A Diverse Virome of Leafroll-Infected Grapevine Unveil by dsRNA Sequencing
Bibliographic record
Abstract
Quebec is the third-largest wine grape producing province in Canada, and the industry is constantly expanding. Traditionally, 90% of the grapevine cultivars grown in Quebec were rustic or semi-rustic and largely dominated by winter hardy interspecific hybrid Vitis sp. cultivars. Over the years, the winter protection techniques adopted by growers and climate changes have offered an opportunity to establish V. vinifera L. cultivars (e.g. Pinot Noir). We characterized the virome of leafroll-infected interspecific hybrid cultivar and compared it to the virome of V. vinifera cultivar to support and facilitate the transition of the industry. A dsRNA sequencing method was used to sequence symptomatic and asymptomatic grapevine leaves of different cultivars. The results suggested a complex virome in terms of composition, abundance, richness, and phylogenetic diversity. Three viruses, grapevine Rupestris stem pitting-associated virus, grapevine leafroll-associated virus (GLR) 3 and 2 and hop stunt viroid (HSVd) largely dominated the virome. However, their presence and abundance varied among grapevine cultivars. The symptomless grapevine cultivar Vidal was frequently infected by multiple virus and viroid species and different strains of the same virus, including GLR virus 3 and 2. Our data shows that viruses and viroids associated with the highest number of grapevines expressing symptoms included HSVd, GLR3 and GLR2, in gradient order. However, co-occurrence analysis revealed that the presence of GLR species was randomly associated with the development of virus-like symptoms. These findings and their implication for grapevine leafroll disease management were discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".