Advances and Challenges in Computational Prediction of Effectors from Plant Pathogenic Fungi
Year: 2015
Type: article
Abstract: Fungi occupy diverse environmental niches and many have evolved to live a pathogenic life-style, causing devastating diseases in plants and animals. The interface between host and patho-gen is complex and constantly evolving. Pathogens secrete effector proteins that manipulate the host to the pathogen’s advantage. Depending on their infection strategy, fungal pathogens may deliver apoplastic effectors into the extracellular spaces and/or cytoplasmic effectors that are taken up by plant cells. Effectors have a broad functional spectrum, ranging from effectors in necrotrophic pathogens with toxic activity that cause plant cell death to avirulence (Avr) ef-fectors in biotrophic pathogens that trigger defense responses and that the plant immune sys-tem has evolved to recognize. Molecular studies have revealed over 60 fungal effectors from different species; however, this represents only the tip of the iceberg. For example, only six ef-fectors have thus far been characterized across three rust fungi, while more than 30 Avr speci-ficities have been identified in flax rust and around 50 in each of stem rust, stripe rust, and leaf rust [1]. Similarly, over 40 Avr specificities occur in interactions betweenMagnaporthe oryzae and rice [2]. With the rising number of sequenced pathogen genomes, computational prediction of effec-
Source: PLoS Pathogens
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,043
OpenAlex ID: W374729652