Cytokinin antagonizes ABA suppression to seed germination of Arabidopsis by downregulating ABI5 expression
Bibliographic record
Abstract
Abscisic acid (ABA) and cytokinin are key hormones controlling plant development. How ABA and cytokinin interplay to control the transition from a dry seed into a young seedling remains elusive. Here we undertook a gain-of-function genetic screen to identify ABA-insensitive mutants during seed germination in Arabidopsis using an estradiol-inducible approach. In the presence of estradiol, one of these mutants gim1 (germination insensitive to ABA mutant 1) exhibited an elevated level of cytokinin that was attributed to the estradiol-induced expression of AtIPT8 that encodes an isopentenyltransferase for the biosynthesis of cytokinins. Our data on OE-2 and Com-1 transgenic plants carrying the ectopically expressing AtIPT8 gene indicated that the elevation of cytokinin level was responsible for the ABA-insensitivity of gim1 seed germination. Further analyses on alterations of gene transcriptomes in the gim1 mutant demonstrated that the expression of some ABA-inducible genes, including ABI5, was reduced, and could not be restored by exogenous ABA treatment. Moreover, we also failed to observe the ABA-mediated repression of a family of cytokinin signal transducers and transcription repressors called type-A ARR4, ARR5 and ARR6 in the gim1 seedlings. Further analysis demonstrated that type-A ARR4, ARR5 and ARR6 could negatively regulate ABI5 expression, and the physical interaction of ABI5 and type-A ARR4, ARR5 and ARR6 proteins was detected. In summary, our study suggests that the interaction of ABA and cytokinin during seed germination and seedling growth can be mediated by the interplay of transcriptional regulators in Arabidopsis.
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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 | 0.001 |
| 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".