Comparative Transcriptome Analyses Uncover Key Candidate Genes Mediating Flight Capacity in Bactrocera dorsalis (Hendel) and Bactrocera correcta (Bezzi) (Diptera: Tephritidae)
Bibliographic record
Abstract
Flight capacity is important for invasive pests during entry, establishment and spreading. Both Bactrocera dorsalis Hendel and Bactrocera correcta Bezzi are invasive fruit flies but their flight capacities differ. Here, a tethered flight mill test demonstrated that B. dorsalis exhibits a greater flight capacity than B. correcta. RNA-Seq was used to determine the transcriptomic differences associated with the flight capacity of two Bactrocera species. Transcriptome data showed that 6392 unigenes were differentially expressed between the two species in the larval stage, whereas in the adult stage, 4104 differentially expressed genes (DEGs) were identified in females, and 3445 DEGs were observed in males. The flight capacity appeared to be correlated with changes in the transcriptional levels of genes involved in wing formation, flight muscle structure, energy metabolism, and hormonal control. Using RNA interference (RNAi) to verify the function of one DEG, the epidermal growth factor receptor (EGFR), we confirmed the role of this gene in regulating wing development, and thereby flight capacity, in both species. This work reveals the flight mechanism of fruit flies and provides insight into fundamental transcriptomics for further studies on the flight performance of insects.
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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 | 0.001 | 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 | 0.000 |
| 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".