Development of a New Genetic Transformation System for White and Green Ash Using Embryogenic Cultures
Bibliographic record
Abstract
All North American ash (Fraxinus spp.) species are threatened by the emerald ash borer (EAB; Agrilus planipennis), an exotic beetle which has already destroyed millions of ash trees in the U.S. and Canada. Although both chemical insecticides and biological control can be effective, and host resistance appears possible, the speed of the invasion has defied traditional management approaches. One potential, innovative approach to managing this destructive insect is to develop a host tree-induced gene silencing strategy using RNA interference (RNAi) constructs targeting EAB-specific genes. An important requirement for applying RNAi technology is a reliable transformation/regeneration system for the host tree species. We developed an Agrobacterium-mediated gene transfer system for white ash (F. americana) and green ash (F. pennsylvanica) using the embryogenic cultures of these species as target material. Embryogenic suspension cultures of multiple genotypes of both species were plated and inoculated with A. tumefaciens carrying the pFHI-GUSi expression vector, which carries the nptII selectable marker and intron-GUS reporter genes, followed by selection on a semi-solid medium containing geneticin. Putative transgenic events showed expression of the GUS gene at all tested developmental stages from callus to plantlets, and transgene presence in the leaves of regenerated plants was confirmed using PCR. The overall average transformation efficiency achieved was 14.5 transgenic events per gram of tissue. Transgenic somatic seedlings of two white ash and three green ash genotypes were produced and acclimated to greenhouse conditions.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".