ABSTRACT: BACKGROUND: Quantitative real-time PCR (qPCR) is a widely used technique for gene expression analysis. Its reliability is highly dependent upon selection of the appropriate reference genes for accurate gene expression normalization. In this study, we investigated the expression stability of 10 commonly used reference genes in a mouse myocardial infarction model. METHODS & RESULTS: The expression stability of the 10 reference genes (Actb, B2m, Eef1a1, Gapdh, Hprt, Polr2a, Ppia, Rpl13a, Tbp, Tpt1) was analyzed using the geNorm software. Overall, the combination of Hprt, Rpl13a and Tpt1 was the most stable reference gene set in our experiments. Gapdh, Polr2a and Actb consistently showed the highest gene expression variability and the expression levels of Gapdh, Polr2a, Actb, B2m and Eef1a1 were found to be selectively up- or downregulated after myocardial infarction. We normalized the expression of Nppb and Vcam1, using different reference gene strategies and demonstrated that their induction after myocardial infarction was most clearly revealed with the optimal reference gene combination. However, the use of suboptimal reference gene combinations resulted in detrimental effects on gene expression levels and variability with a gradual loss of the expression differences and a significant reduction in statistical power. CONCLUSIONS: Hprt, Rpl13a and Tpt1 are a set of stably expressed reference genes for accurate gene expression normalization in myocardial infarction studies in mice. We found that Gapdh, Polr2a and Actb display high expression variability in mouse myocardial infarction tissues and that loss of statistical power and increase in sample size are the evident consequences of choosing suboptimal combinations of reference genes. We furthermore caution against the use of Gapdh, Polr2a, Actb, B2m and Eef1a1 for gene expression normalization in myocardial infarction studies because of selective up- or downregulation after myocardial infarction, which could potentially lead to biased study outcomes.
