EIN3 and ORE1 Accelerate Degreening during Ethylene-Mediated Leaf Senescence by Directly Activating Chlorophyll Catabolic Genes in Arabidopsis
Bibliographic record
Abstract
Degreening, caused by chlorophyll degradation, is the most obvious symptom of senescing leaves. Chlorophyll degradation can be triggered by endogenous and environmental cues, and ethylene is one of the major inducers. ETHYLENE INSENSITIVE3 (EIN3) is a key transcription factor in the ethylene signaling pathway. It was previously reported that EIN3, miR164, and a NAC (NAM, ATAF, and CUC) transcription factor ORE1/NAC2 constitute a regulatory network mediating leaf senescence. However, how this network regulates chlorophyll degradation at molecular level is not yet elucidated. Here we report a feed-forward regulation of chlorophyll degradation that involves EIN3, ORE1, and chlorophyll catabolic genes (CCGs). Gene expression analysis showed that the induction of three major CCGs, NYE1, NYC1 and PAO, by ethylene was largely repressed in ein3 eil1 double mutant. Dual-luciferase assay revealed that EIN3 significantly enhanced the promoter activity of NYE1, NYC1 and PAO in Arabidopsis protoplasts. Furthermore, Electrophoretic mobility shift assay (EMSA) indicated that EIN3 could directly bind to NYE1, NYC1 and PAO promoters. These results reveal that EIN3 functions as a positive regulator of CCG expression during ethylene-mediated chlorophyll degradation. Interestingly, ORE1, a senescence regulator which is a downstream target of EIN3, could also activate the expression of NYE1, NYC1 and PAO by directly binding to their promoters in EMSA and chromatin immunoprecipitation (ChIP) assays. In addition, EIN3 and ORE1 promoted NYE1 and NYC1 transcriptions in an additive manner. These results suggest that ORE1 is also involved in the direct regulation of CCG transcription. Moreover, ORE1 activated the expression of ACS2, a major ethylene biosynthesis gene, and subsequently promoted ethylene production. Collectively, our work reveals that EIN3, ORE1 and CCGs constitute a coherent feed-forward loop involving in the robust regulation of ethylene-mediated chlorophyll degradation during leaf senescence in Arabidopsis.
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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".