<i>ZmbHLH124</i> identified in maize recombinant inbred lines contributes to drought tolerance in crops
Bibliographic record
Abstract
Summary Due to climate change, drought has become a severe abiotic stress that affects the global production of all crops. Elucidation of the complex physiological mechanisms underlying drought tolerance in crops will support the cultivation of new drought‐tolerant crop varieties. Here, two drought‐tolerant lines, RIL70 and RIL73, and two drought‐sensitive lines, RIL44 and RIL93, from recombinant inbred lines (RIL) generated from maize drought‐tolerant line PH4CV and drought‐sensitive line F9721, were selected for a comparative RNA‐seq study. Through transcriptome analyses, we found that gene expression differences existed between drought‐tolerant and ‐sensitive lines, but also differences between the drought‐tolerant lines, RIL70 and RIL73. ZmbHLH124 in RIL73, named as ZmbHLH124T‐ORG which origins from PH4CV and encodes a bHLH type transcription factor, was specifically up‐regulated during drought stress. In addition, we identified a substitution in ZmbHLH124 that produced an early stop codon in sensitive lines (ZmbHLH124S‐ORG). Overexpression of ZmbHLH124T‐ORG, but not ZmbHLH124S‐ORG, in maize and rice enhanced plant drought tolerance and up‐regulated the expression of drought‐responsive genes. Moreover, we found that ZmbHLH124T‐ORG could directly bind the cis‐acting elements in ZmDREB2A promoter to enhance its expression. Taken together, this work identified a valuable genetic locus and provided a new strategy for breeding drought‐tolerant 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".