Cortinariaceae genomics

Family Cortinariaceae currently includes only one genus, Cortinarius, which is the largest Agaricales genus, with thousands of species worldwide. The species are important ectomycorrhizal fungi and form associations with many vascular plant genera from tropicals to arctic regions. Genus Cortinarius contains a lot of morphological variation, and its complexity has led many taxonomists to specialize in particular on infrageneric groups. The previous attempts to divide Cortinarius have been shown to be unnatural and the phylogenetic studies done to date have not been able to resolve the higher-level classification of the group above section level. Genomic approaches have revolutionized our view on fungal relationships and provide a way to tackle difficult groups. We used both targeted capture sequencing and shallow whole genome sequencing (WGS) to produce data and to perform phylogenomic analyses of 75 single-copy genes from 19 species. In addition, a wider 5-locus analysis of 245 species, from the Northern and Southern Hemispheres, was also done. Based on our results, a classification of the family Cortinariaceae into ten genera—Cortinarius, Phlegmacium, Thaxterogaster, Calonarius, Aureonarius, Cystinarius, Volvanarius, Hygronarius, Mystinarius, and Austrocortinarius—is proposed. Seven genera, 10 subgenera, and four sections are described as new to science and five subgenera are introduced as new combinations in a new rank. In addition, 41 section names and 514 species names are combined in new genera and four lecto- and epitypes designated. The position of Stephanopus in suborder Agaricineae remains to be studied. Targeted capture sequencing is used for the first time in fungal taxonomy in Basidiomycetes. It provides a cost-efficient way to produce -omics data in species-rich groups. The -omics data was produced from fungarium specimens up to 21 years old, demonstrating the value of museum specimens in the study of the fungal tree of life. This study is the first family revision in Agaricales based on genomics data and hopefully many others will soon follow.