Genome-Wide Analysis of DEAD-box RNA Helicase Family in Wheat (Triticum aestivum) and Functional Identification of TaDEAD-box57 in Abiotic Stress Responses
Bibliographic record
Abstract
DEAD-box RNA helicases constitute the largest subfamily of RNA helicase superfamily 2 (SF2), and play crucial roles in plant growth, development, and abiotic stress responses. Wheat is one of the most important cereal crops in worldwide, and abiotic stresses greatly restrict its production. So far, the DEAD-box RNA helicase family has yet to be characterized in wheat. Here, we performed a comprehensive genome-wide analysis of the DEAD-box RNA helicase family in wheat, including phylogenetic relationships, chromosomal distribution, duplication events, and protein motifs. A total of 141 TaDEAD-box genes were identified and found to be unevenly distributed across all 21 chromosomes. Whole genome/segmental duplication was identified as the likely main driving factor for expansion of the TaDEAD-box family. Expression patterns of the 141 TaDEAD-box genes were compared across different tissues and under abiotic stresses to identify genes to be important in growth or stress responses. TaDEAD-box57-3B was significantly up-regulated under multiple abiotic stresses, and was therefore selected for further analysis. TaDEAD-box57-3B was localized to the cytoplasm and plasma membrane. Ectopic expression of TaDEAD-box57-3B in Arabidopsis improved tolerance to drought and salt stress as measured by germination rates, root lengths, fresh weights, and survival rates. Transgenic lines also showed higher levels of proline and chlorophyll and lower levels of malonaldehyde (MDA) than WT plants in response to drought or salt stress. In response to cold stress, the transgenic lines showed significantly better growth and higher survival rates than WT plants. These results indicate that TaDEAD-box57-3B may increase tolerance to drought, salt, and cold stress in transgenic plants through regulating the degree of membrane lipid peroxidation. This study provides new insights for understanding evolution and function in the TaDEAD-box gene family.
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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) | 0.000 | 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".