Overexpression of the <i>OsERF71</i> Transcription Factor Alters Rice Root Structure and Drought Resistance
Bibliographic record
Abstract
Plant responses to drought stress require the regulation of transcriptional networks via drought-responsive transcription factors, which mediate a range of morphological and physiological changes. AP2/ERF transcription factors are known to act as key regulators of drought resistance transcriptional networks; however, little is known about the associated molecular mechanisms that give rise to specific morphological and physiological adaptations. In this study, we functionally characterized the rice (Oryza sativa) drought-responsive AP2/ERF transcription factor OsERF71, which is expressed predominantly in the root meristem, pericycle, and endodermis. Overexpression of OsERF71, either throughout the entire plant or specifically in roots, resulted in a drought resistance phenotype at the vegetative growth stage, indicating that overexpression in roots was sufficient to confer drought resistance. The root-specific overexpression was more effective in conferring drought resistance at the reproductive stage, such that grain yield was increased by 23% to 42% over wild-type plants or whole-body overexpressing transgenic lines under drought conditions. OsERF71 overexpression in roots elevated the expression levels of genes related to cell wall loosening and lignin biosynthetic genes, which correlated with changes in root structure, the formation of enlarged aerenchyma, and high lignification levels. Furthermore, OsERF71 was found to directly bind to the promoter of OsCINNAMOYL-COENZYME A REDUCTASE1, a key gene in lignin biosynthesis. These results indicate that the OsERF71-mediated drought resistance pathway recruits factors involved in cell wall modification to enable root morphological adaptations, thereby providing a mechanism for enhancing drought resistance.
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".