HRGRN: enabling graph search and integrative analysis of Arabidopsis signaling transduction, metabolism and gene regulation networks

The biological networks controlling plant signal transduction, metabolism and gene regulation are composed of not only genes, RNA, protein and compounds but also the complicated interactions among them. Yet, even in the most thoroughly studied model plant Arabidopsis thaliana, the knowledge regarding these interactions are scattered throughout literatures and various public databases. Thus, new scientific discovery by exploring these complex and heterogeneous data remains a challenge task for biologists.

We developed a graph-search empowered platform named HRGRN to search known and, more importantly, discover the novel relationships among genes in Arabidopsis biological networks. The HRGRN includes over 51,000 “nodes” that represent very large sets of genes, proteins, small RNAs, and compounds and approximately 150,000 “edges” that are classified into nine types of interactions (interactions between proteins, compounds and proteins, transcription factors (TFs) and their downstream target genes, small RNAs and their target genes, kinases and downstream target genes, transporters and substrates, substrate/product compounds and enzymes, as well as gene pairs with similar expression patterns to provide deep insight into gene-gene relationships) to comprehensively model and represent the complex interactions between nodes. .

The HRGRN allows users to discover novel interactions between genes and/or pathways, and build sub-networks from user-specified seed nodes by searching the comprehensive collections of interactions stored in its back-end graph databases using graph traversal algorithms. The HRGRN database is freely available at http://plantgrn.noble.org/hrgrn/. Currently, we are collaborating the Araport team to develop REST-like web services and provide the HRGRN’s graph search functions to Araport system.