ABA‐dependent inhibition of the ubiquitin proteasome system during germination at high temperature in <i>Arabidopsis</i>
Bibliographic record
Abstract
During germination, endogenous and environmental factors trigger changes in the transcriptome, translatome and proteome to break dormancy. In Arabidopsis thaliana, the ubiquitin proteasome system (UPS) degrades proteins that promote dormancy to allow germination. While research on the UPS has focused on the identification of proteasomal substrates, little information is known about the regulation of its activity. Here we characterized the activity of the UPS during dormancy release and maintenance by monitoring protein ubiquitination and degradation of two proteasomal substrates: Suc-LLVY-AMC, a well characterized synthetic substrate, and FUSCA3 (FUS3), a dormancy-promoting transcription factor degraded by the 26S proteasome. Our data indicate that proteasome activity and protein ubiquitination increase during imbibition at optimal temperature (21°C), and are required for seed germination. However, abscisic acid (ABA) and supraoptimal temperature (32°C) inhibit germination by dampening both protein ubiquitination and proteasome activity. Inhibition of UPS function by high temperature is reduced by the ABA biosynthesis inhibitor, fluridone, and in ABA biosynthetic mutants, suggesting that it is ABA dependent. Accordingly, inhibition of FUS3 degradation at 32°C is also dependent on ABA. Native gels show that inhibition of proteasome activity is caused by interference with the 26S/30S ratio as well as free 19S and 20S levels, impacting the proteasome degradation cycle. Transfer experiments show that ABA-mediated inhibition of proteasome activity at 21°C is restricted to the first 2 days of germination, a time window corresponding to seed sensitivity to environmental and ABA-mediated growth inhibition. Our data show that ABA and high temperature inhibit germination under unfavourable growth conditions by repressing the UPS.
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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) | 0.001 | 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".