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Assessing the stability of suitable reference genes for real-time qPCR analyses in Perina nuda Fabricius
Songkai Liao1, Guihua Luo1, Xinjie Mao1
1State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China.
Abstract:
Perina nuda Fabricius (Lepidoptera, Lymantriidae) is a significant pest affecting banyan trees, with a widely spread across Japan, Southern China, and Southeast Asia. Real-time quantitative polymerase chain reaction is a cornerstone method in molecular biological science to evaluating gene expression; however, the accuracy critically depends on the selection of stable reference genes for standardization. Here, we systematically assessed 12 candidate reference genes' expression stability- actin (ACT), β-actin (BACT), arginine kinase (AK), ribosomal protein S3 (RPS3), ribosomal protein L13 (RPL13), ribosomal protein L28 (RPL28), 18S ribosomal RNA (18S rRNA), 25S ribosomal RNA (25S rRNA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), tubulin (TUB), TATA-box protein (TBP), and elongation factor 1A in eukaryotic (EEF1A)-under 6 distinct experimental conditions relevant to P. nuda biology, including host treatment, temperature stress, starvation, developmental stages, mating status, and tissue specificity. Five algorithmic methods were used to thoroughly evaluate gene expression stability. The findings showed that distinct groups of reference genes were appropriate for varying treatments. Specifically, RPL28 and RPS3 were appropriate for host treatment; RPL13 and BACT for temperature treatment; 25S rRNA and BACT for starvation treatment; RPS3, TBP, and 18S rRNA for developmental stages; RPL28, RPS3, and TBP for mating status; TUB, 18S rRNA, and GAPDH for tissues; 18S rRNA, RPL13, and TBP for all samples. These findings provide actionable guidelines for reliable polymerase chain reaction normalization in P. nuda, facilitating molecular research that directly drive management techniques, including RNA interference (RNAi)-based gene silencing and understanding stress response mechanisms.
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