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在RNA测序数据中超越病毒检测:从基于社区的努力中吸取的教训,以检测细胞植物病原体和害虫

Annelies Haegeman¹, Yoika Foucart¹, Kris De Jonghe¹

¹Plant Sciences Unit, Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), 9820 Merelbeke, Belgium.

Plants (Basel, Switzerland)

|June 10, 2023

概括

高通量测序 (HTS) 数据通常用于植物病毒检测,也可以识别其他植物病原体,如真菌和昆虫. 重新分析现有的RNA测序数据集,在78%的样本中发现了非病毒性病原体,突出了这些数据的未开发潜力.

科学领域:

植物病理学植物病理学
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

高通量测序 (HTS) 和RNA测序 (RNA-seq) 对于植物病毒识别至关重要.
目前的分析往往忽略了非病毒序列,代表了大多数测序阅读.
这种未充分利用意味着错失了检测更广泛的植物健康威胁的机会.

研究的目的:

调查总RNA-seq数据是否适用于检测非病毒性植物病原体和害虫.
评估现有的植物病毒检测数据集是否含有其他生物体的痕迹.
为了证明RNA-seq数据在病毒学之外的实用性.

主要方法:

从植物材料中分析RNA-seq数据集,确认细胞病原体感染.
在社区推动下,对用于病毒检测的101个现有Illumina RNA-seq数据集进行了重新分析.
对37个选定的数据集进行深入分析,并使用定量PCR (qPCR) 确认检测到的病原体.

主要成果:

在37个分析数据集中的29个 (78%) 检测到非病毒性植物病原体或害虫的痕迹.
菌是最常被检测到的 (15/37),其次是昆虫 (13/37) 和 (9/37).
独立的qPCR分析证实了一些检测到的病原体的存在.

结论:

总RNA-seq数据,通常用于植物病毒检测,是有效的识别非病毒病原体,如真菌,昆虫和虫.
这项研究鼓励植物病毒学家扩大他们的生物信息分析,包括非病毒性病原体.
这些发现提倡在植物健康诊断方面采取更综合的方法,利用多个学科的现有数据.

关键词:

在RNA-seqqq.诊断诊断诊断诊断诊断高通量测序的高通量测序转基因组学是指转基因组学.转换代码组学 (metatranscriptomics) 是一个植物病原体的病原体

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