Effects of knocking out three anthocyanin modification genes on the blue pigmentation of gentian flowers
Bibliographic record
Abstract
Genome editing by the CRISPR/Cas9 system has recently been used to produce gene knockout lines in many plant species. We applied this system to analyze Japanese gentian plants that produce blue flowers because of the accumulation of a polyacylated anthocyanin, gentiodelphin. Mutant lines in which anthocyanin modification genes were knocked out were examined to assess the contribution of each gene to the blue pigmentation of flowers. The targeted genes encoded anthocyanin 5-O-glycosyltransferase (Gt5GT), anthocyanin 3'-O-glycosyltransferase (Gt3'GT), and anthocyanin 5/3'-aromatic acyltransferase (Gt5/3'AT). The Gt5GT knockout lines accumulated delphinidin 3G, whereas the Gt3'GT knockout lines accumulated delphinidin 3G-5CafG as the major flower pigment. Knocking out Gt5/3'AT resulted in the accumulation of delphinidin 3G-5G-3'G and delphinidin 3G-5G as the primary and secondary pigments, respectively. These results indicated the existence of two pathways mediating the modification of delphinidin 3G-5G in flowers, with one involving a glycosylation by 3'GT and the other involving an acylation by 5/3'AT. The Gt5GT, Gt3'GT, and Gt5/3'AT transformants produced pale red violet, dull pink, and pale mauve flowers, respectively, unlike the vivid blue flowers of wild-type plants. Thus, the glycosylation and subsequent acylation of the 3'-hydroxy group of the B-ring in delphinidin aglycone is essential for the development of blue gentian flowers.
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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) | 0.001 | 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".