• Title/Summary/Keyword: reverse transcription digital PCR

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Application of Reverse Transcription Droplet Digital PCR for Detection and Quantification of Tomato Spotted Wilt Virus (Reverse Transcription Droplet Digital PCR을 활용한 Tomato Spotted Wilt Virus 검출 및 정량)

  • Lee, Hyo-Jeong;Park, Ki Beom;Han, Yeon Soo;Jeong, Rae-Dong
    • Research in Plant Disease
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    • v.27 no.3
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    • pp.120-127
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    • 2021
  • Plant viruses cause significant yield losses, continuously compromising crop production and thus representing a serious threat to global food security. Tomato spotted wilt virus (TSWV) is the most harmful plant virus that mainly infects horticultural crops and has a wide host range. Reverse-transcription quantitative real-time PCR (RT-qPCR) has been widely used for detecting TSWV with high sensitivity, but its application is limited owing to the lack of standardization. Therefore, in this study, a sensitive and accurate reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) method was established for TSWV detection. Additionally, we compared the sensitivities of RT-qPCR and RT-ddPCR for TSWV detection. Specificity analysis of RT-ddPCR for TSWV showed no amplification for main pepper viruses and negative control. TSWV transcripts levels measured by RT-ddPCR and RT-qPCR showed a high degree of linearity; however, the former yielded results that were at least 10-fold more sensitive and detected lower TSWV copy numbers than the latter. Collectively, our findings show that RT-ddPCR provides improved analytical sensitivity and specificity for TSWV detection, making it suitable for identifying low TSWV concentrations in field samples.

Development and Application of Reverse Transcription Nanoplate-Based Digital PCR Assay for Sensitive and Accurate Detection of Rice Black-Streaked Dwarf Virus in Cereal Crops

  • Hyo-Jeong Lee;Hae-Jun Kim;Sang-Min Kim;Rae-Dong Jeong
    • The Plant Pathology Journal
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    • v.40 no.4
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    • pp.408-413
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    • 2024
  • The emergence of rice black-streaked dwarf virus (RBSDV) poses a significant threat to global cereal crop cultivation, necessitating the urgent development of reliable detection and quantification techniques. This study introduces a reliable approach for the precise and sensitive quantification of the RBSDV in cereal crop samples, employing a reverse transcription digital polymerase chain reaction (RT-dPCR) assay. We assessed the specificity and sensitivity of the RT-dPCR assay proposed for precise RBSDV detection and quantification. Our findings demonstrate that RT-dPCR was specific for detection of RBSDV, with no cross-reactivity observed with other viruses infecting cereal crops. The RT-dPCR sensitivity was over 10 times that of RT-quantitative PCR (RT-qPCR). The detection limit of RT-dPCR was 0.096 copies/㎕. In addition, evaluation of RT-dPCR assay with field samples was conducted on 60 different cereal crop samples revealed that RT-dPCR (45/60) exhibited superior accuracy compared with RT-qPCR (23/60). In this study, we present a specific and accurate RT-dPCR assay for the detection and quantification of RBSDV.

Detection and Quantification of Apple Stem Grooving Virus in Micropropagated Apple Plantlets Using Reverse-Transcription Droplet Digital PCR

  • Kim, Sung-Woong;Lee, Hyo-Jeong;Cho, Kang Hee;Jeong, Rae-Dong
    • The Plant Pathology Journal
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    • v.38 no.4
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    • pp.417-422
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    • 2022
  • Apple stem grooving virus (ASGV) is a destructive viral pathogen of pome fruit trees that causes significant losses to fruit production worldwide. Obtaining ASGV-free propagation materials is essential to reduce economic losses, and accurate and sensitive detection methods to screen ASGV-free plantlets during in vitro propagation are urgently necessary. In this study, ASGV was sensitively and accurately quantified from in vitro propagated apple plantlets using a reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) assay. The optimized RT-ddPCR assay was specific to other apple viruses, and was at least 10-times more sensitive than RT-real-time quantitative PCR assay. Furthermore, the optimized RT-ddPCR assay was validated for the detection and quantification of ASGV using micropropagated apple plantlet samples. This RT-ddPCR assay can be utilized for the accurate quantitative detection of ASGV infection in ASGV-free certification programs, and can thus contribute to the production of ASGV-free apple trees.

