ALBERT

Description: Changes in gene expression patterns can reflect the adaptation of organisms to divergent environments. Quantitative real-time PCR (qRT-PCR) is an important tool for ecological adaptation studies at the gene expression level. The quality of the results of qRT-PCR analysis largely depends on the availability of reliable reference genes (RGs). To date, reliable RGs have not been determined for adaptive evolution studies in insects using a standard approach. Here, we evaluated the reliability of 17 candidate RGs for five Gynaephora populations inhabiting various altitudes of the Tibetan Plateau (TP) using four independent (geNorm, NormFinder, BestKeeper, and the deltaCt method) and one comprehensive (RefFinder) algorithms. Our results showed that EF1- α, RPS15 , and RPS13 were the top three most suitable RGs, and a combination of these three RGs was the most optimal for normalization. Conversely, RPS2 , ACT , and RPL27 were the most unstable RGs. The expression profiles of two target genes ( HSP70 and HSP90 ) were used to confirm the reliability of the chosen RGs. Additionally, the expression patterns of four other genes ( GPI , HIF1A , HSP20 , and USP ) associated with adaptation to extreme environments were assessed to explore the adaptive mechanisms of TP Gynaephora species to divergent environments. Each of these six target genes showed discrepant expression patterns among the five populations, suggesting that the observed expression differences may be associated with the local adaptation of Gynaephora to divergent altitudinal environments. This study is a useful resource for studying the adaptive evolution of TP Gynaephora to divergent environments using qRT-PCR, and it also acts as a guide for selecting suitable RGs for ecological and evolutionary studies in insects. We evaluated the reliability of 17 candidate RGs for five Gynaephora populations inhabiting divergent altitudes of the Tibetan Plateau. EF1-α , RPS15 , and RPS13 were the top three suitable RGs, and the combination of the three RGs was the most optimal normalization number. The expression patterns of six genes associated with the adaptation of animals to extreme environments were detected to explore the adaptive mechanisms of Gynaephora to divergent environments.