Genomics and ecology of Epibryaceae, a psychrophilic family in Chaetothyriales

1 Genomics and ecology of Epibryaceae, a psychrophilic family in Chaetothyriales Bruno Paulo Rodrigues Lustosa1* , Ricardo Belmonte-Lopes2,3* , Sybren de Hoog2,4,5 , Flavia de Fatima Costa6, Bruna Jacomel2,5 , Germana Davila dos Santos5, Emanuel Razzolini1, Yalong Li4,7 , Ruoning Xue4,7 , Valter A. Baura8, Emanuel M. de Souza8, Renata Rodrigues Gomes5, Sarah A. Ahmed9, Laura Selbmann3,10 , Yinggai Song4,7 , Vania Aparecida Vicente1,5,11 1 Bioprocess Engineering and Biotechnology Graduate Program, Federal University of Paraná, Curitiba, PR, Brazil 2 Centre of Expertise for Mycology of Radboud University Medical Centre / Canisius Wilhelmina Hospital, Nijmegen, Netherlands 3 Department of Ecological and Biological Sciences, Tuscia University, Viterbo, Italy 4 Research Center for Medical Mycology, Peking University, Beijing, China 5 Microbiology, Parasitology and Pathology Graduate Program, Federal University of Paraná, Curitiba, PR, Brazil 6 LaboratoryofArtificialIntelligenceAppliedtoBioinformaticsandGraduatePrograminBioinformatics,SEPT,FederalUniversityofParaná,Curitiba,PR,Brazil 7 Department of Dermatology and Venerology, Peking University First Hospital, Beijing, China 8 Department of Biochemistry and Molecular Biology, Federal University of Paraná, Curitiba, PR, Brazil 9 Department of Microbiology, Faculty of Medicine, Kuwait University, Kuwait Kuwait 10 Italian National Antarctic Museum (MNA), Mycological Section, Genoa, Italy 11 Microbiological Collections of Paraná Network – Taxonline (CMRP/Taxonline), Federal University of Paraná, Curitiba, PR, Brazil Corresponding authors: Vania Aparecida Vicente ([email protected]); Yinggai Song (sy[email protected]) Copyright: © Bruno Paulo Rodrigues Lustosa et al. This is an open access article distributed under terms of the Creative Commons Attribution License (Attribution 4.0 International – CC BY 4.0). Research Article Abstract The family Epibryaceae is one of the early-diverging lineages within the order Chaetothyriales. Available molecular data show that most species are associated with mosses, liverworts, and lichens, typically inhabiting apparently psychrophilic environments. However, genomic information about this family remains scarce. This study presents whole-genome sequencing of six reference strains from the genus Epibryon (Chaetothyriales, Epibryaceae), aiming to elucidate their ecological adaptations and evolutionary relationships. Comparative analyses of CAZymes and MEROPS annotations showed that most members of Epibryaceae have a reduced set of enzymes associated with lignin degradation. Additionally, the presence of the CspA protein, linked to freezing tolerance, and the absence of the ClpA/B enzyme, associated with heat stress tolerance, suggest a strong preference for cold environments compared with other Chaetothyriales lineages. Multilocus phylogenetic analyses clarified species boundaries and resulted in the introduction of Epibryon brunneolum comb. nov. within the family. Based on phylogenetic analysis, ecological data regarding the preferred habitat of the family, and the presence of exclusive enzymes associated with extreme cold environments, the results indicate that this family is distinct from other chaetothyrialean fungi. Key words: Black yeast, comparative genomics, Epibryon, extremotolerant fungi, gene expansion and contraction Academic editor: C. Alisha Quandt Received: 27 August 2025 Accepted: 30 October 2025 Published: 22 December 2025 Citation: Lustosa BPR, BelmonteLopes R, de Hoog S, Costa FdeF, Jacomel B, dos Santos GD, Razzolini E, Li Y, Xue R, Baura VA, Souza EMde, Gomes RR, Ahmed SA, Selbmann L, Song Y, Vicente VA (2025) Genomics and ecology of Epibryaceae, a psychrophilic family in Chaetothyriales. IMA Fungus 16: e170120. https://doi.org/10.3897/ imafungus.16.170120 IMA Fungus 16: e170120 (2025) DOI: 10.3897/imafungus.16.170120 * These authors contributed equally to the work. 2 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Introduction The ascomycete order Chaetothyriales comprises melanized fungi closely related to the orders Verrucariales, Pyrenulales, and Phaeomoniellales, which together form the