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Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR.

ABSTRACT: BACKGROUND: Considering the broad variation in the expression of housekeeping genes among tissues and experimental situations, studies using quantitative RT-PCR require strict definition of adequate endogenous controls. For glioblastoma, the most common type of tumor in the central nervous system, there was no previous report regarding this issue. RESULTS: Here we show that amongst seven frequently used housekeeping genes TBP and HPRT1 are adequate references for glioblastoma gene expression analysis. Evaluation of the expression levels of 12 target genes utilizing different endogenous controls revealed that the normalization method applied might introduce errors in the estimation of relative quantities. Genes presenting expression levels which do not significantly differ between tumor and normal tissues can be considered either increased or decreased if unsuitable reference genes are applied. Most importantly, genes showing significant differences in expression levels between tumor and normal tissues can be missed. We also demonstrated that the Holliday Junction Recognizing Protein, a novel DNA repair protein over expressed in lung cancer, is extremely over-expressed in glioblastoma, with a median change of about 134 fold. CONCLUSION: Altogether, our data show the relevance of previous validation of candidate control genes for each experimental model and indicate TBP plus HPRT1 as suitable references for studies on glioblastoma gene expression.

SUBMITTER: Valente V

PROVIDER: S-EPMC2661085 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR.

Valente Valeria V Teixeira Silvia A SA Neder Luciano L Okamoto Oswaldo K OK Oba-Shinjo Sueli M SM Marie Suely K N SK Scrideli Carlos A CA Paçó-Larson Maria L ML Carlotti Carlos G CG

BMC molecular biology 20090303

<h4>Background</h4>Considering the broad variation in the expression of housekeeping genes among tissues and experimental situations, studies using quantitative RT-PCR require strict definition of adequate endogenous controls. For glioblastoma, the most common type of tumor in the central nervous system, there was no previous report regarding this issue.<h4>Results</h4>Here we show that amongst seven frequently used housekeeping genes TBP and HPRT1 are adequate references for glioblastoma gene e ...[more]

PMID: 19257903

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Project description:Selection of reference genes has become an integral step in any real time quantitative PCR (RT-qPCR) based expression studies. The importance of this study stems from the fact that riverine buffaloes are major dairy species of Indian sub-continent and the information generated here will be of great interest to the investigators engaged in functional genomic studies of this important livestock species. In this study, an effort was made to evaluate a panel of 10 candidate reference genes (glyceraldehyde 3-phosphate dehydrogenase (GAPDH), beta- actin (ACTB), ubiquitously expressed transcript (UXT), ribosomal protein S15 (RPS15), ribosomal protein L-4 (RPL4), ribosomal protein S9 (RPS9), ribosomal protein S23 (RPS23), hydroxymethylbilane synthase (HMBS), ?2 Microglobulin (?2M) and eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) across 12 tissues (mammary gland, kidney, spleen, liver, heart, intestine, ovary, lung, muscle, brain, subcutaneous fat and testis) of riverine buffaloes. In addition to overall analysis, tissue wise evaluation of expression stability of individual RG was also performed. Three different algorithms provided in geNorm, NormFinder and BestKeeper softwares were used to evaluate the stability of 10 potential reference genes from different functional classes. The M-value given by geNorm ranged from 0.9797 (RPS9 and UXT) to 1.7362 (RPS15). From the most stable to the least stable, genes were ranked as: UXT/RPS9> RPL4> RPS23> EEF1A1> ACTB> HMBS> GAPDH> B2M> RPS15. While NormFinder analysis ranked the genes as: UXT> RPS23> RPL4> RPS9> EEF1A1> HMBS> ACTB> ?2M> GAPDH> RPS15. Based on the crossing point SD value and range of fold change expression, BestKeeper analysis ranked the genes as: RPS9> RPS23/UXT> RPL4> GAPDH> EEF1A1> ACTB> HMBS> ?2M> RPS15. Overall the study has identified RPS23, RPS9, RPL4 and UXT genes to be the most stable and appropriate RGs that could be utilized for normalization of transcriptional data in various tissues of buffaloes. This manuscript thus provide useful information on panel of reference genes that could be helpful for researchers conducting functional genomic studies in riverine buffaloes.

