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Updated: Sep 22, 2026

Development of a Quantitative Recombinase Polymerase Amplification Assay with an Internal Positive Control
Published on: March 30, 2015
Diagnostic evaluation of an EF1α RT-qPCR assay for RNA quality control in IPNV detection
Yoanna Eissler1, Javiera García Véliz2, David Tapia3
1Universidad de Valparaíso, Valparaíso, CHILE.
Abstract:
Reliable detection of infectious pancreatic necrosis virus (IPNV) by real-time RT-qPCR requires stable internal reference genes to control for variability in RNA quality, extraction efficiency, and reverse transcription. In salmonid diagnostics, the housekeeping gene elongation factor 1 alpha (EF1α) is widely used for this purpose; however, different RT-qPCR protocols targeting EF1α are often adopted without comparative evaluation of assay performance. In this study, we compared three RT-qPCR assays targeting EF1α (Moore, Bowers, and a newly designed assay, ELF4) using 53 field samples from three salmonid species (Salmo salar, Oncorhynchus mykiss, and O. kisutch). Differences in Ct dispersion were observed among assays, with the Bowers and ELF4 protocols showing significantly lower variability than the Moore assay. The ELF4 assay was subsequently validated as an endogenous sample control for diagnostic applications using two independent datasets: 500 pooled kidney-spleen samples collected during a confirmed IPNV outbreak in 2023 and 81 samples (47 survivors and 34 mortality cases) from a previously published experimental challenge. Across outbreak samples, ELF4 Ct values remained consistent, whereas IPNV VP1 Ct values showed wider dispersion, reflecting variability in viral RNA levels. A moderate positive correlation was observed between ELF4 and VP1 Ct values (Spearman's ρ = 0.40, p < 0.001), suggesting that sample-dependent variation in RNA quality may influence viral RNA detectability under field conditions. These results support the use of the ELF4 EF1α RT-qPCR assay as a robust endogenous sample control for IPNV detection. Incorporation of ELF4 into routine diagnostic workflows may improve RNA quality assessment and enhance the reliability of RT-qPCR-based surveillance in salmonid aquaculture.

