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Published on: May 4, 2010
Evaluation of stable reference genes for RT-qPCR analysis in Antheraea assamensis (Lepidoptera: Saturniidae) during
Indumathi Kamatchi Balakrishnan1,2, Himanshu Dubey3, Pawan Shukla1
1Seribiotech Research Laboratory, Central Silk Board, Kodathi, Bangalore, India.
Background:
Gene expression profiling is vital for deciphering immune responses in insects, especially for genes involved in pathogen defense, stress adaptation, and immune regulation. The muga silkworm, Antheraea assamensis Helfer (A. assamensis), a species of considerable economic and cultural significance in Northeast India, is vulnerable to bacterial and viral infections that severely impact silk production. Despite its importance, no prior studies have validated suitable reference genes for reverse-transcription quantitative PCR (RT-qPCR) based expression analysis under pathogenic stress in this species. Given that reference gene expression may vary with tissue type, developmental stage, and infection status, rigorous validation of stable reference genes is essential for accurate normalization.
Methods And Results:
Eight candidate housekeeping genes (EF1α, GAPDH, RPS3A, RPL13A, Actin-A1, Tub1, SDHA, and EIF4A) were selected for evaluation. RT-qPCR assays were conducted on fat body and midgut tissues under bacterial and viral infection conditions. Gene expression stability was assessed using the geNorm, NormFinder, and RefFinder algorithms. Results indicated that GAPDH was the most stable gene in the fat body during bacterial infection, whereas Actin-A1 and RPS3A exhibited the highest stability under viral infection. In the midgut, GAPDH showed the highest stability during bacterial infection, while both GAPDH and Tub1 were stable under viral infection conditions. Overall, RPS3A demonstrated the most consistent expression stability across all tissues and infection conditions.
Conclusion:
This study provides the first validated reference gene set for A. assamensis under pathogenic stress, highlighting RPS3A as the most reliable gene for RT-qPCR normalization. These findings will improve the accuracy of gene expression studies and support future transcriptomic and functional genomic research in this economically important silkmoth species.
