Validation of reference genes for RT-qPCR in marine bivalve ecotoxicology: Systematic review and case study using copper treated primary Ruditapes philippinarum hemocytes

The appropriate selection of reference genes for the normalization of non-biological variance in reverse transcription real-time quantitative PCR (RT-qPCR) is essential for the accurate interpretation of the collected data. The use of multiple validated reference genes has been shown to substantially increase the robustness of the normalization. It is therefore considered good practice to validate putative genes under specific conditions, determine the optimal number of genes to be employed, and report the method or methods used.

Under this premise, we assessed the current state of reference gene based normalization in RT-qPCR bivalve ecotoxicology studies (post 2011), employing a systematic quantitative literature review. A total of 52 papers met our criteria and were analysed for genes used, the use of multiple reference genes, as well as the validation method employed. We further critically discuss methods for reference gene validation based on a case study using copper exposed primary hemocytes from the marine bivalve Ruditapes philippinarum; including the established algorithms geNorm, NormFinder and BestKeeper, as well as the popular online tool RefFinder.

We identified that RT-qPCR normalization is largely performed using single reference genes, while less than 40% of the studies attempted to experimentally validate the expression stability of the genes used. 18s rRNA and β-Actin were the most popular genes, yet their un-validated use did introduce artefactual variance that altered the interpretation of the resulting data. Our findings further suggest that combining the results from multiple individual algorithms and calculating the overall best-ranked gene, as computed by the RefFinder tool, does not by default lead to the identification of the most suitable reference genes.

Moritz Volland, Julián Blasco, Miriam Hampel, Aquatic Toxicology, Volume 185, April 2017, Pages 86–94

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