Arabidopsis-Based Dual-Layered Biological Network Analysis Elucidates Fully Modulated Pathways Related to Sugarcane Resistance on Biotrophic Pathogen Infection.

Hugo V S Rody,Loren H Rieseberg,Silvana Creste,Marie-Anne Van Sluys,Claudia B Monteiro-Vitorello,Luis E A Camargo

doi:10.3389/fpls.2021.707904

Abstract

We assembled a dual-layered biological network to study the roles of resistance gene analogs (RGAs) in the resistance of sugarcane to infection by the biotrophic fungus causing smut disease. Based on sugarcane-Arabidopsis orthology, the modeling used metabolic and protein-protein interaction (PPI) data from Arabidopsis thaliana (from Kyoto Encyclopedia of Genes and Genomes (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 subnetworks with other resistance elements, reaching hub proteins of primary metabolism. This approach may benefit molecular breeders in search of markers associated with quantitative resistance to diseases in non-model systems.

Highlights

Plant defense mechanisms against pathogens are a multi-layered complex of biological interactions
Because (1) some statistics require the network to be fully connected to be applied and (2) finding pathways was the main focus of this study, we considered the latter in all downstream analyses
The K-means unsupervised learning algorithm predicted that most nodes (N = 6,576) belong to group A of less connected nodes (Figure 1C), and only a few super-connected nodes belong to group D (N = 52) (Figures 1C,D)

Summary

Introduction

Plant defense mechanisms against pathogens are a multi-layered complex of biological interactions. Resistance signaling cascades are triggered in plants through direct and indirect associations of resistance proteins with either pathogen/microbe/damage-associated molecular patterns (PAMP, MAMP, and DAMP) or more target-specific effector proteins (Jones and Dangl, 2006; Macho and Zipfel, 2014). Other mechanisms such as the guardee hypothesis (Dangl and Jones, 2001; Jones and Dangl, 2006), the decoy model (Van Der Hoorn and Kamoun, 2008), and the formation of multi-protein R-complexes (Friedman and Baker, 2007) have been shown to trigger resistance in plants. Promising in humans (Khorsand et al, 2020; Kösesoy et al, 2021) and Arabidopsis (Li et al, 2017), the modeling and analysis of biological networks have yet to be widely applied to study plant-pathogen interactions of non-model organisms such as sugarcane

Methods

Results

Conclusion