GhHAI2, GhAHG3, and GhABI2 Negatively Regulate Osmotic Stress Tolerance via ABA-Dependent Pathway in Cotton (Gossypium hirsutum L.)
Bibliographic record
Abstract
The type 2C protein phosphatases (PP2Cs) are well known for their vital roles in plant drought stress responses, but their molecular mechanisms in cotton (Gossypium hirsutum L.) remain largely unknown. Here, we investigated the role of three clade A PP2C genes, namely, GhHAI2, GhAHG3, and GhABI2, in regulating the osmotic stress tolerance in cotton. The transcript levels of GhHAI2, GhAHG3, and GhABI2 were rapidly induced by exogenous abscisic acid (ABA) and polyethylene glycol (PEG) treatment. Silencing of GhHAI2, GhAHG3, and GhABI2 via virus-induced gene silencing (VIGS) improved osmotic tolerance in cotton due to decreased water loss, increase in both relative water content (RWC) and photosynthetic gas exchange, higher antioxidant enzyme activity, and lower malondialdehyde (MDA) content. The root analysis further showed that GhHAI2, GhAHG3, and GhABI2-silenced plants were more responsive to osmotic stress. Yeast two-hybrid (Y2H) and luciferase complementation imaging (LCI) assays further substantiated that GhHAI2, GhAHG3, and GhABI2 interact with the core receptors of ABA signaling, GhPYLs. The expression of several ABA-dependent stress-responsive genes was significantly upregulated in GhHAI2-, GhAHG3-, and GhABI2-silenced plants. Our findings suggest that GhHAI2, GhAHG3, and GhABI2 act as negative regulators in the osmotic stress response in cotton through ABA-mediated 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) | 0.000 | 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".