A Diterpene as an Endogenous Signal for the Activation of Defense Responses to Infection with <i>Tobacco mosaic virus</i> and Wounding in Tobacco
Bibliographic record
Abstract
The potato pathogenesis-related gene PR-10a is transcriptionally activated in response to pathogen infection or elicitor treatment. Characterization of the cis-acting elements of the PR-10a promoter revealed the presence of a silencing element between residues −52 and −27 that contributes to transcriptional regulation. In this study, we have isolated a silencing element binding factor (SEBF) from potato tuber nuclei that binds to the coding strand of the silencing element in a sequence-specific manner. The consensus binding site of SEBF, PyTGTCNC, is present in a number of PR genes and shows striking similarity to the auxin response element. Mutational analysis of the PR-10a promoter revealed an inverse correlation between the in vitro binding of SEBF and the expression of PR-10a. SEBF was purified to homogeneity from potato tubers, and sequencing of the N terminus of the protein led to the isolation of a cDNA clone. Sequence analysis revealed that SEBF is homologous with chloroplast RNA binding proteins that possess consensus sequence–type RNA binding domains characteristic of heterogenous nuclear ribonucleoproteins (hnRNPs). Overexpression of SEBF in protoplasts repressed the activity of a PR-10a reporter construct in a silencing element–dependent manner, confirming the role of SEBF as a transcriptional repressor.
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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".