Whole genome sequencing and analysis of Inonotus hispidus isolated from the Chengde Mountain Resort, China

doi:10.21203/rs.3.rs-4416213/v1

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Whole genome sequencing and analysis of Inonotus hispidus isolated from the Chengde Mountain Resort, China

https://doi.org/10.21203/rs.3.rs-4416213/v1

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Inonotus hispidus is an edible medicinal macrofungus whose nutritional and therapeutic qualities are well-known. The species is widely distributed in Asia, Europe, North Africa, and North America. As a medicinal and health resource it is highly valued in East Asian countries, notably China, Japan, and South Korea. The antiviral, antioxidant, antitumor, hypolipidemic, and immunomodulatory activity of I. hispidus have been documented. In this study, we utilized a combination of Illumina NovaSeq and PacBio Sequel platforms to sequence the whole genome of a strain of I. hispidus named "CDMR" after the Chengde Mountain Resort (Hebei Province, China), where the spores of fresh wild fruiting bodies were collected. The genome size of I. hispidus CDMR was found to be 34.22 Mb, containing 7,723 coding genes, 8,100 repetitive sequences, 91 tRNAs, 13 rRNAs, and 15 snRNAs. Sets of these genes were annotated using the following databases: GO (5,012 genes), KEGG (5,714), COG (1,209), NR (6,576), TCDB (297), InterPro (5,012), and Uniprot (1,639). In addition, we found 313, 340, 128, 116, and 728 genes related to carbohydrate-active enzymes, secretory proteins, secondary metabolism, Cytochrome P450, and pathogen–host interactions, respectively. Our findings offer comprehensive insights into the genome of I. hispidus CDMR, fostering the exploration of genomic and functional variances among I. hispidus populations from diverse regions. Moreover, this study contributes to the advancement of the genetic and genomic investigations of the nutritional and therapeutic attributes of I. hispidus.

Inonotus hispidus Genomics Whole genome sequencing Functional annotation

The fungus is one of the members of the group of eukaryotic organisms, which includes microorganisms like yeasts, molds, and mushrooms (Wikipedia 2022). Scientists researching the diversity of fungi have estimated that there are from 2,200,000 to 3,800,000 fungal species on Earth; however, as of April 16, 2024, only 159,003 species have been described and documented in the Species Fungorum (Kirk 2022). Humans have long used fungi for food preparation, preservation, and folk medicine, and mushroom farming and deep processing have become large-scale industries in many countries. In addition, numerous fungal species have been used or are currently being investigated as potential sources to produce antibiotics, vitamins, and cholesterol-lowering drugs due to the typically high number of secondary metabolites with antimicrobial or other properties. Fungi have also been used as model organisms to explore problems in eukaryotic cell biology and genetics, and to tackle specific biological problems related to plant pathology and medicine (Datta, Ganesan et al. 1990, Dean, Talbot et al. 2005). With the rapid development of high-throughput sequencing technology, fungi can now be identified and classified at a genome-wide level and their secondary metabolites and medicinal properties of the fungi can also be analyzed and studied at the level of whole genome (Tang, Jin et al. 2022, Zhang, Feng et al. 2022). Currently (April 16, 2024), 17,762 fungal genomes have been analyzed and deposited at the National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/data-hub/taxonomy/4751/); most of the collected genomes belong to the phylum Ascomycota (14,320, 80.62%), followed by Basidiomycota (2,585, 14.55%) (NCBI 2022). Studies on the function and diversity of fungal genomes are limited: the whole genomes of only 11.17% (17,762/159,003) of the described fungal species have been sequenced. Whole-genome sequencing of more fungal species will not only improve our understanding of fungal diversity and function, but also have important implications for the study of secondary metabolites and medical applications of fungi.

