The MKK3 MAPK cascade integrates temperature and after-ripening signals to modulate seed germination
Bibliographic record
Abstract
Abstract Temperature is a major environmental cue for seed germination. The permissive temperature range for germination is narrow in dormant seeds and expands during after-ripening. Quantitative trait loci analyses of pre-harvest sprouting in cereals have revealed that MKK3, a mitogen-activated protein kinase (MAPK) cascade protein, is a negative regulator of grain dormancy. Here we show that the MAPKKK19/20-MKK3-MPK1/2/7/14 cascade modulates germination temperature range in Arabidopsis seeds by elevating germinability of the seeds at sub- and supra-optimal temperatures. The expression of MAPKKK19 and MAPKKK20 is regulated by an unidentified temperature sensing and signaling mechanism the sensitivity of which is modulated during after-ripening of the seeds, and MPK7 is activated at the permissive temperature for germination regulated by expression levels of MAPKKK19/20 . Activation of the MKK3 cascade represses abscisic acid (ABA) biosynthesis enzyme gene expression, and induces expression of ABA catabolic enzyme and gibberellic acid biosynthesis enzyme genes, resulting in expansion of the germinable temperature range. Our data demonstrate that the MKK3 cascade integrates temperature and after-ripening signals to germination processes including phytohormone metabolism.
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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) | 0.003 | 0.001 |
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".