Simple analytical and experimental procedure for selection of reference genes for qPCR normalization data

Rodrigo Manjarin1, Nathalie Trottier1, Patty Weber2, James Liesman1, Nathanael Taylor1, Juan Pedro Steibel1,3
1Department of Animal Science, Michigan State University, United States of America; 2Department of Large Animal Clinical Sciences, Michigan State University, United States of America; 3Department of Fisheries and Wildlife, Michigan State University, United States of America

Variation of cellular activity in a tissue induces changes in RNA and DNA concentration between samples, which may affect the validity of mRNA abundance of target genes obtained with real-time quantitative PCR (qPCR) analysis. A common way of accounting for such variation consists of the use of a reference gene as a normaliser. Programs such as geNorm can be used to select suitable reference genes, although a large set of genes that are not co-regulated must be analyzed to obtain accurate results. The objective of this study was to propose an alternative analytical protocol to assess the invariance of reference genes in porcine mammary tissue using mammary RNA and DNA concentrations as correction factors. Mammary glands were biopsied from 4 sows on d 110 of gestation (pre-partum), on d 5 (early) and 17 (peak) of lactation, and on d 5 after weaning (post-weaning). Relative expression of seven potential reference genes, API5, MRPL39, VAPB, ACTB, GAPDH, RPS23 and MTG1, and one candidate gene, SLC7A1, was quantified by qPCR using a relative standard curve. The response in cycles to threshold at each stage of lactation was tested using a linear mixed model fitting RNA and DNA concentration as covariates. Results were compared to those obtained with geNorm analysis and genes selected by each method were used to normalize SLC7A1. Quantified relative mRNA abundance of API5, GAPDH and MRPL39 remained unchanged (P > 0.1) across stages after correcting with RNA and DNA concentration, whereas geNorm analysis selected MTG1, MRPL39 and VAPB as best reference genes. There were no differences between normalization of SLC7A1 with genes selected by the proposed analysis protocol or by geNorm. In conclusion, the proposed analytical protocol and geNorm selected different reference genes, but SLC7A1 fold changes did not differ when using genes obtained under either method. These results indicate that among our set of candidate genes, there is more than one suitable reference gene. The proposed method, however, has the strength of allowing testing each potential reference gene individually and sequentially, so analysis of remaining genes can be spared as soon as a suitable reference gene is identified.

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