Genetic Bases of Fungal White Rot Wood Decay Predicted by Phylogenomic Analysis of Correlated Gene-Phenotype Evolution
Lázló G. Nagy, Robert Riley, Philip J. Bergmann, Kirsztina Krizsán, Francis M. Martin, Igor V. Grigoriev, Dan Cullen, and David S. Hibbett
10 November 2o16, Mol Biol Evol (2016) 34 (1): 35-44; doi: 10.1093/molbev/msw238
Fungal decomposition of plant cell walls (PCW) is a complex process that has diverse industrial applications and huge impacts on the carbon cycle. White rot (WR) is a powerful mode of PCW decay in which lignin and carbohydrates are both degraded. Mechanistic studies of decay coupled with comparative genomic analyses have provided clues to the enzymatic components of WR systems and their evolutionary origins, but the complete suite of genes necessary for WR remains undetermined. Here, we use phylogenomic comparative methods, which we validate through simulations, to identify shifts in gene family diversification rates that are correlated with evolution of WR, using data from 62 fungal genomes. We detected 409 gene families that appear to be evolutionarily correlated with WR. The identified gene families encode well-characterized decay enzymes, e.g., fungal class II peroxidases and cellobiohydrolases, and enzymes involved in import and detoxification pathways, as well as 73 gene families that have no functional annotation. About 310 of the 409 identified gene families are present in the genome of the model WR fungus Phanerochaete chrysosporium and 192 of these (62%) have been shown to be upregulated under ligninolytic culture conditions, which corroborates the phylogenybased functional inferences. These results illuminate the complexity of WR and suggest that its evolution has involved a general elaboration of the decay apparatus, including numerous gene families with as-yet unknown exact functions.
László G. Nagy, Robert Riley, Philip J. Bergmann, Krisztina Krizsán, Francis M. Martin, Igor V. Grigoriev, Dan Cullen, David S. Hibbett; Genetic Bases of Fungal White Rot Wood Decay Predicted by Phylogenomic Analysis of Correlated Gene-Phenotype Evolution. Mol Biol Evol 2016; 34 (1): 35-44. doi: 10.1093/molbev/msw238