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Abstract Fungal pathogens cause various diseases for plant and animal hosts. Despite the extensive impact of fungi on human health and life, the threats posed by emerging fungal pathogens are poorly understood. Specifically, there exist few fungal virulence gene databases, which prevent effective bioinformatics studies on fungal pathogens. Therefore, we constructed a comprehensive online database of known fungal virulence factors, which collected 2058 pathogenic genes produced by 228 fungal strains from 85 genera.

This database creates a pivotal platform capable of stimulating and facilitating further bench studies on fungal pathogens. Database URL. Introduction Fungal organisms comprise one of the most diverse kingdoms on Earth; the number of fungal species is estimated to be ∼1.5 million (). Many fungal taxa are pathogens under certain conditions. For instance, ∼80 000 fungal taxa have pathogenicity on 56 000 vascular plant hosts, according to the Fungus–Host Distributions of US Department of Agriculture (). Fungal pathogens have a broad spectrum of hosts, including plants and animals, and may cause death and disability in humans, yield loss in agricultural crops and even alteration of forest ecosystem dynamics.

For example, fungi in the genus Fusarium cause a variety of blights, seedling disease, root rots or wilts on nearly all species of cultivated plants, and they strongly affect the agriculture economy. Virulence factors are the most important proteins in pathogens, such as toxin synthetic enzymes and secreted biodegradation enzymes (), that permit them to evade the defense mechanisms of the host and, thus, cause diseases (). Currently, the number of reported fungal virulence factors is limited, and many of the data are only available in the literature texts. Memeo Instant Backup Download Deutsch Songs. Please refer to references () for reviews on fungal virulence factors. To maximize the value of this type of data, it is essential that a method of data storage and sharing should be implemented for efficient and effective data mining.