AtEDT1/HDG11 regulates stomatal density and water‐use efficiency via <i>ERECTA</i> and <i>E2Fa</i>
Bibliographic record
Abstract
Improvement of crop drought resistance and water-use efficiency (WUE) has been a major endeavor in agriculture. Arabidopsis ENHANCED DROUGHT TOLERANCE1/HOMEODOMAIN GLABROUS11 (AtEDT1/HDG11), a homeodomain-START transcription factor we previously identified from the enhanced drought tolerance1 mutant (edt1), has been demonstrated to improve drought tolerance and WUE significantly in multiple plant species when constitutively overexpressed. Here, we report the genetic evidence suggesting a genetic pathway, which consists of EDT1/HDG11, ERECTA, and E2Fa loci, and regulates WUE by modulating stomatal density. AtEDT1/HDG11 transcriptionally activates ERECTA by binding to homeodomain-binding (HD) cis-elements in the ERECTA promoter. ERECTA, in turn, depends on E2Fa to modulate the expression of cell cycle-related genes. This modulation affects the transition from mitosis to endocycle, leading to increased ploidy levels in leaf cells, and therefore increased cell size and decreased stomatal density. Our results suggest a possible EDT1/HDG11-ERECTA-E2Fa genetic pathway that reduces stomatal density by increasing cell size and provide a new avenue to improve WUE of crops.
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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".