Perturbation of lignin biosynthesis pathway in <i>Brassica napus</i> (canola) plants using RNAi
Bibliographic record
Abstract
Brassica napus meal contains high levels of lignin, which is one of the most important compositional factors affecting feed utilization by ruminants. We attempted to modify the concentration and composition of lignin in B. napus plants using the RNAi approach. Four genes were targeted for silencing by this approach either independently or in combination; caffeic acid O-methyltransferase (COMT), cinnamate 4-hydroxylase (C4H); coumarate 3-hydroxylase (C3H); ferulic acid 5-hydroxylase (F5H). We successfully developed transgenic B. napus lines expressing CaMV35S:C3H-C4H RNAi, CaMV35S:F5H-COMT RNAi, and Cruciferin:COMT RNAi that contained up to 40% less seed lignin in the transgenic seeds compared to the control. Despite successfully achieving suppression of these lignin biosynthesis genes and reduction in lignin content in B. napus seeds, we observed minor phenotypic effects on the transgenic plants. In lines carrying the cruciferin:COMT RNAi construct we observed a decrease in lignin content (40%) in the seed and anatomical variations when stem sections were examined. While our silencing had no major negative effect on plant growth it resulted in deformation of vessel elements, and minor changes in S-units. Taken together, these results clearly show that by employing RNAi strategy, it is possible to alter seed lignin content and composition in a manner non-detrimental to B. napus plants.Key words: Brassica napus, cruciferin, lignin, COMT, RNAi
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".