Inonotus hispidus, common name "shaggy bracket," is an edible and medicinal macrofungus, renowned for its nutritional and therapeutic values (Talhinhas, Tavares et al. 2017, Angelini, Girometta et al. 2019, Liu, Hou et al. 2019). The species belongs to the phylum Basidiomycota, class Agaricomycetes, order Hymenochaetales, family Hymenochaetaceae (Talhinhas, Tavares et al. 2017). I. hispidus is an annual parasitic mushroom, characterized by soft fibrous fruiting bodies with a brown coloring and can cause white rot in living or dead conifers and deciduous trees, such as Morus alba, Populus spp., Fraxinus mandshurica, and Sophora japonica (Tura, Zmitrovich et al. 2009, Yang, Bao et al. 2019). The species is widely distributed across Asia, Europe, North Africa, and North America and is used as an important health product and medical material, mainly in East Asian countries, namely China, Japan, and South Korea (Rong-Wei, Shuang-Tian et al. 2021, Wu and Dai 2022). In China, the fruiting body of I. hispidus is mostly saturated in water and is as a health drink (Liu, Hou et al. 2019). In addition, it serves as a diuretic, astringent, and therapy for inflammation and oral ulcers in folk medicine (Yousfi, Djeridane et al. 2009). According to recent studies, extracts of the fruiting body of I. hispidus show antiviral, antioxidant, antitumor, hypolipidemic and immunomodulatory effects (Awadh Ali, Mothana et al. 2003, Zan, Qin et al. 2011, Benarous, Bombarda et al. 2015, Gründemann, Arnhold et al. 2016, Ren, Lu et al. 2017). Thus, I. hispidus is currently very highly valued and has strong potential for the future development of health products and medicines.

I. hispidus is also known as Sanghuang in some regions of Chengde (Hebei Province), Xiajin (Shandong Province), Linqing (Shandong Province), and southern Xinjiang, China (Bao, Yang et al. 2017, Li and Bao 2022). Even though dozens of fungal species have been called “Sanghuang” in China, including Phellinus igniarius, Sanghuangporus baumii, and Fomitiporia ellipsoidea, recently only I. hispidus has been regarded as the sole mushroom showing the characteristics of Sanghuang recorded in the ancient Chinese Materia medica books, such as Shen Nong’s Herbal Classic and the Compendium of Materia Medica. (Cui, Dai et al. 2009, Bao, Yang et al. 2017, Li and Bao 2022). I. hispidus has long been used in traditional Chinese medicine in Chengde (Song, Wang et al. 2016, Li and Bao 2022). The I. hispidus strain from Chengde has also been introduced into the Jilin and Shandong Provinces for the purpose of fruiting body production and pharmacological studies (Li and Bao 2022, Zou, Song et al. 2022). The I. hispidus strain from Chengde used in this study was isolated from a mulberry tree over 300 years old at the Chengde Mountain Resort, giving this strain significant historical and research value. Although the I. hispidus strains of Aksu (Xinjiang), Harbin (Heilongjiang), Xiajin (Shandong), and Linqing (Shandong) have been sequenced, whole genome sequencing of the I. hispidus strain from Chengde Mountain Resort still has great significance for studying the genomic and functional differences of I. hispidus from different regions, and to enrich the genomic diversity of I. hispidus (Tang, Jin et al. 2022, Zhang, Feng et al. 2022, Jinglin 2023, Wang, Bao et al. 2023). In addition, access to genomic information on I. hispidus "CDMR" strain can contribute to genetic and genomic research on its nutritional and therapeutic traits.

Sample collection

The mycelium sample of the Chengde Mountain Resort strain of I. hispidus (I. hispidus CDMR) used in this research was obtained from the Institute of Sericulture, Chengde Medical University (Chengde City, Hebei Province, China, 41º 1' 51.14" N, 117º 57' 3.19" E); this strain was artificially cultivated and domesticated from one of the spores of the fresh wild fruiting body originally collected from the Chengde Mountain Resort (Chengde, Hebei province, China, 40º 59' 37.80" N, 117º 55' 42.52" E) (Fig. 1). The specimen was identified as I. hispidus (Hymenochaetaceae: Basidiomycota) based on molecular biology, specifically the internal transcribed spacer region (ITS) sequencing and "blast" data from the database of the National Center for Biotechnology Information (NCBI; https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome).

The mycelium sample was cultivated in potato dextrose broth (PDB) medium (Beijing Solarbio Technology Co., Ltd, China) and cultured in a constant temperature incubator shaker (Changzhou Zhongjie Experimental Instrument Manufacturing Co., Ltd, China) at 150 rpm and 25°C for 12 days in the dark. A 100-mL volume of cultured mycelium fluid was centrifuged at 4000 rcf for 10 min at 4°C, the supernatant was discarded, and the precipitate was washed twice with sterile water before being frozen in liquid nitrogen. The specimen was collected with the permission of the Science and Technology Department of Hebei Province and deposited at the Institute of Sericulture (Chengde Medical University, Yongxue Song, [email protected]) under voucher number CDMUIHSZ5-2021002.

