A fast, simple, high efficient and one-step generation of composite cucumber plants with transgenic roots by Agrobacterium rhizogenes-mediated transformation
Bibliographic record
Abstract
Abstract Agrobacterium rhizogenes -mediated transformation is widely used in different species with various purposes. The development of composite plants (wild-type shoot with transgenic roots) has been a milestone for functional characterization of genes. Previously, composite plants were generated by two steps from inducing of hairy roots to growing in the growth medium. Hairy roots were induced in an induction medium and the growth of composite plants generated were in another different growth medium. The composite plants produced was subject to transplanting. Here, we describe an improved and optimized protocol for generation of composite plant achieved by one-step in cucumber, which has not been reported previously in living plants. Incubation of explants post inoculation to induce transgenic roots and the growth of rooted explants were in the same medium. The primary root of 5-day-old seedling was excised and the slant cut of residual hypocotyl with 1 cm length was inoculated with A. rhizogenes harboring the desired gene construct followed by directly planted into a pot with wet sterile vermiculite. More than 90% of the infected seedlings can produce positive transgenic root. In addition, we further used the one-step transformation protocol to analyze the function of Arabidopsis YAO promoter. The result indicated that p YAO :: GUS was highly conserved expression in whole root and high activity in the root tips. Therefore, a fast, expedient, high efficient, and one-step transformation method of composite cucumber produced is established, which is suitable for promoter functional analysis and other root-related events.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".