Overexpression of a Common Wheat Gene TaSnRK2.8 Enhances Tolerance to Drought, Salt and Low Temperature in Arabidopsis
Bibliographic record
Abstract
Drought, salinity and low temperatures are major factors limiting crop productivity and quality. Sucrose non-fermenting1-related protein kinase 2 (SnRK2) plays a key role in abiotic stress signaling in plants. In this study, TaSnRK2.8, a SnRK2 member in wheat, was cloned and its functions under multi-stress conditions were characterized. Subcellular localization showed the presence of TaSnRK2.8 in the cell membrane, cytoplasm and nucleus. Expression pattern analyses in wheat revealed that TaSnRK2.8 was involved in response to PEG, NaCl and cold stresses, and possibly participates in ABA-dependent signal transduction pathways. To investigate its role under various environmental stresses, TaSnRK2.8 was transferred to Arabidopsis under control of the CaMV-35S promoter. Overexpression of TaSnRK2.8 resulted in enhanced tolerance to drought, salt and cold stresses, further confirmed by longer primary roots and various physiological characteristics, including higher relative water content, strengthened cell membrane stability, significantly lower osmotic potential, more chlorophyll content, and enhanced PSII activity. Meanwhile, TaSnRK2.8 plants had significantly lower total soluble sugar levels under normal growing conditions, suggesting that TaSnRK2.8 might be involved in carbohydrate metabolism. Moreover, the transcript levels of ABA biosynthesis (ABA1, ABA2), ABA signaling (ABI3, ABI4, ABI5), stress-responsive genes, including two ABA-dependent genes (RD20A, RD29B) and three ABA-independent genes (CBF1, CBF2, CBF3), were generally higher in TaSnRK2.8 plants than in WT/GFP controls under normal/stress conditions. Our results suggest that TaSnRK2.8 may act as a regulatory factor involved in a multiple stress response pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".