DNA extraction and sequencing

Genomic DNA from the mycelial sample was extracted using the sodium dodecyl sulfate kit from Beijing Novogene Co., Ltd. (Beijing, China) (Lim, Lee et al. 2016). The quality of the harvested DNA was detected by the agarose gel electrophoresis, and the concentration of it was quantified by Qubit® 2.0 Fluorometer (Thermo Scientific, MA, USA). We integrated the two technologies to sequence the entire genome of I. hispidus CDMR. Sequencing libraries were constructed with the insert sizes of 350 bp and 20 kb, using the NEBNext® Ultra™ DNA Library Prep Kit for Illumina (New England Biolabs Inc., MA, USA) and SMRTbellTM Template Prep Kit 1.0 (Pacific Biosciences, CA, USA) following the manufacturer’s instructions. The constructed sequencing libraries were sequenced using the Illumina NovaSeq and PacBio Sequel platforms from Beijing Novogene Bioinformatics Technology Co., Ltd (Beijing, China).

Genome assembly and component prediction

The raw sequencing data generated from the Illumina NovaSeq platform were filtered using readfq.v8_meta (https://github.com/NovogeneMicro/readfq.v8_meta) to obtain clean data. Subsequently, Jellyfish v2.3.0 (https://github.com/gmarcais/Jellyfish/releases/tag/v2.3.0) and GenomeScope2.0 (https://github.com/tbenavi1/genomescope2.0) were utilized to estimate the genome size, heterozygosity, and repeat content of I. hispidus CDMR. The initial genome assembly of clean sequencing data obtained from the PacBio Sequel platform was conducted using SMRT Link v5.0.1. Subsequently, the Arrow algorithm of the Variant Caller module within SMRT Link v5.0.1 was employed to correct the preliminary assembly results. Upon completion of the genome assembly using PacBio Sequel sequencing data, the first round of correction was performed using the Quiver tool within GenomicConsensus v2.3.3 (https://github.com/lukeping/GenomicConsensus) with default parameters. Subsequently, the clean data from the Illumina NovaSeq platform was aligned to the assembled genome using BWA v0.7.17 (https://github.com/lh3/bwa), followed by the application of Pilon v1.24 (https://github.com/broadinstitute/pilon) to correct errors, which was repeated for a total of five iterations.

The Augustus 2.7 program was used to predict the coding genes. The interspersed repetitive sequences were predicted using RepeatMasker (http://www.repeatmasker.org/), and tandem repeats were analyzed using the Tandem Repeats Finder (https://tandem.bu.edu/trf/trf.html). The transfer RNA (tRNA) genes and ribosome RNA (rRNA) genes were predicted by the tRNAscan – SE 2.0 (http://lowelab.ucsc.edu/tRNAscan-SE/) and rRNAmmer 1.2 (https://services.healthtech.dtu.dk/software.php), respectively. Small RNAs (sRNAs), small nuclear RNAs (snRNAs), and microRNAs (miRNAs) were predicted by the Basic Local Alignment Search Tool (BLAST) against the RNA families (Rfam) database (https://rfam.org/) using the Basic Local Alignment Search Tool. Additionally, detailed genomic component information was visualized using Circos software (https://circos.ca/) (Krzywinski, Schein et al. 2009).

Gene function annotation

The DIAMOND v2.1.5 application (https://github.com/bbuchfink/diamond/releases) was used to annotate functions of the predicted gene sequences by comparing these sequences with seven databases, namely the Gene Ontology (GO, http://geneontology.org/), Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/), Cluster of Orthologous Groups of proteins (COG, http://www.ncbi.nlm.nih.gov/COG/), Non-Redundant (NR) Protein Sequence Database, Transporter Classification Database (TCDB, https://tcdb.org/), InterPro database (https://www.ebi.ac.uk/interpro/), and UniProt database (https://www.ebi.ac.uk/uniprot/) (Li, Jaroszewski et al. 2002, Saier, Reddy et al. 2014, Paysan-Lafosse, Blum et al. 2023). Based on the Carbohydrate-Active Enzymes (CAZy) database, carbohydrate-related enzymes were annotated using HMMER v3.3.2 (http://www.hmmer.org/) (Cantarel, Coutinho et al. 2009). The SignalP v5.0 (https://services.healthtech.dtu.dk/services/SignalP-5.0/) and TMHMM − 2.0 (https://services.healthtech.dtu.dk/services/TMHMM-2.0/) were used to predict the secretory proteins, and the secondary metabolism gene clusters were analyzed using antiSMASH v6.0.1 (Medema, Blin et al. 2011). In addition, based on the Fungal Cytochrome P450 Database (FCPD), DIAMOND v2.1.5 application was used to annotate cytochrome P450 (CYP450) (Park, Lee et al. 2008). Pathogen-host interaction analysis was also performed using DIAMOND v2.1.5, based on the Pathogen Host Interactions Database (PHI, http://www.phi-base.org/) (Urban, Pant et al. 2015).

