Novel NAC Transcription Factor TaNAC67 Confers Enhanced Multi-Abiotic Stress Tolerances in Arabidopsis
Bibliographic record
Abstract
Abiotic stresses are major environmental factors that affect agricultural productivity worldwide. NAC transcription factors play pivotal roles in abiotic stress signaling in plants. As a staple crop, wheat production is severely constrained by abiotic stresses whereas only a few NAC transcription factors have been characterized functionally. To promote the application of NAC genes in wheat improvement by biotechnology, a novel NAC gene designated TaNAC67 was characterized in common wheat. To determine its role, transgenic Arabidopsis overexpressing TaNAC67-GFP controlled by the CaMV-35S promoter was generated and subjected to various abiotic stresses for morphological and physiological assays. Gene expression showed that TaNAC67 was involved in response to drought, salt, cold and ABA treatments. Localization assays revealed that TaNAC67 localized in the nucleus. Morphological analysis indicated the transgenics had enhanced tolerances to drought, salt and freezing stresses, simultaneously supported by enhanced expression of multiple abiotic stress responsive genes and improved physiological traits, including strengthened cell membrane stability, retention of higher chlorophyll contents and Na(+) efflux rates, improved photosynthetic potential, and enhanced water retention capability. Overexpression of TaNAC67 resulted in pronounced enhanced tolerances to drought, salt and freezing stresses, therefore it has potential for utilization in transgenic breeding to improve abiotic stress tolerance in 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".