A transcriptional and functional analysis of heat hardening in two invasive fruit fly species, <i>Bactrocera dorsalis</i> and <i>Bactrocera correcta</i>
Bibliographic record
Abstract
Abstract Many insects have the capacity to increase their resistance to high temperatures by undergoing heat hardening at nonlethal temperatures. Although this response is well established, its molecular underpinnings have only been investigated in a few species where it seems to relate at least partly to the expression of heat shock protein ( Hsp ) genes. Here, we studied the mechanism of hardening and associated transcription responses in larvae of two invasive fruit fly species in China, Bactrocera dorsalis and Bactrocera correcta . Both species showed hardening which increased resistance to 45°C, although the more widespread B. dorsalis hardened better at higher temperatures compared to B. correcta which hardened better at lower temperatures. Transcriptional analyses highlighted expression changes in a number of genes representing different biochemical pathways, but these changes and pathways were inconsistent between the two species. Overall B. dorsalis showed expression changes in more genes than B. correcta . Hsp genes tended to be upregulated at a hardening temperature of 38°C in both species, while at 35°C many Hsp genes tended to be upregulated in B. correcta but not B. dorsalis . One candidate gene (the small heat shock protein gene, Hsp23 ) with a particularly high level of upregulation was investigated functionally using RNA interference (RNAi). We found that RNAi may be more efficient in B. dorsalis , in which suppression of the expression of this gene removed the hardening response, whereas in B. correcta RNAi did not decrease the hardening response. The different patterns of gene expression in these two species at the two hardening temperatures highlight the diverse mechanisms underlying hardening even in closely related species. These results may provide target genes for future control efforts against such pest species.
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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 | 0.000 |
| 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".