Overexpression of <scp> <i>BnNAC19</i> </scp> in <i>Brassica napus</i> enhances resistance to <i>Leptosphaeria maculans</i> , the blackleg pathogen of canola
Bibliographic record
Abstract
Abstract Leptosphaeria maculans is a fungal pathogen that causes blackleg disease in canola ( Brassica napus ), resulting in significant yield and economic losses in Canada and many parts of the world. Plant NAC transcription factors play critical roles in plant development and response to biotic or abiotic stress. In this study, we identified and characterized a BnNAC19 gene from Brassica napus . The overexpression of BnNAC19 in transgenic canola plants contributed to the improvement of seedling resistance against L. maculans . The mycelial growth of a green fluorescent protein‐tagged strain of L. maculans and production of pycnidiospores were shown to be inhibited in the transgenic canola plants overexpressing BnNAC19 . In addition, the canola transgenic line overexpressing BnNAC19 showed increased disease resistance in the adult plant, which was determined by quantitative resistance. Both increased seedling and adult plant resistance in transgenic canola plants overexpressing BnNAC19 indicate that the BnNAC19 gene plays a positive role against L. maculans . The expression pattern of genes BnNAC19 upstream and downstream of BnNAC19 that participate in plant defence pathways were investigated to elucidate the B. napus resistance mechanisms to L. maculans infection, and hence to aid the long‐term blackleg disease‐resistant breeding programmes.
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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".