RNA-seq from disease-infected plant leaves

High-throughput sequencing (HTS), more specifically RNA-sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus data-bases. In this way they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data.

高通量测序（High-throughput sequencing, HTS），具体而言即植物组织的RNA测序（RNA-sequencing），现已成为植物病毒学家检测、鉴定植物病毒的不可或缺的工具。在数据分析环节，植物病毒学家通常会将获取的序列与病毒参考数据库进行比对，此过程往往会忽略那些与病毒无同源性的序列——而这类序列通常占全部测序读段（sequencing reads）的绝大多数。我们据此提出假说：在这些未被利用的序列数据中，或可检测到其他病原体的踪迹。本研究旨在探究：用于植物病毒检测的总RNA测序数据是否同样适用于其他植物病原物与有害生物的检测。作为概念验证，我们首先分析了经确认感染细胞性病原体的植物材料的RNA测序数据集，以此验证能否从该类数据中便捷检出这些非病毒病原体。