Abstract
The grassland caterpillar Gynaephora qinghaiensis (Lepidoptera: Lymantriidae) is a dominant pest species in the alpine meadows of the Tibetan Plateau. Elucidating changes in key gene expression patterns will provide molecular insights into the adaptive evolutionary mechanisms of insects. Quantitative real-time PCR (qRT-PCR) is currently the predominant analytical methodology for assessing gene expression levels. However, variability among samples can compromise result reliability. Thus, selecting stably expressed reference genes for target gene normalization under diverse scenarios is critical. To date, suitable reference genes for G. qinghaiensis under varying experimental conditions have remained unidentified. In this study, the transcriptome data of G. qinghaiensis were obtained using the RNA-seq technique, and 13 candidate reference genes were selected. Four independent algorithms-ΔCt, geNorm, NormFinder, and BestKeeper-as well as a comprehensive online platform, RefFinder, were employed to evaluate the stability under six experimental conditions (tissues, developmental stages, sexes, temperatures, starvation, and insecticide treatments). Our findings identified the following optimal reference gene combinations for each experimental condition: RPS18, RPS15, and RPL19 for tissue samples; RPL19, RPS15, and RPL17 across developmental stages; RPS18 and RPS15 for different sexes; RPS8 and EF1-α under varying temperature conditions; RPL17 and RPL15 during starvation; and RPL19 and RPL17 following insecticide treatments. To validate the feasibility of the reference genes, we examined the expression of the target gene HSP60 in different tissues and under different temperatures. Our results established essential reference standards for qRT-PCR with G. qinghaiensis samples, laying the foundation for precise gene expression quantification in the future.