Dataset Information

An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development.

ABSTRACT: BACKGROUND: Accuracy in quantitative real-time RT-PCR is dependent on high quality RNA, consistent cDNA synthesis, and validated stable reference genes for data normalization. Reference genes used for normalization impact the results generated from expression studies and, hence, should be evaluated prior to use across samples and treatments. Few statistically validated reference genes have been reported in grapevine. Moreover, success in isolating high quality RNA from grapevine tissues is typically limiting due to low pH, and high polyphenolic and polysaccharide contents. RESULTS: We describe optimization of an RNA isolation procedure that compensates for the low pH found in grape berries and improves the ability of the RNA to precipitate. This procedure was tested on pericarp and seed developmental series, as well as steady-state leaf, root, and flower tissues. Additionally, the expression stability of actin, AP47 (clathrin-associated protein), cyclophilin, EF1-alpha (elongation factor 1-alpha), GAPDH (glyceraldehyde 3-phosphate dehydrogenase), MDH (malate dehydrogenase), PP2A (protein phosphatase), SAND, TIP41, alpha-tubulin, beta-tubulin, UBC (ubiquitin conjugating enzyme), UBQ-L40 (ubiquitin L40) and UBQ10 (polyubiquitin) were evaluated on Vitis vinifera cv. Cabernet Sauvignon pericarp using three different statistical approaches. Although several of the genes proved to be relatively stable, no single gene outperformed all other genes in each of the three evaluation methods tested. Furthermore, the effect of using one reference gene versus normalizing to the geometric mean of several genes is presented for the expression of an aquaporin and a sucrose transporter over a developmental series. CONCLUSION: In order to quantify relative transcript abundances accurately using real-time RT-PCR, we recommend that combinations of several genes be used for normalization in grape berry development studies. Our data support GAPDH, actin, EF1-alpha and SAND as the most relevant reference genes for this purpose.

SUBMITTER: Reid KE

PROVIDER: S-EPMC1654153 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development.

Reid Karen E KE Olsson Niclas N Schlosser James J Peng Fred F Lund Steven T ST

BMC plant biology 20061114

<h4>Background</h4>Accuracy in quantitative real-time RT-PCR is dependent on high quality RNA, consistent cDNA synthesis, and validated stable reference genes for data normalization. Reference genes used for normalization impact the results generated from expression studies and, hence, should be evaluated prior to use across samples and treatments. Few statistically validated reference genes have been reported in grapevine. Moreover, success in isolating high quality RNA from grapevine tissues i ...[more]

PMID: 17105665

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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:BACKGROUND: Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR. RESULTS: The expression stability of 32 genes was assessed by qRT-PCR using a set of cDNAs from 24 different plant samples, which included different tissues, developmental stages and temperature stresses. The selected sequences included 12 well-known HKGs representing different functional classes and 20 genes novel with reference to the normalization issue. The expression stability of the 32 candidate genes was tested by the computer programs geNorm and NormFinder using five different data-sets. Some discrepancies were detected in the ranking of the candidate reference genes, but there was substantial agreement between the groups of genes with the most and least stable expression. Three new identified reference genes appear more effective than the well-known and frequently used HKGs to normalize gene expression in wheat. Finally, the expression study of a gene encoding a PDI-like protein showed that its correct evaluation relies on the adoption of suitable normalization genes and can be negatively affected by the use of traditional HKGs with unstable expression, such as actin and alpha-tubulin. CONCLUSION: The present research represents the first wide screening aimed to the identification of reference genes and of the corresponding primer pairs specifically designed for gene expression studies in wheat, in particular for qRT-PCR analyses. Several of the new identified reference genes outperformed the traditional HKGs in terms of expression stability under all the tested conditions. The new reference genes will enable more accurate normalization and quantification of gene expression in wheat and will be helpful for designing primer pairs targeting orthologous genes in other plant species.

