Selection of reference genes for expression analyses in liver of rats with impaired glucose metabolism

Hepatic gene expression studies are vital for identification of molecular factors involved in insulin resistance. However, the need of normalized gene expression data has led to the search of stable genes which are useful as a reference in specific experimental conditions. The aim of this study was to evaluate expression stability of potential reference genes for real-time PCR gene expression studies, in rats with insulin resistance, early programmed in intrauterine environment of maternal insulin resistance and triggered by exposure to a high sucrose and fat diet in adult life. Male rats coming from insulin resistant (F1IR) mothers or normal (F1N) mothers were fed a standard rodent diet from postnatal day 21 to day 56, and then divided in two groups each. One of each subgroups were fed a high sucrose and fat diet (groups F1IR + HSFD and F1N + HSFD respectively), the rest were fed a control diet (groups F1IR + CD and F1N + CD) for 14 days. Glucose metabolism related tests were later performed. After liver extraction, RNA was isolated and gene expression analyzes of seven potential reference genes (Actb, Gapdh, Gusb, Hprt1, Ldha, Rpl13a and Rplp1) were carried out. LinRegPCR software was used to analyze raw data and determinate baseline corrections, threshold lines, efficiency of PCR reactions and corrected Cq values. Evaluations of gene expression stabilities as well as the number of necessary genes for normalization were assessed with geNorm tool. All samples from all groups showed acceptable PCR amplification efficiencies. The most stable genes were Rplp1, Ldha, Hprt1 and Rpl13a and the less stable was Gapdh. For all groups, just 2 to 3 of the most stable genes were necessary for optimal gene expression data normalization in rat liver. Genes encoding ribosomal proteins are the most appropriated for normalization of expression data in the presented animal model. By contrast, Gapdh, one of the most used genes in normalization, is not recommendable due to its high intergroup variation.