Expression of the Kale WRKY Gene BoWRKY10 in Transgenic Tobacco Confers Drought Stress Tolerance
Bibliographic record
Abstract
Abstract WRKYs play important roles in plant growth, defense regulation, and the stress response. However, the mechanisms through which WRKYs are involved in drought tolerance have been rarely characterized in kale (Brassica oleracea var. acephala DC). In this study, we cloned the BoWRKY10 gene from kale and its expression was induced with PEG4000, NaCl, gibberellic acid, cold, H2O2, and abscisic acid (ABA). Bo-WRKY10 was localized in the nucleus. The protein had a WRKY domain and a C2H2 zinc finger structure and belonged to subgroup II. The analysis of yeast transcriptional activity showed that BoWRKY10 may have transcriptional activation activity, which was mainly determined by the carboxyl terminal sequence. BoW-RKY10-overexpressing tobacco (Nicotiana tabacum L.) showed enhanced drought tolerance. After the drought treatment, relative water content and proline contents as well as superoxide dismutase activity were higher in transgenic plants, while malondialdehyde and H2O2 contents were lower. In addition, several genes related to the ABA signaling pathway, sucrose, and the reactive oxygen species scavenging system, were significantly upregulated in the transgenic lines. These results demonstrate that BoWRKY10 confers drought tolerance in tobacco. These results provide clues regarding the mechanism by which BoWRKY10 contributes to the regulation of drought stress tolerance.
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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".