Inferring regulatory change from gene expression: the confounding effects of tissue scaling

Comparative studies of gene expression are often designed with the aim of identifying regulatory changes associated with phenotypic variation. In recent years, large-scale transcriptome sequencing methods have increasingly been applied to nonmodel organisms to ask important ecological or evolutionary questions. Although experimental design varies, many of these studies have been based on RNA libraries obtained from heterogeneous tissue samples, for example homogenized whole bodies. Comparisons between groups of samples that vary in tissue composition can introduce sufficient variation in RNA abundance to produce patterns of differential expression that are mistakenly interpreted as evidence of regulatory differences. Here, we present a simple model that demonstrates this effect. The model describes the relationship between transcript abundance and tissue composition in a two-tissue system, and how this relationship varies under different scaling relationships. Using a range of biologically realistic variables, including real biological examples, to parameterize the model we highlight the potentially severe influence of tissue scaling on relative transcript abundance. We use these results to identify key aspects of experimental design and analysis that can help to limit the influence of tissue scaling on the inference of regulatory difference from comparative studies of gene expression.SHM is grateful for funding from an Early Career Research Fellowship from the Leverhulme Trust, and JEM acknowledges support from the European Research Council (grant agreements 260233 and 680951)