数字农科院2.0

Selection and validation of RT-qPCR reference genes for multi-tissue gene expression normalization in two honeybee subspecies across post-emergence developmental stages

文献类型： 外文期刊

作者： Xuanpeng Liu;Ting Yang;Jilian Li;Chuan Ma

作者机构：

关键词： Antennae;Apis mellifera;Brain;Hypopharyngeal gland;Real-time quantitative PCR

期刊名称： BMC Genomics

ISSN： 1471-2164

年卷期： 2025 年 26 卷 1 期

页码：

收录情况： SCIE（2025版）

摘要： Background: The western honeybee (Apis mellifera) represents a pivotal model organism for investigating social organization and phenotypic plasticity. Behavioral specialization in worker bees induces tissue-specific molecular adaptations, particularly in sensory and secretory tissues. Although real-time quantitative PCR (RT-qPCR) has been extensively employed to quantify gene expression dynamics in these tissues, systematic evaluation of optimal reference genes for RT-qPCR data normalization remains undressed. Results: We systematically assessed nine candidate reference genes across three tissues (antennae, hypopharyngeal glands, and brains) in adult honeybees at three developmental stages (newly emerged bees, nurses, and foragers) from two subspecies (A. m. ligustica and A. m. carnica). Using five statistical algorithms (geNorm, NormFinder, BestKeeper, ΔCT method, and RefFinder), we identified ADP-ribosylation factor 1 (arf1) as the most stable reference gene across all experimental conditions, followed by ribosomal protein L32 (rpL32). Their stability was confirmed by experimental validation through normalization of major royal jelly protein 2 (mrjp2) expression patterns. Notably, three conventional housekeeping genes (α-tubulin, glyceraldehyde-3-phosphate dehydrogenase, and β-actin) displayed consistently poor stability, disqualifying their application in quantitative analyses under these experimental conditions. Conclusions: Our findings provide validated reference genes for precise quantification of tissue-specific gene expression patterns during adult honeybee development. These reference genes facilitate identification of candidate genes associated with honeybee development, social behavior, and productivity traits.

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