From Asymptomatic to Symptomatic: Multiomics profiling of the temporal response of grapevine viral-mixed infection
Bibliographic record
Abstract
Abstract Mixed viral infections are common in grapevines. However, our understanding of the factors and signaling pathways that influence the expression of viral symptoms in mixed infections is still incomplete. In a previous study, we revealed that the presence of grapevine leafroll-associated virus species in mixed infections was randomly associated with the devel-opment of virus-like symptoms. To understand what drives the timing of these virus-like symptoms in mixed infections, we used dsRNA and total RNA sequencing and metabolomic analysis to profile the viromes, metabolites, and transcripts of grapevine leaves collected at two different times of the year (summer and autumn). We demonstrated that neither viral titre nor virome composition changes were associated with symptom expression in autumn. The total phenolic content and antioxidant capacity increased in most plants except for those with early onset symptoms. According to the results of differential gene expression analysis, cell wall biosynthesis pathways were significantly downregulated in all grapevine plants infected with grapevine leafroll-associated virus 3, grapevine asteroid mosaic-associated virus, and grape-vine Pinot gris virus. In addition, polyketide pathways were significantly upregulated in all cultivars, while flavonoid precursor (e.g. abscisic acid) production was significantly reduced in plants that expressed strong virus-like symptoms. In the ‘Vidal’ cultivar, an uncharacterized double-stranded RNA-binding protein (DRB) appears to play a critical role in the plant’s an-tiviral defences, supporting the recent hypothesis that DRBs make an important contribution to dominant antiviral responses in plants. The seasonality of the expression virus-like symptoms appears to be a consequence of the dynamic interactions between antiviral factors and viral counter-defences that occur at different developmental stages of grapevine.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".