Characterization and Genome Analysis of Cladobotryum mycophilum, the Causal Agent of Cobweb Disease of Morchella sextelata in China

Cobweb disease is a fungal disease that can cause serious damage to edible mushrooms worldwide. To investigate cobweb disease in Morchella sextelata in Guizhou Province, China, we isolated and purified the pathogen responsible for the disease. Through morphological and molecular identification and pathogenicity testing on infected M. sextelata, we identified Cladobotryum mycophilum as the cause of cobweb disease in this region. This is the first known occurrence of this pathogen causing cobweb disease in M. sextelata anywhere in the world. We then obtained the genome of C. mycophilum BJWN07 using the HiFi sequencing platform, resulting in a high-quality genome assembly with a size of 38.56 Mb, 10 contigs, and a GC content of 47.84%. We annotated 8428 protein-coding genes in the genome, including many secreted proteins, host interaction-related genes, and carbohydrate-active enzymes (CAZymes) related to the pathogenesis of the disease. Our findings shed new light on the pathogenesis of C. mycophilum and provide a theoretical basis for developing potential prevention and control strategies for cobweb disease.


Introduction
Morels (Morchella spp.) are a rare edible and medicinal mushroom known for their high nutritional value, including high protein and low-fat content, and rich variety of essential minerals, vitamins, and other nutrients. They also have antioxidant, anti-tumor, and immune-regulating properties, making them a promising source of medicinal benefits with broad development prospects [1][2][3][4][5][6].
Wild morels are mainly found in Yunnan, Sichuan, Gansu, Heilongjiang, and Xinjiang provinces in China [7]. Morels have been cultivated for over 130 years, with the cultivation area expanding from 6.67 ha in 2003 to 10,050 ha in 2020 [7]. As of today, morels are cultivated almost everywhere in China, except for Hainan, Taiwan, Hong Kong, and Macao, and have become an important tool for poverty alleviation and rural revitalization [8].
In recent years, the cultivation and scale of morels have increased, but this has also led to new challenges. These challenges include changing and abnormal weather patterns and disease problems resulting from improper cultivation management. These factors have become important reasons for serious production losses or crop failure [9], which significantly hinder the stable development of the morel industry. Currently, reported morel diseases mainly include white mold disease caused by Paecilomyces penicillatus

Field Surveys
In June 2022, a field survey was conducted to investigate the incidence and symptoms of cobweb disease in M. sextelata during the off-season at a forest cultivation base in Weining County, Bijie City, Guizhou Province, China. A total of 300 M. sextelata fruiting bodies were investigated in triplicate, with 100 fruiting bodies being studied in different M. sextelata arch sheds. Additionally, 10 M. sextelata fruiting bodies with typical cobweb disease symptoms were collected for further studies. The aim was to determine the incidence and symptoms of the disease and disease occurrence period as well as to isolate and culture the pathogen responsible for the disease.

Isolation and Purification of the Fungal Pathogens
To isolate and purify the fungal pathogens responsible for cobweb disease in M. sextelata, small tissue blocks were taken from the healthy junction of new fruiting bodies displaying cobweb disease symptoms. Before inoculating these tissue blocks onto PDA plates, they were disinfected with a 75% ethanol solution for 30 s, followed by a 1% sodium hypochlorite solution, and washed three times with sterile water. The plates were then cultured in a dark 25 • C incubator. Once the mycelium of the fungi had grown, single spores were isolated from these cultures to obtain pure cultures of the pathogen.

Morphological and Molecular Biological Characterization of Pathogens 2.3.1. Morphological Identification
The purified pathogens were inoculated on PDA plates and cultured in the dark at 25 • C for 5, 10, and 20 days to observe the morphological characteristics of the fungal colony, including the appearance of the mycelium, conidiophores, conidia, and chlamydospores. In addition, the sizes of 60 conidia were measured. The morphological identification of the fungal pathogens followed the method described in a book titled "The Genera of Hyphomycetes" [30].
The sequencing results were subjected to BLAST sequence analysis in GenBank (NCBI, http://www.ncbi.nlm.gov (accessed on 12 November 2022)), the correct sequences of the same and similar species as the pathogens were selected from GenBank and downloaded, and the multiple sequence comparison was performed by BioEdit v7.2.5 software [35]. Phylogenetic analyses were performed based on ITS, TEF1, and RPB2 sequence data. Maximum likelihood analysis (ML) was performed using the GTR + G + I model of RAxML-8.0.26 [36], and Bayesian inference (BI) analysis was performed using MrBayes v3.2 [37] to determine the posterior probability (PP). The identification of the pathogen strains was determined according to the phylogenetic relationship. The gene sequences used to construct the phylogenetic tree are shown in Table 1.

