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PMID: 21418615 Published · epublish English Journal Article Research Support, Non-U.S. Gov't Validation Study

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization.

BMC genomics ·Vol. 12 ·2011-03-21 ·Pages 156

Hruz T, Wyss M, Docquier M, Pfaffl MW, Masanetz S, Borghi L, Verbrugghe P, Kalaydjieva L, Bleuler S, Laule O, Descombes P, Gruissem W, Zimmermann P

Abstract

RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts. Using the Genevestigator database of normalized and well-annotated microarray experiments, we describe the expression stability characteristics of the transciptomes of several organisms. The results show that a) no genes are universally stable, b) most commonly used reference genes yield very high transcript abundances as compared to the entire transcriptome, and c) for each biological context a subset of stable genes exists that has smaller variance than commonly used reference genes or genes that were selected for their stability across all conditions. We therefore propose the normalization of RT-qPCR data using reference genes that are specifically chosen for the conditions under study. RefGenes is a community tool developed for that purpose. Validation RT-qPCR experiments across several organisms showed that the candidates proposed by RefGenes generally outperformed commonly used reference genes. RefGenes is available within Genevestigator at http://www.genevestigator.com.

MeSH Terms
Algorithms Animals Arabidopsis/genetics Cattle Computational Biology/methods Databases, Genetic Female Gene Expression Profiling/methods,standards Humans Mice Oligonucleotide Array Sequence Analysis Reference Standards Reverse Transcriptase Polymerase Chain Reaction/methods,standards Software Swine User-Computer Interface
Authors & Affiliations
13 authors, click to expand affiliations / ORCID
Hruz Tomas
Department of Biology, ETH Zurich, 8092 Zurich, Switzerland.
Wyss Markus
Docquier Mylene
Pfaffl Michael W
Masanetz Sabine
Borghi Lorenzo
Verbrugghe Phebe
Kalaydjieva Luba
Bleuler Stefan
Laule Oliver
Descombes Patrick
Gruissem Wilhelm
Zimmermann Philip
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Article Info
Journal
BMC genomics
Abbr.
BMC Genomics
ISSN
1471-2164
Published
2011-03-21
Epub
2011-00-21
Pages
156
Language
English
Region
England
NLM ID
100965258
PMCID
PMC3072958
Subset
IM
Analysis Services
Analysis Services

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