Genome sequencing, assembly, and component prediction

Because the ITS sequence of I. hispidus CDMR shares 99.76% identity with the I. hispidus clone SH2.107 (MN699466.1), it was conclusively identified as I. hispidus (Fig.S1). On the Illumina NovaSeq platform, 4,137 Mbp of raw data were generated and subsequently filtered to yield 3,259 Mbp of clean data (Table S1). With K-mer = 15, the genome size of I. hispidus CDMR was estimated to be 38.46 Mbp (Table S2, Fig.S2). Additionally, genome heterozygosity and repeat rates were 0.76% and 32.45%, respectively (Table S2). On the PacBio Sequel platform, a total of 4,956 Mbp clean data were obtained, and the N50 length of the reads was 15,589 bp (Table S3). The final assembled genome of the I. hispidus CDMR was 34.22 Mb in length; the N50 length of contigs was 617,498 bp, and the guanine-cytosine (GC) content was 48.40% (Table S4).

The genome of I. hispidus CDMR was predicted to contain 7,723 coding genes, totaling 15,111,180 bp, with an average gene length of 1,957 bp (Table S5). In addition, 8,100 repetitive sequences with a total length of 1,131,456 bp were predicted, accounting for 3.31% of the whole genome of I. hispidus CDMR (Tables S6 and S7). Among the predicted repetitive sequences, there were 2,589 interspersed repetitive sequences and 5,511 tandem repeats (Tables S6 and S7). The interspersed repetitive sequences included 1,791 long terminal repeats (LTR, 763,503 bp in total), 453 transposons (56,717 bp in total), 291 long scattered elements (LINE, 21,238 bp in total), six short scattered elements (SINE, 620 bp in total), 36 rolling circles (RC, 10,832 bp in total), and 12 unknown interspersed repetitive sequences (997 bp in total) (Table S6). The tandem repeats included 2,977 long tandem repeats (LTAR, 166,872 bp in total), 1,916 minisatellite DNAs (88,250 bp in total), and 618 microsatellite DNAs (23,427 bp in total) (Table S7). In addition, the ncRNAs in the genome of the I. hispidus CDMR was predicted to include 91 tRNAs (7,573 bp in total), 13 rRNAs (26,431 bp in total), and 15 snRNAs (1,877 bp in total) (Table S8). Furthermore, based on the aforementioned findings, detailed genomic component information was visually represented (Fig.S3).

Gene function annotation

To gain a comprehensive understanding of the general function of the 7,723 predicted coding genes in the genome of the I. hispidus CDMR, they were analyzed using 9 publicly available databases (GO, KEGG, COG, NR, TCDB, InterPro, and UniProt) based on sequence and motif similarities and differences between the genes annotated from our sample and the relevant genes from the databases (Table S9).

There were 5,012 genes annotated by functional classification in the GO database. In terms of ontology, the largest number of genes were involved in biological processes (Table S9, Fig. 2A). The functional class of cellular processes (2,679 genes) had the highest gene enrichment in the ontology of biological process, both the class of cell (1,739 genes) and the class of cell part (1,739 genes) had the highest gene enrichment in the ontology of cellular component, and the class of binding (2,894 genes) had the highest gene enrichment in the ontology of molecular function (Fig. 2A).

