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The fungal kingdom is too large to be discovered exclusively by classical genetics. The access to omics data opens a new opportunity to study the diversity within the fungal kingdom and how adaptation to new environments shapes fungal metabolism. Genomes are the foundation of modern science but their quality is crucial when analysing omics data. In this study, we demonstrate how one gold-standard genome can improve functional prediction across closely related species to be able to identify key enzymes, reactions and pathways with the focus on primary carbon metabolism. Based on this approach we identified alternative genes encoding various steps of the different sugar catabolic pathways, and as such provided leads for functional studies into this topic. We also revealed significant diversity with respect to genome content, although this did not always correlate to the ability of the species to use the corresponding sugar as a carbon source.

The draft genome, morphological description, and phylogenetic placement of Coniella lustricola sp. nov. (Schizoparmeaceae) are provided. The species was isolated from submerged detritus in a fen at Black Moshannon State Park, Pennsylvania, USA and differs from all other Coniella species by having ellipsoid to fusoid, inequilateral conidia that are rounded on one end and truncate or obtuse on the other end, with a length to width ratio of 2.8. The draft genome is 36.56 Mbp and consists of 870 contigs on 634 scaffolds (L50 = 0.14 Mb, N50 = 76 scaffolds), with 0.5% of the scaffold length in gaps. It contains 11,317 predicted gene models, including predicted genes for cellulose, hemicellulose, and xylan degradation, as well as predicted regions encoding for amylase, laccase, and tannase enzymes. Many members of the Schizoparmeaceae are plant pathogens of agricultural crops. This draft genome represents the first sequenced Coniella genome and will be a valuable tool for comparisons among pathogenic Coniella species.