RNA interference in the Asian Longhorned Beetle:Identification of Key RNAi Genes and Reference Genes for RT-qPCR
Bibliographic record
Abstract
Asian Longhorned Beetle (ALB) Anoplophora glabripennis is a serious invasive forest pest in several countries including the United States, Canada, and Europe. RNA interference (RNAi) technology is being developed as a novel method for pest management. Here, we identified the ALB core RNAi genes including those coding for Dicer, Argonaute, and double-stranded RNA-binding proteins (dsRBP) as well as for proteins involved in dsRNA transport and the systemic RNAi. We also compared expression of six potential reference genes that could be used to normalize gene expression and selected gapdh and rpl32 as the most reliable genes among different tissues and stages of ALB. Injection of double-stranded RNA (dsRNA) targeting gene coding for inhibitor of apoptosis (IAP) into larvae and adults resulted in a significant knockdown of this gene and caused the death of 90% of the larvae and 100% of adults. No mortality of both larvae and adults injected with dsRNA targeting gene coding for green fluorescence protein (GFP, as a negative control) was observed. These data suggest that functional RNAi machinery exists in ALB and a potential RNAi-based method could be developed for controlling this insect.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".