Insights into the Mechanisms Underlying Ultraviolet-C Induced Resveratrol Metabolism in Grapevine (V. amurensis Rupr.) cv. “Tonghua-3”
Bibliographic record
Abstract
Stilbene compounds belong to a family of secondary metabolites that are derived from the phenylpropanoid pathway. Production of the stilbene phytoalexin, resveratrol, in grape (Vitis spp.) berries is known to be induced by ultraviolet-C radiation (UV-C), which has numerous regulatory effects on plant physiology. While previous studies have described changes in gene expression caused by UV-C light in several plant species, such information has yet to be reported for grapevine. We investigated both the resveratrol content and gene expression responses of berries from V. amurensis cv. Tonghua-3 following UV-C treatment, to accelerate research into resveratrol metabolism. Comparative RNA-Seq profiling of UV-C treated and untreated grape berries resulted in the identification of a large number of differentially expressed genes. Gene ontology (GO) term classification and biochemical pathway analyses suggested that UV-C treatment caused changes in various cellular processes, as well as in both hormone and secondary metabolism. The data further indicate that UV-C induced increases in resveratrol may be related to the transcriptional regulation of genes involved in the production of secondary metabolites and signaling, as well as several transcription factors. We also observed that following UV-C treatment, 22 stilbene synthase (STS) genes exhibited increases in their expression levels and a VaSTS promoter drove the expression of the GUS reporter gene when expressed in tobacco. We therefore propose that UV-C induction of VaSTS expression is an important factor in promoting resveratrol accumulation. This transcriptome data set provides new insight into the response of grape berries to UV-C treatment, and suggests candidate genes, or promoter activity of related genes, that could be used in future functional and molecular biological studies of resveratrol metabolism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".