Systemic plant signal triggers genome instability
Bibliographic record
Abstract
Previously, we have shown that infection of tobacco plants with a viral pathogen triggers local and systemic induction of homologous recombination (HR). Here, we have tested the hypothesis of whether free radicals are potentially involved in the induction of the systemic effect. We report a significant induction of HR in tobacco plants treated with radical-generating agents, UVC or rose Bengal (RB). Importantly, the recombination increase was observed in local (treated) as well as systemic (non-treated) tissue. The systemic increase in recombination implies the existence of a signal that is transmitted to non-treated tissue. Several sets of grafting experiments proved the generation of said signal by both RB and UVC exposure. A statistically significant increase in HR was observed in tissue that received a systemic signal via a grafted leaf. Similar data were obtained from transgenic plants naphthalene degrading salicylate 1-hydroxylase (NahG) unable to accumulate salicylic acid (SA). Interestingly, pre-treatment of plants with the radical-scavenging compound N-acetyl-l-cysteine (NAC) led to a significantly lower recombination increase upon grafting after treatment with UVC and RB. Moreover, leaves taken for grafting from NAC-pre-treated plants exhibited a lower level of oxidized organic compounds. Our data suggest the involvement of free radical production in either generation or maintenance of the recombination signal. We discuss potential mechanisms for generation of the signal and possible adaptive advantages of enhanced genomic flexibility following exposure to DNA-damaging agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".