Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes
Open accessAbstract
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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Relative gene expression levels were calculated by normalization to the day 0 gene expression level and the geometric average of the three reference genes as described in Vandesompele et al. (2002).
“Relative gene expression levels were calculated by normalization to the day 0 gene expression level and the geometric average of the three reference genes as described in Vandesompele et al. (2002[42]).”
From Optimization of extracellular matrix for primary human hepatocyte cultures using mixed collagen-matrigel matrices (2023) · cites this paper as Vandesompele et al. (2002[42])
The Results section on normalization-factor calculation (page unavailable) recommends the geometric mean of at least three stable internal control genes, supporting that part of the method. The passages do not describe normalization to a day 0 gene-expression level, so the citation does not establish that the full procedure was described in this paper. (LLM, conf=0.83)
Experimental — accuracy not yet measuredNormalization factor calculation based on the geometric mean of multiple control genes was performed for selection of endogenous control genes.
“Normalization factor calculation based on the geometric mean of multiple control genes was performed for selection of the endogenous control genes (Vandesompele et al., 2002).”
From Human ApoE Isoforms Differentially Modulate Brain Glucose and Ketone Body Metabolism: Implications for Alzheimer's Disease Risk Reduction and Early Intervention (2018) · cites this paper as Vandesompele et al., 2002
The Results section on normalization-factor calculation recommends using the geometric mean of the most stable control genes and assessing whether additional genes improve the factor. But the Results section on gene-stability ranking says control genes are selected by their expression-stability measure M; the geometric-mean factor is calculated from selected genes, rather than being the primary method for selecting them. Our copy provides section labels but no page numbers. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe geometric mean of RPL13A, RPL4 and GAPDH was used as reference genes, following GeNorm and Normfinder algorithm.
“The geometric mean of RPL13A, RPL4 and GAPDH was taken as reference genes, following GeNorm and Normfinder algorithm [18, 19].”
From Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients (2022) · cites this paper as [18]
Target mRNA expression data were normalized to the geometric mean of Hprt and Tbp expression.
“Data were normalized to the geometric mean (Vandesompele et al., 2002) of Hprt and Tbp expression.”
From Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib (2017) · cites this paper as Vandesompele et al., 2002
Reference genes YWHAZ and HPRT were selected according to geNorm calculations.
“YWHAZ and HPRT were selected as reference genes, according to geNorm calculations54.”
From A SWI/SNF-related autism syndrome caused by de novo mutations in ADNP (2014) · cites this paper as [54]
mRNA expression levels were normalized by the geometric mean of GAPDH and HPRT.
“The mRNA expression levels for each gene of interest were normalized by the geometric mean of two housekeeping genes, GAPDH and HPRT (Vandesompele et al., 2002), and relative expression was calculated with qbasePLUS software via the Ct method (Hellemans et al., 2007).”
From The duration of nicotine withdrawal-associated deficits in contextual fear conditioning parallels changes in hippocampal high affinity nicotinic acetylcholine receptor upregulation (2012) · cites this paper as Vandesompele et al., 2002
Normalisation of qPCR data was carried out according to Vandesompele et al. using the three most stable reference genes (Actb, Atp5b, Canx) out of seven potential reference genes tested.
“Normalisation of qPCR data was carried out according to Vandesompele et al. [43] using the three most stable (Actb, Atp5b, Canx) out of seven potential reference genes tested.”
From Effect of Ecdysterone on the Hepatic Transcriptome and Lipid Metabolism in Lean and Obese Zucker Rats (2021) · cites this paper as [43]
The three most stable reference genes (Actb, Canx and Mdh1) were used to calculate GeNorm normalization factors.
“The three most stable reference genes used to calculate GeNorm normalization factors according to [28] were: Actb, Canx and Mdh1.”
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References 25 · Cited by 20,038
- Authors
- Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., & Speleman, F.
- Affiliations
- Ghent University Hospital (BE)
- Corresponding author
- Speleman, Frank
- Venue
- Genome Biology
- Published
- 2002-06-18
- Volume
- 3
- Issue
- 7
- Pages
- RESEARCH0034-RESEARCH0034
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC126239
- OpenAlex
- W1577577364
- Cited by
- 20,038
- References
- 25
- Citations by year
- 2026: 545 · 2025: 726 · 2024: 808 · 2023: 881 · 2022: 970 · 2021: 1118 · 2020: 1236 · 2019: 1132 · 2018: 1118 · 2017: 1114 · 2016: 1247 · 2015: 1221 · 2014: 1246 · 2013: 1222 · 2012: 1124
- FWCI
- 45.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Genome biology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion, other-oa)
- Funders
- Fonds Wetenschappelijk Onderzoek
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- real-time RT-PCR, normalization, housekeeping genes, internal control genes, geometric mean, gene expression stability, normalization factor, human tissue, microarray validation, gene expression profiling
- MeSH terms
- Algorithms, Female, Humans, Reference Standards, RNA, Time Factors, Tumor Cells, Cultured, Reproducibility of Results, DNA, Complementary, Reverse Transcriptase Polymerase Chain Reaction, Gene Expression Profiling
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