\u003eThe overall or combined accuracy, Sensitivity, and Specificity of the in-house designed RT qPCR \u003cem\u003eN gene\u003c/em\u003e and \u003cem\u003eE genes\u003c/em\u003e. The assay performed well with a sensitivity of 96.08% (95% CI 86.54% to 99.52%) and a specificity of 100.00% (95% CI 93.02% to 100.00%). Also, it demonstrated a 100% positive predictive value and a 96.23% negative predictive value (95% CI 86.76% to 99.00%). Finally, the test's accuracy was 98.04% (95% CI 93.10% to 99.76%).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primers and TaqMan fluorogenic probes were designed based on conserved regions of the SARS-CoV-2 genome. The SARS-CoV-2 virus E and N genes were retrieved from Genbank by NCBI (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.ncbi.nlm.nih.gov\" target=\"_blank\"\u003ewww.ncbi.nlm.nih.gov\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.epicov.org\u003c/span\u003e\u003cspan address=\"https://www.epicov.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The primers and probes for these genes were then designed using the primer3plus website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and NCBI ( \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://blast.ncbi.nlm.nih.gov/Blast.cgi\\PROGRAM=blastn\u0026amp;BLAST_SPEC=GeoBlast\u0026amp;PAGE_TYPE=BlastSearch\u003c/span\u003e\u003cspan address=\"https://blast.ncbi.nlm.nih.gov/Blast.cgi\\PROGRAM=blastn\u0026amp;BLAST_SPEC=GeoBlast\u0026amp;PAGE_TYPE=BlastSearch\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e ). Conventional gradient PCR reactions were used to check the correct amplification of the desired fragments and to fine-tune the optimal annealing temperature for the designed primers. The optimal annealing temperature for the designed SARS-CoV-2 (E gene and N gene) primers was 58\u0026deg;C; the other annealing temperatures (46\u0026deg;C, 49\u0026deg;C, 52\u0026deg;C, and 55\u0026deg;C) also yielded positive results.\u003c/p\u003e\u003cp\u003eSince there is no quantitative molecular detection of SARS-CoV-2 in Iraq, this study aimed to establish an RT quantitative PCR assay for the detection of SARS-CoV-2 viral load. This was achieved by making 100-fold serial dilutions of a single positive sample for the two targets (N and E genes) with viral load 52 \u0026times; 10^8 copies/ml, which were diluted by TBE buffer to 0.52 copies/\u0026micro;l, 2.6 copies per reaction, then multiplex qPCR was conducted using an in-house designed kit. This assumption also aligns with Myungsun et al. in Korea in 2020, who used SARS-CoV-2 cDNA as a positive control and human-derived HEK-293T cDNA as the human IPC [10]. Actually, preparing an absolute quantitative real-time RT-qPCR has several advantages over the qualitative commercial assays. First, the in-house-prepared kit enables scientists and clinicians to estimate viral load precisely in nasopharyngeal swabs or blood, facilitating decision-making and research. Second, the in-house-prepared kit contains a standard curve for each run, which increases accuracy and repeatability by precisely estimating the variance and performance of the kit in both intra- and inter-assay analyses.\u003c/p\u003e\u003cp\u003eDuring the COVID-19 pandemic, the primary diagnostic priority is identifying the infection, the infectious, and the vulnerable [11]. The limit of detection (LoD) of the SARS-CoV-2 virus was determined using an in-house designed qPCR multiplex with 0.52 copies/l and 2.6 copies per reaction. \u003cem\u003eYushen etal.\u003c/em\u003e In 2021, in China, they found that the test's true LoD falls between 10 and 1 copies/\u0026micro;L [12]. Other studies confirmed the preliminary LoD by testing 20 replicates of 2-fold dilutions (50 cp/\u0026micro;L, 25 cp/\u0026micro;L, 12.5 cp/\u0026micro;L, 6.25 cp/\u0026micro;L, 3.125 cp/\u0026micro;L, and 1.25 cp/\u0026micro;L)[13].\u003c/p\u003e\u003cp\u003eThe study's findings reveal a broad spectrum of viral loads, suggesting that specific infected individuals with viral loads near, within, or even below the limits of detection of many standard assays may remain undiagnosed. As a result, these undetected individuals could potentially transmit the infection to others.