ORCID Profile
0000-0002-9561-7016
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Publisher: MDPI AG
Date: 29-05-2023
Abstract: 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 databases. 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. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected s les (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their s le(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.
Publisher: Wiley
Date: 08-2022
DOI: 10.1111/EPP.12863
Abstract: High‐throughput sequencing (HTS) is a powerful tool that enables the simultaneous detection and potential identification of any organisms present in a s le. The growing interest in the application of HTS technologies for routine diagnostics in plant health laboratories is triggering the development of guidelines on how to prepare laboratories for performing HTS testing. This paper describes general and technical recommendations to guide laboratories through the complex process of preparing a laboratory for HTS tests within existing quality assurance systems. From nucleic acid extractions to data analysis and interpretation, all of the steps are covered to ensure reliable and reproducible results. These guidelines are relevant for the detection and identification of any plant pest (e.g. arthropods, bacteria, fungi, nematodes, invasive plants or weeds, protozoa, viroids, viruses), and from any type of matrix (e.g. pure microbial culture, plant tissue, soil, water), regardless of the HTS technology (e.g. licon sequencing, shotgun sequencing) and of the application (e.g. surveillance programme, phytosanitary certification, quarantine, import control). These guidelines are written in general terms to facilitate the adoption of HTS technologies in plant pest routine diagnostics and enable broader application in all plant health fields, including research. A glossary of relevant terms is provided among the Supplementary Material.
No related grants have been discovered for Oscar Hurtado-Gonzales.