Plastid Transformation of Micro-Tom Tomato with a Hemipteran Double-Stranded RNA Results in RNA Interference in Multiple Insect Species
Bibliographic record
Abstract
Plant-mediated RNA interference (RNAi) holds great promise for insect pest control, as plants can be transformed to produce double-stranded RNA (dsRNA) to selectively down-regulate insect genes essential for survival. For optimum potency, dsRNA can be produced in plant plastids, enabling the accumulation of unprocessed dsRNAs. However, the relative effectiveness of this strategy in inducing an RNAi response in insects using different feeding mechanisms is understudied. To investigate this, we first tested an in vitro-synthesized 189 bp dsRNA matching a highly conserved region of the v-ATPaseA gene from cotton mealybug (Phenacoccus solenopsis) on three insect species from two different orders that use leaf-chewing, lacerate-and-flush, or sap-sucking mechanisms to feed, and showed that the dsRNA significantly down-regulated the target gene. We then developed transplastomic Micro-tom tomato plants to produce the dsRNA in plant plastids and showed that the dsRNA is produced in leaf, flower, green fruit, red fruit, and roots, with the highest dsRNA levels found in the leaf. The plastid-produced dsRNA induced a significant gene down-regulation in insects using leaf-chewing and lacerate-and-flush feeding mechanisms, while sap-sucking insects were unaffected. Our results suggest that plastid-produced dsRNA can be used to control leaf-chewing and lacerate-and-flush feeding insects, but may not be useful for sap-sucking insects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".