subclass Chaetothyriomycetidae within the class Eurotiomycetes (Gueidan et al. 2008, 2014; Stenroos et al. 2010; Muggia et al. 2021). Reconstructions of the ancestral state suggest that the order likely originated from melanized, slow-growing, rock-inhabiting fungi (RIF) or lichen-associated ancestors that may have given rise to all extant species within the Chaetothyriales (Gueidan et al. 2008, 2011; Muggia et al. 2015, 2021; Quan et al. 2020). Currently, many of these fungi can be found in extreme environments characterized by nutrient scarcity, drastic fluctuations in temperature and hydration, and high levels of UV radiation (Muggia et al. 2021; Coleine et al. 2024). Their ability to thrive under such harsh conditions has led to the recognition of diverse ecological niches, including opportunistic, epiphytic, lichen-associated, rock-inhabiting, ant-associated (e.g., carton and domatia), bryophytic, and toxigenic ecologies (Quan et al. 2020, 2024; Coleine et al. 2024; de Hoog et al. 2024; Wang et al. 2025). These ecological adaptations are thought to be driven by their low competitive ability against co-occurring microorganisms, as evidenced by the need for selective isolation methods to recover these fungi from environmental samples (Vicente et al. 2014, 2017; Costa et al. 2023). Presently, the order Chaetothyriales is divided into at least seven families: Chaetothyriaceae, Cyphellophoraceae, Domatiomycetaceae, Epibryaceae, Herpotrichiellaceae, Paracladophialophoraceae, and Trichomeriaceae (Teixeira et al. 2017; Quan et al. 2020, 2024; Wang et al. 2025). Among these, the family Epibryaceae is of particular interest, as it represents one of the early-diverging lineages within the order (Gueidan 2014; Döbbeler and Davidson 2019; Fu et al. 2023). The most recognizable genus in this family is Epibryon, which comprises over 50 described species mostly isolated from mosses, liverworts, lichens, and rocks (Döbbeler 1978, 1997; Döbbeler and Davidson 2019; Döbbeler et al. 2023). Similarly, other species recently described as Epibryon have been isolated from rocks and plants in high-latitude regions and linked to low temperatures (Crous et al. 2007; Davey et al. 2007; Quan et al. 2020; Fu et al. 2023; Kularathnage et al. 2025). Genomic information on the family Epibryaceae remains limited, hindering detailed investigations of their ecology and evolutionary history, especially regarding the elucidation of genes related to their apparently psychrotolerant or psychrophilic tendency (Fu et al. 2023). In this study, whole-genome sequencing (WGS) was conducted for six species of Epibryaceae to enable comparisons with other members of Chaetothyriales and closely related orders, with the aim of uncovering ecological adaptations and evolutionary relationships. Methods DNA extraction and sequencing Six reference strains from members of the family Epibryaceae were selected for sequencing, including Epibryon bryophilum (CBS 126278), E. humicola (CBS 117536T), E. interlamellare (CBS 126286), E. minutissimum (CBS 121758T), E. turfosorum (CBS 126587), and E. sylvestris (CBS 350.83T). The strains were 3 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae grown on Sabouraud’s Glucose Agar (SGA) at 28 °C for 7 days. DNA extraction was performed using the cetyltrimethylammonium bromide (CTAB) method with chloroform:isoamyl alcohol (CIA) 24:1 v/v, according to Vicente et al. (2017). DNA concentration was quantified using a Qubit Fluorometer (Invitrogen, Carlsbad, CA, USA), followed by library construction using Nextera XT (Illumina, San Diego, USA) following the manufacturer’s instructions. Sequencing of 150 bp paired-end reads was performed on one of the following platforms: E. bryophilum, E. interlamellare, and E. turfosorum were sequenced with Illumina NovaSeq 6000; E. humicola and E. minutissimum with Illumina MiSeq 500; and E. sylvestris with BGI-Seq500 (MGI, Guangdong, China). De novo assembly, prediction, and annotation Quality control of the reads was performed using FastQC v0.11.9 (Andrews 2010). Low-quality reads and adapters from the respective sequencing technologies were removed using Trimmomatic v0.39 (Bolger et al. 2014), with a head crop of up to 15 bp when necessary. For assembly