Titre
Selecting control genes for RT-QPCR using public microarray data.
Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Popovici, V.
Auteure/Auteur
Goldstein, D.R.
Auteure/Auteur
Antonov, J.
Auteure/Auteur
Jaggi, R.
Auteure/Auteur
Delorenzi, M.
Auteure/Auteur
Wirapati, P.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
1471-2105
Statut éditorial
Publié
Date de publication
2009
Volume
10
Première page
42
Peer-reviewed
Oui
Langue
anglais
Résumé
Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones.
Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/
Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.
Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/
Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.
PID Serval
serval:BIB_2C446942B4A8
PMID
Open Access
Oui
Date de création
2012-02-23T11:07:47.468Z
Date de création dans IRIS
2025-05-20T19:41:28Z
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Nom
BIB_2C446942B4A8.P001.pdf
Version du manuscrit
preprint
Taille
806.58 KB
Format
Adobe PDF
PID Serval
serval:BIB_2C446942B4A8.P001
URN
urn:nbn:ch:serval-BIB_2C446942B4A89
Somme de contrôle
(MD5):a2c9f09452286ce5183f2f5f9bd0a1e1