Transgenic corn plants with modified ribosomal protein L3 show decreased ear rot disease after inoculation with Fusarium graminearum
Bibliographic record
Abstract
Cereal crops are susceptible to various Fusarium species worldwide. Fusarium graminearum is a major pathogen of corn that causes ear rot disease and contaminates kernels with mycotoxins such as deoxynivalenol (DON). DON binds with the 60S ribosomal protein L3 (RPL3), blocking the translational machinery in the eukaryotic cells. Previously, the modified rice Rpl3 gene (resulting in a change in amino acid residue at 258 from tryptophan to cysteine) was transformed into tobacco and resulted in increased resistance to DON. In the present study, the same modified Rpl3 gene was used to develop two types of transgenic corn plants in which the modified Rpl3 gene was controlled by a constitutive 35S CaMV promoter or a silk-specific ZmGRP5 promoter. The transgenic lines were evaluated for the ear rot disease in the field by inoculating F. graminearum spores in silk and kernel tissues. The overall disease symptoms in the transgenic lines were significantly lower than wild type plants. Transgenic plants having the Rpl3 gene with 35S CaMV promoter showed a 23 to 58% decrease in disease scores whereas the transgenic plants expressing the modified Rpl3 gene under silk specific promoter showed a 27 to 62% decrease in disease scores compared to wild type plants. The kernel inoculation gave lesser disease symptoms in both types of transgenic plants compared to silk inoculation. The maximum decrease in disease scores was observed (up to 62%) in transgenic plants expressing modified Rpl3 gene with silk specific promoter when inoculations were done through kernels. The present report is the first field study of transgenic corn plants developed to reduce F. graminearum infection. Taken together, the results suggest that the modified Rpl3 gene is effective in reducing ear rot disease in corn.
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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".