Dataset Information

Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue.

ABSTRACT:

Background

Studies of gene expression in post mortem human brain can contribute to understanding of the pathophysiology of neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Quantitative real-time PCR (RT qPCR) is often used to analyse gene expression. The validity of results obtained using RT qPCR is reliant on accurate data normalization. Reference genes are generally used to normalize RT qPCR data. Given that expression of some commonly used reference genes is altered in certain conditions, this study aimed to establish which reference genes were stably expressed in post mortem brain tissue from individuals with AD, PD or DLB.

Results

The present study investigated the expression stability of 8 candidate reference genes, (ubiquitin C [UBC], tyrosine-3-monooxygenase [YWHAZ], RNA polymerase II polypeptide [RP II], hydroxymethylbilane synthase [HMBS], TATA box binding protein [TBP], beta-2-microglobulin [B2M], glyceraldehyde-3-phosphate dehydrogenase [GAPDH], and succinate dehydrogenase complex-subunit A, [SDHA]) in cerebellum and medial temporal gyrus of 6 AD, 6 PD, 6 DLB subjects, along with 5 matched controls using RT qPCR (TaqMan(R) Gene Expression Assays). Gene expression stability was analysed using geNorm to rank the candidate genes in order of decreasing stability in each disease group. The optimal number of genes recommended for accurate data normalization in each disease state was determined by pairwise variation analysis.

Conclusion

This study identified validated sets of mRNAs which would be appropriate for the normalization of RT qPCR data when studying gene expression in brain tissue of AD, PD, DLB and control subjects.

SUBMITTER: Coulson DT

PROVIDER: S-EPMC2396658 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Publications

Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue.

Coulson David T R DT Brockbank Simon S Quinn Joseph G JG Murphy Suzanne S Ravid Rivka R Irvine G Brent GB Johnston Janet A JA

BMC molecular biology 20080506

<h4>Background</h4>Studies of gene expression in post mortem human brain can contribute to understanding of the pathophysiology of neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Quantitative real-time PCR (RT qPCR) is often used to analyse gene expression. The validity of results obtained using RT qPCR is reliant on accurate data normalization. Reference genes are generally used to normalize RT qPCR data. Given that e ...[more]

PMID: 18460208

Similar Datasets

Project description:BackgroundA critical step in the RT-qPCR workflow for studying gene expression is data normalization, one of the strategies being the use of reference genes. This study aimed to identify and validate a selection of reference genes for relative quantification in Talaromyces versatilis, a relevant industrial filamentous fungus. Beyond T. versatilis, this study also aimed to propose reference genes that are applicable more widely for RT-qPCR data normalization in filamentous fungi.ResultsA selection of stable, potential reference genes was carried out in silico from RNA-seq based transcriptomic data obtained from T. versatilis. A dozen functionally unrelated candidate genes were analysed by RT-qPCR assays over more than 30 relevant culture conditions. By using geNorm, we showed that most of these candidate genes had stable transcript levels in most of the conditions, from growth environments to conidial germination. The overall robustness of these genes was explored further by showing that any combination of 3 of them led to minimal normalization bias. To extend the relevance of the study beyond T. versatilis, we challenged their stability together with sixteen other classically used genes such as β-tubulin or actin, in a representative sample of about 100 RNA-seq datasets. These datasets were obtained from 18 phylogenetically distant filamentous fungi exposed to prevalent experimental conditions. Although this wide analysis demonstrated that each of the chosen genes exhibited sporadic up- or down-regulation, their hierarchical clustering allowed the identification of a promising group of 6 genes, which presented weak expression changes and no tendency to up- or down-regulation over the whole set of conditions. This group included ubcB, sac7, fis1 and sarA genes, as well as TFC1 and UBC6 that were previously validated for their use in S. cerevisiae.ConclusionsWe propose a set of 6 genes that can be used as reference genes in RT-qPCR data normalization in any field of fungal biology. However, we recommend that the uniform transcription of these genes is tested by systematic experimental validation and to use the geometric averaging of at least 3 of the best ones. This will minimize the bias in normalization and will support trustworthy biological conclusions.

Dataset Information

Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue.

Background

Results

Conclusion

Publications

Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue.

Similar Datasets

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