Arabidopsis <scp>RAV</scp>1 transcription factor, phosphorylated by <scp>S</scp>n<scp>RK</scp>2 kinases, regulates the expression of <i><scp>ABI</scp>3</i>,<i><scp>ABI</scp>4</i>, and <i><scp>ABI</scp>5</i> during seed germination and early seedling development
Bibliographic record
Abstract
The phytohormone abscisic acid (ABA) modulates a number of processes during plant growth and development. In this study, the molecular mechanism of Arabidopsis RAV (Related to ABI3/VP1) transcription factor RAV1 involving ABA signaling was investigated. RAV1-underexpressing lines were more sensitive to ABA than wild-type plants during seed germination and early seedling development, whereas RAV1-overexpressing lines showed strong ABA-insensitive phenotypes. Overexpression of RAV1 repressed ABI3, ABI4, and ABI5 expression, and RAV1 bound to the ABI3, ABI4, and ABI5 promoters in vitro and in vivo, indicating that RAV1 directly down-regulates the expression of ABI3, ABI4, and ABI5. The interruption of ABI5 function in RAV1-U abi5 plants abolished the ABA-hypersensitive phenotype of RAV1-U plants, demonstrating that ABI5 is epistatic to RAV1. RAV1 interacted with SNF1-RELATED PROTEIN KINASE SnRK2.2, SnRK2.3 and SnRK2.6 in the nucleus. In vitro kinase assays showed that SnRK2.2, SnRK2.3 and SnRK2.6 phosphorylated RAV1. Transient expression assays revealed that SnRK2.2, SnRK2.3 and SnRK2.6 reduced the RAV1-dependent repression of ABI5, and the ABA-insensitive phenotype of the RAV1-overexpressing line was impaired by overexpression of SnRK2.3 in the RAV1 OE3 plants. Together, these results demonstrated that the Arabidopsis RAV1 transcription factor plays an important role in ABA signaling by modulating the expression of ABI3, ABI4, and ABI5, and that its activity is negatively affected by SnRK2s.
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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) | 0.002 | 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".