<scp>ERFVII</scp>‐controlled hypoxia responses are in part facilitated by <scp>MEDIATOR SUBUNIT</scp> 25 in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Flooding impairs plant growth through oxygen deprivation, which activates plant survival and acclimation responses. Transcriptional responses to low oxygen are generally associated with the activation of group VII ETHYLENE-RESPONSE FACTOR (ERFVII) transcription factors. However, the exact mechanisms and molecular components by which ERFVII factors initiate gene expression are not fully elucidated. Here, we show that the ERFVII factors RELATED TO APETALA 2.2 (RAP2.2) and RAP2.12 cooperate with the Mediator complex subunit AtMED25 to coordinate gene expression under hypoxia in Arabidopsis thaliana. Respective med25 knock-out mutants display reduced low-oxygen stress tolerance. AtMED25 physically associates with a distinct set of hypoxia core genes and its loss partially impairs transcription under hypoxia due to decreased RNA polymerase II recruitment. Association of AtMED25 with target genes requires the presence of ERFVII transcription factors. Next to ERFVII protein stabilisation, also the composition of the Mediator complex including AtMED25 is potentially affected by hypoxia stress as shown by protein-complex pulldown assays. The dynamic response of the Mediator complex to hypoxia is furthermore supported by the fact that two subunits, AtMED8 and AtMED16, are not involved in the establishment of hypoxia tolerance, whilst both act in coordination with AtMED25 under other environmental conditions. We furthermore show that AtMED25 function under hypoxia is independent of ethylene signalling. Finally, functional conservation at the molecular level was found for the MED25-ERFVII module between A. thaliana and the monocot species Oryza sativa, pointing to a potentially universal role of MED25 in coordinating ERFVII-dependent transcript responses to hypoxia in plants.
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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) | 0.001 | 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 | 0.001 |
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".