Arabidopsis-Based Dual-Layered Biological Network Analysis Elucidates Fully Modulated Pathways Related to Sugarcane Resistance on Biotrophic Pathogen Infection - Rody, Hugo V. S.; Camargo, Luis E. A.; Creste, Silvana; Van Sluys, Marie-Anne; Rieseberg, Loren H.; Monteiro-Vitorello, Claudia B. (Frontiers in Plant Science, 2021)
We assembled a dual-layered biological network to study the roles of Resistance Gene Analogs (RGAs) in the resistance of sugarcane upon infection by the biotrophic fungus causing smut disease. Based on sugarcane-Arabidopsis orthology, the modeling used metabolic and protein-protein interaction data from A. thaliana (from KEGG and BioGRID databases), and plant resistance curated knowledge for Viridiplantae obtained through text-mining of the Uniprot/SwissProt database. With the network, we integrated functional annotations and transcriptome data from two sugarcane genotypes that differ significantly in resistance to smut, and applied a series of analyses to compare the transcriptomes and understand both signal perception and transduction in plant resistance. We show that the smut-resistant sugarcane has a larger arsenal of RGAs encompassing transcriptionally modulated sub-networks with other resistance elements, reaching hub proteins of primary metabolism. This approach may benefit molecular breeders in search for markers associated with quantitative resistance to diseases in non-model systems.