Engineered Cleistogamy in<i>Camelina sativa</i>for bioconfinement
Bibliographic record
Abstract
Abstract Camelina sativa is a self-pollinating and facultative outcrossing oilseed crop. Genetic engineering has been used to improve camelina yield potential for altered fatty acid composition, modified protein profiles, improved seed and oil yield, and enhanced drought resistance. The deployment of transgenic camelina in the field posits high risks related to the introgression of transgenes into non-transgenic camelina and wild relatives. Thus, effective bioconfinement strategies need to be developed to prevent pollen-mediated gene flow (PMGF) from transgenic camelina. In the present study, we overexpressed the cleistogamy (i.e. floral petal non-openness)-inducing PpJAZ1 gene from peach in transgenic camelina. Transgenic camelina overexpressing PpJAZ1 showed three levels of cleistogamy, affected pollen germination rates after anthesis but not during anthesis, and caused a minor silicle abortion only on the main branches. We also conducted field trials to examine the effects of the overexpressed PpJAZ1 on PMGF in the field, and found that the overexpressed PpJAZ1 dramatically inhibited PMGF from transgenic camelina to non-transgenic camelina under the field conditions. Thus, the engineered cleistogamy using the overexpressed PpJAZ1 is a highly effective bioconfinement strategy to limit PMGF from transgenic camelina, and could be used for bioconfinement in other dicot species.
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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".