Expression of OsMYB55 in maize activates stress-responsive genes and enhances heat and drought tolerance
Bibliographic record
Abstract
BACKGROUND: Plant response mechanisms to heat and drought stresses have been considered in strategies for generating stress tolerant genotypes, but with limited success. Here, we analyzed the transcriptome and improved tolerance to heat stress and drought of maize plants over-expressing the OsMYB55 gene. RESULTS: Over-expression of OsMYB55 in maize decreased the negative effects of high temperature and drought resulting in improved plant growth and performance under these conditions. This was evidenced by the higher plant biomass and reduced leaf damage exhibited by the transgenic lines compared to wild type when plants were subjected to individual or combined stresses and during or after recovery from stress. A global transcriptomic analysis using RNA sequencing revealed that several genes induced by heat stress in wild type plants are constitutively up-regulated in OsMYB55 transgenic maize. In addition, a significant number of genes up-regulated in OsMYB55 transgenic maize under control or heat treatments have been associated with responses to abiotic stresses including high temperature, dehydration and oxidative stress. The latter is a common and major consequence of imposed heat and drought conditions, suggesting that this altered gene expression may be associated with the improved stress tolerance in these transgenic lines. Functional annotation and enrichment analysis of the transcriptome also pinpoint the relevance of specific biological processes for stress responses. CONCLUSIONS: Our results show that expression of OsMYB55 can improve tolerance to heat stress and drought in maize plants. Enhanced expression of stress-associated genes may be involved in OsMYB55-mediated stress tolerance. Possible implications for the improved tolerance to heat stress and drought of OsMYB55 transgenic maize are discussed.
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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".