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下一代测序技术在大豆大规模病原体诊断中的应用。

Applications of Next-Generation Sequencing for Large-Scale Pathogen Diagnoses in Soybean.

机构信息

Department of Biology, Brandon University, Brandon, Manitoba R78 6A9, Canada.

出版信息

Plant Dis. 2019 Jun;103(6):1075-1083. doi: 10.1094/PDIS-05-18-0905-RE. Epub 2019 Apr 22.

DOI:10.1094/PDIS-05-18-0905-RE
PMID:31009362
Abstract

Soybean () has become an important crop in Manitoba, Canada, with a 10-fold increase in dedicated acreage over the past decade. Given the rapid increase in production, scarce information about foliar diseases present in the province has been recorded. In order to describe the foliar pathogens affecting this legume, we harnessed next-generation sequencing (NGS) to carry out a comprehensive survey across Manitoba in 2016. Fields were sampled during the V2/3 (33 fields) and R6 (70 fields) growth stages, with at least three symptomatic leaves per field collected and subjected to RNA sequencing. We successfully detected several bacteria, fungi, and viruses known to infect soybean, including pv. , , and , as well as pathogens not previously identified in the province (e.g., pv. , , and ). For some microorganisms, we were able to disentangle the different pathovars present and/or assemble their genome sequence. Since NGS generates data on the entire flora and fauna occupying a leaf sample, we also identified residual pathogens (i.e., pathogens of crops other than soybean) and multiple species of arthropod pests. Finally, the sequence information produced by NGS allowed for the development of polymerase chain reaction-based diagnostics for some of the most widespread and important pathogens. Although there are many benefits of using NGS for large-scale plant pathogen diagnoses, we also discuss some of the limitations of this technology.

摘要

大豆(Soybean)已成为加拿大马尼托巴省的重要作物,在过去十年中,专用种植面积增加了 10 倍。鉴于产量的快速增长,该省记录的关于叶片病害的信息却很少。为了描述影响这种豆科植物的叶片病原体,我们利用下一代测序(NGS)技术于 2016 年在马尼托巴省进行了全面调查。在 V2/3(33 个地块)和 R6(70 个地块)生长阶段采集了田间样本,每个地块至少采集了 3 片有症状的叶片,并进行了 RNA 测序。我们成功检测到了几种已知感染大豆的细菌、真菌和病毒,包括 pv. 、 、 、 ,以及该省以前未鉴定出的病原体(例如 pv. 、 、 )。对于一些微生物,我们能够区分存在的不同致病变种并/或组装它们的基因组序列。由于 NGS 会生成关于占据叶片样本的整个动植物群的数据,因此我们还鉴定了残留病原体(即除大豆以外的作物病原体)和多种节肢动物害虫。最后,NGS 产生的序列信息可用于为一些最广泛和最重要的病原体开发基于聚合酶链反应的诊断方法。尽管使用 NGS 进行大规模植物病原体诊断有很多好处,但我们也讨论了该技术的一些局限性。

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