Abstract
The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.
Highlights
The use of real-time quantitative PCR (RT-qPCR, hereafter abbreviated to qPCR) to quantify mRNA transcription has revolutionised our understanding of cellular responses triggered by the developmental progression or experimental manipulation of individuals [1]
We investigated the influence of the number of GOIs investigated on the amount of effort expended in testing and using reference genes via GLMs with the following three response variables and associated error distributions: 1) whether or not RG stability was tested; 2) the number of RGs used to normalise data (Poisson error); and 3) the number of RGs included in the panel amongst the subset of studies that tested RG stability (Poisson error)
We aimed to investigate the current state of research practice with respect to data normalisation in qPCR studies of gene expression
Summary
The use of real-time quantitative PCR (RT-qPCR, hereafter abbreviated to qPCR) to quantify mRNA transcription has revolutionised our understanding of cellular responses triggered by the developmental progression or experimental manipulation of individuals [1]. While several methods of data normalisation are available (reviewed in [4,5,6]), the most commonly employed is the use of stably expressed reference genes (RGs) as endogenous (i.e. internal) controls. This method is essential when results are expressed in terms of relative quantification (fold-change) using the popular 2-ΔΔCT method [7] or modified versions thereof An essential step in development of qPCR assays is identification of appropriate RGs for normalisation of the data. As correct normalisation is such an integral component of gene expression analysis, it has been strongly advocated that at least two RGs be employed and the geometric mean of RG expression levels be used for normalisation (e.g. [2, 4, 11])
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