Preservation and Faithful Expression of Transgene via Artificial Seeds in Alfalfa
Bibliographic record
Abstract
Proper preservation of transgenes and transgenic materials is important for wider use of transgenic technology in plants. Here, we report stable preservation and faithful expression of a transgene via artificial seed technology in alfalfa. DNA constructs containing the uid reporter gene coding for β-glucuronidase (GUS) driven by a 35S promoter or a tCUP promoter were introduced into alfalfa via Agrobacterium-mediated genetic transformation. Somatic embryos were subsequently induced from transgenic alfalfa plants via in vitro technology. These embryos were treated with abscisic acid to induce desiccation tolerance and were subjected to a water loss process. After the desiccation procedure, the water content in dried embryos, or called artificial seeds, was about 12-15% which was equivalent to that in true seeds. Upon water rehydration, the dried somatic embryos showed high degrees of viability and exhibited normal germination. Full plants were subsequently developed and recovered in a greenhouse. The progeny plants developed from artificial seeds showed GUS enzyme activity and the GUS expression level was comparable to that of plants developed from somatic embryos without the desiccation process. Polymerase chain reaction analysis indicated that the transgene was well retained in the plants and Southern blot analysis showed that the transgene was stably integrated in plant genome. The research showed that the transgene and the new trait can be well preserved in artificial seeds and the progeny developed. The research provides a new method for transgenic germplasm preservation in different plant 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) | 0.000 | 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 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".