of the nuclear genome, the trimmed paired and single reads were subjected to read correction with BayesHammer (Nikolenko et al. 2013) in SPAdes v3.15.5 (Bankevich et al. 2012) and then assembled in SPAdes using the “isolate” mode with k-mer sizes of 31, 51, 71, 91, and 111, followed by gap closing and polishing of the assemblies with GapCloser v1.12 (Luo et al. 2012). The resulting assemblies were filtered to remove contamination from non-eukaryotic DNA using Tiara (Karlicki et al. 2022) with a minimum scaffold length of 500 bp. Additionally, to evaluate the completeness of the assembled genomes, BUSCO analysis was performed using the Chaetothyriales_odb10 trained database (Simão et al. 2015; Kriventseva et al. 2018; Manni et al. 2021). Gene prediction and annotation were performed using the Funannotate pipeline v1.8.15 (Palmer and Stajich 2022). Initially, the pipeline was used to pre-trim the assembled genomes to remove scaffolds smaller than 500 bp. Subsequently, the scaffolds were sorted by size, and repetitive scaffolds were removed using the “mask” step. Prediction was then performed using the self-training mode of the GeneMark-ES v4.71 program (Lomsadze et al. 2005) with the ab initio predictors Augustus v3.4.0 (Stanke and Morgenstern 2013), SNAP v200607-28 (Korf 2004), and GlimmerHMM v3.0.4 (Majoros et al. 2004), trained with the orthologous gene database Chaetothyriales_odb10 (Kriventseva et al. 2018). The predictions from GeneMark-ES and Augustus were combined using Evidence Modeler v1.1.1 (Haas et al. 2008). The predicted genes were then annotated using the following software and databases: (1) InterProScan v5.63-95 (Jones et al. 2014) with the InterPro v95 database; (2) HMMER v3.3.2 (Eddy 2011) with the PFAM v35 (Finn et al. 2013) and dbCAN v11 (Zhang et al. 2018) databases; (3) DIAMOND v2.1.8 (Buchfink et al. 2021) with the MEROPS v11 (Rawlings et al. 2012), UniProt v2023_03 (The UniProt Consortium 2023), Repeats v1.0 (Domenico et al. 2014), and MIBiG v1.4 (Medema et al. 2015) databases; and (4) eggNOG Mapper v2.1.11 (Hernandez-Plaza et al. 2021) on the EggNOG 5.0 database (Huerta-Cepas et al. 2019). Annotation results from the UniProt and eggNOG databases were combined using Gene2Product v1.88 software. All genomes obtained were deposited in the NCBI database (BioProjects PRJNA1129533 and PRJNA1208936). 4 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Gene orthology, phylogenomic, and phylogenetic analysis Evolutionary analysis of the family Epibryaceae was performed based on gene orthology, phylogenomic, and phylogenetic data. For this purpose, the assembled genomes from strains of Epibryaceae were compared with publicly available reference genomes of species from the orders Chaetothyriales, Phaeomoniellales, Pyrenulales, and Verrucariales listed in GenBank (Suppl. material 1: table S1). The genome assemblies were downloaded and subjected to gene prediction and annotation following the methodology described above. Gene orthology analysis was performed using OrthoFinder2 v2.5.5 (Emms and Kelly 2019), focusing on classifying genes according to their presence in different orthogroups (e.g., present in one, two, three, four, or more orthogroups). Phylogenomic analysis was conducted to identify sets of orthologous genes among the analyzed strains using default parameters for DNA sequence analysis. Homology searches were performed with DIAMOND v2.1.13, and the orthogroup sequences were aligned with MAFFT v7.526 (Katoh and Standley 2013). A total of 296 orthogroups, with a minimum of 84.7% of the species having single-copy genes in any orthogroup, were used for ML tree inference with FastTree v2.1.11 (Price et al. 2010). A multilocus phylogenetic analysis was performed for species delimitation within the family Epibryaceae using ribosomal genes (rDNA), including the large subunit ribosomal gene (LSU), small subunit ribosomal gene (SSU), internal transcribed spacer region (ITS), and the RNA polymerase II gene (RPB2) from sequences obtained from reference strains (Suppl. material 1: table S2). Ribosomal genes of the WGS Epibryaceae species were extracted from the trimmed paired reads by genome skimming with GetOrganelle v1.7.7.0 (Jin et al. 2020) using the