A Computational Atlas of Tissue-specific Regulatory Networks

Abstract

The pattern of how gene co-regulation varies across tissues determines human health. However, inferring tissue-specific regulatory networks and associating them with human phenotypes represent a substantial challenge because multi-tissue projects, including the GTEx, typically contain expression data measured only at one time point from highly heterogeneous donors. Here, we implement an interdisciplinary framework for assembling and programming genomic data from multiple tissues into fully informative gene networks, encapsulated by a complete set of bi-directional, signed, and weighted interactions, from static expression data. This framework can monitor how gene networks change simultaneously across tissues and individuals, infer gene-driven inter-tissue wiring networks, compare and test topological alterations of gene/tissue networks between health states, and predict how regulatory networks evolve across spatiotemporal gradients. Our framework provides a tool to catalogue a comprehensive encyclopedia of mechanistic gene networks that walk medical researchers through tissues in each individual and through individuals for each tissue, facilitating the translation of multi-tissue data into clinical practices.