Genome-scale data resolve ancestral rock-inhabiting lifestyle in Dothideomycetes (Ascomycota)

Abstract

Dothideomycetes is the most diverse fungal class in Ascomycota and includes species with a wide range of lifestyles. Previous multilocus studies have investigated the taxonomic and evolutionary relationships of these taxa but often failed to resolve early diverging nodes and frequently generated inconsistent placements of some clades. Here, we use a phylogenomic approach to resolve relationships in Dothideomycetes, focusing on two genera of melanized, extremotolerant rock-inhabiting fungi, Lichenothelia and Saxomyces, that have been suggested to be early diverging lineages. We assembled phylogenomic datasets from newly sequenced (4) and previously available genomes (238) of 242 taxa. We explored the influence of tree inference methods, supermatrix vs. coalescent-based species tree, and the impact of varying amounts of genomic data. Overall, our phylogenetic reconstructions provide consistent and well-supported topologies for Dothideomycetes, recovering Lichenothelia and Saxomyces among the earliest diverging lineages in the class. In addition, many of the major lineages within Dothideomycetes are recovered as monophyletic, and the phylogenomic approach implemented strongly supports their relationships. Ancestral character state reconstruction suggest that the rock-inhabiting lifestyle is ancestral within the class.

Evolution of lifestyles in Capnodiales

“…Several transitions have occurred to evolve lichenised, epiphytic and plant and human pathogenic lifestyles ( Hongsanan et al. 2016 , Ametrano et al. 2019 ), with the sooty mould ecology apparently having evolved more recently.…”

“…The Dothideomycetes represents a class of ecologically diverse and cosmopolitan fungi from aquatic to terrestrial ecosystems. Diverse lifestyles are found amongst the Dothideomycetes including epiphytes, endophytes, saprobes, plant and animal pathogens, mycoparasites, mycorrhizal, lichenised and rock-inhabiting fungi ( Schoch et al., 2009 , Schoch and Grube, 2015 , Ametrano et al., 2019 ). The Dothideomycetes is divided into two subclasses, Pleosporomycetidae and Dothideomycetidae, and some incertae sedis lineages, accommodating more than 25 orders, 110 families and over 19 000 species, thereby representing the largest class of Ascomycota ( Schoch et al., 2009 , Hyde et al., 2013 , Jaklitsch et al., 2015 , Schoch and Grube, 2015 , Van Nieuwenhuijzen et al., 2016 , Bezerra et al., 2017 , Videira et al., 2017 , Wijayawardene et al, 2017 ).…”

An Overview of Genomics, Phylogenomics and Proteomics Approaches in Ascomycota

“…Draft genomes were presented for Rachicladosporium antarcticum (CCFEE 5527) and Rachicladosporium sp. (CCFEE 5018) [ 93 ], Lichenothelia convexa (LMCC0061, MUT5682), Lichenothelia intermixta (LMCC0543), Saxomyces alpinus (CCFEE5470, CBS135222), and Saxomyces americanus (LMCC0060, MUT5853) [ 94 ] and Cladophialophora immunda (CBS 110551) [ 95 ], Exophiala mesophila (CCFEE 6314) [ 96 ], and Knufia petricola (wild type MA5798) and its spontaneous non melanized mutant (MA5790) [ 97 ].…”

“…The most inconspicuous fungal species in Dothideomycetes, such as those representing rock-inhabiting fungi (RIF), instead, were neglected by genomic researches due to the difficulty to retrieve them in nature, isolate and grow them axenically in vitro. Only recently a few RIF genomes became available [ 94 , 95 , 97 , 101 ], though they have not been fully annotated yet. These were considered by Ametrano et al [ 94 ], who assembled different phylogenomic datasets including four newly sequenced species of the two RIF genera Lichenothelia and Saxomyces and 238 previously available genomes.…”

Using target enrichment sequencing to study the higher-level phylogeny of the largest lichen-forming fungi family: Parmeliaceae (Ascomycota)

“…Our understanding of evolutionary relationships of fungi at all phylogenetic levels has dramatically improved with the availability of genetic data from entire genomes following remarkable progress in sequencing technologies (Ametrano et al 2019 ; Ebersberger et al 2012 ; Robbertse et al 2006 ; Spatafora et al 2017 ). In addition to sequencing complete genomes, a number of more cost-efficient methods have been developed to sample subsets of genome-scale data.…”