Validation of quantitative real-time PCR reference genes for the determination of seasonal and labor-specific gene expression profiles in the head of Western honey bee, Apis mellifera

Kyung Hwan Moon, Si Hyeock Lee, Young Ho Kim

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

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.

Original languageEnglish
Article numbere0200369
JournalPLoS ONE
Volume13
Issue number7
DOIs
StatePublished - Jul 2018

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