<scp><i>SIZ1</i></scp>deficiency causes reduced stomatal aperture and enhanced drought tolerance via controlling salicylic acid‐induced accumulation of reactive oxygen species in<scp>A</scp>rabidopsis
Bibliographic record
Abstract
Transpiration and gas exchange occur through stomata. Thus, the control of stomatal aperture is important for the efficiency and regulation of water use, and for the response to drought. Here, we demonstrate that SIZ1-mediated endogenous salicylic acid (SA) accumulation plays an important role in stomatal closure and drought tolerance. siz1 reduced stomatal apertures. The reduced stomatal apertures of siz1 were inhibited by the application of peroxidase inhibitors, salicylhydroxamic acid and azide, which inhibits SA-dependent reactive oxygen species (ROS) production, but not by an NADPH oxidase inhibitor, diphenyl iodonium chloride, which inhibits ABA-dependent ROS production. Furthermore, the introduction of nahG into siz1, which reduces SA accumulation, restored stomatal opening. Stomatal closure is generally induced by water deficit. The siz1 mutation caused drought tolerance, whereas nahG siz1 suppressed the tolerant phenotype. Drought stresses also induced expression of SA-responsive genes, such as PR1 and PR2. Furthermore, other SA-accumulating mutants, cpr5 and acd6, exhibited stomatal closure and drought tolerance, and nahG suppressed the phenotype of cpr5 and acd6, as did siz1 and nahG siz1. Together, these results suggest that SIZ1 negatively affects stomatal closure and drought tolerance through the accumulation of SA.
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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 | 0.001 |
| 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".