polyamine uptake transporter 2 (put2) and decaying seeds enhance phyA-mediated germination by overcoming PIF1 repression of germination
Bibliographic record
Abstract
Red light promotes germination after activating phytochrome phyB, which destabilizes the germination repressor PIF1. Early upon seed imbibition, canopy light, unfavorable for photosynthesis, represses germination by stabilizing PIF1 after inactivating phyB. Paradoxically, later upon imbibition, canopy light stimulates germination after activating phytochrome phyA. phyA-mediated germination is poorly understood and, intriguingly, is inefficient, compared to phyB-mediated germination, raising the question of its physiological significance. A genetic screen identified polyamine uptake transporter 2 (put2) mutants that overaccumulate polyamines, a class of antioxidant polycations implicated in numerous cellular functions, which we found promote phyA-mediated germination. In WT seeds, our data suggest that canopy light represses polyamines accumulation through PIF1 while red light promotes polyamines accumulation. We show that canopy light also downregulates PIF1 levels, through phyA; however, PIF1 reaccumulates rapidly, which limits phyA-mediated germination. High polyamines levels in decaying seeds bypass PIF1 repression of germination and stimulate phyA-mediated germination, suggesting an adaptive mechanism promoting survival when viability is compromised.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".