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      Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

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          Abstract

          Using real-time reverse transcription PCR ten housekeeping genes from different abundance and functional classes in various human tissues were evaluated. The conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested.

          Abstract

          Background

          Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem.

          Results

          We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data.

          Conclusions

          The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.

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          Most cited references 20

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          Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

          A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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            Housekeeping genes as internal standards: use and limits.

             O Thellin,  W Zorzi,  B Lakaye (1999)
            Quantitative studies are commonly realised in the biomedical research to compare RNA expression in different experimental or clinical conditions. These quantifications are performed through their comparison to the expression of the housekeeping gene transcripts like glyceraldehyde-3-phosphate dehydrogenase (G3PDH), albumin, actins, tubulins, cyclophilin, hypoxantine phsophoribosyltransferase (HRPT), L32. 28S, and 18S rRNAs are also used as internal standards. In this paper, it is recalled that the commonly used internal standards can quantitatively vary in response to various factors. Possible variations are illustrated using three experimental examples. Preferred types of internal standards are then proposed for each of these samples and thereafter the general procedure concerning the choice of an internal standard and the way to manage its uses are discussed.
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              Systematic variation in gene expression patterns in human cancer cell lines.

              We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                2002
                18 June 2002
                : 3
                : 7
                : research0034.1-research0034.11
                Affiliations
                [1 ]Center for Medical Genetics, Ghent University Hospital 1K5, De Pintelaan 185, B-9000 Ghent, Belgium
                Corresondence: Frank Speleman. E-mail: franki.speleman@rug.ac.be
                Article
                gb-2002-3-7-research0034
                126239
                12184808
                Copyright © 2002 Vandesompele et al., licensee BioMed Central Ltd
                Categories
                Research

                Genetics

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