Dataset Information

Quantitative evaluation and selection of reference genes in a rat model of extended liver resection.

ABSTRACT: Partial hepatectomy (PHx) is a frequently used experimental model for the study of liver regeneration. Real-time quantitative PCR (qPCR) has become the one of the methods of choice for expression profiling of selected genes in order to elucidate the regulation of liver function and regeneration. The expression of five commonly used housekeeping genes (HKGs; Alb, UBC, Hprt, Ywhaz, and GAPDH) were evaluated by qPCR in 70% and 90% rat PHx model at 1, 2, and 7 d after PHx. We set up a closely controlled qPCR procedure validating each critical step and the gene expression stability was statistically evaluated by linear regression and analysis of variance. Our results showed the HKG best suited for the evaluation of gene expression in the extended 90% PHx model is Hprt. The amplification of an HKG can be omitted when the same amount of cDNA from all samples is introduced into the amplification reaction. Determination of cDNA concentration employing the bioanalyzer proved to be an easy and reproducible approach. Using this technique the potential regulation of the transcription level of the HKG in response to the experimental condition tested or the stability of a housekeeping gene becomes irrelevant.

SUBMITTER: Xing W

PROVIDER: S-EPMC2685606 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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Quantitative evaluation and selection of reference genes in a rat model of extended liver resection.

Xing Wei W Deng Meihong M Zhang Jinyan J Huang Hai H Dirsch Olaf O Dahmen Uta U

Journal of biomolecular techniques : JBT 20090401 2

Partial hepatectomy (PHx) is a frequently used experimental model for the study of liver regeneration. Real-time quantitative PCR (qPCR) has become the one of the methods of choice for expression profiling of selected genes in order to elucidate the regulation of liver function and regeneration. The expression of five commonly used housekeeping genes (HKGs; Alb, UBC, Hprt, Ywhaz, and GAPDH) were evaluated by qPCR in 70% and 90% rat PHx model at 1, 2, and 7 d after PHx. We set up a closely contro ...[more]

PMID: 19503622

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Project description:BackgroundCardiac arrest, and the associated arrest of blood circulation, immediately leads to permanent brain damage because of the exhaustion of oxygen, glucose and energy resources in the brain. Most hippocampal CA1 neurons die during the first week post the insult. Molecular data concerning the recovery after resuscitation are sparse and limited to the early time period. Expression analysis of marker genes via quantitative real-time RT-PCR enables to follow up the remodeling process. However, proper validation of the applied normalization strategy is a crucial prerequisite for reliable conclusions.Therefore, the present study aimed to determine the expression stability of ten commonly used reference genes (Actb, actin, beta; B2m, beta-2 microglobulin;CypA, cyclophilin A; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; Hprt, hypoxanthine guanine phosphoribosyl transferase; Pgk1, phosphoglycerate kinase 1; Rpl13a, ribosomal protein L13A; Sdha, succinat dehydrogenase complex, subunit a, flavoprotein (Fp); Tbp, TATA box binding protein; Ywhaz, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide) in the rat hippocampus four, seven and twenty-one days after cardiac arrest. Moreover, experimental groups treated with the anti-inflammatory and anti-apoptotic drug minocycline have been included in the study as well.ResultsThe microglial marker Mac-1, used as a target gene to validate the experimental model, was found to be upregulated about 10- to 20-fold after cardiac arrest. Expression stability of candidate reference genes was analyzed using geNorm and NormFinder software tools. Several of these genes behave rather stable. CypA and Pgk1 were identified by geNorm as the two most stable genes 4 and 21 days after asphyxial cardiac arrest, CypA and Gapdh at 7 days post treatment. B2m turned out to be the most variable candidate reference gene, being about 2-fold upregulated in the cardiac arrest treatment groups.ConclusionWe have validated endogenous control genes for qRT-PCR analysis of gene expression in rat hippocampus after resuscitation from cardiac arrest. For normalization purposes in gene profiling studies a combination of CypA and Pgk1 should be considered 4 and 21 days post injury, whereas CypA and Gapdh is the best combination at 7 days. CypA is most favorable if restriction to a single reference gene for all time points is required.

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.

Project description:Real-time PCR is an efficient tool to measure transcripts and provide valuable quantitative information on gene expression of preimplantation stage embryos. Finding valid reference genes for normalization is essential to interpret the real-time PCR results accurately, and understand the biological dynamics during early development. The use of reference genes also known as housekeeping genes is the most widely applied approach. However, the different genes are not systematically compared, and as a result there is no uniformity between studies in selecting the reference gene. The goals of this study were to compare a wide selection of the most commonly used housekeeping genes in mouse oocytes and preimplantation stage embryos produced under different culture conditions, and select the best stable genes for normalization of gene expression data.Quantitative real time PCR method was used to evaluate 12 commonly used housekeeping genes (Actb, Gapdh, H2afz, Hprt, Ppia, Ubc, Eef1e1, Tubb4, Hist2h2aa1, Tbp, Bmp7, Polr2a) in multiple individual embryos representing six different developmental stages. The results were analysed, and stable genes were selected using the geNorm software. The expression pattern was almost similar despite differences in the culture system; however, the transcript levels were affected by culture conditions. The genes have showed various stabilities, and have been ranked accordingly.Compared to earlier studies with similar objectives, we used a unique approach in analysing larger number of genes, comparing embryo samples derived in vivo or in vitro, analysing the expression in the early and late maternal to zygote transition periods separately, and using multiple individual embryos. Based on detailed quantification, pattern analyses and using the geNorm application, we found Ppia, H2afz and Hprt1 genes to be the most stable across the different stages and culture conditions, while Actb, the classical housekeeping gene, showed the least stability. We recommend the use of the geometric averages of those three genes for normalization in mouse preimplantation-stage gene expression studies.

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Quantitative evaluation and selection of reference genes in a rat model of extended liver resection.

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Quantitative evaluation and selection of reference genes in a rat model of extended liver resection.

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