The ci‐ <scp>miR</scp> ‐5 regulates the <i>CiCYP18A1</i> to control moulting process of <i>Chilo infuscatellus</i> : Prospective target for pest control
Bibliographic record
Abstract
The microRNAs (miRNAs) play an important role in the regulation of gene expression, influencing the outcome of many biological processes in insects. The introduction of miRNA into the insect body can lead to pest developmental abnormalities indicating that miRNAs are potential targets for pest control. In this study, we employed small RNA sequencing to characterise and analyse the expression of miRNAs in the sugarcane shoot borer Chilo infuscatellus (Snellen). By integrating previously published transcriptome sequencing data, we predicted and identified miRNAs and their target genes involved in the ecdysone metabolic pathway. We confirmed the target relationships between Ci-miR-4, Ci-miR-5 and CiCYP18A1 by RT-qPCR and dual-luciferase reporter assays in vivo and in vitro. Additionally, injection of miRNA mimics reduced the transcripts of CiCYP18A1 and led to abnormal moulting, which is similar to the defect phenotype of depletion of CiCYP18A1 by dsRNA. Furthermore, we also mixed the synthesised Ci-miR-5 mimic into artificial diets and found similar stunting results of the injection method. These results demonstrated that Ci-miR-5 could target CiCYP18A1 to regulate the moulting process and the successful use of an insect miRNA for gene silencing studies in this sugarcane pest. The method provided an effective novel approach for future RNAi-based pest control strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".