Comparative genomic sequence data from fungal species are beginning to provide insights into the crucial ecological roles fungi serve in nature. Recent studies suggest a major class of fungi that associate with plants as root symbionts, called ectomycorrhizal fungi, likely influence the cycling of organic carbon in nature. This research seeks to investigate the evolution of the ability to decompose organic compounds in the diverse fungal family, Russulaceae. The project will produce genome sequence data from species across the family to test how species and groups within the Russulaceae are related to each other, the ecological roles these fungi serve in nature, and how the traits that govern these ecological roles have evolved. One graduate student will be trained and a series of workshops will train undergraduates in new molecular methods and genome analysis techniques. This research will also promote interdisciplinary collaboration through established international networks between scientists in Europe, Canada, Asia, and the U.S. Genomic data from this study has the potential to lead to advances in biofuel production within fungi.
This project will produce a new molecular systematic framework for Russula, Russulaceae, and Russulales through the application of phylogenetic and phylogenomic methods, which will enable the classification of novel diversity for additional systematic studies. This study will also identify genes within the genomes of the Russulales that encode oxidoreductases and are capable of breaking down cellulose, hemicellulose, lignin, and other structural plant molecules. Genomic sequence data from representative species across the Russulaceae will be generated by the Joint Genome Institute and will be assembled through the MycoCosm pipeline. Functional gene prediction will be informed by previous studies on degradative gene composition of known saprotrophs, with particular focus on those members from Russulales. Researchers will investigate functional variation throughout the lineage, emphasizing the diversity of class II peroxidases, CAZymes, and/or laccases. Evolution of functional genes will be inferred using gene family phylogenies and ancestral state reconstruction methods.