Project description:For accurate and reliable gene expression analysis, normalization of gene expression data against reference genes is essential. In most studies on ticks where (semi-)quantitative RT-PCR is employed, normalization occurs with a single reference gene, usually beta-actin, without validation of its presumed expression stability. The first goal of this study was to evaluate the expression stability of commonly used reference genes in Rhipicephalus appendiculatus and Rhipicephalus (Boophilus) microplus ticks. To demonstrate the usefulness of these results, an unresolved issue in tick vaccine development was examined. Commercial vaccines against R. microplus were developed based on the recombinant antigen Bm86, but despite a high degree of sequence homology, these vaccines are not effective against R. appendiculatus. In fact, Bm86-based vaccines give better protection against some tick species with lower Bm86 sequence homology. One possible explanation is the variation in Bm86 expression levels between R. microplus and R. appendiculatus. The most stable reference genes were therefore used for normalization of the Bm86 expression profile in all life stages of both species to examine whether antigen abundance plays a role in Bm86 vaccine susceptibility.The transcription levels of nine potential reference genes: beta-actin (ACTB), beta-tubulin (BTUB), elongation factor 1alpha (ELF1A), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), glutathione S-transferase (GST), H3 histone family 3A (H3F3A), cyclophilin (PPIA), ribosomal protein L4 (RPL4) and TATA box binding protein (TBP) were measured in all life stages of R. microplus and R. appendiculatus. ELF1A was found to be the most stable expressed gene in both species following analysis by both geNorm and Normfinder software applications, GST showed the least stability. The expression profile of Bm86 in R. appendiculatus and R. microplus revealed a more continuous Bm86 antigen abundance in R. microplus throughout its one-host life cycle compared to the three-host tick R. appendiculatus where large variations were observed between different life stages.Based on these results, ELF1A can be proposed as an initial reference gene for normalization of quantitative RT-PCR data in whole R. microplus and R. appendiculatus ticks. The observed differences in Bm86 expression profile between the two species alone can not adequately explain the lack of a Bm86 vaccination effect in R. appendiculatus.

Project description:BACKGROUND: Grapevine leafroll-associated virus 3 (GLRaV-3) is the main contributing agent of leafroll disease worldwide. Four of the six GLRaV-3 variant groups known have been found in South Africa, but their individual contribution to leafroll disease is unknown. In order to study the pathogenesis of leafroll disease, a sensitive and accurate diagnostic assay is required that can detect different variant groups of GLRaV-3. METHODS: In this study, a one-step real-time RT-PCR, followed by high-resolution melting (HRM) curve analysis for the simultaneous detection and identification of GLRaV-3 variants of groups I, II, III and VI, was developed. A melting point confidence interval for each variant group was calculated to include at least 90% of all melting points observed. A multiplex RT-PCR protocol was developed to these four variant groups in order to assess the efficacy of the real-time RT-PCR HRM assay. RESULTS: A universal primer set for GLRaV-3 targeting the heat shock protein 70 homologue (Hsp70h) gene of GLRaV-3 was designed that is able to detect GLRaV-3 variant groups I, II, III and VI and differentiate between them with high-resolution melting curve analysis. The real-time RT-PCR HRM and the multiplex RT-PCR were optimized using 121 GLRaV-3 positive samples. Due to a considerable variation in melting profile observed within each GLRaV-3 group, a confidence interval of above 90% was calculated for each variant group, based on the range and distribution of melting points. The intervals of groups I and II could not be distinguished and a 95% joint confidence interval was calculated for simultaneous detection of group I and II variants. An additional primer pair targeting GLRaV-3 ORF1a was developed that can be used in a subsequent real-time RT-PCR HRM to differentiate between variants of groups I and II. Additionally, the multiplex RT-PCR successfully validated 94.64% of the infections detected with the real-time RT-PCR HRM. CONCLUSION: The real-time RT-PCR HRM provides a sensitive, automated and rapid tool to detect and differentiate different variant groups in order to study the epidemiology of leafroll disease.

Dataset Information

An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development.

Publications

An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RT-PCR during berry development.

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