Pathogenicity Determination
To determine the pathogenicity of the isolated and purified pathogen strains, they were grown on PDA plates in a constant temperature dark environment at 25 • C for 15 days. After collecting the conidia, a spore suspension was prepared by diluting them with sterile water to a concentration of 5 × 10 6 spores/mL. This suspension was sprayed onto the foundation soil of healthy M. sextelata fruiting bodies in a controlled cultivation shed with a temperature range of 10~18 • C, and the relative humidity was 85~95%.
Nine fresh and healthy M. sextelata fruiting bodies were inoculated with a 10-µL droplet of the conidial suspension of each pathogen strain. In contrast, fresh M. sextelata fruiting bodies inoculated with sterile water were used as controls for each experiment. The disease incidence was observed and recorded daily in both inoculated and uninoculated fruiting bodies. The pathogen was reisolated from new symptomatic M. sextelata fruiting bodies to fulfil Koch's postulate. This pathogenicity test was repeated three times.

Genome Sequencing and Assembly
The genomic DNA of C. mycophilum BJWN07 was extracted using the SDS method [38]. The DNA was assessed for quantity, quality, and integrity using agarose gel electrophoresis, Qubit ® 2.0 Fluorometer (Thermo Fisher Scientific, Foster City, CA, USA), and Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). For PacBio sequencing, the DNA was sheared with Covaris g-TUBE (Covaris, MA, USA) into target fragment size, and DNA damage and fragments were repaired. The DNA fragment was then purified and selected using AMpure PB magnetic beads (PacBio, CA, USA) to construct the SMRT Bell Library. The BluePippin system (SageScience, MA, USA) was used to select an insert size of 20 kb. The SMRT Bell library was sequenced on the PacBio RSII platform (Pacific Biosciences, Menlo Park, CA, USA).
For Illumina sequencing, the DNA library was constructed with an insert size of 350 bp using the NEBNext ® Ultra™ DNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA). The sequencing libraries were analyzed using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Once the library inspection was qualified, the whole genome was sequenced on the Illumina HiSeq PE150 (Illumina, San Diego, CA, USA). High-precision HiFi reads were generated and assembled using the CCS software. The polished consensus sequences were corrected using Illumina sequencing data for the final assembly. All sequencing and library preparation was carried out at the Beijing Novogene Bioinformatics Technology Co., Ltd. (Beijing, China).

Cobweb Disease Symptoms and Incidence
Cobweb disease symptoms were observed in a morel farm located in Weining County, Bijie City, Guizhou Province, China. The disease incidence ranged from 5% to 60%. The most common symptoms observed were a small amount of white flocculate aerial mycelium on the surface of the stipe ( Figure 1A), thick white mycelium covering the fruiting body (resembling cotton catkins), and the fruiting body becoming soft ( Figure 1B). In severe infections, the entire fruiting body was covered with white hyphelium, the stipe was lodged, and, eventually, the whole mushroom died ( Figure 1C). During the later stage of the infection, the pathogens produced numerous conidia, and the mycelium changed from white to pink ( Figure 1D). J. Fungi 2023, 9, x FOR PEER REVIEW 6 of 18 stage of the infection, the pathogens produced numerous conidia, and the mycelium changed from white to pink ( Figure 1D).

Morphological Characterization of the Pathogen
To begin with, strains BJWN07, BJWN12, and BJWN24 showed consistent morphological and micromorphological features. These strains grew rapidly on PDA plates after 5 days of cultivation and formed colonies that reached 60-75 cm in diameter with abundant aerial hyphae that resembled cotton wool (Figure 2A,B). Initially, the colonies were white, but over time they turned yellow from the center and became progressively darker, reaching a dark yellow color after 25 days ( Figure 2C,D), pink after 50 days ( Figure 2E,F), and dark pink after 60 days ( Figure 2G,H). The conidial stem had a septum and branches that were either broom or round in shape ( Figure 2I,J). The fungus produced chlamydospores, and cells expanded into a string ( Figure 2K). The conidia were colorless, ovalshaped, blunt round at both ends, and measured 17.

