ROS Induces Anthocyanin Production Via Late Biosynthetic Genes and Anthocyanin Deficiency Confers the Hypersensitivity to ROS-Generating Stresses in Arabidopsis
Bibliographic record
Abstract
Anthocyanins are known to have antioxidant activities. Their accumulation can be triggered by many chemical and environmental factors, including reactive oxygen species (ROS). However, the mechanism of ROS-induced anthocyanin accumulation and the role of anthocyanins in the response of Arabidopsis (Arabidopsis thaliana) to different stresses are largely unknown. Here, we study the cross-regulation between ROS and anthocyanin production. Ten Arabidopsis mutants covering the main anthocyanin regulatory and biosynthetic genes are systematically analyzed under ROS-generating stresses. We find that ROS triggers anthocyanin accumulation by up-regulating the anthocyanin late biosynthetic and the corresponding regulatory genes. The anthocyanin-deficient mutants have more endogenous ROS and are more sensitive to ROS-generating stresses while having decreased antioxidant capacity. Supplementation with cyanidin makes them less susceptible to ROS, with increased anthocyanin and reduced ROS accumulation. In contrast, pap1-D, which overaccumulates anthocyanins, shows the opposite responses. Gene expression analysis reveals that photosynthetic capacity is more impaired in anthocyanin-deficient mutants under high-light stress. Expression levels of ROS-scavenging enzyme genes are not correlated with the radical-scavenging activity in different mutants. We conclude that ROS are an important source signal to induce anthocyanin accumulation by up-regulating late biosynthetic and the corresponding regulatory genes and, as a feed-back regulation, anthocyanins modulate the ROS level and the sensitivity to ROS-generating stresses in maintaining photosynthetic capacity.
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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 | 0.000 |
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".