Comparison of Digital PCR and Quantitative PCR with Various SARS-CoV-2 Primer-Probe Sets

  • Park, Changwoo;Lee, Jina;Hassan, Zohaib ul;Ku, Keun Bon;Kim, Seong-Jun;Kim, Hong Gi;Park, Edmond Changkyun;Park, Gun-Soo;Park, Daeui;Baek, Seung-Hwa;Park, Dongju;Lee, Jihye;Jeon, Sangeun;Kim, Seungtaek;Lee, Chang-Seop;Yoo, Hee Min;Kim, Seil
    • Journal of Microbiology and Biotechnology
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    • v.31 no.3
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    • pp.358-367
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    • 2021
  • The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, which is the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (CT) of the viral RNA by RT-PCR significantly varied according to the sequences of the primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of the viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be equal to or more than that of the RT-qPCR. However, the ddPCR assay is more suitable for determining the copy number of reference materials. These findings suggest that the qPCR assay with the ddPCR defined reference materials could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.

Gene Expression Profile and Its Interpretation in Squamous Cell Lung Cancer

  • Park, Dong-Yoon;Kim, Jung-Min;Kim, Ja-Eun;Yoo, Chang-Hyuk;Lee, Han-Yong;Song, Ji-Young;Hwang, Sang-Joon;Yoo, Jae-Cheal;Kim, Sung-Han;Park, Jong-Ho;Yoon, Jeong-Ho
    • Molecular & Cellular Toxicology
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    • v.2 no.4
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    • pp.273-278
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    • 2006
  • 95 squamous cell lung carcinoma samples (normal tissue: 40 samples, tumor: 55 samples) were analyzed with 8 K cDNA microarray. 1-way ANOVA test was employed to select differentially expressed genes in tumor with FDR<0.01. Among the selected 1,655 genes, final 212 genes were chosen according to the expression fold change and used for following analysis. The expression of up-regulated 64 genes was verified with Reverse Transcription PCR and 10 genes were identified as candidates for SCC markers. In our opinion, those candidates can be exploited as diagnostic or therapeutic purposes. Gene Ontology (GO) based analysis was performed using those 212 genes, and following categories were revealed as significant biological processes: Immune response (GO: 0006955), antigen processing (GO: 0030333), inflammatory response (GO: 0006954), Cell adhesion (GO: 0007155), and Epidermis differentiation (GO: 0008544). Gene set enrichment analysis (GSEA) also carried out on overall gene expression profile with 522 functional gene sets. Glycolysis, cell cycle, K-ras and amino acid biosynthesis related gene sets were most distinguished. These results are consistent with the known characteristics of SCC and may be interconnected to rapid cell proliferation. However, the unexpected results from ERK activation in squamous cell carcinoma gripped our attention, and further studies are under progress.

Molecular epidemiologic trends of norovirus and rotavirus infection and relation with climate factors: Cheonan, Korea, 2010-2019 (노로바이러스 및 로타바이러스 감염의 역학 및 기후요인과의 관계: 천안시, 2010-2019)

  • Oh, Eun Ju;Kim, Jang Mook;Kim, Jae Kyung
    • Journal of Digital Convergence
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    • v.18 no.12
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    • pp.425-434
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    • 2020
  • Background: Viral infection outbreaks are emerging public health concerns. They often exhibit seasonal patterns that could be predicted by the application of big data and bioinformatic analyses. Purpose: The purpose of this study was to identify trends in diarrhea-causing viruses such as rotavirus (Gr.A), norovirus G-I, and norovirus G-II in Cheonan, Korea. The identified related factors of diarrhea-causing viruses may be used to predict their trend and prevent their infections. Method: A retrospective analysis of 4,009 fecal samples from June 2010 to December 2019 was carried out at Dankook University Hospital in Cheonan. Reverse transcription-PCR (RT-PCR) was employed to identify virus strains. Information about seasonal patterns of infection was extracted and compared with local weather data. Results: Out of the 4,009 fecal samples tested using multiplex RT-PCR (mRT-PCR), 985 were positive for infection with Gr.A, G-I, and G-II. Out of these 985 cases, 95.3% (n = 939) were under 10 years of age. Gr.A, G-I, and G-II showed high infection rates in patients under 10 years of age. Student's t-test showed a significant correlation between the detection rate of Gr.A and the relative humidity. The detection rate of G-II significantly correlated with wind-chill temperature. Conclusion: Climate factors differentially modulate rotavirus and norovirus infection patterns. These observations provide novel insights into the seasonal impact on the pathogenesis of Gr.A, G-I, and G-II.