\u003c/p\u003e\u003cp\u003eThe coefficient of variation (CV%) of the E gene for the threshold cycle values ranged between (0% \u0026minus;\u0026thinsp;7.64%) for inter-assay, with an average of high and low CV% equal to 10.56%, and (0-9.75%) for intra-assay, with an average CV% equal to 3.02%. For N gene, the coefficient of variation (CV%) for the threshold cycle values ranged between (0\u0026ndash;5.07%) for inter-assay, with an average of high and low CV% equal to 9.88%, and (0\u0026ndash;8.85%) for intra-assay with an average CV% equal to 2.51%, the CT values means ranged (14.65\u0026ndash;33.50 CT). As a result, the intra- and inter-assay variability values of the in-house prepared kit are excellent, falling well within the 10% and 15% acceptable ranges, respectively, considered to be within international acceptable ranges [14].\u003c/p\u003e\u003cp\u003eThe current study shows that an in-house assay is adequate for the identification of SARS-CoV-2 RNA in clinical samples when compared with the commercial AccuPower\u0026reg; SARS-CoV-2 Multiplex Real-Time RT-PCR Kit. Regarding the relationship between the in-house N gene CT value with a mean of 22 CT and the commercial N gene CT value with a mean of 23 CT, the Pearson\u0026rsquo;s correlation in sample size 100 nasopharyngeal swap specimens showed a 95% confidence interval (0.088 to 0.578) and a significant association at P value 0.01; this association may be explained by the fact that the in-house designed primers and probe targeting the N gene region target more conserved regions than the commercial primers and probe did. Furthermore, the correlation between the in-house E gene CT value (mean 24.2) and the commercial E gene CT value (mean 23.4) has a 95% confidence interval of -0.044 to 0.48, and there was no significant association at a P value of 0.09. This study is partially superior to the correlation values reported by Dayakar et al. in 2022 in the USA, who found a significant association between the CDC-modified SARS-CoV-2 real-time PCR assay and four commercial assays [15]. A 2021 study by Yushen et al. in China indicated that using the E gene region for primary screening of viral infection, the highly conserved N gene can specifically detect the SARS-CoV-2 virus [12].\u003c/p\u003e\u003cp\u003eThe nasopharyngeal swab panels were tested for CT values of the N and E genes, which were positive or negative. The commercial kit was used as the gold standard to assess the sensitivity and specificity of the in-house-designed multiplex RT-qPCR assay. The in-house E gene RT-qPCR assay performed admirably, with a sensitivity of 96% and a specificity of 98.11%; it also demonstrated positive and negative predictive values of 97.96% and 96.30%, respectively. The test's accuracy was 97.09%. The in-house-designed RT-qPCR assay for the N gene also performed well, with a sensitivity of 92.31% and a specificity of 98.11%, and it demonstrated 97.96% positive and 92.86% negative predictive values. The test's accuracy was 95.24%. Accordingly, the overall performance of the in-house-designed multiplex RT-qPCR targeting both N and E genes was 96.08% sensitivity and 100.00% specificity, with 100% positive predictive and 96.23% negative predictive values. Finally, the overall test accuracy was 98.04%.\u003c/p\u003e\u003cp\u003eIn this study, the high sensitivity of the in-house designed kit came from the optimization procedures used for annealing temperatures on real Iraqi strains of SARS-CoV-2 by using gradient conventional PCR to select the highest yield but still specific annealing temperature for primers, as well as the lengthy optimization steps done for the primers and probes concentrations; moreover, perfect samples collection and processing as well as using efficient RNA extraction protocols might have a role in the production of high sensitivity and specificity. The high specificity of in-house multiplex RT qPCR with no cross-reactivity with common human respiratory viruses came from the primers and probes design tools used in this study; the designed primers and probes were theoretically tested on all SARS-CoV-2 variants from the reference wild-type variant to the Omicron variant by using NCBI and GISAID GenBank and bioinformatics tools. Many RT-PCR kits for detecting the SARS-CoV-2 virus have been developed by laboratories around the world since the outbreak began, each with its own sensitivity and specificity. \u003cem\u003eYes, in 2022, in Switzerland, Bello-Lemus et al. developed a triplex RT-qPCR assay for identifying SARS-CoV-2 that was 98.3% sensitive, 100% specific, and 99.2% accurate\u003c/em\u003e [16]. A different study compared their in-house kit with the commercial Sansure kit, finding that the proposed in-house assay had a sensitivity of 93% and a specificity of 97% [17]. Although the US CDC recommends a set of primers for the N region, these 2019-nCoV N2 primers have been shown to have substantial background cross-reactivity in at least three separate investigations [18].\u003c/p\u003e\u003cp\u003eAccording to the findings of the current study, the conclusions are: The in-house-designed multiplex real-time RT-qPCR kit was more sensitive than the commercial kit for detecting SARS-CoV-2. The in-house designed kits were far less expensive than the commercial kits. This study demonstrated a broad range of viral loads, which means some infected individuals with low viral loads might be below the LOD of many commonly used assays. A library of SARS-CoV-2 recombinant S1 subunits was prepared in competent bacteria and can be used at any time for various purposes (e.g., diagnostic tool development and research). The in-house anti-SARS-CoV-2 human IgG-ELISA was sensitive and specific for detecting IgG antibodies in individuals exposed to SARS-CoV-2.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cb\u003eEthics approval and consent to participate\u003c/b\u003e.\u003c/strong\u003e\u003cp\u003eThe Institutional Review Board approved the study. Board (IRB) of Al-Nahrain University, College of Medicine, Baghdad, Iraq. Approval Number: 2020/983. Approval Date: January 10, 2021.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe author declares no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis study did not receive any external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAbdul-Sattar AL-Saeedi led the project, designed the study, and supervised its implementation. Ahmed Sahib Abdulamir developed the research plan and provided oversight. Iman M. Aufi assisted with laboratory work, while Salah Hashim Shaheed contributed to primer and probe design and performed computational analysis.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e\u003cp\u003eThe author expresses gratitude to the technical staff and laboratory teams for their help and support in carrying out this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed in this study are included in this article and its supplementary files. For more details, please reach out to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eÖzdemir, Ö., \u003cem\u003eCoronavirus disease 2019 (COVID-19): diagnosis and management.\u003c/em\u003e Journal of Clinical Practice and Research, 2020. \u003cb\u003e42\u003c/b\u003e(3): p. 242.\u003c/li\u003e\n\u003cli\u003eÖzdemir, Ö., \u003cem\u003eCoronavirus Disease 2019 (COVID-19): Diagnosis and Management (narrative review).\u003c/em\u003e Erciyes Medical Journal, 2020.\u003c/li\u003e\n\u003cli\u003eSalahshoori, I., et al., \u003cem\u003eOverview of COVID-19 Disease: Virology, Epidemiology, Prevention, Diagnosis, Treatment, and Vaccines.\u003c/em\u003e Biologics, 2021. \u003cb\u003e1\u003c/b\u003e(1): p. 2–40.\u003c/li\u003e\n\u003cli\u003eSu, S., et al., \u003cem\u003eEpidemiology, Genetic Recombination, and Pathogenesis of Coronaviruses.\u003c/em\u003e Trends Microbiol, 2016. \u003cb\u003e24\u003c/b\u003e(6): p. 490–502.\u003c/li\u003e\n\u003cli\u003eYurkovetskiy, L., et al., \u003cem\u003eStructural and Functional Analysis of the D614G SARS-CoV-2 Spike Protein Variant.\u003c/em\u003e Cell, 2020. \u003cb\u003e183\u003c/b\u003e(3): p. 739–751.e8.\u003c/li\u003e\n\u003cli\u003e\u003cem\u003e\u0026lt;WHO Director-General's opening remarks at the media briefing on COVID-19–11 March 2020.pdf\u0026gt;.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eLiu, R., et al., \u003cem\u003ePositive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020.\u003c/em\u003e Clinica chimica acta, 2020. \u003cb\u003e505\u003c/b\u003e: p. 172–175.\u003c/li\u003e\n\u003cli\u003eAbduljalil, J., \u003cem\u003eLaboratory diagnosis of SARS-CoV-2: available approaches and limitations.\u003c/em\u003e New microbes and new infections, 2020. \u003cb\u003e36\u003c/b\u003e: p. 100713.\u003c/li\u003e\n\u003cli\u003eShereen, M.A., et al., \u003cem\u003eCOVID-19 infection: Origin, transmission, and characteristics of human coronaviruses.\u003c/em\u003e J Adv Res, 2020. \u003cb\u003e24\u003c/b\u003e: p. 91–98.\u003c/li\u003e\n\u003cli\u003ePark, M., et al., \u003cem\u003eOptimization of primer sets and detection protocols for SARS-CoV-2 of coronavirus disease 2019 (COVID-19) using PCR and real-time PCR.\u003c/em\u003e Experimental \u0026amp; molecular medicine, 2020. \u003cb\u003e52\u003c/b\u003e(6): p. 963–977.\u003c/li\u003e\n\u003cli\u003eArnaout, R., et al., \u003cem\u003eSARS-CoV2 testing: the limit of detection matters.\u003c/em\u003e BioRxiv, 2020.