Expression of Mannose-Binding Insecticidal Lectin Gene in Transgenic Cotton (<i>Gossypium</i>) Plant
Bibliographic record
Abstract
Cotton ( Gossypium spp ) is an important world crop. Despite the efforts made through traditional breeding methods, cotton breeders still faced with many problems, i.e., narrow genetic base, inability to use alien genes and difficulty in breaking gene linkages. Breeders attempted genetic transformations analyses tools to overcome these problems with very little success, hence the need for transgenic intervention. In this report, an optimized cotton regeneration system from shoot apices used to transform cotton wit insecticidal lectin gene from Allium sativum . Cotton regeneration system was observed to be genotype independent with a regeneration rate of 85% obtained within 16 weeks. The age of explants and the size of isolated tips have a significant effect on shoot tip elongation. The elongation rates of the three varieties were not significantly different from each other (p=0.1573). It was observed that Samcot 9 had the highest rooting efficiency (47%), and Samcot 13 had the least rooting efficiency (36%). Though the difference in rooting efficiency was not significant in the three varieties (P=0.08) Transgenic cotton plants were obtained via Agrobacterium -mediated transformation using shoot apices as explants. Transformation rate was 1.3% using LBA 4404 with β-glucuronidase (GUS) gene. The mean number of GUS positive apices was 67% higher when acetosyringone was included in the medium. Agrobacterium concentration and co-cultivation time have a significant effect on transient GUS expression. The highest GUS positive number was observed at OD 600 0.6 and co-cultivation for 3 days. Putative transgenic plants were confirmed by leaf GUS assay, kanamycin leaf test and molecular analysis of putative young leaves.
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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) | 0.001 | 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".