A systems-oriented analysis of the grapevine R2R3-MYB transcription factor family uncovers new insights into the regulation of stilbene accumulation
Bibliographic record
Abstract
R2R3-MYB transcription factors (TFs) belong to a large and functionally diverse protein superfamily in plants. In this study, we explore the evolution and function of this family in grapevine (Vitis vinifera L.), a high-value fruit crop. We identified and manually curated 134 genes using RNA-Seq data, and named them systematically according to the Super-Nomenclature Committee. We identified novel genes, splicing variants and grapevine/woody-specific duplicated subgroups, suggesting possible neo- and sub-functionalization events. Regulatory network analysis ascribed biological functions to uncharacterized genes and validated those of known genes (e.g. secondary cell wall biogenesis and flavonoid biosynthesis). A comprehensive analysis of different MYB binding motifs in the promoters of co-expressed genes predicted grape R2R3-MYB binding preferences and supported evidence for putative downstream targets. Enrichment of cis-regulatory motifs for diverse TFs reinforced the notion of transcriptional coordination and interaction between MYBs and other regulators. Analysis of the network of Subgroup 2 showed that the resveratrol-related VviMYB14 and VviMYB15 share common co-expressed STILBENE SYNTHASE genes with the uncharacterized VviMYB13. These regulators have distinct expression patterns within organs and in response to biotic and abiotic stresses, suggesting a pivotal role of VviMYB13 in regulating stilbene accumulation in vegetative tissues and under biotic stress conditions.
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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 | 0.001 |
| 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".