RT-RPA 分析法与侧流带相结合检测大豆花叶病毒。

IF 1.8 3区 农林科学 Q2 PLANT SCIENCES
Bong Geun Oh, Ju-Yeon Yoon, Ho-Jong Ju
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引用次数: 0

摘要

大豆(Glycine max L.)是世界上种植和使用最广泛的豆科植物之一,可用于食品、动物饲料产品和工业生产。大豆花叶病毒(SMV)是感染大豆植物最普遍的病毒。本研究利用反转录-重组聚合酶扩增(RT-RPA)技术结合侧流条带(LFS)开发了一种快速灵敏检测 SMV 的诊断方法。利用扩增部分 VPg 蛋白基因的引物组对检测 SMV 的 RT-RPA 和 RT-RPA-LFS 条件进行了优化。本研究中使用的 RT-RPA 引物和 RT-RPA-LFS 引物的优化反应温度均为 38℃,最短反应时间分别为 10 分钟和 5 分钟。在检测 10 pg/μl 总 RNA 的 SMV 时,RT-RPA-LFS 的灵敏度与 RT-PCR 不相上下。利用从大豆田中采集的叶片对所开发的 RT-RPA-LFS 检测方法的可靠性进行了评估。本研究开发的 RT-RPA-LFS 诊断方法可作为一种诊断方法,在资源有限的地方农场进行 SMV 流行病学调查和抗 SMV 品种选育过程中快速、准确地检测 SMV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RT-RPA Assay Combined with a Lateral Flow Strip to Detect Soybean Mosaic Virus.

Soybean (Glycine max L.) is one of the most widely planted and used legumes in the world, being used for food, animal feed products, and industrial production. The soybean mosaic virus (SMV) is the most prevalent virus infecting soybean plants. This study developed a diagnostic method for the rapid and sensitive detection of SMV using a reverse transcription-recombinase polymerase amplification (RT-RPA) technique combined with a lateral flow strip (LFS). The RT-RPA and RT-RPA-LFS conditions to detect the SMV were optimized using the selected primer set that amplified part of the VPg protein gene. The optimized reaction temperature for the RT-RPA primer and RT-RPA-LFS primer used in this study was 38℃ for both, and the minimum reaction time was 10 min and 5 min, respectively. The RT-RPA-LFS was as sensitive as RT-PCR to detect SMV with 10 pg/μl of total RNA. The reliability of the developed RT-RPA-LFS assay was evaluated using leaves collected from soybean fields. The RT-RPA-LFS diagnostic method developed in this study will be useful as a diagnostic method that can quickly and precisely detect SMV in the epidemiological investigation of SMV, in the selection process of SMV-resistant varieties, on local farms with limited resources.

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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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