Morphological Characterization of the Pathogen
To begin with, strains BJWN07, BJWN12, and BJWN24 showed consistent morphological and micromorphological features. These strains grew rapidly on PDA plates after 5 days of cultivation and formed colonies that reached 60-75 cm in diameter with abundant aerial hyphae that resembled cotton wool (Figure 2A,B). Initially, the colonies were white, but over time they turned yellow from the center and became progressively darker, reaching a dark yellow color after 25 days ( Figure 2C,D), pink after 50 days ( Figure 2E,F), and dark pink after 60 days ( Figure 2G,H). The conidial stem had a septum and branches that were either broom or round in shape ( Figure 2I,J). The fungus produced chlamydospores, and cells expanded into a string ( Figure 2K). The conidia were colorless, oval-shaped, blunt round at both ends, and measured 17.2-19.8 × 8.4-9.3 µm. They had 1-3 diaphragms and were slightly bent at the diaphragm ( Figure 2L-O).

Molecular Identification of the Pathogen
The internal transcribed spacer (ITS), TEF1, and RNA polymerase II largest subunit (RPB2) regions of three strains, BJWN07, BJWN12, and BJWN24, were amplified by PCR and sequenced. The ITS fragment length was between 562-566 bp (GenBank accession numbers OP714368, OP714369, and OP714393), the TEF1 fragment length was between 927-939 bp (GenBank accession numbers OP759638, OP759639, and OP759640), and the RPB2 fragment length was between 1118-1121 bp (GenBank accession numbers OP718561, OP718562, and OP718563). After searching and comparing the sequences with the NCBI database BLAST, it was found that they were 100% similar to the accession numbers MH185858 (ITS), HF911622 (TEF1), and OK458561 (RPB2), respectively.

Molecular Identification of the Pathogen
The internal transcribed spacer (ITS), TEF1, and RNA polymerase II largest subunit (RPB2) regions of three strains, BJWN07, BJWN12, and BJWN24, were amplified by PCR and sequenced. The ITS fragment length was between 562-566 bp (GenBank accession numbers OP714368, OP714369, and OP714393), the TEF1 fragment length was between 927-939 bp (GenBank accession numbers OP759638, OP759639, and OP759640), and the RPB2 fragment length was between 1118-1121 bp (GenBank accession numbers OP718561, OP718562, and OP718563). After searching and comparing the sequences with the NCBI database BLAST, it was found that they were 100% similar to the accession numbers MH185858 (ITS), HF911622 (TEF1), and OK458561 (RPB2), respectively.
Next, a phylogenetic tree was constructed using the rDNA ITS regions and partial sequences of TEF1 and RPB2 genes. The sequences of strains BJWN07, BJWN12, and Next, a phylogenetic tree was constructed using the rDNA ITS regions and partial sequences of TEF1 and RPB2 genes. The sequences of strains BJWN07, BJWN12, and BJWN24 were found to be in the same branch as H. odoratus (asexual type: C. mycophilum) ( Figure 3) and were most closely related with high statistical support (ML/BI: 100/1). The strains BJWN07, BJWN12, and BJWN24 were identified as C. mycophilum based on morphological and molecular phylogenetic analyses.
BJWN24 were found to be in the same branch as H. odoratus (asexual type: C. mycophilum) ( Figure 3) and were most closely related with high statistical support (ML/BI: 100/1). The strains BJWN07, BJWN12, and BJWN24 were identified as C. mycophilum based on morphological and molecular phylogenetic analyses.

Pathogenicity Determination
The pathogenicity of three strains (BJWN07, BJWN12, and BJWN24) was investigated by inoculating healthy fresh soil with spore suspensions at the base of the stipe ( Figure  1E). After seven days, white, cobweb-like mycelia appeared, infecting the stipe's base and gradually spreading to the cap ( Figure 1F). The fruiting body became soft, and the mycelium covered it entirely, leading to lodging and death ( Figure 1G). These symptoms were consistent with those observed under natural conditions. Inoculation with sterile water had no effect ( Figure 1H). Koch's postulates were verified, and molecular identification confirmed the presence of the same pathogen.

Pathogenicity Determination
The pathogenicity of three strains (BJWN07, BJWN12, and BJWN24) was investigated by inoculating healthy fresh soil with spore suspensions at the base of the stipe ( Figure 1E). After seven days, white, cobweb-like mycelia appeared, infecting the stipe's base and gradually spreading to the cap ( Figure 1F). The fruiting body became soft, and the mycelium covered it entirely, leading to lodging and death ( Figure 1G). These symptoms were consistent with those observed under natural conditions. Inoculation with sterile water had no effect ( Figure 1H). Koch's postulates were verified, and molecular identification confirmed the presence of the same pathogen.

