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.

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. The Western honey bee, Apis mellifera L., plays an important role as a pollinator 1. In addition, the honey bee is considered to be a key model insect due to its relatively complex behaviours, including sociality, labour division and colony management 2. Previous studies have demonstrated that endocrine system status and gene expression are important factors for flexible honey bee colony management, which involves colonies seasonally regulating their labour division and population dynamics 3-5. In order to extend our understanding of the molecular mechanisms that underlie the regulation of honey bee colony physiology, information on the physiological functions of the genes putatively associated with colony management can be determined by analysing their expression profiles among different seasons and honey bee tissues 6,7. In quantitative real-time PCR (qRT-PCR), gene-specific mRNA (or cDNA) is quantified; this method has been used extensively because of its relative speed, sensitivity, replicability and accuracy 8,9. Therefore, qRT-PCR would be an ideal method for analysing the expression patterns of honey bee genes putatively involved in the plasticity of colony molecular physiology in samples collected across different seasons and tissues. However, because qRT-PCR results are highly sensitive to the initial amount of RNA content in the amplification reaction, the interpretation of target gene expression levels among various conditions would result in appreciable errors without the use of a reliable internal standard 7-10. Therefore, prior to analysing target gene expression levels among conditions, reference genes are requir...

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Air pollutants and agricultural pesticides can be environmental stressors to pollinators. In this study, to investigate the expression of detoxification-related genes and heavy metal concentrations in honey bees and honey possibly exposed to environmental stresses, we collected samples from apiaries located in mountainous, agricultural, and urban areas. Compared with the mountainous and agricultural areas, the mercury and lead concentrations were highest in honey and bees collected from urban areas. In addition, the expression levels of CYP9Q1 , CYP9Q2 , CYP9Q3 , and genes encoding catalase and superoxide dismutase were markedly higher in urban bees than those from agricultural and mountainous areas, discreetly indicating that the notable induction of the detoxification metabolism in urban bees might be because of heavy metal pollutant exposure. Our study suggests that honey bees actively respond to environmental stressors, such as heavy metals derived from urban areas.

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