RNAi-Directed Downregulation of Vacuolar H+-ATPase Subunit A Results in Enhanced Stomatal Aperture and Density in Rice
Bibliographic record
Abstract
Stomatal movement plays a key role in plant development and response to drought and salt stress by regulating gas exchange and water loss. A number of genes have been demonstrated to be involved in the regulation of this process. Using inverse genetics approach, we characterized the function of a rice (Oryza sativa L.) vacuolar H(+)-ATPase subunit A (OsVHA-A) gene in stomatal conductance regulation and physiological response to salt and osmotic stress. OsVHA-A was constitutively expressed in different rice tissues, and the fusion protein of GFP-OsVHA-A was exclusively targeted to tonoplast when transiently expressed in the onion epidermal cells. Heterologous expression of OsVHA-A was able to rescue the yeast mutant vma1Δ (lacking subunit A activity) phenotype, suggesting that it partially restores the activity of V-ATPase. Meanwhile, RNAi-directed knockdown of OsVHA-A led to a reduction of vacuolar H(+)-ATPase activity and an enhancement of plasma membrane H(+)-ATPase activity, thereby increasing the concentrations of extracellular H(+) and intracellular K(+) and Na(+) under stress conditions. Knockdown of OsVHA-A also resulted in the upregulation of PAM3 (plasma membrane H(+)-ATPase 3) and downregulation of CAM1 (calmodulin 1), CAM3 (calmodulin 3) and YDA1 (YODA, a MAPKK gene). Altered level of the ion concentration and the gene expression by knockdown of OsVHA-A probably resulted in expanded aperture of stomatal pores and increased stomatal density. In addition, OsVHA-A RNAi plants displayed significant growth inhibition under salt and osmotic stress conditions. Taken together, our results suggest that OsVHA-A takes part in regulating stomatal density and opening via interfering with pH value and ionic equilibrium in guard cells and thereby affects the growth of rice plants.
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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 | 0.001 |
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".