CHOTTO1, a Putative Double APETALA2 Repeat Transcription Factor, Is Involved in Abscisic Acid-Mediated Repression of Gibberellin Biosynthesis during Seed Germination in Arabidopsis
Bibliographic record
Abstract
The phytohormones abscisic acid (ABA) and gibberellins (GAs) are the primary signals that regulate seed dormancy and germination. In this study, we investigated the role of a double APETALA2 repeat transcription factor, CHOTTO1 (CHO1), in seed dormancy, germination, and phytohormone metabolism of Arabidopsis (Arabidopsis thaliana). Wild-type seeds were dormant when freshly harvested seeds were sown, and these seeds were released from dormancy after a particular period of dry storage (after-ripening). The cho1 mutant seeds germinated easily even in a shorter period of storage than wild-type seeds. The cho1 mutants showed reduced responsiveness to ABA, whereas transgenic plants constitutively expressing CHO1 (p35SCHO1) showed an opposite phenotype. Notably, after-ripening reduced the ABA responsiveness of the wild type, cho1 mutants, and p35SCHO1 lines. Hormone profiling demonstrated that after-ripening treatment decreased the levels of ABA and salicylic acid and increased GA(4), jasmonic acid, and isopentenyl adenine when wild-type seeds were imbibed. Expression analysis showed that the transcript levels of genes for ABA and GA metabolism were altered in the wild type by after-ripening. Hormone profiling and expression analyses indicate that cho1 seeds, with a short period of storage, resembled fully after-ripened wild-type seeds. Genetic analysis showed that the cho1 mutation partially restored delayed seed germination and reduced GA biosynthesis activity in the ABA-overaccumulating cyp707a2-1 mutant background but did not restore seed germination in the GA-deficient ga1-3 mutant background. These results indicate that CHO1 acts downstream of ABA to repress GA biosynthesis during seed 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 | 0.000 |
| 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".