RNAi-Mediated Suppression of <i>DET1</i> Alters the Levels of Carotenoids and Sinapate Esters in Seeds of Brassica napus
Bibliographic record
Abstract
Carotenoids and sinapate esters in Brassica napus affect the nutritional value of the seed. In this study, the B. napus regulatory gene DE-ETIOLATED1 (DET1), which is a negative regulator of light-mediated responses in plants and affects carotenoid and flavonoid pathways in tomato, was suppressed both constitutively and in a seed-specific manner by RNAi. Constitutive silencing of DET1 resulted in transgenic seeds with substantially elevated levels of lutein, beta-carotene, and zeaxanthin relative to nontransgenic seeds. Levels of these carotenoids were also enhanced but to a lesser extent in seeds of transgenic plants with seed-specific silencing of DET1. Moreover, sinapate esters 1,2-disinapoylgentiobiose and 1,2-di-O-sinapoylglucose were identified in the seeds using 1D and 2D NMR, as well as ESI-MS spectrum analyses. The levels of 1,2-di-O-sinapoylglucose in seeds in both sets of transgenic plants were lower compared to nontransgenic seeds. The results revealed that DET1 suppression in B. napus can increase the levels of carotenoids and reduce the levels of sinapate esters simultaneously in the seeds, thus enhancing their overall nutritional value.
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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".