Redox‐sensitive proteome and antioxidant strategies in wheat seed dormancy control
Bibliographic record
Abstract
Oxidative signalling by ROS has been demonstrated to play a role in seed dormancy alleviation, but the detailed molecular mechanisms underlying this process remain largely unknown. Here, we show dynamic differences in redox-sensitive proteome upon wheat seed dormancy release. Using thiol-specific fluorescent labelling, solubility-based protein fractionation, 2-D IEF PAGE, and MS analysis in conjunction with wheat EST sequence libraries, proteins with reversible oxidoreductive changes were characterized. Altogether, 193 reactive Cys were found in 79 unique proteins responding differentially in dormant, non-dormant, abscisic, or gibberellic acid-treated seed protein extracts from RL4137, a wheat cultivar with extreme dormancy. The identified proteins included groups that are redox-, stress-, and pathogen-responsive, involved in protein synthesis and storage, are enzymes of carbohydrate metabolism, proteases, and those involved in transport and signal transduction. Two types of redox response could be detected: (i) a dramatic increase in protein thiol redox state in seeds during imbibition and hormonal treatment; (ii) higher antioxidant capacity related to sensing of a threshold redox potential and balancing the existing redox pools, in dry dormant versus non-dormant seeds. These results highlight occurrence of the antioxidant defence mechanisms required for the protection of seed during a dormancy stage.
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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".