A virus-derived small RNA targets the rice transcription factor ROC1 to induce disease-like symptom
Bibliographic record
Abstract
Abstract Virus-derived small interfering RNAs (vsiRNAs) in plants can target host transcripts to induce symptom development. Southern rice black-streaked dwarf virus (SRBSDV) is the most damaging rice-infecting virus, which causes severe stunting and poorly developed roots in rice plants, thereby posing a serious threat to rice production. In this study, we show that a vsiRNA (vsiR-S9-18), generated from SRBSDV genome segment 9, targets the transcription factor ROC1 in rice. SRBSDV infection triggered the production of vsiR-S9-18 and resulted in the downregulation of ROC1 in rice plants. Transient expression of vsiR-S9-18 in rice protoplasts and tobacco leaves further demonstrated the specific association of vsiR-S9-18 with ROC1. Moreover, the ROC1-knockout rice plants displayed shortened roots, similar to the phenotype of root growth inhibition caused by SRBSDV infection. We propose that vsiR-S9-18 inhibits root elongation via ROC1, which has been proven to regulate root growth. This finding extends our understanding of the role of vsiRNA in viral disease development and is helpful for the development of new antiviral approaches.
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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 | 0.001 |
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".