TaSnRK3.23B, a CBL-interacting protein kinase of wheat, confers drought stress tolerance by promoting ROS scavenging in Arabidopsis
Bibliographic record
Abstract
Sucrose non-fermenting-1-related protein kinases (SnRKs) have been implicated in plant growth and stress responses. Although SnRK3.23 is known to be involved in drought stress, the underlying mechanism of resistance differs between Arabidopsis and rice, and little is known about its function in wheat. In the current work, TaSnRK3.23B was detected on the cell membrane and in the nucleus. TaSnRK3.23B overexpression in Arabidopsis promoted reactive oxygen species (ROS) scavenging via the accumulation of antioxidant enzymes, including superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) and then conferred significant tolerance to drought. The prediction analysis, yeast two-hybrid, and bimolecular fluorescence complementation (BiFC) assays revealed that TaSnRK3.23B interacted with TaCBL2B and TaCBL6B, which are calcineurin B-like (CBL) proteins. The predicted model demonstrated that TaSnRK3 subfamily proteins participate in Ca 2+ signaling mediated by TaCBL2B/TaCBL6B and subsequently provide drought stress tolerance by promoting ROS scavenging in wheat. Altogether, the obtained findings contribute to a better understanding of the functions of SnRK3.23 in wheat and offer genetic suggestions for improving drought resistance of wheat.
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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 | 0.000 |
| 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".