CsMYB Transcription Factors Participate in Jasmonic Acid Signal Transduction in Response to Cold Stress in Tea Plant (Camellia sinensis)
Bibliographic record
Abstract
Low-temperature stress is an increasing problem for the cultivation of tea (Camellia sinensis), with adverse effects on plant growth and development and subsequent negative impacts on the tea industry. Methyl jasmonate (MeJA), as a plant inducer, can improve the cold-stress tolerance in tea plants. R2R3-MYB transcription factors (TFs) are considered potentially important regulators in the resistance to cold stress in plants. However, the molecular mechanisms, by which MYB TFs via the jasmonic acid pathway respond to cold stress in the tea plant, remain unknown. In this study, physiological and biochemical assays showed that exogenous MeJA application could effectively promote ROS scavenging in the tea plant under cold stress, maintaining the stability of the cell membrane. Sixteen R2R3-MYB TFs genes were identified from the tea plant genome database. Quantitative RT-PCR analysis showed that three CsMYB genes were strongly induced under a combination of MeJA and cold-stress treatment. Subcellular localization assays suggest CsMYB45, CsMYB46, and CsMYB105 localized in the nucleus. Exogenous MeJA treatment enhanced the overexpression of CsMYB45, CsMYB46, and CsMYB105 in E. coli and improved the growth and survival rates of recombinant cells compared to an empty vector under cold stress. Yeast two-hybrid and bimolecular fluorescence complementation experiments confirmed that CsMYB46 and CsMYB105 interacted with CsJAZ3, CsJAZ10, and CsJAZ11 in the nucleus. Taken together, these results highlight that CsMYB45, CsMYB46, and CsMYB105 are not only key components in the cold-stress signal response pathway but also may serve as points of confluence for cold stress and JA signaling pathways. Furthermore, our findings provide new insight into how MYB TFs influence cold tolerance via the jasmonic acid pathway in tea and provide candidate genes for future functional studies and breeding.
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 | 0.001 |
| 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".