Gene-family profiling: a normalization-free real-time RT-PCR approach with increased physiological resolution.

Here we present gene-family profiling, an approach for improved real-time RT-PCR analyses. It is based on recently published data, and we argue that it bring solutions to two major problems. First, it is normalization-free and therefore unbiased by variation in normalization agents such as reference gene expression. This strengthens data validity and also increases data resolution, reducing coefficients of variation by approximately 48% in our data sets. Second, it includes all members of a particular gene family, treating individual genes as constituting fractions of collective gene-family expression rather than as unrelated entities. Because different family members typically fulfill similar, but complementary roles, this increases the physiological relevance. Gene-family profiling is particularly useful for evaluation of cellular adaptations to physiological challenges and for comparison of properties between different experimental systems such as species, tissues or tissue regions. In addition, it seems suitable for analyses of inherent patterns of gene expression in singular biological samples. In our opinion, the approach is valuable for both research and diagnostic purposes, and should be readily applicable for many studies of gene expression. Its value is likely to increase as science continues to unravel gene function.