fungi_nr v0.0.1 ribosomal database with up to 20 rounds of read recruitment and multiple k-mer values (21, 45, 65, 85, 105) for the assembly of the recruited reads. Additionally, RPB2 sequences from the genomes were extracted based on the functional annotation using Funannotate v1.8.15. All sequences were aligned using MAFFT v7 (Katoh et al. 2013), and phylogenetic analysis was performed by maximum likelihood with 10,000 replicates using IQ-TREE v2.3.6 (Nguyen et al. 2015) with default parameters. Functional genomic comparison of genes associated with extremotolerance Genes previously reported in the literature to be associated with the survival of black yeasts in extreme, cold, or hot environments and with UV-radiation tolerance were selected for comparison across all genomes in this study. These include genes identified as upor downregulated in transcriptomic studies or present in higher copy numbers in chaetothyrialean species occupying distinct ecological niches (Blasi et al. 2014; Wang et al. 2014; Tesei et al. 2015; Jung et al. 2016; Moreno et al. 2017; Teixeira et al. 2017; Vicente et al. 2017; Quan et al. 2024; Coleine et al. 2024). For this comparison, functional PFAM domains and InterPro families of the selected genes were assessed based on annotations generated using the same methodology described above. 5 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Gene expansion and contraction Ancestral state reconstruction based on gene expansion and contraction in the phylogenomic tree was performed using the function “ace” from the ape package v5.0 (Paradis and Schliep 2019) in R (R Core Team 2024). For this analysis, the phylogenomic tree was compared with the copy number of each gene associated with extreme cold and heat stress, generating a separate phylogenetic tree for each gene. In addition, genes annotated from the Carbohydrate-Active enZymes (CAZyme) and MEROPS peptidase databases were included to assess the expansion and contraction of metabolic pathways. The analysis used the “continuous” mode under a Brownian motion (BM) model, which assumes that characters evolve randomly following a random walk (Felsenstein 1973; Schluter et al. 1997). This approach estimated the possible ancestral copy numbers at each node of the phylogenomic tree. In this context, ancestral states were calculated for all nodes of the phylogenomic tree. Afterwards, only genes showing evidence of expansion or contraction at node VI (representing the last common ancestor of the order Chaetothyriales) and node VII (representing the last common ancestor of the family Epibryaceae) were selected to infer potential expansions and contractions in these lineages. Genes associated with hot and cold stress are shown as separate phylogenetic trees, while the CAZyme and MEROPS gene expansions and contractions at the respective nodes are presented in the Suppl. material 1: table S3. Results Genome assembly and annotation Whole-genome sequencing (WGS) of six species—Epibryon bryophilum, E. interlamellare, E. turfosorum, E. sylvestris, E. humicola, and E. minutissimum— within the family Epibryaceae was performed and compared with other members of the Chaetothyriales and closely related orders. De novo assemblies of the new genomes showed an average size of 29.09 Mbp (ranging from 26.20 to 34.97 Mbp). The final annotation revealed an average of 10,495 predicted genes, ranging from 9,908 to 10,915 genes (Table 1). Genome completeness estimated with BUSCO using 6,265 genes from the Chaetothyriales odb_10 database showed the genomes to have an average of 85.8% complete copies (ranging from 84.2 to 87.2), of which 0.48% (0.7 to 0.3) were duplicated and 85.3% (86.7 to 83.8) were single copies. Additionally, 0.65% (1.0 to 0.5) were considered fragmented, and 13.5% (12.4 to 14.8) were considered missing genes. The genome comparison using OrthoFinder v2.5.5 was performed for the family Epibryaceae, including additional publicly available genomes from the Chaetothyriomycetidae subclass, of which one was from the order Phaeomoniellales, two from the Pyrenulales, two from the Verrucariales, and 62 from the Chaetothyriales. Of the latter, 36 belonged to the family Herpotrichiellaceae, nine to Trichomeriaceae, six to Domatiomycetaceae, two to Cyphellophoraceae, one to Chaetothyriaceae, and one genome was from a species identified as incertae sedis. The genome accession numbers are presented in the Suppl. material 1: table S1. 