Dataset Information

Selection of the optimal reference genes for expression analyses in different materials of Eriobotrya japonica.

ABSTRACT: Background:Loquat (Eriobotrya japonica) is a subtropical tree bearing fruit that ripens during late spring and early summer, which is the off-season for fruit production. The specific flowering habit of loquat, which starts in fall and ends in winter, has attracted an increasing number of researchers who believe that it may represent an ideal model for studying flowering shift adaptations to climate change in Rosaceae. These studies require an understanding of gene expression patterns within the fruit and other tissues of this plant. Although ACTINs (ACTs) have previously been used as reference genes (RGs) for gene expression studies in loquats, a comprehensive analysis of whether these RGs are optimal for normalizing RT-qPCR data has not been performed. Results:In this study, 11 candidate RGs (RIBOSOMAL-LIKE PROTEIN4 (RPL4), RIBOSOMAL-LIKE PROTEIN18 (RPL18), Histone H3.3 (HIS3), Alpha-tubulin-3 (TUA3), S-Adenosyl Methionine Decarboxylase (SAMDC), TIP41-like Family Protein (TIP41), (UDP)-glucose Pyrophosphorylase (UGPase), 18S ribosomal RNA (18S), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), Plasma Intrinsic Protein 2 (PIP2) and ACTIN(ACT)) were assessed to determine their expression stability in 23 samples from different tissues or organs of loquat. Integrated expression stability evaluations using five computational statistical methods (GeNorm, NormFinder, ?Ct, BestKeeper, and RefFinder) suggested that a RG set, including RPL4, RPL18, HIS3 and TUA3, was the most stable one across all of the tested loquat samples. The expression pattern of EjCDKB1;2 in the tested loquat tissues normalized to the selected RG set demonstrated its reliability. Conclusions:This study reveals the reliable RGs for accurate normalization of gene expression in loquat. In addition, our findings demonstrate an efficient system for identifying the most effective RGs for different organs, which may be applied to related rosaceous crops.

SUBMITTER: Su W

PROVIDER: S-EPMC6348664 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Selection of the optimal reference genes for expression analyses in different materials of <i>Eriobotrya japonica</i>.

Su Wenbing W Yuan Yuan Y Zhang Ling L Jiang Yuanyuan Y Gan Xiaoqing X Bai Yunlu Y Peng Jiangrong J Wu Jincheng J Liu Yuexue Y Lin Shunquan S

Plant methods 20190128

<h4>Background</h4>Loquat (<i>Eriobotrya japonica</i>) is a subtropical tree bearing fruit that ripens during late spring and early summer, which is the off-season for fruit production. The specific flowering habit of loquat, which starts in fall and ends in winter, has attracted an increasing number of researchers who believe that it may represent an ideal model for studying flowering shift adaptations to climate change in Rosaceae. These studies require an understanding of gene expression patt ...[more]

PMID: 30705689

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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:Hepatic gene expression studies are vital for identification of molecular factors involved in insulin resistance. However, the need of normalized gene expression data has led to the search of stable genes which are useful as a reference in specific experimental conditions. The aim of this study was to evaluate expression stability of potential reference genes for real-time PCR gene expression studies, in rats with insulin resistance, early programmed in intrauterine environment of maternal insulin resistance and triggered by exposure to a high sucrose and fat diet in adult life. Male rats coming from insulin resistant (F1IR) mothers or normal (F1N) mothers were fed a standard rodent diet from postnatal day 21 to day 56, and then divided in two groups each. One of each subgroups were fed a high sucrose and fat diet (groups F1IR + HSFD and F1N + HSFD respectively), the rest were fed a control diet (groups F1IR + CD and F1N + CD) for 14 days. Glucose metabolism related tests were later performed. After liver extraction, RNA was isolated and gene expression analyzes of seven potential reference genes (Actb, Gapdh, Gusb, Hprt1, Ldha, Rpl13a and Rplp1) were carried out. LinRegPCR software was used to analyze raw data and determinate baseline corrections, threshold lines, efficiency of PCR reactions and corrected Cq values. Evaluations of gene expression stabilities as well as the number of necessary genes for normalization were assessed with geNorm tool. All samples from all groups showed acceptable PCR amplification efficiencies. The most stable genes were Rplp1, Ldha, Hprt1 and Rpl13a and the less stable was Gapdh. For all groups, just 2 to 3 of the most stable genes were necessary for optimal gene expression data normalization in rat liver. Genes encoding ribosomal proteins are the most appropriated for normalization of expression data in the presented animal model. By contrast, Gapdh, one of the most used genes in normalization, is not recommendable due to its high intergroup variation.

Dataset Information

Selection of the optimal reference genes for expression analyses in different materials of Eriobotrya japonica.

Publications

Selection of the optimal reference genes for expression analyses in different materials of <i>Eriobotrya japonica</i>.

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