Characterization of the β-Carotene Hydroxylase Gene <i>DSM2</i> Conferring Drought and Oxidative Stress Resistance by Increasing Xanthophylls and Abscisic Acid Synthesis in Rice
Bibliographic record
Abstract
Drought is a major limiting factor for crop production. To identify critical genes for drought resistance in rice (Oryza sativa), we screened T-DNA mutants and identified a drought-hypersensitive mutant, dsm2. The mutant phenotype was caused by a T-DNA insertion in a gene encoding a putative β-carotene hydroxylase (BCH). BCH is predicted for the biosynthesis of zeaxanthin, a carotenoid precursor of abscisic acid (ABA). The amounts of zeaxanthin and ABA were significantly reduced in two allelic dsm2 mutants after drought stress compared with the wild type. Under drought stress conditions, the mutant leaves lost water faster than the wild type and the photosynthesis rate, biomass, and grain yield were significantly reduced, whereas malondialdehyde level and stomata aperture were increased in the mutant. The mutant is also hypersensitive to oxidative stresses. The mutant had significantly lower maximal efficiency of photosystem II photochemistry and nonphotochemical quenching capacity than the wild type, indicating photoinhibition in photosystem II and decreased capacity for eliminating excess energy by thermal dissipation. Overexpression of DSM2 in rice resulted in significantly increased resistance to drought and oxidative stresses and increases of the xanthophylls and nonphotochemical quenching. Some stress-related ABA-responsive genes were up-regulated in the overexpression line. DSM2 is a chloroplast protein, and the response of DSM2 to environmental stimuli is distinctive from the other two BCH members in rice. We conclude that the DSM2 gene significantly contributes to control of the xanthophyll cycle and ABA synthesis, both of which play critical roles in the establishment of drought resistance in rice.
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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".