Insect cuticular hydrocarbons (CHCs) are organic compounds of the surface lipid layer, which function as a barrier against water loss and xenobiotic penetration, while also serving as chemical signals. Plasticity of CHC profiles can vary depending upon numerous biological and environmental factors. Here, we investigated potential sources of variation in CHC profiles of Nilaparvata lugens, Laodelphax striatellus and Sogatella furcifera, which are considered to be the most important rice pests in Asia. CHC profiles were quantified by GC/MS, and factors associated with variations were explored by conducting principal component analysis (PCA). Transcriptomes were further compared under different environmental conditions. The results demonstrated that CHC profiles differ among three species and change with different developmental stages, sexes, temperature, humidity and host plants. Genes involved in cuticular lipid biosynthesis pathways are modulated, which might explain why CHC profiles vary among species under different environments. Our study illustrates some biological and ecological variations in modifying CHC profiles, and the underlying molecular regulation mechanisms of the planthoppers in coping with changes of environmental conditions, which is of great importance for identifying potential vulnerabilities relating to pest ecology and developing novel pest management strategies.

The German cockroach, Blattella germanica, and the American cockroach, Periplaneta americana are the most common and synanthropic household pests of interest to public health. While they have increasingly served as model systems in hemimetabolous insects for studying many biological issues, there is still a lack of stable reference gene evaluation for reliable quantitative real-time PCR (qPCR) outputs and functional genomics. Here, we evaluated the expression variation of common insect reference genes, including the historically used actin, across various tissues and developmental stages, and also under experimental treatment conditions in these two species by using three individual algorithms (geNorm, BestKeeper, and NormFinder) and a comprehensive program (RefFinder). RPL32 in B. germanica and EF1α in P. americana showed the overall lowest variation among all examined samples. Based on the stability rankings by RefFinder, the optimal but varied reference genes under specific conditions were selected for qPCR normalization. In addition, the combination of RPL32 and EF1α was recommended for all the tested tissues and stages in B. germanica, whereas the combination of multiple reference genes was unfavorable in P. americana. This study provides a condition-specific resource of reference gene selection for accurate gene expression profiling and facilitating functional genomics in these two important cockroaches.