ABSCISIC ACID-INSENSITIVE 4 negatively regulates flowering through directly promoting Arabidopsis<i>FLOWERING LOCUS C</i>transcription
Bibliographic record
Abstract
During the life cycle of a plant, one of the major biological processes is the transition from the vegetative to the reproductive stage. In Arabidopsis, flowering time is precisely controlled by extensive environmental and internal cues. Gibberellins (GAs) promote flowering, while abscisic acid (ABA) is considered as a flowering suppressor. However, the detailed mechanism through which ABA inhibits the floral transition is poorly understood. Here, we report that ABSCISIC ACID-INSENSITIVE 4 (ABI4), a key component in the ABA signalling pathway, negatively regulates floral transition by directly promoting FLOWERING LOCUS C (FLC) transcription. The abi4 mutant showed the early flowering phenotype whereas ABI4-overexpressing (OE-ABI4) plants had delayed floral transition. Consistently, quantitative reverse transcription-PCR (qRT-PCR) assay revealed that the FLC transcription level was down-regulated in abi4, but up-regulated in OE-ABI4. The change in FT level was consistent with the pattern of FLC expression. Chromatin immunoprecipitation-qPCR (ChIP-qPCR), electrophoretic mobility shift assay (EMSA), and tobacco transient expression analysis showed that ABI4 promotes FLC expression by directly binding to its promoter. Genetic analysis demonstrated that OE-ABI4::flc-3 could not alter the flc-3 phenotype. OE-FLC::abi4 showed a markedly delayed flowering phenotype, which mimicked OE-FLC::WT, and suggested that ABI4 acts upstream of FLC in the same genetic pathway. Taken together, these findings suggest that ABA inhibits the floral transition by activating FLC transcription through ABI4.
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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".