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Updated: Sep 24, 2026

Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes
Published on: July 27, 2018
Exploring the practical application of nanopore sequencing for plant virus and viroid detection: Choice of input
Dan Sanderson1, Harvinder Bennypaul1
1Canadian Food Inspection Agency, Centre for Plant Health, 8801 East Saanich Road, North Saanich, BC, V8L 1H3, Canada.
Abstract:
The Oxford Nanopore Technologies (ONT) MinION MK1b sequencer was found to be a useful low-cost entry device for the detection of plant viruses and viroids, especially when double-stranded RNA (dsRNA) is used as input material. Extractions from either dormant wood or mature leaf tissue are suitable for this purpose. A set of 45 plant samples with various known virus and viroid infections was sequenced with both a MinION Mk1b and an Illumina NextSeq 500, for the purpose of comparing detection rates between sequencing methods. Despite the larger sequencing capacity of the NextSeq, the MinION reproduced the Illumina detection results in nearly all instances (94%); a regression model comparison showed no significant difference in performance (p = 0.44), though a non-inferiority test also did not show significance. The relative sensitivity of the MinION sequencer was compared with that of reverse transcriptase PCR (RT-PCR) gel electrophoresis when testing for six different viruses in serially diluted nucleic acid extractions. Three separate criteria for detecting positive virus signals were applied to the ONT dataset; only the most permissive threshold (the presence of any target reads) resulted in ONT showing a statistically significant higher sensitivity than RT-PCR, based on mixed-effects logistic regression modeling (LRT p-value = 0.043). Using the SQK-PCB109 kit for library prep and the Viroscope service for data analysis, screening 12 libraries on one flow cell over a 72 h sequencing run was sufficient to detect all but the weakest pathogen signals known to be present (91% agreement with the expected detection pattern). Overall, the most obvious limiting factor for the MinION as a detection tool for plant pathogens such as viruses is the amount of data generated per run.

