Gene expression and functional analyses in brassinosteroid‐mediated stress tolerance
Bibliographic record
Abstract
The plant hormone brassinosteroid (BR) plays essential roles in plant growth and development, while also controlling plant stress responses. This dual ability of BR is intriguing from a mechanistic point of view and as a viable solution for stabilizing crop yields under the changing climatic conditions. Here we report a time course analysis of BR responses under both stress and no-stress conditions, the results of which establish that BR incorporates many stress-related features even under no-stress conditions, which are then accompanied by a dynamic stress response under unfavourable conditions. Found within the BR transcriptome were distinct molecular signatures of two stress hormones, abscisic acid and jasmonic acid, which were correlated with enhanced endogenous levels of the two hormones in BR-treated seedlings. The marked presence of genes related to protein metabolism and modification, defence responses and calcium signalling highlights the significance of their associated mechanisms and roles in BR processes. Functional analysis of loss-of-function mutants of a subset of genes selected from the BR transcriptome identified abiotic stress-related roles for ACID PHOSPHATASE5 (ACP5), WRKY33, JACALIN-RELATED LECTIN1-3 (JAC-LEC1-3) and a BR-RESPONSIVE-RECEPTOR-LIKE KINASE (BRRLK). Overall, the results of this study provide a clear link between the molecular changes impacted by BR and its ability to confer broad-range stress tolerance, emphasize the importance of post-translational modification and protein turnover as BR regulatory mechanisms and demonstrate the BR transcriptome as a repertoire of new stress-related regulatory and structural genes.
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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 | 0.001 |
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".