While the cells of some mammals, such as humans, maintain their internal temperature within tightly controlled ranges, the cells of others, such as dromedary camels, experience wide ranges of temperature variation. In order to understand these differences, it is critical to identify differentially expressed genes (DEGs) and their interactions; however, the data available are often insufficient to obtain statistically significant results. We develop an explanatory model to understand the mechanisms of response of mammalian species to environmental perturbation on the basis of empirical gene expression data. Our approach is motivated by the novel idea that approximately preserved or reduced inter-individual variability of expression levels upon environmental change is an indicator that a given gene contributes to a homeostasis-preserving mechanism for the species. To identify such genes, we use a simple non-statistical criterion that is suitable even when the number of replicates is limited. We then identify four extreme subgroups of the DEGs, and from these construct an intuitive neural network architecture that best interpolates the data and describes the principal response rules of the considered species. Finally, we propose measures of the robustness of homeostasis (well-being) from these networks based on perturbation analysis and entropy computations. The data used to develop the model were collected from homogeneous cell cultures of skin fibroblasts. Even with data available for just a few individuals, our model identifies extreme response sets of genes, using inter-individual variability to provide a faithful representation of the response of the species to environmental perturbations. Sets of genes identified as relevant in individual species are useful for comparing responses across species. All the measures of cellular well-being introduced in this work rank camels higher than humans for both the 32° and 41° treatments.
González et al. (Fri,) studied this question.