Exploration of real-time fluorescence quantitative PCR by analyzing effective reference genes in <i>Galleria mellonella</i> (Lepidoptera: Pyralidae)

Galleria mellonella Linnaeus (Lepidoptera: Pyralidae) is a major pest of the Chinese honey bees. Real-time quantitative Polymerase Chain Reaction (RT-qPCR) is a stable method for quantifying gene expression, and the selection of appropriate reference genes is necessary for standardizing gene expression analysis. In this study, the expression profiles of 12 candidate reference genes (GAPDH2, TUBB2B, TBP, RPL7, RPL13, RPL22, SOD, AK1, RPS7, RPS20, RPS25, and PKG21D) were analyzed via 5 different treatments. The stability of candidate reference gene expression was assessed using geNorm, NormFinder, BestKeeper, ΔCt, and RefFinder. Significant differences in optimal reference gene combinations were observed under diverse experimental conditions. Based on different developmental stages, larval tissues, UV irradiation of males, low- and high-temperature treatments of females, high-temperature treatments of males, and insecticide applications, the most suitable reference gene combinations were RPL13 + RPS20, RPL7 + RPL13, RPL22 + RPL7, RPS7 + SOD, RPS25 + RPL22, RPL22 + RPS20, and TBP + RPS25. For UV irradiation to females and low-temperature treatment to males, the best reference gene combination was consistently identified as RPL22 + RPL13. These results laid the foundation for the standardization of RT-qPCR analysis and provided crucial support for developing targeted control strategies for the greater wax moth, such as RNA interference and gene editing, for future studies.

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Publication Details

Journal
Journal of Insect Science
Published
2025-11-07
DOI
https://doi.org/10.1093/jisesa/ieaf103
Citations
1
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.81

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article

Exploration of real-time fluorescence quantitative PCR by analyzing effective reference genes in Galleria mellonella (Lepidoptera: Pyralidae)

Yang Yang Liu, Yan Li, Kai Lang Zhang, Xu Yu Ran et al.
1 citations
Journal of Insect Science
Molecular Biology Techniques and Applications
0.81
article

Exploration of real-time fluorescence quantitative PCR by analyzing effective reference genes in Galleria mellonella (Lepidoptera: Pyralidae)

Yang Yang Liu, Yan Li, Kai Lang Zhang, Xu Yu Ran, Xiao Lan Cheng
article en
1 citations

Abstract

Galleria mellonella Linnaeus (Lepidoptera: Pyralidae) is a major pest of the Chinese honey bees. Real-time quantitative Polymerase Chain Reaction (RT-qPCR) is a stable method for quantifying gene expression, and the selection of appropriate reference genes is necessary for standardizing gene expression analysis. In this study, the expression profiles of 12 candidate reference genes (GAPDH2, TUBB2B, TBP, RPL7, RPL13, RPL22, SOD, AK1, RPS7, RPS20, RPS25, and PKG21D) were analyzed via 5 different treatments. The stability of candidate reference gene expression was assessed using geNorm, NormFinder, BestKeeper, ΔCt, and RefFinder. Significant differences in optimal reference gene combinations were observed under diverse experimental conditions. Based on different developmental stages, larval tissues, UV irradiation of males, low- and high-temperature treatments of females, high-temperature treatments of males, and insecticide applications, the most suitable reference gene combinations were RPL13 + RPS20, RPL7 + RPL13, RPL22 + RPL7, RPS7 + SOD, RPS25 + RPL22, RPL22 + RPS20, and TBP + RPS25. For UV irradiation to females and low-temperature treatment to males, the best reference gene combination was consistently identified as RPL22 + RPL13. These results laid the foundation for the standardization of RT-qPCR analysis and provided crucial support for developing targeted control strategies for the greater wax moth, such as RNA interference and gene editing, for future studies.

Journal of Insect ScienceVol. 25(6)
Guizhou University (CN), Guiyang University (CN), Seventh People's Hospital of Dalian (CN)
Department of Education of Guizhou Province, Guiyang University, Science and Technology Program of Guizhou Province
Openalex Percentile: Top 20%
Molecular Biology Techniques and Applications
0.81
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