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ABSTRACT Modern taxonomic classification is often based on phylogenetic analyses of a few molecular markers, although single-gene studies are still common. Here, we leverage genome-scale molecular phylogenetics (phylogenomics) of species and populations to reconstruct evolutionary relationships in a dense data set of 710 fungal genomes from the biomedically and technologically important genusAspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific forAspergillusand provided profile Hidden Markov Models for each, facilitating their use by others. Examining the resulting phylogeny helped resolve ongoing taxonomic controversies, identified new ones, and revealed extensive strain misidentification (7.59% of strains were previously misidentified), underscoring the importance of population-level sampling in species classification. These findings were corroborated using the current standard, taxonomically informative loci. These findings suggest that phylogenomics of species and populations can facilitate accurate taxonomic classifications and reconstructions of the Tree of Life.IMPORTANCEIdentification of fungal species relies on the use of molecular markers. Advances in genomic technologies have made it possible to sequence the genome of any fungal strain, making it possible to use genomic data for the accurate assignment of strains to fungal species (and for the discovery of new ones). We examined the usefulness and current limitations of genomic data using a large data set of 710 publicly available genomes from multiple strains and species of the biomedically, agriculturally, and industrially important genusAspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly availableAspergillusgenomes are misidentified. Our work highlights the usefulness of genomic data for fungal systematic biology and suggests that systematic genome sequencing of multiple strains, including reference strains (e.g., type strains), of fungal species will be required to reduce misidentification errors in public databases. 

Lentinulais a broadly distributed group of fungi that contains the cultivated shiitake mushroom,L. edodes. We sequenced 24 genomes representing eight described species and several unnamed lineages ofLentinulafrom 15 countries on four continents.Lentinulacomprises four major clades that arose in the Oligocene, three in the Americas and one in Asia–Australasia. To expand sampling of shiitake mushrooms, we assembled 60 genomes ofL. edodesfrom China that were previously published as raw Illumina reads and added them to our dataset.Lentinula edodessensu lato (s. lat.) contains three lineages that may warrant recognition as species, one including a single isolate from Nepal that is the sister group to the rest ofL. edodess. lat., a second with 20 cultivars and 12 wild isolates from China, Japan, Korea, and the Russian Far East, and a third with 28 wild isolates from China, Thailand, and Vietnam. Two additional lineages in China have arisen by hybridization among the second and third groups. Genes encoding cysteine sulfoxide lyase (lecsl) and γ-glutamyl transpeptidase (leggt), which are implicated in biosynthesis of the organosulfur flavor compound lenthionine, have diversified inLentinula. Paralogs of both genes that are unique toLentinula(lecsl3 andleggt5b) are coordinately up-regulated in fruiting bodies ofL. edodes. The pangenome ofL. edodess. lat. contains 20,308 groups of orthologous genes, but only 6,438 orthogroups (32%) are shared among all strains, whereas 3,444 orthogroups (17%) are found only in wild populations, which should be targeted for conservation. 

Summary The ectomycorrhizal (ECM) symbiosis has independently evolved from diverse types of saprotrophic ancestors. In this study, we seek to identify genomic signatures of the transition to the ECM habit within the hyperdiverse Russulaceae.We present comparative analyses of the genomic architecture and the total and secreted gene repertoires of 18 species across the order Russulales, of which 13 are newly sequenced, including a representative of a saprotrophic member of Russulaceae,Gloeopeniophorella convolvens.The genomes of ECM Russulaceae are characterized by a loss of genes for plant cell wall‐degrading enzymes (PCWDEs), an expansion of genome size through increased transposable element (TE) content, a reduction in secondary metabolism clusters, and an association of small secreted proteins (SSPs) with TE ‘nests’, or dense aggregations of TEs. Some PCWDEs have been retained or even expanded, mostly in a species‐specific manner. The genome ofG. convolvenspossesses some characteristics of ECM genomes (e.g. loss of some PCWDEs, TE expansion, reduction in secondary metabolism clusters).Functional specialization in ECM decomposition may drive diversification. Accelerated gene evolution predates the evolution of the ECM habit, indicating that changes in genome architecture and gene content may be necessary to prime the evolutionary switch. 

ABSTRACT Fungi play many essential roles in ecosystems. They facilitate plant access to nutrients and water, serve as decay agents that cycle carbon and nutrients through the soil, water and atmosphere, and are major regulators of macro‐organismal populations. Although technological advances are improving the detection and identification of fungi, there still exist key gaps in our ecological knowledge of this kingdom, especially related to function.Trait‐based approaches have been instrumental in strengthening our understanding of plant functional ecology and, as such, provide excellent models for deepening our understanding of fungal functional ecology in ways that complement insights gained from traditional and ‐omics‐based techniques. In this review, we synthesize current knowledge of fungal functional ecology, taxonomy and systematics and introduce a novel database of fungal functional traits (Fun^Fun). Fun^Funis built to interface with other databases to explore and predict how fungal functional diversity varies by taxonomy, guild, and other evolutionary or ecological grouping variables. To highlight how a quantitative trait‐based approach can provide new insights, we describe multiple targeted examples and end by suggesting next steps in the rapidly growing field of fungal functional ecology.