A Role for Brassinosteroids in Germination in Arabidopsis
Bibliographic record
Abstract
This paper presents evidence that plant brassinosteroid (BR) hormones play a role in promoting germination. It has long been recognized that seed dormancy and germination are regulated by the plant hormones abscisic acid (ABA) and gibberellin (GA). These two hormones act antagonistically with each other. ABA induces seed dormancy in maturing embryos and inhibits germination of seeds. GA breaks seed dormancy and promotes germination. Severe mutations in GA biosynthetic genes in Arabidopsis, such as ga1-3, result in a requirement for GA application to germinate. Whereas previous work has shown that BRs play a critical role in controlling cell elongation, cell division, and skotomorphogenesis, no germination phenotypes have been reported in BR mutants. We show that BR rescues the germination phenotype of severe GA biosynthetic mutants and of the GA-insensitive mutant sleepy1. This result shows that BR stimulates germination and raises the possibility that BR is needed for normal germination. If true, we would expect to detect a germination phenotype in BR mutants. We found that BR mutants exhibit a germination phenotype in the presence of ABA. Germination of both the BR biosynthetic mutant det2-1 and the BR-insensitive mutant bri1-1 is more strongly inhibited by ABA than is germination of wild type. Thus, the BR signal is needed to overcome inhibition of germination by ABA. Taken together, these results point to a role for BRs in stimulating germination.
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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 | 0.000 | 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 | 0.001 |
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".