UV-C–Irradiated <i>Arabidopsis</i> and Tobacco Emit Volatiles That Trigger Genomic Instability in Neighboring Plants
Bibliographic record
Abstract
We have previously shown that local exposure of plants to stress results in a systemic increase in genome instability. Here, we show that UV-C-irradiated plants produce a volatile signal that triggers an increase in genome instability in neighboring nonirradiated Arabidopsis thaliana plants. This volatile signal is interspecific, as UV-C-irradiated Arabidopsis plants transmit genome destabilization to naive tobacco (Nicotiana tabacum) plants and vice versa. We report that plants exposed to the volatile hormones methyl salicylate (MeSA) or methyl jasmonate (MeJA) exhibit a similar level of genome destabilization as UV-C-irradiated plants. We also found that irradiated Arabidopsis plants produce MeSA and MeJA. The analysis of mutants impaired in the synthesis and/or response to salicylic acid (SA) and/or jasmonic acid showed that at least one other volatile compound besides MeSA and MeJA can communicate interplant genome instability. The NONEXPRESSOR OF PATHOGENESIS-RELATED GENES1 (npr1) mutant, defective in SA signaling, is impaired in both the production and the perception of the volatile signals, demonstrating a key role for NPR1 as a central regulator of genome stability. Finally, various forms of stress resulting in the formation of necrotic lesions also generate a volatile signal that leads to genomic instability.
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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 | 0.000 |
| 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".