The <i>Arabidopsis tt19‐4</i> mutant differentially accumulates proanthocyanidin and anthocyanin through a 3′ amino acid substitution in glutathione <i>S</i>‐transferase
Bibliographic record
Abstract
The Arabidopsis transparent testa (tt) mutant tt19-4 shows reduced seed coat colour, but stains darkly with DMACA and accumulates anthocyanins in aerial tissues. Positional cloning showed that tt19-4 was allelic to tt19-1 and has a G-to-T mutation in a conserved 3'-domain in the TT19-4 gene. Soluble and unextractable seed proanthocyanidins and hydrolysis of unextractable proanthocyanidin differ between wild-type Col-4 and both mutants. However, seed quercetins, unextractable proanthocyanidin hydrolysis, and seedling anthocyanin content, and flavonoid gene expression differ between tt19-1 and tt19-4. Transformation of tt19-1 with a TT19-4 cDNA results in vegetative anthocyanins, whereas TT19-4 cDNA cannot complement the proanthocyanidin and pale seed coat phenotype of tt19-1. Both recombinant TT19 and TT19-4 enzymes are functional GSTs and are localized in the cytosol, but TT19 did not function with wide range of flavonoids and natural products to produce conjugation products. We suggest that the dark seed coat of Arabidopsis is related to soluble proanthocyanidin content and that quercetin holds the key to the function of TT19. In addition, TT19 appears to have a 5' GSH-binding domain influencing both anthocyanin and proanthocyanidin accumulation and a 3' domain affecting proanthocyanidin accumulation by a single amino acid substitution.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".