Transcriptome analysis of the synergistic mechanisms between two strains of potato virus Y in Solanum tuberosum L.
Bibliographic record
Abstract
Many viruses employ a process known as superinfection exclusion (SIE) to block subsequent entry or replication of the same or closely related viruses in the cells they occupy. SIE is also referred to as Cross-protection refers to the situation where a host plant infected by a mild strain of a virus or viroid gains immunity against a more severe strain closely related to the initial infectant. The mechanisms underlying cross-protection are not fully understood. In this study, we performed a comparative transcriptomic analysis of potato (Solanum tuberosum L.) leaves. The strains PVYN−Wi-HLJ-BDH-2 and PVYNTN−NW-INM-W-369-12 are henceforth designated as BDH and 369, respectively. In total, 806 differentially expressed genes (DEGs) were detected between the Control and JZ (preinfected with BDH and challenge with 369) treatment. Gene Ontology (GO) analysis showed that the response to external biological stimulation, signal transduction, kinase, immunity, redox pathways were significantly enriched. Among these pathways, we identified numerous differentially expressed metabolites related to virus infection. Moreover, our data also identified a small set of genes that likely play important roles in the establishment of cross-protection. Specifically, we observed significant differential expression of the A1-II gamma-like gene, elongation factor 1-alpha-like gene, and subtilisin-like protease StSBT1.7 gene, with StSBT1.7 being the most significant in our transcriptome data. These genes can stimulate the expression of defense plant genes, induce plant chemical defense, and participate in the induction of trauma and pathogenic bacteria. Our findings provided insights into the mechanisms underlying the ability of mild viruses to protect host plants against subsequent closely related virus infection in Solanum tuberosum L.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".