Automated generation of context-specific gene regulatory networks with a weighted approach in Drosophila melanogaster

Abstract

The regulation of gene expression is a key factor in the development and maintenance of life in all organisms. Even so, little is known at whole genome scale for most genes and contexts.We propose a method, Tool forWeighted Epigenomic Networks in Drosophila melanogaster (Fly T-WEoN), to generate contextspecific gene regulatory networks starting from a reference network that contains all known gene regulations in the fly. Unlikely regulations are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, includingDNAmethylation, chromatin accessibility, histone modifications and gene expression. Fly T-WEoNis based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from the literature. Experimental data files can be generated with several standard procedures and used solely when and if available. Fly T-WEoN is available as a Cytoscape application that permits integration with other tools and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster.