Literature DB >> 17394773

Identification of novel universal housekeeping genes by statistical analysis of microarray data.

Seram Lee1, Minjoung Jo, Jungeun Lee, Sang Seok Koh, Soyoun Kim.   

Abstract

Housekeeping genes are widely used as internal controls in a variety of study types, including real time RT-PCR, microarrays, Northern analysis and RNase protection assays. However, even commonly used housekeeping genes may vary in stability depending on the cell type or disease being studied. Thus, it is necessary to identify additional housekeeping-type genes that show sample-independent stability. Here, we used statistical analysis to examine a large human microarray database, seeking genes that were stably expressed in various tissues, disease states and cell lines. We further selected genes that were expressed at different levels, because reference and target genes should be present in similar copy numbers to achieve reliable quantitative results. Real time RT-PCR amplification of three newly identified reference genes, CGI-119, CTBP1 and GOLGAl, alongside three well-known housekeeping genes, B2M, GAPD, and TUBB, confirmed that the newly identified genes were more stably expressed in individual samples with similar ranges. These results collectively suggest that statistical analysis of microarray data can be used to identify new candidate housekeeping genes showing consistent expression across tissues and diseases. Our analysis identified three novel candidate housekeeping genes (CGI-119, GOLGA1, and CTBP1) that could prove useful for normalization across a variety of RNA-based techniques.

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Year:  2007        PMID: 17394773     DOI: 10.5483/bmbrep.2007.40.2.226

Source DB:  PubMed          Journal:  J Biochem Mol Biol        ISSN: 1225-8687


  41 in total

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2.  Dynamism in gene expression across multiple studies.

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Review 3.  Consensus reference gene(s) for gene expression studies in human cancers: end of the tunnel visible?

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4.  Analysis of variance components reveals the contribution of sample processing to transcript variation.

Authors:  Douwe van der Veen; José Miguel Oliveira; Willy A M van den Berg; Leo H de Graaff
Journal:  Appl Environ Microbiol       Date:  2009-02-20       Impact factor: 4.792

5.  Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes.

Authors:  Armin P Piehler; Runa M Grimholt; Reidun Ovstebø; Jens P Berg
Journal:  BMC Immunol       Date:  2010-05-04       Impact factor: 3.615

6.  Normalization with genes encoding ribosomal proteins but not GAPDH provides an accurate quantification of gene expressions in neuronal differentiation of PC12 cells.

Authors:  Lihan Zhou; Qing-En Lim; Guoqiang Wan; Heng-Phon Too
Journal:  BMC Genomics       Date:  2010-01-29       Impact factor: 3.969

7.  The transcriptome of retinal Müller glial cells.

Authors:  Karin Roesch; Ashutosh P Jadhav; Jeffrey M Trimarchi; Michael B Stadler; Botond Roska; Ben B Sun; Constance L Cepko
Journal:  J Comp Neurol       Date:  2008-07-10       Impact factor: 3.215

8.  Identification of novel reference genes using multiplatform expression data and their validation for quantitative gene expression analysis.

Authors:  Mi Jeong Kwon; Ensel Oh; Seungmook Lee; Mi Ra Roh; Si Eun Kim; Yangsoon Lee; Yoon-La Choi; Yong-Ho In; Taesung Park; Sang Seok Koh; Young Kee Shin
Journal:  PLoS One       Date:  2009-07-07       Impact factor: 3.240

9.  Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae.

Authors:  Marie-Ange Teste; Manon Duquenne; Jean M François; Jean-Luc Parrou
Journal:  BMC Mol Biol       Date:  2009-10-30       Impact factor: 2.946

10.  A comprehensive functional analysis of tissue specificity of human gene expression.

Authors:  Zoltán Dezso; Yuri Nikolsky; Evgeny Sviridov; Weiwei Shi; Tatiana Serebriyskaya; Damir Dosymbekov; Andrej Bugrim; Eugene Rakhmatulin; Richard J Brennan; Alexey Guryanov; Kelly Li; Julie Blake; Raymond R Samaha; Tatiana Nikolskaya
Journal:  BMC Biol       Date:  2008-11-12       Impact factor: 7.431

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