Honey bees are both important pollinators and model insects due to their highly developed sociality and colony management. To better understand the molecular mechanisms underlying honey bee colony management, it is important to investigate the expression of genes putatively involved in colony physiology. Although quantitative real-time PCR (qRT-PCR) can be used to quantify the relative expression of target genes, internal reference genes (which are stably expressed across different conditions) must first be identified to ensure accurate normalisation of target genes. To identify reliable reference genes in honey bee (Apis mellifera) colonies, therefore, we evaluated seven candidate genes (ACT, EIF, EF1, RPN2, RPS5, RPS18 and GAPDH) in samples collected from three honey bee tissue types (head, thorax and abdomen) across all four seasons using three analysis programmes (NormFinder, BestKeeper and geNorm). Subsequently, we validated various normalisation methods using each of the seven reference genes and a combination of multiple genes by calculating the expression of catalase (CAT). Although the genes ranked as the most stable gene were slightly different on conditions and analysis methods, our results suggest that RPS5, RPS18 and GAPDH represent optimal honey bee reference genes for target gene normalisation in qRT-PCR analysis of various honey bee tissue samples collected across seasons.

Honey bee is not only considered an important pollinator in agriculture, but is also widely used as a model insect in biological sciences, thanks to its highly evolved sociality, specialization of labor division, and flexibility of colony management. For an intensive investigation of the seasonal and labor-dependent expression patterns of its genes, accurate quantification of the target gene transcription level is a fundamental step. To date, quantitative real-time PCR (qRT-PCR) has been widely used for rapid quantification of gene transcripts, with reliable reference gene(s) for normalization. To this end, in an attempt to search for reliable reference genes, the amplification efficiencies of six candidate reference genes (rp49, rpL32, rpS18, tbp, tub, and gapdh) were determined. Subsequently, four genes (rpL32, rpS18, tbp, and gapdh) with PCR efficiencies of 90% to 110% were evaluated for their expression stabilities with three programs (geNorm, NormFinder, and BestKeeper) and used for normalization of seasonal expression patterns of target genes in the forager and nurse heads. Although the three programs revealed slightly different results, two genes, rpS18 and gapdh, were suggested to be the optimal reference genes for qRT-PCR-based determination of seasonal and labor-specific gene expression profiles. Furthermore, the combined use of these two genes yielded a more accurate normalization, compared with the use of a single gene in the head of honey bee. The validated reference genes can be widely used for quantification of target gene expression in honey bee head although it is still remained to be elucidated the expression levels of the selected reference genes in specific tissues in head.

Acetylcholinesterase 1 (AmAChE1) of the honey bee, Apis mellifera, has been suggested to have non-neuronal functions. A systematic expression profiling of AmAChE1 over a year-long cycle on a monthly basis revealed that AmAChE1 was predominantly expressed in both head and abdomen during the winter months and was moderately expressed during the rainy summer months. Interestingly, AmAChE1 expression was inhibited when bees were stimulated for brood rearing by placing overwintering beehives in strawberry greenhouses with a pollen diet, whereas it resumed when the beehives were moved back to the cold field, thereby suppressing brood rearing. In early spring, pollen diet supplementation accelerated the induction of brood-rearing activity and the inhibition of AmAChE1 expression. When active beehives were placed in a screen tent in late spring, thereby artificially suppressing brood-rearing activity, AmAChE1 was highly expressed. In contrast, AmAChE1 expression was inhibited when beehives were allowed to restore brood rearing by removing the screen, supporting the hypothesis that brood rearing status is a main factor in the regulation of AmAChE1 expression. Since brood rearing status is influenced by various stress factors, including temperature and diet shortage, our finding discreetly suggests that AmAChE1 is likely involved in the stress response or stress management.

Utilizing chemical agents in pest management in modern agricultural practices has been the predominant approach since the advent of synthetic insecticides. However, insecticide resistance is an emerging issue, as pest populations evolve to survive exposure to chemicals that were once effective in controlling them, underlining the need for advanced and innovative approaches to managing pests. In insects, microRNAs (miRNAs) serve as key regulators of a wide range of biological functions, characterized by their dynamic expression patterns and the ability to target genes. Recent studies are increasingly attributed to the significance of miRNAs in contributing to the evolution of insecticide resistance in numerous insect species. Abundant miRNAs have been discovered in insects using RNA sequencing and transcriptome analysis and are known to play vital roles in regulation at both the transcriptional and post-transcriptional levels. Globally, there is growing research interest in the characterization and application of miRNAs, especially for their potential role in managing insecticide resistance. This review focuses on how miRNAs contribute to regulating insecticide resistance across various insect species. Furthermore, we discuss the gain and loss of functions of miRNAs and the techniques for delivering miRNAs into the insect system. The review emphasizes the application of miRNA-based strategies to studying their role in diminishing insecticide resistance, offering a more efficient and lasting approach to insect management.