Expression of Anthocyanins and Proanthocyanidins after Transformation of Alfalfa with Maize <i>Lc</i>
Bibliographic record
Abstract
Three anthocyanin regulatory genes of maize (Zea mays; Lc, B-Peru, and C1) were introduced into alfalfa (Medicago sativa) in a strategy designed to stimulate the flavonoid pathway and alter the composition of flavonoids produced in forage. Lc constructs included a full-length gene and a gene with a shortened 5'-untranslated region. Lc RNA was strongly expressed in Lc transgenic alfalfa foliage, but accumulation of red-purple anthocyanin was observed only under conditions of high light intensity or low temperature. These stress conditions induced chalcone synthase and flavanone 3-hydroxylase expression in Lc transgenic alfalfa foliage compared with non-transformed plants. Genotypes containing the Lc transgene construct with a full-length 5'-untranslated region responded more quickly to stress conditions and with a more extreme phenotype. High-performance liquid chromatography analysis of field-grown tissue indicated that flavone content was reduced in forage of the Lc transgenic plants. Leucocyanidin reductase, the enzyme that controls entry of metabolites into the proanthocyanidin pathway, was activated both in foliage and in developing seeds of the Lc transgenic alfalfa genotypes. Proanthocyanidin polymer was accumulated in the forage, but (+)-catechin monomers were not detected. B-Peru transgenic and C1 transgenic populations displayed no visible phenotypic changes, although these transgenes were expressed at detectable levels. These results support the emerging picture of Lc transgene-specific patterns of expression in different recipient species. These results demonstrate that proanthocyanidin biosynthesis can be stimulated in alfalfa forage using an myc-like transgene, and they pave the way for the development of high quality, bloat-safe cultivars with ruminal protein bypass.
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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".