Reference genes selection for qRT-PCR analysis in Dendroctonus rufipennis
Bibliographic record
Abstract
• Evaluated 8 candidate reference genes across experimental conditions of D. rufipennis. • RPL32 , RPS18 , and SDHA are the best reference genes across developmental stages. • TUBB and RPS18 are suitable for sex-specific and larval facultative diapause research. • RPL32 and RPS18 are optimal for adult diapause termination and cold exposure. Dendroctonus rufipennis (Coleoptera: Curculionidae) is a major forest pest in North America, yet molecular studies on this species remain limited due to the lack of validated reference genes for quantitative gene expression analysis. This study systematically evaluated eight candidate reference genes ( AK , EF1A , RPL32 , RPS18 , SDHA , TUBA , TUBB , and UBIQ ) across diverse experimental conditions and developmental stages of the insect. The expression stability of these genes was assessed using four widely accepted algorithms: geNorm, NormFinder, BestKeeper, and ΔCt method. Our findings demonstrate that RPL32, RPS18 , and SDHA exhibit the highest stability across developmental stages; TUBB and RPS18 are optimal for sex-specific and larval facultative diapause studies; RPL32 and RPS18 perform best for adult obligatory diapause termination and short-term cold exposure experiments. The relative expression levels of target gene kr-h1 significantly varied according to normalization with recommended combinations and the least suited reference genes. These findings provide a robust set of reference genes for normalizing gene expression in D. rufipennis , offering a valuable foundation for future molecular research on this ecologically significant pest.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".