Why are using single gene normalizers not the best way to analyze gene expression data?
The traditional approach to measure gene expression changes from Real-Time PCR data has been to normalize the results of a gene of interest with respect to a housekeeping gene (aka. a reference or normalizer gene). The general assumption is that the level of expression of the normalizer gene does not change in the context of the experiment and can be used to normalize the variability in RNA quantity between individual samples. By normalizing to a housekeeping gene, in theory, a magnitude of change can be calculated between groups of samples for a gene of interest. However, this method of analysis is greatly complicated by the fact that housekeeping genes commonly used as normalizers (e.g., GAPDH, β-actin, and HPRT) can change expression levels when comparing tissues or cells in different states (Bustin 2000; Schmittgen et al. 2000; Goidin et al. 2001; Hamalainen et al. 2001). 18S rRNA is another normalizer that intuitively and experimentally appears to be more stable, but even 18S can
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