REVIEW Real-time RT-PCR normalisation strategies and considerations J Huggett1,2, K Dheda1,2,3, S Bustin4 and A Zumla1,2 1Centre for Infectious Diseases and International Health, University College London, London, UK 2Royal Free Medical School, London, UK 3Department of Thoracic and HIV Medicine, Royal Free Hospital, London, UK 4Centre for Academic Surgery, Barts and the London, Queen Mary���s School of Medicine and Dentistry, London, UK Real-time RT-PCR has become a common technique, no longer limited to specialist core facilities. It is in many cases the only method for measuring mRNA levels of vivo low copy number targets of interest for which alternative assays either do not exist or lack the required sensitivity. Benefits of this procedure over conventional methods for measuring RNA include its sensitivity, large dynamic range, the potential for high throughout as well as accurate quantification. To achieve this, however, appropriate normalisation strategies are required to control for experimental error introduced during the multistage process required to extract and process the RNA. There are many strategies that can be chosen these include normalisation to sample size, total RNA and the popular practice of measuring an internal reference or housekeeping gene. However, these methods are frequently applied without appropriate validation. In this review we discuss the relative merits of different normalisation strategies and suggest a method of validation that will enable the measurement of biologically meaningful results. Genes and Immunity (2005) 6, 279���284. doi:10.1038/sj.gene.6364190 Published online 7 April 2005 Keywords: qPCR real-time RT-PCR housekeeping genes normalisation reference gene Introduction Real-time reverse transcription PCR (real-time RT-PCR) is an established technique for quantifying mRNA in biological samples. Benefits of this procedure over conventional methods for measuring RNA include its sensitivity, large dynamic range, and the potential for high throughout as well as accurate quantification. Its enhanced specificity is particularly useful for immuno- logical research, which frequently involves analysis of proteins derived from different splice variants of the original transcript.1 Furthermore, many of the key proteins (eg cytokines and transcription factors) are found in such low abundance that real-time RT-PCR quantification of their mRNAs represents the only technique sensitive enough to measure reliably their expression in vivo.2,3 Although real-time RT-PCR is widely used to quanti- tate biologically relevant changes in mRNA levels, there remain a number of problems associated with its use. These include the inherent variability of RNA, variability of extraction protocols that may copurify inhibitors, and different reverse transcription and PCR efficiencies.4 Consequently, it is important that an accurate method of normalisation is chosen to control for this error. Unfortunately, normalisation remains one of real-time RT-PCRs most difficult problems.5 Several strategies have been proposed for normalising real-time RT-PCR data. These range from ensuring that a similar sample size is chosen to using an internal housekeeping or reference gene (Table 1). These ap- proaches are not mutually exclusive and can be incorporated into a protocol at many stages (Figure 1). Here we discuss the respective advantages and dis- advantages of each technique. Normalisation sample size Ensuring a similar sample size is obtained, by sampling similar tissue volume or weight, is the first stage of reducing experimental error. This may appear to be straightforward, but experimental sample groups of similar size are often not representative. It can be difficult to ensure that different samples contain the same cellular material. A good example is blood, which is relatively easy to sample and ensure similar volumes are compared. However, this can be misleading, as is illustrated when sampling a similar volume of blood from HIV �� ve patients (Figure 2). Patients with HIV that have less advanced immunosupression (CD4 counts X200 cells/ml) will yield a higher amount RNA than patients with CD4 counts p200 cells/ml. This is simply because there are fewer cells per millilitre of blood in the Received 1 November 2004 revised 20 December 2004 accepted 21 December 2004 published online 7 April 2005 Correspondence: Dr J Huggett, Centre for Infectious Diseases and International Health, University College London, Windeyer Institute of Medical Research, 46 Cleveland St, London W1T 4JF, UK. E-mail: j.huggett@ucl.ac.uk Genes and Immunity (2005) 6, 279���284 & 2005 Nature Publishing Group All rights reserved 1466-4879/05 $30.00 www.nature.com/gene

latter group. It would be misleading to directly compare these groups based on sample volume alone. When dealing with in vitro cell culture, it can also be difficult to estimate sample size (cell number) because cells will often clump up or have different morphologies, particularly when cultured as a monolayer. Cells can be treated chemically or enzymatically to assist counting however, this will undoubtedly effect gene expression and is likely to confuse the experimental findings. While ensuring a similar sample size is important it clearly is not sufficient on its own. Normalisation RNA quantification It is essential to quantitate accurately and quality assess RNA prior to reverse transcription.4,6 If the two HIV groups, discussed in Figure 2, are to be assessed then input RNA for the reverse transcription reaction should be similar. There are several methods for quantifying RNA, arguably the most accurate being ribogreen (molecular probes) and the LabChip (Agilent 2100). Frequently overlooked is the concomitant need for interpreting the quality of the RNA (Figure 3). If RNA quality is not good then the measurement can be effected (Figure 4 and Bustin and Nolan4). Normal- ising a sample against total RNA has the drawback of not controlling for variation inherent in the reverse tran- scription7 or PCR reactions. Normalising to total RNA also primarily measures ribosomal RNA (rRNA), which Table 1 Comparison of the actual amount of RNA used in different reverse transcription reactions with the respective amount of HuPO cDNA measured by real time RT-PCR Normalisation strategy Pros Cons Note Similar sample size/tissue volume Relatively easy Sample size/tissue volume may be difficult to estimate and/or may not be biological representative Simple first step to reduce experimental error Total RNA Ensures similar reverse transcriptase input. May provide information on the integrity (depending on technique used) Does not control for error introduced at the reverse transcription or PCR stages. Assumes no variation in rRNA/ mRNA ratio Requires a good method of assessing quality and quantity Genomic DNA Give an idea of the cellular sample size. May vary in copy number per cell. Difficult to extract with RNA Rarely used. Can be measured optically or by real time PCR Reference genes ribosomal RNAs (rRNA) Internal control that is subject to the same conditions as the RNA of interest. Also measured by real time RT-PCR Must be validated using the same experimental samples. Resolution of assay is defined by the error of the reference gene Oligo dt priming of RNA for reverse transcription will not work well with rRNA as no polyA tail is present. Usually in high abundance Reference genes messenger RNAs (mRNA) Internal control that is subject to the same conditions as the mRNA of interest. Also measured by real time RT-PCR Must be validated using the same experimental samples. Resolution of assay is defined by the error of the reference gene Most, but not all, of mRNAs contain polyA tails and can be primed with oligo dt for reverse transcription Alien molecules Internal control that is subject to most of the conditions as the mRNA of interest. Is without the biological variability of a reference gene Must be identified and cloned or synthesised. Unlike the RNA of interest, is not extracted from the within the cells Requires more characterisation and to be made available commercially There is good correlation between the RNA concentration used and the real time PCR estimation of the different amounts of HuPO cDNA (using omniscript reverse transcriptase). Sample RNA cDNA Result Extract RNA Ensure similar sample size Generate cDNA Ensure similar RNA concentration Measure cDNA by Real time PCR Measure internal reference Figure 1 Processes required to generate a real time RT-PCR result. Black arrows indicate points, which should be considered for a good normalisation strategy. Total RNA extracted 200 200 0 50 100 150 p = 0.035 CD4 count (cells/ml) RNA yield ng / �� l Figure 2 Total RNA yields from two different groups of HIV patients. Total RNA extracted using PAXtubes (Qiagen) as for Dheda et al.5 Real-time RT-PCR normalisation J Huggett et al 280 Genes and Immunity