Dataset Information

Quantitative Evaluation and Selection of Reference Genes for Quantitative RT-PCR in Mouse Acute Pancreatitis.

ABSTRACT: The analysis of differences in gene expression is dependent on normalization using reference genes. However, the expression of many of these reference genes, as evaluated by quantitative RT-PCR, is upregulated in acute pancreatitis, so they cannot be used as the standard for gene expression in this condition. For this reason, we sought to identify a stable reference gene, or a suitable combination, for expression analysis in acute pancreatitis. The expression stability of 10 reference genes (ACTB, GAPDH, 18sRNA, TUBB, B2M, HPRT1, UBC, YWHAZ, EF-1?, and RPL-13A) was analyzed using geNorm, NormFinder, and BestKeeper software and evaluated according to variations in the raw Ct values. These reference genes were evaluated using a comprehensive method, which ranked the expression stability of these genes as follows (from most stable to least stable): RPL-13A, YWHAZ > HPRT1 > GAPDH > UBC > EF-1? > 18sRNA > B2M > TUBB > ACTB. RPL-13A was the most suitable reference gene, and the combination of RPL-13A and YWHAZ was the most stable group of reference genes in our experiments. The expression levels of ACTB, TUBB, and B2M were found to be significantly upregulated during acute pancreatitis, whereas the expression level of 18sRNA was downregulated. Thus, we recommend the use of RPL-13A or a combination of RPL-13A and YWHAZ for normalization in qRT-PCR analyses of gene expression in mouse models of acute pancreatitis.

SUBMITTER: Yan Z

PROVIDER: S-EPMC4812220 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Quantitative Evaluation and Selection of Reference Genes for Quantitative RT-PCR in Mouse Acute Pancreatitis.

Yan Zhaoping Z Gao Jinhang J Lv Xiuhe X Yang Wenjuan W Wen Shilei S Tong Huan H Tang Chengwei C

BioMed research international 20160316

The analysis of differences in gene expression is dependent on normalization using reference genes. However, the expression of many of these reference genes, as evaluated by quantitative RT-PCR, is upregulated in acute pancreatitis, so they cannot be used as the standard for gene expression in this condition. For this reason, we sought to identify a stable reference gene, or a suitable combination, for expression analysis in acute pancreatitis. The expression stability of 10 reference genes (ACT ...[more]

PMID: 27069927

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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:Isolation and culture of both embryonic and tissue specific stem cells provide an enormous opportunity to study the molecular processes driving development. To gain insight into the initial events underpinning mammalian embryogenesis, pluripotent stem cells from each of the three distinct lineages present within the preimplantation blastocyst have been derived. Embryonic (ES), trophectoderm (TS) and extraembryonic endoderm (XEN) stem cells possess the developmental potential of their founding lineages and seemingly utilize distinct epigenetic modalities to program gene expression. However, the basis for these differing cellular identities and epigenetic properties remain poorly defined.Quantitative reverse transcription-polymerase chain reaction (qPCR) is a powerful and efficient means of rapidly comparing patterns of gene expression between different developmental stages and experimental conditions. However, careful, empirical selection of appropriate reference genes is essential to accurately measuring transcriptional differences. Here we report the quantitation and evaluation of fourteen commonly used references genes between ES, TS and XEN stem cells. These included: Actb, B2m, Hsp70, Gapdh, Gusb, H2afz, Hk2, Hprt, Pgk1, Ppia, Rn7sk, Sdha, Tbp and Ywhaz. Utilizing three independent statistical analysis, we identify Pgk1, Sdha and Tbp as the most stable reference genes between each of these stem cell types. Furthermore, we identify Sdha, Tbp and Ywhaz as well as Ywhaz, Pgk1 and Hk2 as the three most stable reference genes through the in vitro differentiation of embryonic and trophectoderm stem cells respectively.Understanding the transcriptional and epigenetic regulatory mechanisms controlling cellular identity within these distinct stem cell types provides essential insight into cellular processes controlling both embryogenesis and stem cell biology. Normalizing quantitative RT-PCR measurements using the geometric mean CT values obtained for the identified mRNAs, offers a reliable method to assess differing patterns of gene expression between the three founding stem cell lineages present within the mammalian preimplantation embryo.

Project description:BackgroundOdontocete cetaceans occupy the top position of the marine food-web and are particularly sensitive to the bioaccumulation of lipophilic contaminants. The effects of environmental pollution on these species are highly debated and various ecotoxicological studies have addressed the impact of xenobiotic compounds on marine mammals, raising conservational concerns. Despite its sensitivity, quantitative real-time PCR (qRT-PCR) has never been used to quantify gene induction caused by exposure of cetaceans to contaminants. A limitation for the application of qRT-PCR is the need for appropriate reference genes which allow the correct quantification of gene expression. A systematic evaluation of potential reference genes in cetacean skin biopsies is presented, in order to validate future qRT-PCR studies aiming at using the expression of selected genes as non-lethal biomarkers.ResultsTen commonly used housekeeping genes (HKGs) were partially sequenced in the striped dolphin (Stenella coeruleoalba) and, for each gene, PCR primer pairs were specifically designed and tested in qRT-PCR assays. The expression of these potential control genes was examined in 30 striped dolphin skin biopsy samples, obtained from specimens sampled in the north-western Mediterranean Sea. The stability of selected control genes was determined using three different specific VBA applets (geNorm, NormFinder and BestKeeper) which produce highly comparable results. Glyceraldehyde-3P-dehydrogenase (GAPDH) and tyrosine 3-monooxygenase (YWHAZ) always rank as the two most stably expressed HKGs according to the analysis with geNorm and Normfinder, and are defined as optimal control genes by BestKepeer. Ribosomal protein L4 (RPL4) and S18 (RPS18) also exhibit a remarkable stability of their expression levels. On the other hand, transferrin receptor (TFRC), phosphoglycerate kinase 1 (PGK1), hypoxanthine ribosyltransferase (HPRT1) and beta-2-microglobin (B2M) show variable expression among the studied samples and appear as less suitable reference genes for data normalization.ConclusionIn this work, we have provided essential background information for the selection of control genes in qRT-PCR studies of cetacean skin biopsies, as a molecular technique to investigate ecotoxicological hazard in marine mammals. Of 10 HKGs tested, those encoding for YWHAZ and GAPDH appear as the most reliable control genes for the normalization of qRT-PCR data in the analysis of striped dolphin skin biopsies. Potentially useful reference genes are also those encoding for ribosomal proteins L4 and S18.

Dataset Information

Quantitative Evaluation and Selection of Reference Genes for Quantitative RT-PCR in Mouse Acute Pancreatitis.

Publications

Quantitative Evaluation and Selection of Reference Genes for Quantitative RT-PCR in Mouse Acute Pancreatitis.

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