Common practice in molecular biology may introduce statistical bias and misleading biological interpretation

Abstract

In studies on enzyme activity or gene expression at the protein level, data are usually analyzed by using a standard curve after subtracting blank values. In most cases and for most techniques (spectrophotometric assays, ELISA), this approach satisfies the basic principles of linearity and specificity. In our experience, this might be also the case for Western-blot analysis. By contrast, mRNA data are usually presented as arbitrary units of the ratio of a target RNA over levels of a control RNA species. We here demonstrate by simple experiments and various examples that this data-normalization procedure may result in misleading conclusions. Common molecular biology techniques have never been carefully tested according to the basic principles of validation of quantitative techniques. We thus prefer a regression-based approach for quantifying mRNA levels relatively to a control RNA species by Northern-blot, semi-quantitative RT-PCR or similar techniques. This type of techniques is also characterized by a lower reproducibility for repeated assays when compared to biochemical analyses. Therefore, we also recommend to design experiments, which allow the detection of a similar range of variance by biochemical and molecular biology techniques. Otherwise, spurious conclusions may be provided regarding the control level of gene expression.