101 Dothideomycetes genomes: A test case for predicting lifestyles and emergence of pathogens

Authors: Sajeet Haridas, R. Albert, M. Binder, J. Bloem, Kurt LaButti, Asaf Salamov, B. Andreopoulos, Scott Baker, Kerrie Barry, Gerald F. Bills, Burton H. Bluhm, C. Cannon, Raúl Castanera, Deborah Culley, Chris Daum, D. Ezra, Jennifer B González, Bernard Henrissat, Alan Kuo, Chen Liang, Anna Lipzen, François Lutzoni, Jon Magnuson, Stephen J. Mondo, Matt Nolan, Robin A. Ohm, Jasmyn Pangilinan, H.-J. Park, Lucı́a Ramı́rez, Manuel Alfaro, Hui Sun, Andrew Tritt, Yuko Yoshinaga, L.H. Zwiers, B. Gillian Turgeon, Stephen B. Goodwin, Joseph W. Spatafora, P.W. Crous, Igor V. Grigoriev - Studies in Mycology 2020 cited by 233

phylogeny linked to ecological niches providing insights into genome evolution and adaptation across this group. Using machine-learning methods we classified fungi into lifestyle classes with >95 % accuracy and identified a small number of gene families that positively correlated with these distinctions. This can become a valuable tool for genome-based prediction of species lifestyle, especially for rarely seen and poorly studied species.