PIF4 interacts with ABI4 to serve as a transcriptional activator complex to promote seed dormancy by enhancing ABA biosynthesis and signaling
Bibliographic record
Abstract
Transcriptional regulation plays a key role in the control of seed dormancy, and many transcription factors (TFs) have been documented. However, the mechanisms underlying the interactions between different TFs within a transcriptional complex regulating seed dormancy remain largely unknown. Here, we showed that TF PHYTOCHROME-INTERACTING FACTOR4 (PIF4) physically interacted with the abscisic acid (ABA) signaling responsive TF ABSCISIC ACID INSENSITIVE4 (ABI4) to act as a transcriptional complex to promote ABA biosynthesis and signaling, finally deepening primary seed dormancy. Both pif4 and abi4 single mutants exhibited a decreased primary seed dormancy phenotype, with a synergistic effect in the pif4/abi4 double mutant. PIF4 binds to ABI4 to form a heterodimer, and ABI4 stabilizes PIF4 at the protein level, whereas PIF4 does not affect the protein stabilization of ABI4. Subsequently, both TFs independently and synergistically promoted the expression of ABI4 and NCED6, a key gene for ABA anabolism. The genetic evidence is also consistent with the phenotypic, physiological and biochemical analysis results. Altogether, this study revealed a transcriptional regulatory cascade in which the PIF4-ABI4 transcriptional activator complex synergistically enhanced seed dormancy by facilitating ABA biosynthesis and signaling.
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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 | 0.001 |
| 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) | 0.002 | 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".