Genome Sequencing and Assembly
The representative strain BJWN07 was sequenced using the HiFi sequencing platform, generating a total of 4.91 Gb of data with a sequencing depth of approximately 130×. The assembled genome is 38.56 Mb, consisting of 10 contigs, with a GC content of 47.84% and an N50 value of 5.42 Mb. The genome assembly resulted in the identification of 8428 proteincoding sequences (CDS) and 330 RNA genes, including 264 tRNA, 53 5S rRNA, 6 18S rRNA, and 7 28S rRNA genes ( Table 2). The prediction of repeated DNA sequences in the BJWN07 genome identified 2198 long terminal repeats, which make up 0.4237% of the genome, with a total length of 171,302 bp. Additionally, there were 2239 DNA transposons that constituted 0.7662% of the genome, with a total length of 309,760 bp. The genome also contained 977 scattered repeats that added up to 83,955 bp, representing 0.2077% of the genome. Among these scattered repeats were 47 short scattered repeats, 104 rolling rings, and 70 unknown scattered repeats. Tandem repeat prediction identified 11,990 tandem repeats with a total length of 492,550 bp, making up 1.2183% of the genome. The genome also contained 7609 small-satellite DNA sequences, which added up to 311,395 bp, representing 0.7702% of the genome. In addition, there were 3071 microsatellite DNA sequences with a total length of 118,888 bp, representing 0.2941% of the genome.
In the KOG category, there were 1964 genes ( Figure S4). The category with the highest number of genes was "Posttranslational modification, protein turnover, chaperones" with 222 genes, followed by "General function prediction only" with 210 genes, "Translation, ribosomal structure and biogenesis" with 208 genes, "Energy production and conversion" with 166 genes, and "Amino acid transport and metabolism" with 166 genes.
In the KOG category, there were 1964 genes ( Figure S4). The category with the highest number of genes was "Posttranslational modification, protein turnover, chaperones" with 222 genes, followed by "General function prediction only" with 210 genes, "Translation, ribosomal structure and biogenesis" with 208 genes, "Energy production and conversion" with 166 genes, and "Amino acid transport and metabolism" with 166 genes.
The TCDB database annotation assigned 551 protein-coding genes to seven functional categories, including "Channels/pores", "Electrochemical Potential-driven Transporters", "Primary Active Transporters", "Group Translocators", "Transmembrane Electron Carriers", "Accessory Factors Involved in Transport", and "Incompletely Characterized Transport Systems" (Figure 4). The categories with the highest number of genes were "Electrochemical Potential-driven Transporters" with 176 genes and "Primary Active Transporters" with 160 genes. The BJWN07 genome contained 499 annotated CAZymes, which included various families of carbohydrate-binding molecules (CBM), carbohydrate esterases (CE), glycoside hydrolases (GHs), glycosyltransferases (GTs), polysaccharide lyases (PLs), and auxiliary activities (AA) ( Table 4). The GHs family had the most genes, with 249 genes accounting for 49.90% of the total number of CAZymes. The next largest family was the GTs family, with 111 genes accounting for 22.16% of the total number of CAZymes. Among the GHs families, GH18 had the highest number of genes at 31, while in the GTs family, GT31 had the highest number of genes at 15. Table 4. Carbohydrate-active enzyme annotation results of C. mycophilum BJWN07. The BJWN07 genome contained 499 annotated CAZymes, which included various families of carbohydrate-binding molecules (CBM), carbohydrate esterases (CE), glycoside hydrolases (GHs), glycosyltransferases (GTs), polysaccharide lyases (PLs), and auxiliary activities (AA) ( Table 4). The GHs family had the most genes, with 249 genes accounting for 49.90% of the total number of CAZymes. The next largest family was the GTs family, with 111 genes accounting for 22.16% of the total number of CAZymes. Among the GHs families, GH18 had the highest number of genes at 31, while in the GTs family, GT31 had the highest number of genes at 15. The antiSMASH analyses identified 78 secondary metabolic gene clusters and 773 secondary metabolic genes (Table 5). Of these, 23 clusters were identified as type 1 polyketide synthase (T1PKS) gene clusters containing 229 genes, accounting for 29.62% of the total secondary metabolic genes. The analysis also identified 18 non-ribosomal peptide synthetase (NRPS) gene clusters containing 175 genes, representing 22.64% of the total secondary metabolic genes. Additionally, 12 terpene gene clusters were identified, containing 59 genes. There were eight NRPS-T1PKS gene clusters containing 79 genes and seven NRPS-like gene clusters containing 69 genes. Overall, this analysis provides insight into the metabolic potential of C. mycophilum BJWN07 and the types of secondary metabolites it may produce. Annotation of the genome by the PHI database identified 1429 proteins related to pathogenicity, representing 16.85% of all the encoded proteins in the genome ( Figure 5). Among these, the most abundant category is "reduced virulence," which includes 567 proteins and accounts for 39.68% of the total candidate pathogenicity-related proteins. The second most abundant category is "unaffected pathogenicity," which includes 535 proteins and accounts for 37.44% of the total candidate pathogenicity-related proteins. Additionally, 104 proteins belong to the "loss of pathogenicity" category, and 84 proteins belong to the "lethal" category.

