Dynamics of Gene Co-expression Networks in Time-Series Data: A Case Study in Drosophila melanogaster Embryogenesis - Lau, Li Yieng; Reverter, Antonio; Hudson, Nicholas J.; Naval-Sanchez, Marina; Fortes, Marina R. S.; Alexandre, Pâmela A. (Frontiers in Genetics, 2020)
Gene Regulatory Networks (GRN) tightly coordinate the spatiotemporal patterns of gene expression unfolding development. Due to the dynamic nature of developmental processes simply overlaying gene expression patterns onto static representations of GRN may be misleading. Here, we aim to formally quantitate topological changes of GRN during embryonic development using a publicly available Drosophila melanogaster transcriptome data set comprising 14 time points. We deployed a network approach which inferred 10 discrete co-expression networks by smoothly sliding along from early to late development using 5 consecutive time points per window. This allows changing network structure, including the presence of hubs, modules and other topological parameters to be quantitated. To explore the dynamic aspects of gene expression captured by our approach, we focused on regulator genes with apparent influence over particular aspects of development. Those key regulators were selected using a differential network algorithm to contrast the first 7 (early) with the last 7 (late) developmental time points. This assigns high scores to genes whose connectivity to abundant differentially expressed target genes has changed dramatically between states. We have produced a list of key regulators - some increasing (e.g. Tusp, slbo, Sidpn, DCAF12, chinmo) and some decreasing (Rfx, bap, Hmx, Awh, mld) connectivity during development - which reflects their role in different stages of embryogenesis. The networks we have constructed can be explored and interpreted within Cytoscape software and provide a new systems biology approach for the Drosophila research community to better visualize and interpret developmental regulation of gene expression.