In addition, based on the functional classification of the KEGG database, there were a total of 5,714 genes annotated (Table S9). Among the six classifications of the KEGG pathways, the metabolism classification involved the highest number of genes (1,456) (Fig. 2B). Furthermore, we discovered that the gene function with the strongest enrichment in the classification of metabolism was the “global and overview maps” (554 genes), while the gene function with the highest enrichment in the classification of genetic information processing was "translation" (224 genes), the gene function with the highest enrichment in the classification of human diseases was "infectious diseases: viral" (132 genes), the gene function with the highest enrichment in the classification of cellular processes was "transport and catabolism" (207 genes), the gene function with the highest enrichment in the classification of organismal systems was "endocrine system" (84 genes), and the gene function with the highest enrichment in the classification of environmental information processing was " signal transduction" (197 genes) (Fig. 2B).

Based on the annotation results of the COG database, 1,209 genes were classified into 24 categories, and the top 5 enriched categories were: “posttranslational modification protein turnover chaperones” (148 genes), “translation ribosomal structure and biogenesis” (136 genes), “general function prediction only” (120 genes), “energy production and conversion” (103 genes), and “amino acid transport and metabolism” (99 genes) (Table S9, Fig. 3A). Furthermore, 6,576 genes were annotated using the NR database. Figure 3B presents the top 20 rankings based on the number of genes identified as matches with genes from other species in the NR protein sequence database (Table S9). The top 3 matched species were Sanghuangporus baumii (4,624 genes), Fomitiporia mediterranea (1,228 genes), and Phellinidium pouzarii (235 genes) (Fig. 3B).

Figure 3 Gene function annotation of I. hispidus CDMR using the COG database (A) and the top 20 ranking based on the number of genes identified as matches with genes from other species in the NR protein sequence database (B)

Figure 4A shows the classification of 297 genes into 7 transporter classes based on the TCDB annotation results (Table S9). The top three transporter classes were as follows: "3: Primary active transporters", with 96 genes; "2: Electrochemical potential-driven transporters", with 95 genes; and "9: Incompletely characterized transport systems", with 43 genes (Fig. 4A). Moreover, based on the annotation results of the InterPro database, there were a total of 5,012 genes annotated, and the top three enriched clans were: “P-loop containing nucleoside triphosphate hydrolase superfamily” (1,399 genes), “FAD/NAD(P)-binding Rossmann fold superfamily” (893 genes), and “Protein kinase superfamily” (465 genes) (Table S9, Fig. 4B). In addition, 1,639 genes were annotated by comparison with the UniProt database (Table S9).

Carbohydrate-active enzymes analysis

Based on the annotation results from the CAZy database, 313 genes were classified into 134 CAZy families belonging to six CAZy classes (Table S10, Fig. 5A). The results indicate that there are 150 genes (72 families) in the glycoside hydrolases (GHs) class, 72 genes (26 families) in the glycosyl transferases (GTs) class, 44 genes (12 families) in the auxiliary activities (AAs) class, 21 genes (9 families) in the carbohydrate esterases (CEs) class, 16 genes (7 families) in the carbohydrate-binding modules (CBMs) class, and 10 genes (8 families) in the polysaccharide lyases (PLs) class (Fig. 5A). Moreover, the top 3 CAZy families ranking based on the number of genes annotated in the GHs class is GH18 (11 genes), GH16_1 (7 genes), and GH5_9 (7 genes); the top 3 CAZy families ranked based on the number of genes annotated in the GTs class were GT22 (12 genes), GT0 (7 genes, glycosyl transferases not yet assigned to a family), and GT4 (7 genes); the top 3 CAZy families ranking based on the number of genes annotated in the AAs class were AA3_2 (12 genes), AA9 (8 genes), and AA2 (7 genes). The top 3 CAZy families ranked based on the number of genes annotated in the CEs class were CE4 (6 genes), CE8 (5 genes), and CE5 (3 genes). The top 3 CAZy families ranked based on the number of genes annotated in the CBMs class were CBM13 (8 genes), CBM1 (2 genes), and CBM50 (2 genes); and the PL14_4 CAZy family has the most of genes annotated in the PLs class. Each of the rest of the CAZy families had only one gene (Table S10). Figure 5B presents the top 20 CAZy family rankings based on the number of genes annotated in the CAZy database; the top 3 CAZy families were AA3_2 (12 genes), GT22 (12 genes), and GH18 (11 genes). These rankings are shown in Table S11.

Secretory proteins analysis

The SignalP v5.0 software identified 507 proteins that contained signal peptides, and the TMHMM software (version 2.0) recognized 1,542 proteins that contained transmembrane helices (Table S12, S13). Ultimately, 340 secretory proteins were identified, which were distinguished by the presence of a signal peptide lacking transmembrane helices (Table S14).

