The wheat <i>Ta<scp>GBF</scp>1</i> gene is involved in the blue‐light response and salt tolerance
Bibliographic record
Abstract
Light and abiotic stress both strongly modulate plant growth and development. However, the effect of light-responsive factors on growth and abiotic stress responses in wheat (Triticum aestivum) is unknown. G-box binding factors (GBFs) are blue light-specific components, but their function in abiotic stress responses has not been studied. Here we identified a wheat GBF1 gene that mediated both the blue light- and abiotic stress-responsive signaling pathways. TaGBF1 was inducible by blue light, salt and exposure to abscisic acid (ABA). TaGBF1 interacted with a G-box light-responsive element in vitro and promoted a blue-light response in wheat and Aradidopsis thaliana. Both TaGBF1 over-expression in wheat and its heterologous expression in A. thaliana heighten sensitivity to salinity and ABA, but its knockdown in wheat conferred resistance to high salinity and ABA. The expression of AtABI5, a key component of the ABA signaling pathway in A. thaliana, and its homolog Wabi5 in wheat was increased by transgenic expression of TaGBF1. The hypersensitivity to salt and ABA caused by TaGBF1 was not observed in the abi5 mutant background, showing that ABI5 is the mediator in TaGBF1-induced abiotic stress responses. However, the hypersensitivity to salt conferred by TaGBF1 is not dependent on light. This suggests that TaGBF1 is a common component of blue light- and abiotic stress-responsive signaling pathways.
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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 | 0.000 |
| 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 | 0.001 |
| 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".