Dataset Information

Selection of Reference Genes for Quantitative Real-Time RT-PCR Studies in Tomato Fruit of the Genotype MT-Rg1.

ABSTRACT: Quantitative real-time RT-PCR (qRT-PCR) has become one of the most widely used methods for accurate quantification of gene expression. Since there are no universal reference genes for normalization, the optimal strategy to normalize raw qRT-PCR data is to perform an initial comparison of a set of independent reference genes to assess the most stable ones in each biological model. Normalization of a qRT-PCR experiment helps to ensure that the results are both statistically significant and biologically meaningful. Tomato is the model of choice to study fleshy fruit development. The miniature tomato (Solanum lycopersicum L.) cultivar Micro-Tom (MT) is considered a model system for tomato genetics and functional genomics. A new genotype, containing the Rg1 allele, improves tomato in vitro regeneration. In this work, we evaluated the expression stability of four tomato reference genes, namely CAC, SAND, Expressed, and ACTIN2. We showed that the genes CAC and Exp are the best reference genes of the four we tested during fruit development in the MT-Rg1 genotype. Furthermore, we validated the reference genes by showing that the expression profiles of the transcription factors FRUITFULL1 and APETALA2c during fruit development are comparable to previous reports using other tomato cultivars.

SUBMITTER: Gonzalez-Aguilera KL

PROVIDER: S-EPMC5021083 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Selection of Reference Genes for Quantitative Real-Time RT-PCR Studies in Tomato Fruit of the Genotype MT-Rg1.

González-Aguilera Karla L KL Saad Carolina F CF Chávez Montes Ricardo A RA Alves-Ferreira Marcio M de Folter Stefan S

Frontiers in plant science 20160913

Quantitative real-time RT-PCR (qRT-PCR) has become one of the most widely used methods for accurate quantification of gene expression. Since there are no universal reference genes for normalization, the optimal strategy to normalize raw qRT-PCR data is to perform an initial comparison of a set of independent reference genes to assess the most stable ones in each biological model. Normalization of a qRT-PCR experiment helps to ensure that the results are both statistically significant and biologi ...[more]

PMID: 27679646

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Project description:BackgroundThe elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR.ResultsIn this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (CAC), SGN-U321250 (TIP41), SGN-U346908 ("Expressed") and SGN-U316474 (SAND) genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process.ConclusionThis work constitutes the first effort for the selection of optimal endogenous controls for quantitative real-time RT-PCR studies of gene expression during tomato development process. From our study a tool-kit of control genes emerges that outperform the traditional genes in terms of expression stability.

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:BACKGROUND: Heart and lung transplantation is frequently the only therapeutic option for patients with end stage cardio respiratory disease. Organ donation post brain stem death (BSD) is a pre-requisite, yet BSD itself causes such severe damage that many organs offered for donation are unusable, with lung being the organ most affected by BSD. In Australia and New Zealand, less than 50% of lungs offered for donation post BSD are suitable for transplantation, as compared with over 90% of kidneys, resulting in patients dying for lack of suitable lungs. Our group has developed a novel 24 h sheep BSD model to mimic the physiological milieu of the typical human organ donor. Characterisation of the gene expression changes associated with BSD is critical and will assist in determining the aetiology of lung damage post BSD. Real-time PCR is a highly sensitive method involving multiple steps from extraction to processing RNA so the choice of housekeeping genes is important in obtaining reliable results. Little information however, is available on the expression stability of reference genes in the sheep pulmonary artery and lung. We aimed to establish a set of stably expressed reference genes for use as a standard for analysis of gene expression changes in BSD. RESULTS: We evaluated the expression stability of 6 candidate normalisation genes (ACTB, GAPDH, HGPRT, PGK1, PPIA and RPLP0) using real time quantitative PCR. There was a wide range of Ct-values within each tissue for pulmonary artery (15-24) and lung (16-25) but the expression pattern for each gene was similar across the two tissues. After geNorm analysis, ACTB and PPIA were shown to be the most stably expressed in the pulmonary artery and ACTB and PGK1 in the lung tissue of BSD sheep. CONCLUSION: Accurate normalisation is critical in obtaining reliable and reproducible results in gene expression studies. This study demonstrates tissue associated variability in the selection of these normalisation genes in BSD sheep and underlines the importance of selecting the correct reference genes for both the animal model and tissue studied.

Dataset Information

Selection of Reference Genes for Quantitative Real-Time RT-PCR Studies in Tomato Fruit of the Genotype MT-Rg1.

Publications

Selection of Reference Genes for Quantitative Real-Time RT-PCR Studies in Tomato Fruit of the Genotype MT-Rg1.

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