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Selection of suitable reference genes for normalization of quantitative real-time PCR in cartilage tissue injury and repair in rabbits.

ABSTRACT: When studying the altered expression of genes associated with cartilage regeneration by quantitative real-time RT-PCR (RT-qPCR), reference genes with highly stable expression during different stages of chondrocyte developmental are necessary to normalize gene expression accurately. Until now, no reports evaluating expression changes of commonly used reference genes in rabbit articular cartilage have been published. In this study, defects were made in rabbit articular cartilage, with or without insulin-like growth factor 1 (IGF-1) treatment, to create different chondrocyte living environments. The stability and intensity of the expressions of the candidate reference genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18S Ribosomal RNA (18S rRNA), cyclophilin (CYP), hypoxanthine phosphoribosyl transferase (HPRT1), and beta-2-microglobulin (B2M) were evaluated. The data were analyzed by geNorm and NormFinder. B2M and 18S rRNA were identified to be suitable reference genes for rabbit cartilage tissues.

SUBMITTER: Peng XX

PROVIDER: S-EPMC3509584 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Selection of suitable reference genes for normalization of quantitative real-time PCR in cartilage tissue injury and repair in rabbits.

Peng Xiao-Xiang XX Zhao Rong-Lan RL Song Wei W Chu Hai-Rong HR Li Meng M Song Shu-Ya SY Li Guang-Zhou GZ Liang Dong-Chun DC

International journal of molecular sciences 20121106 11

When studying the altered expression of genes associated with cartilage regeneration by quantitative real-time RT-PCR (RT-qPCR), reference genes with highly stable expression during different stages of chondrocyte developmental are necessary to normalize gene expression accurately. Until now, no reports evaluating expression changes of commonly used reference genes in rabbit articular cartilage have been published. In this study, defects were made in rabbit articular cartilage, with or without i ...[more]

PMID: 23203068

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Project description:BackgroundQuantitative 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 & resultsThe 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.ConclusionsHprt, 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.

Project description:BackgroundNormalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.ResultsWe propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.ConclusionsThe proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.

Dataset Information

Selection of suitable reference genes for normalization of quantitative real-time PCR in cartilage tissue injury and repair in rabbits.

Publications

Selection of suitable reference genes for normalization of quantitative real-time PCR in cartilage tissue injury and repair in rabbits.

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