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Record W1013680284 · doi:10.1371/journal.pgen.1005399

EIN3 and ORE1 Accelerate Degreening during Ethylene-Mediated Leaf Senescence by Directly Activating Chlorophyll Catabolic Genes in Arabidopsis

2015· article· en· W1013680284 on OpenAlexfundno aff
Kai Qiu, Zhongpeng Li, Zhen Yang, Junyi Chen, Shouxin Wu, Xiaoyu Zhu, Shan Gao, Jiong Gao, Guodong Ren, Benke Kuai, Xin Zhou

Bibliographic record

VenuePLoS Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsnot available
FundersInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesState Key Laboratory of Genetic EngineeringPeking UniversityUniversität PotsdamFudan UniversityScience and Technology Commission of Shanghai MunicipalityShanghai Institutes for Biological Sciences, Chinese Academy of SciencesDirectorate for Biological SciencesChinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of China
KeywordsChromatin immunoprecipitationTranscription factorBiologyArabidopsisElectrophoretic mobility shift assayPromoterBiochemistryChlorophyllGene expressionCell biologyRegulation of gene expressionMutantMolecular biologyGeneBotany

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.244
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations357
Published2015
Admission routes1
Has abstractyes

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