6 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Phylogenomic analysis showed that all Epibryon species shared a common ancestor and that the species Cladophialophora brunneola (CGMCC 3.18770T) is also part of this family (Fig. 1). Ortholog analysis revealed that members of Epibryaceae have between 51.8% and 98.3% of their genes assigned to an orthogroup. Cladophialophora brunneola CGMCC 3.18770T, isolated from karst rock, when compared with other species originating from moss, presented a higher proportion of orthogroups with two genes assigned (10.7%, Fig. 1, bar plot marked in green). Regarding the proportion of shared orthogroups within the Epibryaceae, E. humicola CBS 117536T and E. minutissimum CBS 121758T shared 98.3% of orthogroups. In contrast, the remaining strains shared, on average, 50.5% of orthogroups, with values ranging from 34.4% to 71.8% (Suppl. material 1: table S4). The multilocus analysis (Fig. 2A) based on the ribosomal genes (SSU, ITS, LSU) and RPB2 is concordant with the genome tree (Fig. 1). This phylogenetic analysis revealed that C. brunneola, E. bryophilum, E. interlamellare, E. sylvestris, and E. turfosorum represent well-supported taxa. In contrast, E. humicola and E. minutissimum yielded statistically insignificant differences to support them as separate species (Fig. 2A). Additionally, the present analysis indicates that Cladophialophora brunneola, previously described as an early-diverging lineage within the Chaetothyriales (Fu et al. 2023), is placed within the family Epibryaceae (Figs 1, 2A), suggesting that this species is better classified in the genus Epibryon. Moreover, E. hepaticola and E. intercapillare cluster on a separate branch from the main Epibryon group (Fig. 2A). Among isolates with available molecular data, no ecological differences were observed among species of Epibryaceae (Suppl. material 1: table S2). Most species were described in association with mosses (Döbbeler 1978, 1979; Davey et al. 2007; Stenroos et al. 2010; Newsham et al. 2014; Hirose et al. 2016), indicating a consistent ecological niche (Fig. 2A). In contrast, some species were reported from rock surfaces (Fu et al. 2023), soil (Crous et al. 2007; Iliushin et al. 2022), or as epiphytes (Crous et al. 2007). Based on Köppen climate classification (Beck et al. 2023), several isolates originated from polar regions as well as cold and temperate continental zones, with precipitation distributed throughout the year and temperatures ranging from extremely cold to humid subtropical (Fig. 2B). Table 1. Epibryaceae genome data assemblies of six species of Epibryon. Species Strain Genome size (Mbp) Number of contigs GC content (%) Number of proteins predicted Number of duplications* GenBank accession number E. bryophilum CBS 126278 30.74 303 51.05 10776 38 JBQQWO000000000 E. humicola CBS 117536T27.05 939 49.9 10329 76 JBQQWI000000000 E. interlamellare CBS 126286 26.20 79 50.39 9908 43 JBQQWN000000000 E. minutissimum CBS 121758T27.79 916 49.83 10537 206 JBQQWH000000000 E. sylvestris CBS 350.83T27.76 120 51.16 10506 42 JBQQWE000000000 E. turfosorum CBS 126587 34.97 642 48.96 10915 80 JBQQWM000000000 *Number of duplications was assigned with OrthoFinder v2.5.5 based on 41,386 orthogroups. 7 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae CAZyme and MEROPS in the family Epibryaceae On average, species within the family Epibryaceae had 297 genes assigned to the Carbohydrate-Active enZymes (CAZyme) database, with values ranging from 280 to 339, encompassing a total of 106 different CAZyme families (Suppl. material 1: table S5). There was an average of 50.7 auxiliary activity (AA) enzymes (range: 46–59), 2.5 carbohydrate-binding modules (CBM; range: 1–3), 11.8 carbohydrate esterases (CE; range: 8–14), 145.9 glycoside hydrolases (GH; range: 135–167), and 86.0 glycosyltransferases (GT; range: 79–96), with no genes assigned to the polysaccharide lyase (PL) family (Suppl. material 1). Cladophialophora brunneola possessed the highest number of CAZyme