Amplification of <scp>ABA</scp> biosynthesis and signaling through a positive feedback mechanism in seeds
Bibliographic record
Abstract
Abscisic acid is an essential hormone for seed dormancy. Our previous study using the plant gene switch system, a chemically induced gene expression system, demonstrated that induction of 9-cis-epoxycarotenoid dioxygenase (NCED), a rate-limiting ABA biosynthesis gene, was sufficient to suppress germination in imbibed Arabidopsis seeds. Here, we report development of an efficient experimental system that causes amplification of NCED expression during seed maturation. The system was created with a Triticum aestivum promoter containing ABA responsive elements (ABREs) and a Sorghum bicolor NCED to cause ABA-stimulated ABA biosynthesis and signaling, through a positive feedback mechanism. The chimeric gene pABRE:NCED enhanced NCED and ABF (ABRE-binding factor) expression in Arabidopsis Columbia-0 seeds, which caused 9- to 73-fold increases in ABA levels. The pABRE:NCED seeds exhibited unusually deep dormancy which lasted for more than 3 months. Interestingly, the amplified ABA pathways also caused enhanced expression of Arabidopsis NCED5, revealing the presence of positive feedback in the native system. These results demonstrated the robustness of positive feedback mechanisms and the significance of NCED expression, or single metabolic change, during seed maturation. The pABRE:NCED system provides an excellent experimental system producing dormant and non-dormant seeds of the same maternal origin, which differ only in zygotic ABA. The pABRE:NCED seeds contain a GFP marker which enables seed sorting between transgenic and null segregants and are ideal for comparative analysis. In addition to its utility in basic research, the system can also be applied to prevention of pre-harvest sprouting during crop production, and therefore contributes to translational biology.
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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".