Excision of a selectable marker in transgenic lily (Sorbonne) using the<i>Cre/loxP</i>DNA excision system
Bibliographic record
Abstract
Li, S. H., Du, Y.-P., Wu, Z. H.-Y., Huang, C.-L., Zhang, X.-H., Wang, Z. H.-X. and Jia, G.-X. 2013. Excision of a selectable marker in transgenic lily (Sorbonne) using the Cre/loxP DNA excision system. Can. J. Plant Sci. 93: 903–912. To generate transgenic lily plants with no selectable marker and improved tolerance to abiotic stress, two vectors were co-transformed into the Lilium oriental hybrid Sorbonne by particle bombardment. The pKSB vector included the Cre/loxp-mediated site-specific cDNA excision system under control of the inducible promoter rd29A, and the pBPC-P5CS-F129A vector carried the P5CS gene, which we hypothesized would improve resistance to drought and salt stresses in transgenic lily plantlets. The presence of the two genes was simultaneously detected by PCR and Southern blotting in two resistant plantlets. The co-transformation rate was 0.16%. Subsequently, inducer expression was tested under varying conditions to optimize the deletion of marker gene. Results from molecular detection assays revealed that maintaining bases of bulblet scales at 4°C for 12 h resulted in an increase in the excision rate, reaching 60%. Expression of P5CS improved resistance to salt stress in transgenic lily plantlets. These results demonstrated the feasibility of using the Cre/loxP-based marker elimination system to generate marker-free transgenic plantlets with improved stress tolerance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".