Identification of Differentially Expressed Genes in Brassinosteroid-Treated Brassica napus Seedlings
Bibliographic record
Abstract
Brassinosteroid-mediated gene expression changes have been reported primarily in Arabidopsis thaliana but not in its close relative Brassica napus . To obtain an initial idea of the molecular changes induced by long-term exposure to 24-epibrassinolide (EBR) in B. napus seedlings, we used the differential display–reverse transcription PCR technique. Six differentially expressed cDNAs were isolated and characterized. These encode a mitochondrial transcription termination factor (mTERF)-related protein, glycine-rich protein 22 (GRP22), myrosinase, 3-ketoacyl-CoA thiolase, and a copia-like polyprotein. The first four were upregulated in EBR-treated seedlings while the latter was expressed at higher levels in untreated seedlings. Transcripts of mTERF-related protein, GRP22, and myrosinase were present at higher levels in treated seedlings under nonstress conditions, whereas those of 3-ketoacyl-CoA thiolase rose to higher levels in treated seedlings during exposure to heat stress. The results of the present study indicate that EBR treatment in B. napus leads to substantial changes in the expression levels of genes involved in a variety of physiologic responses. The results provide a useful framework for further research into EBR-mediated molecular changes in B. napus , which will also add to our understanding of how brassinosteroids mediate stress tolerance in this agriculturally important oil crop.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".