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. 2014 Jun 25;9(6):e100529.
doi: 10.1371/journal.pone.0100529. eCollection 2014.

Identification of endogenous reference genes for the analysis of microRNA expression in the hippocampus of the pilocarpine-induced model of mesial temporal lobe epilepsy

Affiliations

Identification of endogenous reference genes for the analysis of microRNA expression in the hippocampus of the pilocarpine-induced model of mesial temporal lobe epilepsy

Mykaella Andrade de Araújo et al. PLoS One. .

Abstract

Real-time quantitative RT-PCR (qPCR) is one of the most powerful techniques for analyzing miRNA expression because of its sensitivity and specificity. However, in this type of analysis, a suitable normalizer is required to ensure that gene expression is unaffected by the experimental condition. To the best of our knowledge, there are no reported studies that performed a detailed identification and validation of suitable reference genes for miRNA qPCR during the epileptogenic process. Here, using a pilocarpine (PILO) model of mesial temporal lobe epilepsy (MTLE), we investigated five potential reference genes, performing a stability expression analysis using geNorm and NormFinder softwares. As a validation strategy, we used each one of the candidate reference genes to measure PILO-induced changes in microRNA-146a levels, a gene whose expression pattern variation in the PILO injected model is known. Our results indicated U6SnRNA and SnoRNA as the most stable candidate reference genes. By geNorm analysis, the normalization factor should preferably contain at least two of the best candidate reference genes (snoRNA and U6SnRNA). In fact, when normalized using the best combination of reference genes, microRNA-146a transcripts were found to be significantly increased in chronic stage, which is consistent with the pattern reported in different models. Conversely, when reference genes were individually employed for normalization, we failed to detect up-regulation of the microRNA-146a gene in the hippocampus of epileptic rats. The data presented here support that the combination of snoRNA and U6SnRNA was the minimum necessary for an accurate normalization of gene expression at the different stages of epileptogenesis that we tested.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Levels of five non-coding RNAs candidate reference genes for microRNA qRT-PCR analysis in the hippocampus of the systemic PILO-injected and control rats.
Values are given in the form of RT-qPCR threshold cycle numbers (Ct values), mean formula image SD (n = 6). ANOVA, * formula image, ** formula image, *** formula image.
Figure 2
Figure 2. Selection of the most suitable reference genes for microRNA qRT-PCR analysis in the systemic PILO-model samples using geNorm analysis.
A) Expression stability measurements (M) for the five reference genes analyzed. The x-axis from left to right indicates the ranking of the genes according to their expression stability; lower M values indicate higher expression stability. B) Determination of the optimal number of reference genes for normalization was conducted. The software calculates the normalization factor from at least two genes at which the variable V defines the pair-wise variation between two sequential normalization factors.
Figure 3
Figure 3. NormFinder analysis of expression stability of candidate reference genes for microRNA qRT-PCR analysis in the systemic PILO-model samples.
Ranking of candidate reference genes based on stability values calculated by NormFinder software.
Figure 4
Figure 4. Relative quantities of miR-146a in the hippocampus of the systemic PILO- injected rats upon different normalization approaches.
qRT-PCR data were normalized by single reference gene and best combination derived by geNorm or NormFinder analysis (mean formula image SD, n = 6). The diagram shows mean levels of miR-146a transcripts in naive animals, epileptogenesis (0 h and 24 h) and chronic period. ANOVA, * formula image, ** formula image, *** formula image.

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