Corteva Agriscience, Indianapolis, IN 46268.
Department of Plant Pathology, North Dakota State University, Fargo, ND 58108.
Plant Dis. 2021 Dec;105(12):3848-3857. doi: 10.1094/PDIS-01-21-0129-RE. Epub 2021 Dec 3.
The soybean cyst nematode (SCN) continues to be a major threat to soybean production worldwide. Morphological discrimination between SCN and other nematodes of the group is not only difficult and time-consuming but also requires high expertise in nematode taxonomy. Molecular assays were developed to differentiate SCN from sugar beet cyst nematode (SBCN) and other nematodes and to quantify SCN directly from DNA extracts of field soils. SCN- and SBCN-specific quantitative real-time PCR (qPCR) primers were designed from a nematode-secreted CLAVATA gene and used for these assays. The primers were evaluated on the basis of target specificity to SCN or SBCN using DNA from 20 isolates of SCN and 32 isolates of other plant-parasitic nematodes. A standard curve relating threshold cycle and log values of nematode numbers was generated from artificially infested soils and was used to quantify SCN in naturally infested field soils. There was a high correlation between the SCN numbers estimated from naturally infested field soils by conventional methods, and the numbers quantified using the SYBR Green I-based qPCR assay. The qPCR assay is highly specific and sensitive and provides improved SCN detection sensitivity down to 1 SCN egg in 20 g of soil (10 eggs/200 g soil). This assay is useful for efficient detection and quantification of SCN directly from field soil. Species-specific conventional PCR assays were also developed each for SCN and SBCN, alongside a qPCR assay that simultaneously discriminates SCN from SBCN. These assays require no expertise in nematode taxonomy and morphology, and they may serve as useful diagnostic tools in research, diagnostic laboratories, and extension services for SCN management. Sensitive and accurate detection and quantification of SCN are essential for recommending effective management measures against SCN. We also investigated the impact of soil texture and nematode life stage on molecular quantification of SCN.
大豆胞囊线虫(SCN)仍然是全球大豆生产的主要威胁。SCN 与该组其他线虫的形态鉴别不仅困难且耗时,而且需要线虫分类学方面的专业知识。已经开发了分子测定法来区分 SCN 与甜菜胞囊线虫(SBCN)和其他线虫,并直接从田间土壤的 DNA 提取物中定量 SCN。从线虫分泌的 CLAVATA 基因设计了 SCN 和 SBCN 特异性定量实时 PCR(qPCR)引物,并用于这些测定。使用 20 个 SCN 分离株和 32 个其他植物寄生线虫的分离株的 DNA 评估了引物对 SCN 或 SBCN 的靶特异性。从人工侵染土壤中生成了与阈值循环和线虫数量对数相关的标准曲线,并用于定量自然侵染田间土壤中的 SCN。通过常规方法从自然侵染田间土壤中估算的 SCN 数量与使用 SYBR Green I 基 qPCR 测定法定量的 SCN 数量之间存在高度相关性。qPCR 测定法具有高度特异性和敏感性,并提供了改进的 SCN 检测灵敏度,可达到每 20 克土壤中有 1 个 SCN 卵(200 克土壤中有 10 个卵)。该测定法可直接从田间土壤中有效检测和定量 SCN。还为 SCN 和 SBCN 各自开发了特异性常规 PCR 测定法,以及同时区分 SCN 和 SBCN 的 qPCR 测定法。这些测定法不需要线虫分类学和形态学方面的专业知识,它们可以作为研究、诊断实验室和 SCN 管理推广服务的有用诊断工具。对 SCN 进行敏感且准确的检测和定量对于推荐有效的 SCN 管理措施至关重要。我们还研究了土壤质地和线虫生活阶段对 SCN 分子定量的影响。