The genome of the emerging barley pathogen Ramularia collo-cygni

Background Ramularia collo-cygni is a newly important, foliar fungal pathogen of barley that causes the disease Ramularia leaf spot. The fungus exhibits a prolonged endophytic growth stage before switching life habit to become an aggressive, necrotrophic pathogen that causes significant losses to green leaf area and hence grain yield and quality. Results The R. collo-cygni genome was sequenced using a combination of Illumina and Roche 454 technologies. The draft assembly of 30.3 Mb contained 11,617 predicted gene models. Our phylogenomic analysis confirmed the classification of this ascomycete fungus within the family Mycosphaerellaceae, order Capnodiales of the class Dothideomycetes. A predicted secretome comprising 1053 proteins included redox-related enzymes and carbohydrate-modifying enzymes and proteases. The relative paucity of plant cell wall degrading enzyme genes may be associated with the stealth pathogenesis characteristic of plant pathogens from the Mycosphaerellaceae. A large number of genes associated with secondary metabolite production, including homologs of toxin biosynthesis genes found in other Dothideomycete plant pathogens, were identified. Conclusions The genome sequence of R. collo-cygni provides a framework for understanding the genetic basis of pathogenesis in this important emerging pathogen. The reduced complement of carbohydrate-degrading enzyme genes is likely to reflect a strategy to avoid detection by host defences during its prolonged asymptomatic growth. Of particular interest will be the analysis of R. collo-cygni gene expression during interactions with the host barley, to understand what triggers this fungus to switch from being a benign endophyte to an aggressive necrotroph

Visualisation: An Approach to Knowledge Building

The chapter proposes the use of the Interactive Visualisation Tool (InViTo) as a method for sharing information by using spatial data visualisation, also known as geo-visualisation, applied to support spatial decision making and planning. InViTo is based on the idea that interacting with data can improve the users knowledge process, while visualisation should contribute to increase intuitive perception. Therefore, through the interactive and visual exploration of geo-referenced data, participants to spatial processes are supported to evaluate strategies and objectives for several alternative development options. The visual system works both on two-dimensional and three-dimensional views, so as to better meet users' skills in interpreting images. InViTo has been used in different applications, with diverse purposes and spatial scopes, showing its effectiveness in creating a common language among the involved actors and enabling discussions on spatial developmen