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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 samples (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 sample(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.
Keywords: plant viruses, plant virus detection, plant virology, high-throughput sequencing, RNA sequencing, plant tissues, plant pathogen, diagnostics, high-throughput sequencing, metagenomics, metatranscriptomics
Published in DiRROS: 12.07.2024; Views: 4; Downloads: 3
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Abstract: One of the key steps of the molecular identification of bark beetles is obtaining a sufficient quantity of high-quality DNA extract. In this study, we investigated the influence of different storage procedures for Ips typographus (L.) specimens and various DNA extraction protocols on the quantity and quality of DNA intended for use in molecular diagnostics. Adult beetles were frozen at -20 °C, either dry or in ethanol. We tested four different protocols for DNA extraction. We compared the quantity of extracted DNA and assessed its quality with PCR and Sanger sequencing. Different storage protocols had no significant effect on the quantity of DNA extracted. However, freezing specimens in ethanol provided higher-quality DNA for molecular applications. Only two of the extraction protocols produced sequenceable amplicons, and the difference in the amount of extracted DNA between them was not significant. We propose the optimal combination of storing specimens in ethanol at -20°C and using the Nucleospin Insect DNA extraction kit from Macherey Nagel, enabling a timeefficient identification process.
Keywords: early detection, specimen storage, total DNA extraction, PCR, polymerase chain reaction, Sanger sequencing, molecular diagnostics
Published in DiRROS: 02.02.2024; Views: 704; Downloads: 256
Full text (1,17 MB)
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