Tobacco Mosaic Virus Infection Results in an Increase in Recombination Frequency and Resistance to Viral, Bacterial, and Fungal Pathogens in the Progeny of Infected Tobacco Plants
Bibliographic record
Abstract
Our previous experiments showed that infection of tobacco (Nicotiana tabacum) plants with Tobacco mosaic virus (TMV) leads to an increase in homologous recombination frequency (HRF). The progeny of infected plants also had an increased rate of rearrangements in resistance gene-like loci. Here, we report that tobacco plants infected with TMV exhibited an increase in HRF in two consecutive generations. Analysis of global genome methylation showed the hypermethylated genome in both generations of plants, whereas analysis of methylation via 5-methyl cytosine antibodies demonstrated both hypomethylation and hypermethylation. Analysis of the response of the progeny of infected plants to TMV, Pseudomonas syringae, or Phytophthora nicotianae revealed a significant delay in symptom development. Infection of these plants with TMV or P. syringae showed higher levels of induction of PATHOGENESIS-RELATED GENE1 gene expression and higher levels of callose deposition. Our experiments suggest that viral infection triggers specific changes in progeny that promote higher levels of HRF at the transgene and higher resistance to stress as compared with the progeny of unstressed plants. However, data reported in these studies do not establish evidence of a link between recombination frequency and stress resistance.
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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".