Integrating Genomic and Physiological Data to Unravel the Key Hub Nodes of Mammalian Regulatory Networks: The Case of Peroxisome Proliferator-Activated Receptor γ Co-Activator 1α
Within the signaling and regulatory pathways that control the physiological states of mammalian cells, there are a number of nodes that integrate different input signals and affect downstream targets. In this study, we focus on the peroxisome proliferator-activated receptor γ co-activator 1α (PGC1α).
The key challenge in this and other current systems is to elucidate the mechanism by which these key regulatory proteins affect and activate their downstream pathways. To address these fundamental questions, genomic readouts, such as transcriptomes (RNA seq) and chromatin-state (ChIP seq) under different perturbations will be combined with computational modeling to infer the regulatory interactions.
The functional significance of changes at thousands of genomic loci remains unclear: the key differences in gene expression that have physiological effects may only be a small subset of the total number of gene expression and chromatin state changes that are being observed.
To address this, we aim to include physiological data in order to separate perturbations which drive physiological responses from those which are non-functional side effects.
Keywords: Regulatory networks, mathematical modeling, PGC1α, gene expression, metabolismback