Nanopore Sequencing with GraphMap for Comprehensive Pathogen Detection in Potato Field Soil
Early detection of causal pathogens is important to prevent crop loss from diseases. However, some diseases, such as soilborne diseases, are difficult to diagnose due to the absence of visible or characteristic symptoms. In the present study, the use of the Oxford Nanopore MinION sequencer as a mole...
| Veröffentlicht in: | Plant disease. - 1997. - 107(2023), 8 vom: 01. Aug., Seite 2288-2295 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | Plant disease |
| Schlagworte: | Journal Article MinION comprehensive pathogen detection long-read sequencing pathogen detection potato field soil powdery scab Soil |
| Zusammenfassung: | Early detection of causal pathogens is important to prevent crop loss from diseases. However, some diseases, such as soilborne diseases, are difficult to diagnose due to the absence of visible or characteristic symptoms. In the present study, the use of the Oxford Nanopore MinION sequencer as a molecular diagnostic tool was assessed due to its long-read sequencing capabilities and portability. Nucleotide samples (DNA or RNA) from potato field soils were sequenced and analyzed using a locally curated pathogen database, followed by identification via sequence mapping. We performed computational speed tests of three commonly used mapping/annotation tools (BLAST, BWA-BLAST, and BWA-GraphMap) and found BWA-GraphMap to be the fastest tool for local searching against our curated pathogen database. The data collected demonstrate the high potential of Nanopore sequencing as a minimally biased diagnostic tool for comprehensive pathogen detection in soil from potato fields. Our GraphMap-based MinION sequencing method could be useful as a predictive approach for disease management by identifying pathogens present in field soil prior to planting. Although this method still needs further experimentation with a larger sample size for practical use, the data analysis pipeline presented can be applied to other cropping systems and diagnostics for detecting multiple pathogens |
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| Beschreibung: | Date Completed 31.08.2023 Date Revised 31.08.2023 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 0191-2917 |
| DOI: | 10.1094/PDIS-01-23-0052-SR |