Secondary metabolism gene clusters analysis

AntiSMASH v6.0.1 recognized 18 secondary metabolism gene clusters, which contained 128 genes in total, and these genes were distributed among 15 contigs (1–3, 6, 8–10, 23, 24, 32, 36, 42, 43, 54, and 64) (Table S15). The secondary metabolism gene clusters were classified into five categories (Fig. 6). The terpene category contained the largest number of secondary metabolism gene clusters (10) and 58 predicted genes. The other four categories were NRPS – like (Nonribosomal peptide synthetase - like), T1PKS - NRPS – like hybrid (Simultaneously regulate Type I Polyketide Synthase and Nonribosomal peptide synthetase - like), NRPS (Nonribosomal Peptide Synthetases), and T1PKS (Type I Polyketide Synthase), and they had 4, 2, 1, 1 secondary metabolism gene clusters, respectively, and contained 35, 19, 6, 10 predicted genes, respectively (Fig. 6).

Cytochrome P450 analysis

A total of 116 genes were annotated using the Fungal Cytochrome P450 Database; 104 of these genes were classified into 6 P450 classes, and the class of the remaining 12 genes was undetermined (Table S16). Class E-class P450, group I (74 genes), had the highest number of annotated genes among the 6 P450 classes (Table S16, Fig. 7). The remainder of the 5 P450 classes were Cytochrome P450 (14 genes), E-class P450, group IV (9 genes), Pisatin demethylase-like (3 genes), P450, and CYP52 (3 genes), and E-class P450, CYP2D (1 gene) (Fig. 7).

Pathogen–host interactions analysis

In total, 728 genes were annotated using the PHI database (Table S17). In addition, 694 of these genes were sorted into 7 PHI phenotypes, whereas the phenotypes of the remaining 34 genes were undetermined (Fig. 8). Moreover, the PHI phenotype with reduced virulence, comprising 353 predicted genes, exhibited the highest number of annotated genes among the 7 PHI phenotypes. The rest of the six PHI phenotypes were as follows (Fig. 8): the PHI phenotype of unaffected pathogenicity (166 genes), the PHI phenotype of loss of pathogenicity (84 genes), the PHI phenotype of lethality (55 genes), the PHI phenotype of increased virulence (hypervirulence) (24 genes), the PHI phenotype of effector (plant avirulence determinant) (9 genes), and the PHI phenotype of chemistry target: resistance to chemicals (3 genes).

Comparison of genomic information

In Chengde (Hebei Province), Xiajin (Shandong Province), Linqing (Shandong Province), and southern Xinjiang, I. hispidus is commonly referred to as Sanghuang because of its morphological similarity to Sanghuang-like fungi. Currently, the strains of I. hispidus in various regions and certain species of Sanghuang-like fungi have undergone complete genome sequencing. In the present study, we sequenced the whole genome of the I. hispidus strain of Chengde Mountain Resort (CDMR). There are four known strains of I. hispidus in China: Xiajin (Shandong Province), Linqing (Shandong Province), Aksu Prefecture (Xinjiang Province), and Harbin (Heilongjiang Province) have had their whole genome sequenced, and the genome size is reported to be 34.14, 35.68, 34.02, and 40.27 Mb, respectively (Table S18) (Tang, Jin et al. 2022, Zhang, Feng et al. 2022, Jinglin 2023, Wang, Bao et al. 2023). The genome sizes of the known strains range from 34.02 to 40.27 Mb, and the genome size of I. hispidus CDMR, being 34.33 Mb, falls within this range. The variation in genome size among these five strains of I. hispidus may be attributed to genome differences among the strains distributed in different regions as well as the differences in sequencing and genome assembly strategies. Such differences were also found in Inonotus obliquus and Sanghuangporus sanghuang. In the case of the former the genome size of the Harbin strain (Heilongjiang Province) and the strain from the China Forestry Culture Collection Center (Beijing Province, China) were 38.18 and 36.13 Mb respectively. As for S. sanghuang, the genome size of the Shanghai strain (Shanghai Province) and the Zhejiang strain (Zhejiang Province) were 40.50 and 33.34 Mb, respectively (Table S18) (Jiang, Wu et al. 2021, Duan, Han et al. 2022, Hao, Wang et al. 2023, Wang, Wei et al. 2024). Furthermore, noticeable differences were also found in GC content, predicted gene count, average gene size, and quantity of tRNAs and rRNAs among the five strains of I. hispidus (Table S18). The GC content across these strains ranged from 47.76–51.62%, and the predicted gene counts ranged from 7,723 to 12,304. The average gene size varied from 1,537 to 2,024 bp, and the number of tRNAs and rRNAs ranged from 88 to 123 and 9 to 17, respectively (Table S18). Similar differences were also noted in different strains of Inonotus obliquus and Sanghuangporus sanghuang (Table S18). The GC content and predicted gene count of the Harbin strain (Heilongjiang Province) and the China Forestry Culture Collection Center strain (Beijing Province, China) of Inonotus obliquus were 47.56% and 47.39%, and 12,525 and 8,353, respectively (Table S18). The GC content, predicted gene count, and average gene size of the Shanghai and Zhejiang strains of Sanghuangporus sanghuang were 47.89% and 48.04%, 12,307 and 8,278 genes, 1, 877 and 1,597 bp, respectively (Table S18). Hence, by sequencing the entire genome of various strains from different regions of the same species, we can gain deeper insights into the genomic information of this species. Moreover, this research has significant implications for understanding the adaptability of regional strains to their respective locales.

