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.

IF 1.8 3区 农林科学 Q2 PLANT SCIENCES
Hyo-Jeong Lee, Hae-Jun Kim, Sang-Min Kim, Rae-Dong Jeong
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Abstract

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/μl. 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.

基于反转录纳米片的数字 PCR 检测方法的开发与应用,用于灵敏、准确地检测谷类作物中的水稻黑条矮缩病病毒。
水稻黑条矮缩病病毒(RBSDV)的出现对全球谷类作物种植构成了重大威胁,因此迫切需要开发可靠的检测和定量技术。本研究采用一种反转录数字聚合酶链反应(RT-dPCR)检测方法,为精确、灵敏地定量检测谷类作物样本中的 RBSDV 引入了一种可靠的方法。我们评估了为精确检测和量化 RBSDV 而提出的 RT-dPCR 检测方法的特异性和灵敏度。我们的研究结果表明,RT-dPCR 对检测 RBSDV 具有特异性,与感染谷类作物的其他病毒没有交叉反应。RT-dPCR 的灵敏度是 RT 定量 PCR(RT-qPCR)的 10 倍以上。RT-dPCR 的检测限为 0.096 个拷贝/微升。此外,通过对 60 份不同的谷类作物样本进行田间样本 RT-dPCR 分析评估发现,与 RT-qPCR(23/60)相比,RT-dPCR(45/60)表现出更高的准确性。在本研究中,我们提出了一种用于检测和定量 RBSDV 的特异而准确的 RT-dPCR 分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Plant Pathology Journal
Plant Pathology Journal 生物-植物科学
CiteScore
4.90
自引率
4.30%
发文量
71
审稿时长
12 months
期刊介绍: Information not localized
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