Phylogenomics Analysis of C. mycophilum
From the 14 species, a total of 16,159 direct orthologous groups were identified. To construct a phylogenetic tree, 1731 single-copy orthologous genes were used. The analysis revealed that C. mycophilum BJWN07, H. rosellus (asexual type was C. dendroides), and C. protrusum belong to the same genus. However, C. mycophilum BJWN07 is distantly related to the outgroup N. crassa ( Figure 6).

Phylogenomics Analysis of C. mycophilum
From the 14 species, a total of 16,159 direct orthologous groups were identified. To construct a phylogenetic tree, 1731 single-copy orthologous genes were used. The analysis revealed that C. mycophilum BJWN07, H. rosellus (asexual type was C. dendroides), and C. protrusum belong to the same genus. However, C. mycophilum BJWN07 is distantly related to the outgroup N. crassa ( Figure 6).

Discussion
In this study, we investigated cobweb disease affecting M. sextelata in Weining County, Bijie City, Guizhou Province, China. Our findings revealed that the disease had a median incidence of 15%. The causal agent was identified as C. mycophilum, which was previously unreported as causing cobweb disease in M. sextelata in China or globally. Cobweb disease, caused by different Cladobotryum species [61][62][63], has been observed in many countries, including China [12,22,25,64,65], Korea [26,63], South Africa [24], and Spain [27,66,67], causing significant economic losses in the edible mushroom industry [13,15]. C. mycophilum has a broad host range and produces a large number of conidia in the form of dry powder in the later stages of infection, making it easily transmitted by wind and humidity, resulting in outbreaks and epidemics [26,27,[61][62][63]. Due to the expansion of the morel industry and inadequate adoption of good agricultural practices, cobweb disease has become a significant challenge in various cultivation areas in Guizhou Province. Therefore, we recommend a comprehensive investigation of cobweb disease in the primary morel cultivation areas in China, particularly Guizhou Province, to identify pathogen species and their genetic diversity in different regions. This approach may provide a theoretical basis for the scientific prevention and control of cobweb disease, which is crucial for sustaining the morel industry.
The genome size of C. mycophilum assembled in this study is 38.56 Mb, which is the first high-quality genome of C. mycophilum published and similar to those of the other two species of the same genus reported previously viz C. protrusum (39.09 Mb) [28] and C. dendroides (36.69 Mb) [29]. However, the genome of another species in the same genus, H. perniciosus (44.0 Mb) [50], is larger and contains a higher proportion of repeated DNA sequences (25.27%). These findings suggest that genome size and repeat sequences can vary across species within the same genus, which could have implications for the evolution and ecology of these fungi [68].
During the early stages of infection by pathogenic fungi, the use of cell wall degrading enzymes to destroy the host cell wall is crucial for successful host infection [69]. The number of CAZymes in the genome of C. mycophilum is 499, which is higher than that of C. protrusum (412) [28] and C. dendroides (327) [29], possibly contributing to C. mycophilum's ability to infect more hosts. The genome of C. mycophilum contains 30 GH18 genes, the