genes across all Epibryaceae. In contrast, E. bryophilum had the lowest copy numbers of AA and GT genes; E. humicola had the fewest CBM genes; and E. turfosorum showed the lowest counts of CE and GH genes among the analyzed species (Fig. 3). Analyses of MEROPS proteases showed that members of the Epibryaceae had an average of 345.7 genes annotated in this database, with values ranging from 318 to 397 genes, representing 89 distinct MEROPS families (Suppl. material 1: table S6). Regarding distribution across different peptidase classes, the genomes contained an average of 20.4 genes belonging to the aspartic (A) family (range: 16–25), 62.0 to the cysteine (C) family (range: 59–66), 0.42 to the glutamic (G) family (range: 0–3), 7.1 to the inhibitor (I) family (range: 6–8), 75.7 to the metallo (M) family (range: 72–80), one to the mixed (P) family, 157.4 to the serine (S) family (range: 135–192), 20.8 to Figure 1. Maximum likelihood phylogenomic tree and core ortholog analysis. The phylogenomic tree was inferred with FastTree v2.1.11 using 296 orthogroups identified with OrthoFinder v2.5.5, each containing single-copy genes in at least 84.7% of the analyzed species. Proportion of genes per species assigned to orthogroups. The bar plot shows, for each genome, the percentage of orthogroups containing a single gene (red), two genes (green), three genes (blue), or four or more genes (yellow) assigned per species. The proportion of genes not assigned to any orthogroup is represented in gray. 8 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Figure 2. Phylogenetic tree and global distribution of family Epibryaceae members. A Maximum likelihood phylogenetic tree of the family Epibryaceae based on SSU, ITS, LSU, and RPB2 gene sequences inferred with IQ-TREE v2.4.0. Bootstrap values were calculated from 10,000 replicates; values > 80% are shown. The tree was rooted with Coccodinum bartschii CBS 121709. Species with sequences extracted from genomes are shown in bold. T = ex-type strains. B Geographic distribution of isolation sites for Epibryaceae strains. Some locations correspond to more than one isolate. Coordinates for each strain included in the phylogenetic tree are provided in Suppl. material 1: table S2. Circles represent isolated species, with each color indicating a different taxon. Background colors on the map follow the Köppen climate classification (Beck et al. 2023), with the legend shown in Suppl. material 1: fig. S1. 9 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae the threonine (T) family (range: 20–22), and 0.7 to the unknown (U) family (range: 0–1), with no copies assigned to the asparagine (N) family. Within this context, C. brunneola exhibited the highest number of genes from the A, C, M, S, and T families and was the only species with genes assigned to the G family, with three copies. In contrast, E. bryophilum and E. turfosorum contained the highest number of genes assigned to the I family, each with eight copies. E. interlamellare had the fewest genes from the A family, while both E. interlamellare and E. bryophilum showed the lowest counts for the C family. E. minutissimum and E. humicola had the lowest counts for the I, M, and S families, and both E. bryophilum and E. turfosorum had the fewest genes in the T protease family (Fig. 3). Expansion or contraction of CAZyme and MEROPS The analysis of CAZyme and MEROPS gene copy numbers revealed multiple expansions and losses within the Chaetothyriales lineage compared with the outgroups. CAZyme families AA1, AA4, GH1, GH3, GH10, GH13, GH16, GH20, GH27, GH28, GH31, GH76, GT22, and GT76 showed clear signatures of expansion in the last common ancestor of the order Chaetothyriales (Suppl. material 1: table S3). For example, AA1 (laccases) increased from approximately seven copies in the ancestral state to 11–20 copies across the order, and GH3 (glucosidases) expanded from six copies to an average of 8–13. In addition, several gene families originated and expanded in certain species within the order, including AA14, CBM13, CBM52, CE2, CE3, GH10, GH12, GH28, GH29, GH33, GH39, GH105, GH115, GH127, GH154, GH162, GT76, GT91, and GT109. Conversely, some contractions were observed compared with the ancestral