Project description:BackgroundQuantitative real-time reverse-transcription polymerase chain reaction is frequently used as research tool in experimental oncology. There are some studies of valid endogenous control genes in the field of human glioma research, which, however, only focus on the comparison between normal brain with tumor tissue and malignant transformation toward secondary glioblastomas. Aim of this study was to validate a more general reference gene also suitable for pre- and posttreatment analysis and other evaluations (eg, primary vs secondary glioblastoma).MethodsThis quantitative polymerase chain reaction analysis was performed to test a panel of the 6 most suitable reference genes from other studies representing different physiological pathways (ACTB, GAPDH, POLR2A, RPL13A, SDHA, and TBP) in all common glioma groups, namely: diffuse astrocytoma World Health Organization II, anaplastic astrocytoma World Health Organization III, secondary glioblastoma World Health Organization IV with and without chemotherapy, primary glioblastoma, recurrent glioblastoma, and gliomas before and after radiation. Expression stability was tested during the longitudinal course of the disease in 8 single patients.ResultsEvaluation of the expression levels of the 6 target genes showed that ACTB, GAPDH, and RPL13A show higher expression compared to SDHA, POLR2A, and TBP. ACTB, GAPDH, and RPL13A showed different expression levels between astrozytoma grade II and primary glioblastoma. Except for this difference, the candidate genes were not differentially expressed between primary and secondary glioblastomas and between the World Health Organization tumor grades. Furthermore, they remained stable before and after radiotherapy and/or chemotherapy. Therefore, they are adequate references for glioblastoma gene expression studies. The comparison of all tested genes resulted in SDHA and ACTB as most stable reference genes determined by the NormFinder software. Our data revealed lowest intragroup variation in the SDHA, highest in the RPL13A gene.ConclusionsAll tested genes may be recommended as universal reference genes for data normalization in gene expression studies under different treatment regimens both in primary glioblastomas and astrocytomas of different grades (World Health Organization grades II-IV), respectively. In summary, ACTB and SDHA exhibited the best stability values and showed the lowest intergroup expression variability.

Project description:BackgroundThe veined rapa whelk Rapana venosa is an important commercial shellfish in China and quantitative real-time PCR (qRT-PCR) has become the standard method to study gene expression in R. venosa. For accurate and reliable gene expression results, qRT-PCR assays require housekeeping genes as internal controls, which display highly uniform expression in different tissues or stages of development. However, to date no studies have validated housekeeping genes in R. venosa for use as internal controls for qRT-PCR.MethodsIn this study, we selected the following 13 candidate genes for suitability as internal controls: elongation factor-1α (EF-1α), α-actin (ACT), cytochrome c oxidase subunit 1 (COX1), nicotinamide adenine dinucleotide dehydrogenase (ubiquinone) 1α subcomplex subunit 7 (NDUFA7), 60S ribosomal protein L5 (RL5), 60S ribosomal protein L28 (RL28), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-tubulin (TUBB), 40S ribosomal protein S25 (RS25), 40S ribosomal protein S8 (RS8), ubiquitin-conjugating enzyme E2 (UBE2), histone H3 (HH3), and peptidyl-prolyl cis-trans isomerase A (PPIA). We measured the expression levels of these 13 candidate internal controls in eight different tissues and twelve larvae developmental stages by qRT-PCR. Further analysis of the expression stability of the tested genes was performed using GeNorm and RefFinder algorithms.ResultsOf the 13 candidate genes tested, we found that EF-1α was the most stable internal control gene in almost all adult tissue samples investigated with RL5 and RL28 as secondary choices. For the normalization of a single specific tissue, we suggested that EF-1α and NDUFA7 are the best combination in gonad, as well as COX1 and RL28 for intestine, EF-1α and RL5 for kidney, EF-1α and COX1 for gill, EF-1α and RL28 for Leiblein and mantle, EF-1α, RL5, and NDUFA7 for liver, GAPDH, PPIA, and RL28 for hemocyte. From a developmental perspective, we found that RL28 was the most stable gene in all developmental stages measured, and COX1 and RL5 were appropriate secondary choices. For the specific developmental stage, we recommended the following combination for normalization, PPIA, RS25, and RL28 for stage 1, RL5 and RL28 for stage 2 and 5, RL28 and NDUFA7 for stage 3, and PPIA and TUBB for stage 4.DiscussionOur results are instrumental for the selection of appropriately validated housekeeping genes for use as internal controls for gene expression studies in adult tissues or larval development of R. venosa in the future.

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.

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Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR.

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Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR.

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