Discussion
In this study, we investigated cobweb disease affecting M. sextelata in Weining County, Bijie City, Guizhou Province, China. Our findings revealed that the disease had a median incidence of 15%. The causal agent was identified as C. mycophilum, which was previously unreported as causing cobweb disease in M. sextelata in China or globally. Cobweb disease, caused by different Cladobotryum species [61][62][63], has been observed in many countries, including China [12,22,25,64,65], Korea [26,63], South Africa [24], and Spain [27,66,67], causing significant economic losses in the edible mushroom industry [13,15]. C. mycophilum has a broad host range and produces a large number of conidia in the form of dry powder in the later stages of infection, making it easily transmitted by wind and humidity, resulting in outbreaks and epidemics [26,27,[61][62][63]. Due to the expansion of the morel industry and inadequate adoption of good agricultural practices, cobweb disease has become a significant challenge in various cultivation areas in Guizhou Province. Therefore, we recommend a comprehensive investigation of cobweb disease in the primary morel cultivation areas in China, particularly Guizhou Province, to identify pathogen species and their genetic diversity in different regions. This approach may provide a theoretical basis for the scientific prevention and control of cobweb disease, which is crucial for sustaining the morel industry.
The genome size of C. mycophilum assembled in this study is 38.56 Mb, which is the first high-quality genome of C. mycophilum published and similar to those of the other two species of the same genus reported previously viz C. protrusum (39.09 Mb) [28] and C. dendroides (36.69 Mb) [29]. However, the genome of another species in the same genus, H. perniciosus (44.0 Mb) [50], is larger and contains a higher proportion of repeated DNA sequences (25.27%). These findings suggest that genome size and repeat sequences can vary across species within the same genus, which could have implications for the evolution and ecology of these fungi [68].
During the early stages of infection by pathogenic fungi, the use of cell wall degrading enzymes to destroy the host cell wall is crucial for successful host infection [69]. The number of CAZymes in the genome of C. mycophilum is 499, which is higher than that of C. protrusum (412) [28] and C. dendroides (327) [29], possibly contributing to C. mycophilum's ability to infect more hosts. The genome of C. mycophilum contains 30 GH18 genes, the most abundant type of the GH family. This family of genes produces a chitinase-like protein that aids in chitin degradation [70]. Since the mushroom cell wall primarily consists of chitin, we speculate that a large number of GH18 family members in the C. mycophilum genome are mainly utilized for the early infection stage of mushroom cell wall degradation, enabling C. mycophilum to invade mushroom cells and cause diseases.
Furthermore, the C. mycophilum genome also contains five GH75 genes that are associated with chitin degradation [71]. C. mycophilum genome contains 111 CAZymes genes encoding GT, the most among the family Hypocreaceae, with GT31 (15) being the most abundant. These GT gene families are mainly involved in chitin synthesis, cell wall biosynthesis, and glycosylation [50]. Therefore, the results suggest that CAZymes play a significant role in C. mycophilum's ability to infect hosts.
Pathogenic fungi produce various secondary metabolites, including toxins, pigments, antibiotics, repellents, insecticides, anti-tumor, and cholesterol-lowering substances. In the case of C. mycophilum BJWN07, its secondary metabolite genes produce toxins, pigments, and compounds with potential resistance to harsh environmental conditions. One of these genes is aur1, which produces aurofusarin and possibly the red pigment in C. mycophilum. This pigment was first discovered in another fungus, F. graminearum [72]. There are also many unknown secondary metabolites in C. mycophilum BJWN07, suggesting that this strain has the potential to produce bioactive compounds.
When a pathogen infects a host, it produces a large number of virulence factors, including effector proteins, which play a crucial role in pathogenesis [73,74]. The genome of C. mycophilum BJWN07 contains 661 genes of secreted proteins, 1429 pathogen and host interaction-related genes, and 499 carbohydrate-active enzymes (CAZy) associated with the fungal host cell wall. All 1429 candidate disease-related proteins contained the PHI-base, which provides a valuable genetic resource for subsequent functional genomics research and in-depth investigation of disease-related proteins. These findings can aid in analyzing the pathogenic mechanism of C. mycophilum infection on mushrooms and developing effective prevention and control strategies for cobweb disease.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/jof9040411/s1. Figure S1: Predicted proteins from C. mycophilum BJWN07 genome to the NCBI non-redundant proteins database among different bacteria species. Figure S2: GO functional classification of C. mycophilum BJWN07. Figure S3: Classification of KEGG metabolic pathways in C. mycophilum BJWN07. Figure S4: KOG functional classification of C. mycophilum BJWN07. Table S1: Genome features and background information of C. mycophilum and other representative fungi analyzed in this study. Table S2