<i>Agrobacterium</i>-mediated genetic transformation of peanut and the efficient recovery of transgenic plants
Bibliographic record
Abstract
Chen, M., Yang, Q., Wang, T., Chen, N., Pan, L., Chi, X., Yang, Z., Wang, M., and Yu, S. 2015. Agrobacterium-mediated genetic transformation of peanut and the efficient recovery of transgenic plants. Can. J. Plant Sci. 95: 735–744. Four genotypes of peanut and two sources of explants (cotyledon and mesocotyl) were tested for their susceptibility to genetic transformation by the Agrobacterium tumefaciens strain LBA4404 that harbored the binary vector pCAMBIA1301. This plasmid contains the hygromycin phosphotransferase (hpt) and β-glucuronidase (GUS) genes, each under the control of a CaMV35S promoter. Comparative analyses of regeneration and transformation efficiencies indicated that mesocotyl was a better target tissue than cotyledon, and peanut genotypes of that mature early and have relatively small seeds (such as Huayu 26 and Huayu 20) were shown to be comparatively responsive to transformation. Sonication of explants soaked with solutions containing Agrobacterium was shown to optimize transformation. Culture of explants on medium supplemented with 3 mg L−1 indole-3-butyric acid and 0.1 mg L−1 napthaleneacetic acid enabled vigorous rooting from almost all transgenic shoots. More than 85% of the transplanted plants could produce morphologically normal flowers and pods with viable seeds. Phenotypic and genotypic monitoring of the inheritance of hpt and GUS genes through two generations indicated the expected 3:1 inheritance. Our results make Agrobacterium-mediated transformation a viable and useful tool for both breeding and functional genomic analysis of peanut.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".