Normalization of real-time quantitative reverse transcription-PCR data: A model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets

被引:5759
作者
Andersen, CL
Jensen, JL
Orntoft, TF [1 ]
机构
[1] Aarhus Univ Hosp, Mol Diagnost Lab, Dept Clin Biochem, DK-8200 Aarhus N, Denmark
[2] Aarhus Univ, Dept Theoret Stat, Aarhus C, Denmark
[3] Aarhus Univ, Dept Math Sci, Aarhus C, Denmark
关键词
D O I
10.1158/0008-5472.CAN-04-0496
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.
引用
收藏
页码:5245 / 5250
页数:6
相关论文
共 14 条
[1]   A comparison of normalization methods for high density oligonucleotide array data based on variance and bias [J].
Bolstad, BM ;
Irizarry, RA ;
Åstrand, M ;
Speed, TP .
BIOINFORMATICS, 2003, 19 (02) :185-193
[2]   Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays [J].
Bustin, SA .
JOURNAL OF MOLECULAR ENDOCRINOLOGY, 2000, 25 (02) :169-193
[3]   Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems [J].
Bustin, SA .
JOURNAL OF MOLECULAR ENDOCRINOLOGY, 2002, 29 (01) :23-39
[4]   Identifying distinct classes of bladder carcinoma using microarrays [J].
Dyrskjot, L ;
Thykjaer, T ;
Kruhoffer, M ;
Jensen, JL ;
Marcussen, N ;
Hamilton-Dutoit, S ;
Wolf, H ;
Orntoft, TF .
NATURE GENETICS, 2003, 33 (01) :90-96
[5]   Classification of Dukes' B and C colorectal cancers using expression arrays [J].
Frederiksen, CM ;
Knudsen, S ;
Laurberg, S ;
Orntoft, TF .
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2003, 129 (05) :263-271
[6]   Summaries of affymetrix GeneChip probe level data [J].
Irizarry, RA ;
Bolstad, BM ;
Collin, F ;
Cope, LM ;
Hobbs, B ;
Speed, TP .
NUCLEIC ACIDS RESEARCH, 2003, 31 (04) :e15
[7]  
Kent WJ, 2002, GENOME RES, V12, P656, DOI [10.1101/gr.229202, 10.1101/gr.229202. Article published online before March 2002]
[8]   Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method [J].
Livak, KJ ;
Schmittgen, TD .
METHODS, 2001, 25 (04) :402-408
[9]   Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR [J].
Schmittgen, TD ;
Zakrajsek, BA .
JOURNAL OF BIOCHEMICAL AND BIOPHYSICAL METHODS, 2000, 46 (1-2) :69-81
[10]   Control selection for RNA quantitation [J].
Suzuki, T ;
Higgins, PJ ;
Crawford, DR .
BIOTECHNIQUES, 2000, 29 (02) :332-+