Transgenic Sugarcane with a cry1Ac Gene Exhibited Better Phenotypic Traits and Enhanced Resistance against Sugarcane Borer
Bibliographic record
Abstract
We developed sugarcane plants with improved resistance to the sugarcane borer, Diatraea saccharalis (F). An expression vector pGcry1Ac0229, harboring the cry1Ac gene and the selectable marker gene, bar, was constructed. This construct was introduced into the sugarcane cultivar FN15 by particle bombardment. Transformed plantlets were identified after selection with Phosphinothricin (PPT) and Basta. Plantlets were then screened by PCR based on the presence of cry1Ac and 14 cry1Ac positive plantlets were identified. Real-time quantitative PCR (RT-qPCR) revealed that the copy number of cry1Ac gene in the transgenic lines varied from 1 to 148. ELISA analysis showed that Cry1Ac protein levels in 7 transgenic lines ranged from 0.85 μg/FWg to 70.92 μg/FWg in leaves and 0.04 μg/FWg to 7.22 μg/FWg in stems, and negatively correlated to the rate of insect damage that ranged from 36.67% to 13.33%, respectively. Agronomic traits of six transgenic sugarcane lines with medium copy numbers were similar to the non-transgenic parental line. However, phenotype was poor in lines with high or low copy numbers. Compared to the non-transgenic control plants, all transgenic lines with medium copy numbers had relatively equal or lower sucrose yield and significantly improved sugarcane borer resistance, which lowered susceptibility to damage by insects. This suggests that the transgenic sugarcane lines harboring medium copy numbers of the cry1Ac gene may have significantly higher resistance to sugarcane borer but the sugarcane yield in these lines is similar to the non-transgenic control thus making them superior to the control lines.
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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 | 0.001 |
| 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".