state, such as a reduction in GH114 (Suppl. material 1: table S3). MEROPS peptidase analysis also indicated expansion within the Chaetothyriales profile. The ancestral state of this order showed expansion of proteins A01A, M20D, M38, S10, S12, S28, S33, and S09X—the latter (a prolyl oligopeptidase) increasing from approximately 26 copies in the ancestral state to 37–87 copies across families. Similarly, MEROPS families such as N09, S09A, and U74 were inferred to have originated within the order. In contrast, contractions or complete losses were observed for families C85, M04, M13, M35, and M77, which are absent in several lineages relative to the ancestral Chaetothyriales (Suppl. material 1: table S3). Within the family Epibryaceae, a distinct CAZyme and MEROPS profile was observed compared with other genomes. For instance, the Epibryaceae possess the exclusive CAZyme CBM52, and the ancestral lineage of the family showed expansions of AA5 and GH29—the latter being shared only with the Domatiomycetaceae. In addition, GT25 and GT34 were expanded compared with other families, while AA7, AA9, and GH12 showed contractions within the Epibryaceae (Suppl. material 1: table S3). Regarding MEROPS, the Epibryaceae ancestral state showed expansions in S53 and T02 compared with other families, and members of this family uniquely possess the enzyme U74, which has a nonspecific catalytic site capable of digesting proteins without substrate size restriction (Rey et al. 2016; Ting et al. 2022). Meanwhile, contractions were observed for C26 and C85 proteases (Suppl. material 1: table S3). 16 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Conclusion This study expands the scope of genomic comparisons within the subclass Chaetothyriomycetidae. The family Epibryaceae possesses a distinct set of enzymes associated with cold tolerance, such as the cold shock protein A (CspA), which is absent in other members of the order Chaetothyriales (Fig. 5). This supports the hypothesis that the family predominantly inhabits low-temperature environments. Sampling records further confirm that most species with available molecular data have been isolated from cold habitats, including polar regions and mountainous areas (Fig. 2B). Comparative analyses of CAZyme and MEROPS annotations revealed that, while many Chaetothyriales exhibit expansions in lignin-degrading enzymes, such as auxiliary activity enzymes, the Epibryaceae display a reduced number of these proteins (Suppl. material 1: table S3). This limited enzymatic capacity for lignin and complex polysaccharide breakdown aligns with their association with mosses and lichens, which provide readily accessible carbon sources in nutrient-poor, cold environments. Phylogenomic analyses position the Epibryaceae basally within the Chaetothyriales and support the inclusion of Epibryon brunneolum comb. nov. in the family (Fig. 1). Collectively, the results indicate that the Epibryaceae represent a psychrotolerant lineage adapted to cold environments, often in association with mosses and occasionally with lichens, as well as in epiphytic, rock-inhabiting, and soil contexts. These findings suggest that the family shares an ancestral ecological state with members of closely related orders but has evolved unique traits distinguishing it from other Chaetothyriales. Acknowledgments This work was conducted within the framework of the National Institutes for Science and Technology in Conservation and Exploitation of Biological Resources on Network Collections (INCT-CERBC). We would also like to acknowledge the support of the National Council for Technological and Scientific Development (CNPq, Brazil) and the National Natural Science Foundation of China (NSFC). Additional information Conflict of interest The authors have declared that no competing interests exist. Ethical statement No ethical statement was reported. Use of AI No use of AI was reported. Adherence to national and international regulations All the fungal strains used in this study have been legally obtained, respecting the Convention on Biological Diversity (Rio Convention). 