Sustained low abscisic acid levels increase seedling vigor under cold stress in rice (Oryza sativa L.)
Bibliographic record
Abstract
Stress-induced abscisic acid (ABA) is mainly catabolized by ABA 8'-hydroxylase (ABA8ox), which also strictly regulates endogenous ABA levels. Although three members of the ABA8ox gene family are conserved in rice, it is not clear which stressors induce expression of these genes. Here, we found that OsABA8ox1 was induced by cold stress within 24 h and that OsABA8ox2 and OsABA8ox3 were not. In contrast, OsABA8ox2 and OsABA8ox3 were ABA-inducible, but OsABA8ox1 was not. OsABA8ox1, OsABA8ox2, and OsABA8ox3 restored germination of a cyp707a1/a2/a3 triple mutant of Arabidopsis to rates comparable to those of the wild type, indicating that OsABA8ox1, OsABA8ox2, and OsABA8ox3 function as ABA-catabolic genes in vivo. Transgenic rice lines overexpressing OsABA8ox1 showed decreased levels of ABA and increased seedling vigor at 15 °C. These results indicate that sustained low levels of ABA lead to increased seedling vigor during cold stress. On the other hand, excessively low endogenous ABA levels caused reduced drought and cold tolerance, although some of the transgenic rice lines expressing OsABA8ox1 at moderate levels did not show these harmful effects. Adequate regulation of endogenous ABA levels is thought to be crucial for maintaining seedling vigor under cold stress and for cold and drought tolerance 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".