Bacterio-opsin gene overexpression fails to elevate fungal disease resistance in transgenic poplar (<i>Populus</i>)
Bibliographic record
Abstract
Overexpression of the bacterio-opsin (bO) gene in tobacco had previously been shown to induce hypersensitive-response-like lesions, increase viral and bacterial disease resistance, and stimulate pathogenesis-related gene expression. To see if this gene enhanced resistance to fungal pathogens of poplar, we generated a total of 35 transgenic lines in two clones of Populus trichocarpa Torr. & A. Gray × Populus deltoides Bartr. ex Marsh. and one clone of P. trichocarpa × Populus nigra L. and challenged them with the fungal pathogens Melampsora occidentalis H. Jack (leaf rust), Venturia populina (Vuill.) Fabric. (leaf and shoot blight), Septoria musiva Peck, and Septoria populicola Peck (leaf spot and stem canker) in greenhouse, field, or laboratory inoculations. Northern analysis showed that the bO gene was expressed in the transgenic poplars; however, no increase in expression of phenylalanine ammonia-lyase (PAL1) or two wound-inducible poplar chitinase genes (WIN6 and WIN8) were observed, even in one line that showed very high bO expression, intensive lesion development, and retarded growth. Poplars required a high threshold of bO expression for lesion development, and susceptibility to all of the pathogens tested was unaffected by bO overexpression.
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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".