Network Analysis of Transcriptome to Reveal Interactions Among Genes and Signaling Pathways

Abstract

Availability of large-scale gene-interaction network of model organisms presents a unique opportunity to identify novel genes and pathways that play an important role in complex biological functions. Still, it is not straightforward to identify significant genes and interactions from the complex highly connected network. We present a novel method for implicating biological processes in adaptation using a coarse-graining network analysis technique, network clustering and kinetic transcriptome profiling. Applying this method to a bacterial infection model of Caenorhabditis elegans and Pseudomonas aeruginosa to discern genes and processes related to immune response, we identified functionally coherent gene clusters and unraveled possible interactions of two signaling pathways, Hedgehog signaling pathway and glutamate signaling pathway, with other immune response pathways. This allowed us not only to identify novel genes involved in immune response, but also to implicate for the first time the two signaling pathways in the response to infection. Our approach can be applied to other adaptation processes, using large-scale dynamics data taken during the relevant environmental shift.