Structural analogs of ABA reveal novel features of ABA perception and signaling in Arabidopsis
Bibliographic record
Abstract
Changes in gene expression produced by the application of (+)-abscisic acid (ABA) to Arabidopsis thaliana plants were compared with changes produced by the ABA structural analogs (-)-ABA, (+)-8'-acetylene ABA and (-)-2',3'-dihydroacetylenic abscisyl alcohol. The maximum expression of many rapidly (+)-ABA-induced genes occurred prior to peak hormone accumulation, suggesting negative feedback regulation that may be mediated by the induction of genes encoding PP2C-type protein phosphatases. For most rapidly (+)-ABA-induced genes, expression was delayed in ABA analog treatments although analogs accumulated to higher levels than did (+)-ABA. For each analog, some genes exhibited a hypersensitive response to the analog and some genes were less sensitive to the analog than to (+)-ABA. Variations in the sensitivity of gene expression to (+)-ABA and analogs reflect the different structural requirements of two or more classes of hormone receptors. By using ABA analogs to reveal and confirm weakly (+)-ABA-regulated genes, we estimate that 14% of Arabidopsis genes are ABA-regulated in aerial tissues. Treatments with the analog (+)-8'-acetylene ABA (PBI425) led to the identification of new ABA-regulated genes. As an example, the transcription factor MYBR1 was significantly induced by PBI425, but not by (+)-ABA, and is shown to play a role in ABA signaling by phenotypic analysis of gain-of-function and loss-of-function mutants.
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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".