ANAC032 Positively Regulates Age-Dependent and Stress-Induced Senescence in<i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Members of the NAC transcription factor family have been implicated in the regulation of different processes of plant development including senescence. In this study, the role of ANAC032 is analyzed in Arabidopsis thaliana (Col-0). ANAC032 is shown to act as a transcriptional activator and its expression is induced in senescing leaves as well as in dark-treated detached leaves. Analysis of transgenic overexpressors (OXs) and chimeric repressors (SRDXs) of ANAC032 indicates that ANAC032 positively regulates age-dependent and dark-induced leaf senescence. Quantitative real-time PCR analysis showed that ANAC032 regulates leaf senescence mainly through the modulation of expression of the senescence-associated genes AtNYE1, SAG113 and SAUR36/SAG201, which are involved in Chl degradation, and ABA and auxin promotion of senescence, respectively. In addition, ANAC032 expression is induced by a range of oxidative and abiotic stresses. As a result, ANAC032 overexpression lines exhibited enhanced leaf senescence when challenged with different oxidative (3-aminotriazole, fumonisin B1 and high light) and abiotic stress (osmotic and salinity) conditions compared with the wild type. In contrast, ANAC032 SRDX lines displayed the opposite phenotype. ANAC032 transgenic lines showed altered 2,4-D-mediated root tip swelling and root inhibition responses when compared with the wild type. The altered response to auxin, oxidative and abiotic stress treatments in ANAC032 transgenic lines involves differential accumulation of H2O2 compared with the wild type. Taken together, these results indicate that ANAC032 is an important transcription factor that positively regulates age-dependent and stress-induced senescence in A. thaliana by modulating reactive oxygen species production.
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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) | 0.001 | 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".