\u003c/li\u003e\n\u003cli\u003eJiang, Y., et al., \u003cem\u003eEstablishment of a quantitative RT-PCR detection of SARS-CoV-2 virus.\u003c/em\u003e European journal of medical research, 2021. \u003cb\u003e26\u003c/b\u003e(1): p. 1–7.\u003c/li\u003e\n\u003cli\u003e\u003cem\u003e\u0026lt;EUA-Labcorp-COVID-EUAsum_1.pdf\u0026gt;.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eThomsson, O., et al., \u003cem\u003eValidation of an enzyme-linked immunosorbent assay developed for measuring cortisol concentration in human saliva and serum for its applicability to analyze cortisol in pig saliva.\u003c/em\u003e Acta Veterinaria Scandinavica, 2014. \u003cb\u003e56\u003c/b\u003e(1): p. 1–5.\u003c/li\u003e\n\u003cli\u003eSeetha, D., A. Ravikumar, and R.R. Nair, \u003cem\u003eComparative performance of CDC-modified SARS-CoV-2 real-time PCR assay with four different commercial assays: laboratory-based study.\u003c/em\u003e Comparative Clinical Pathology, 2022: p. 1–9.\u003c/li\u003e\n\u003cli\u003eBello-Lemus, Y., et al., \u003cem\u003eComparative Analysis of In-House RT-qPCR Detection of SARS-CoV-2 for Resource-Constrained Settings.\u003c/em\u003e Diagnostics, 2022. \u003cb\u003e12\u003c/b\u003e(11): p. 2883.\u003c/li\u003e\n\u003cli\u003eSarkar, S.L., et al., \u003cem\u003eDevelopment and validation of cost-effective one-step multiplex RT-PCR assay for detecting the SARS-CoV-2 infection using SYBR Green melting curve analysis.\u003c/em\u003e Scientific reports, 2022. \u003cb\u003e12\u003c/b\u003e(1): p. 1–13.\u003c/li\u003e\n\u003cli\u003eVogels, C.B., et al., \u003cem\u003eAnalytical sensitivity and efficiency comparisons of SARS-CoV-2 RT–qPCR primer–probe sets.\u003c/em\u003e Nature microbiology, 2020. \u003cb\u003e5\u003c/b\u003e(10): p. 1299–1305.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8233598/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8233598/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe widespread use of accurate real-time RT-PCR tests for community individuals is a critical approach to managing the disease and reducing COVID-19 transmission effectively. In addition, serological ELISA assays are another essential tool for detecting and/or quantifying SARS-CoV-2 IgG and IgM antibodies or for screening for SARS-CoV-2 infection.\u003c/p\u003e\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eThe objective of the current study is to develop an in-house multiplex real-time RT-qPCR kit for molecular detection of SARS-CoV-2 \u003cem\u003eN and E genes\u003c/em\u003e.\u003c/p\u003e\u003ch2\u003eMaterials and methods\u003c/h2\u003e\u003cp\u003eA total of 100 samples from the Central Public Health Laboratory were analyzed: 50 tested positive for SARS-CoV-2 RNA and 50 tested negative.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe in-house multiplex qPCR assay showed a significant association at P value 0.01 between the in-house N gene CT Value and the commercial N gene CT value, but there was no significant association at P value 0.09 between the in-house E gene CT Value and the commercial E gene CT Value. The in-house-designed RT-qPCR-E gene had a sensitivity of 96% and a specificity of 98.11%. The in-house-designed RT-qPCR N gene had a sensitivity of 92.31% and a specificity of 98.11%. Overall, or combined, sensitivity and specificity of the in-house-designed RT qPCR assay were 96.08% and 100.00%, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe in-house-designed multiplex real-time RT-qPCR kit was more sensitive than the commercial kit for detecting SARS-CoV-2, and the in-house ELISA kit showed acceptable sensitivity and specificity, given its very low cost. The in-house designed kits were far less expensive than the commercial kits. This study demonstrated a broad range of viral loads, which means some infected individuals with low viral loads might be below the limit of detection of commercial assays.\u003c/p\u003e","manuscriptTitle":"Designing and making an in-house real-time RT qPCR kit for the detection of SARS-CoV- 2 infection at high sensitivity and low cost","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-10 09:27:48","doi":"10.21203/rs.3.rs-8233598/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b4568ba1-0d17-432c-b8aa-d26f8db70c7f","owner":[],"postedDate":"December 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-15T10:09:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-10 09:27:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8233598","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8233598","identity":"rs-8233598","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}