Abstract
Quantitative real-time reverse-transcription polymerase chain reaction (RT-qPCR) remains the most sensitive technique for nucleic acid quantification. Its popularity is reflected in the remarkable number of publications reporting RT-qPCR data. Careful normalisation within RT-qPCR studies is imperative to ensure accurate quantification of mRNA levels. This is commonly achieved through the use of reference genes as an internal control to normalise the mRNA levels between different samples. The selection of appropriate reference genes can be a challenge as transcript levels vary with physiology, pathology and development, making the information within the transcriptome flexible and variable. In this study, we examined the variation in expression of a panel of nine candidate reference genes in HCT116 and HT29 2-dimensional and 3-dimensional cultures, as well as in normal and cancerous colon tissue. Using normfinder we identified the top three most stable genes for all conditions. Further to this we compared the change in expression of a selection of PKC coding genes when the data was normalised to one reference gene and three reference genes. Here we demonstrated that there is a variation in the fold changes obtained dependent on the number of reference genes used. As well as this, we highlight important considerations namely; assay efficiency tests, inhibition tests and RNA assessment which should also be implemented into all RT-qPCR studies. All this data combined demonstrates the need for careful experimental design in RT-qPCR studies to help eliminate false interpretation and reporting of results.
Highlights
Gene expression analysis is a critical and important tool in molecular diagnostics and medicine[1,2,3,4]
One of the major difficulties is the selection of appropriate reference genes for the normalisation of data
The purpose of this study was to evaluate the stability in expression of nine candidate reference genes in two colon cancer cell lines as well as in normal and cancerous tissue from colon cancer patients
Summary
Gene expression analysis is a critical and important tool in molecular diagnostics and medicine[1,2,3,4]. The most popular and widely used method for gene expression is fluorescence based quantitative real time PCR (RT-qPCR)[9]. It is the most sensitive and flexible of the quantitative methods with a capacity to detect and measure minute amounts of nucleic acids[10,11]. There are two types of quantitative methods that can be applied within RT-qPCR; absolute quantification and relative quantification. Absolute quantification relates the PCR signal to a standard curve to determine the input copy number of the gene of interest. Relative quantification evaluates the change in expression of a target gene relative to a reference group, for example an untreated control[12]
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