17 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Funding The authors gratefully acknowledge financial support from the National Council for Technological and Scientific Development (CNPq, Brazil), the National Institute of Science and Technology – CERBC (INCT-CERBC, Brazil; grant no. 406645/2022-1), and the National Natural Science Foundation of China (NSFC, China; grant no. 82272354). Individual fellowships were awarded as follows: B.P.R.L., CNPq no. 445831/2024-3; R.B-L., CNPq no. 200025/2023-6; F.F.C. and G.D.S., CNPq no. 406645/2022-1; B.J., CNPq no. 443861/2023-4; E.L.R., CNPq no. 409184/2022-5; and V.A.V., CNPq no. 316213/2023-3. Author contributions Conceptualization (S.H., L.S., Y.S., V.A.V.); Data curation (R.B-L., F.F.C.); Formal analysis (B.P.R.L.); Funding acquisition (Y.S., V.A.V.); Investigation (B.P.R.L., B.J., G.D.S., V.A.B., Y.L., R.X.); Methodology (B.P.R.L., R.B-L.); Project administration (Y.S., V.A.V.); Resources (G.D.S., E.R., V.A.B.); Software (R.B-L., F.F.C.); Supervision (S.H., V.A.V.); Validation (R.B-L., B.J., E.R., V.A.B., E.M.S., S.A.A.); Visualization (B.P.R.L., F.F.C., R.R.G.); Writing—original draft (B.P.R.L., F.F.C.); Writing—review and editing (B.P.R.L., S.H., R.B-L., F.F.C., B.J., G.D.S., E.M.S., R.R.G., S.A.A., L.S., Y.S., V.A.V.). B.P.R.L. and R.B-L. contributed equally to this work and share first authorship. All authors have read and approved the final manuscript. Author ORCIDs Bruno Paulo Rodrigues Lustosa https://orcid.org/0000-0002-0150-5962 Ricardo Belmonte-Lopes https://orcid.org/0000-0002-3122-0271 Sybren de Hoog https://orcid.org/0000-0002-5344-257X Flavia de Fatima Costa https://orcid.org/0000-0003-4092-4673 Bruna Jacomel https://orcid.org/0000-0001-9552-9369 Germana Davila dos Santos https://orcid.org/0000-0002-0774-354X Emanuel Razzolini https://orcid.org/0000-0002-9391-5271 Yalong Li https://orcid.org/0009-0006-6914-2877 Ruoning Xue https://orcid.org/0000-0002-4218-5387 Valter A. Baura https://orcid.org/0000-0003-2827-6239 Emanuel M. de Souza https://orcid.org/0000-0003-1546-9218 Renata Rodrigues Gomes https://orcid.org/0000-0002-1827-3408 Sarah A. Ahmed https://orcid.org/0000-0003-0155-8113 Laura Selbmann https://orcid.org/0000-0002-8967-3329 Yinggai Song https://orcid.org/0000-0002-1644-6942 Vania Aparecida Vicente https://orcid.org/0000-0002-2953-4861 Data availability All gene and genome sequences generated in this study are available in GenBank under the accession numbers provided. All data supporting the findings of this study are included in the main text and the Supplementary Information. References Barnett ME, Zolkiewska A, Zolkiewski M (2000) Structure and activity of ClpB from Escherichia coli: role of the amino-and carboxyl-terminal domains. Journal of Biological Chemistry 275(48): 37565-37571. https://doi.org/10.1074/jbc.M005211200 18 IMA Fungus 16: e170120 (2025), DOI: 10.3897/imafungus.16.170120 Bruno Paulo Rodrigues Lustosa et al.: Genomics and ecology of Epibryaceae Beck HE, McVicar TR, Vergopolan N, et al. (2023) High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections. 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Nucleic Acids Research 46(W1): W95–101. https://doi.org/10.1093/nar/gky418 Supplementary material 1 Additional information Authors: Bruno Paulo Rodrigues Lustosa, Ricardo Belmonte-Lopes, Sybren de Hoog, Flavia de Fatima Costa, Bruna Jacomel, Germana Davila dos Santos, Emanuel Razzolini, Yalong Li, Ruoning Xue, Valter A. Baura, Emanuel M. de Souza, Renata Rodrigues Gomes, Sarah A. Ahmed, Laura Selbmann, Yinggai Song, Vania Aparecida Vicente Data type: xlsx Explanation note: table S1. Genome accesion public available genomes accessed in the NCBI. table S2. Additional information about the reference strains and isolates, coordinates of isolate genes and ecology. table S3. Genes expansion and contraction based on copy number of Carbohydrate-Active enZymes. table S4. Orthogroups species overlap. table S5. Distribution of CAZyme enzymes according to genome prediction from the selected genomes. table S6. Distribution of MEROPS enzymes according to genome prediction from the selected genomes. fig. S1. Climate plot map according to Köppen-Geiger climate classification. The colors represent a different climate with different seasons. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/imafungus.16.170120.suppl1