Overexpression of the brassinosteroid biosynthetic gene DWF4 in Brassica napus simultaneously increases seed yield and stress tolerance
Bibliographic record
Abstract
As a resource allocation strategy, plant growth and defense responses are generally mutually antagonistic. Brassinosteroid (BR) regulates many aspects of plant development and stress responses, however, genetic evidence of its integrated effects on plant growth and stress tolerance is lacking. We overexpressed the Arabidopsis BR biosynthetic gene AtDWF4 in the oilseed plant Brassica napus and scored growth and stress response phenotypes. The transgenic B. napus plants, in comparison to wild type, displayed increased seed yield leading to increased overall oil content per plant, higher root biomass and root length, significantly better tolerance to dehydration and heat stress, and enhanced resistance to necrotrophic fungal pathogens Leptosphaeria maculans and Sclerotinia sclerotiorum. Transcriptome analysis supported the integrated effects of BR on growth and stress responses; in addition to BR responses associated with growth, a predominant plant defense signature, likely mediated by BES1/BZR1, was evident in the transgenic plants. These results establish that BR can interactively and simultaneously enhance abiotic and biotic stress tolerance and plant productivity. The ability to confer pleiotropic beneficial effects that are associated with different agronomic traits suggests that BR-related genes may be important targets for simultaneously increasing plant productivity and performance under stress conditions.
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 | 0.000 |
| 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".