Gene function analysis

The plant cell wall is primarily composed of cellulose, hemicelluloses, pectin, and lignin (Aro, Pakula et al. 2005). Among these components, cellulose is the most abundant polysaccharide in nature. Approximately 4 billion tons of cellulose are produced each year but do not persist in this form, as fungi and bacteria continually break down this material (Aro, Pakula et al. 2005). Fungi are the foremost microorganisms in the natural degradation of lignocellulose, and most wood-degrading fungi belong to the Basidiomycota division (Yongxin 2015, Jibin, Chenyang et al. 2017). Basidiomycota fungi are mainly composed of large fungi represented by edible and medicinal fungi. I. hispidus, S. sanghuang, Ganoderma, and Lentinula edodes, etc., all belong to the Basidiomycota (Microbiology 2019). Fungi degrade lignocellulose primarily through the secretion of various enzymes, including carbohydrate-active enzymes (Xulie 2020). Carbohydrate-active enzymes are important tools for fungi to adapt to the environment and absorb carbon-sourced nutrients (Jinglin 2023). These enzymes deconstruct, synthesize, and catalyze carbohydrates in various ways (Gavande, Goyal et al. 2023). Among the carbohydrate-active enzymes, the AAs class is a widely distributed category of catalytic modules essential for the degradation of plant cell walls (Aro, Pakula et al. 2005). Enzymes classified under family 3 of the AAs class (AA3 enzymes) belong to the glucose-methanol-choline oxidoreductases family (Aro, Pakula et al. 2005). These enzymes are predominantly found in wood-degrading fungi and play a crucial role in facilitating lignocellulose degradation, often in conjunction with other AA enzymes, such as peroxidases (AA2) and lytic polysaccharide monooxygenases (AA9) (CAZypedia 2024). Moreover, aryl alcohol oxidoreductases within the AA3_2 family are secreted by basidiomycete fungi and are believed to play pivotal roles in lignin degradation (CAZypedia 2024). In the present study, the top 3 CAZy families based on the number of genes annotated in the AA class of I. hispidus CDMR were AA3_2 (12 genes), AA9 (8 genes), and AA2 (7 genes). Remarkably, family AA3_2 not only ranked first within the AA class but also held the top position across all six CAZy classes in terms of gene annotations. Our results are consistent with the aforementioned description; enzymes within the AA3_2 family secreted by I. hispidus CDMR play a pivotal role in lignin degradation and have important roles in maintaining the growth and development of I. hispidus CDMR.

In recent decades, there has been growing focus on triterpenes, a class of compounds characterized by a five- or four-ring skeleton accompanied by carboxyl, hydroxyl, or oxo groups (Bednarczyk-Cwynar and Zaprutko 2015). Triterpenes are mainly secreted by the living tissues of plants and certain fungi, notably several commonly utilized Chinese herbal medicines, such as Ginseng, Astragalus, Panax notoginseng, Ganoderma lucidum, and Antrodia camphorate (Bednarczyk-Cwynar and Zaprutko 2015, Tingting 2017). Triterpenes display extensive chemical diversity and a spectrum of biological properties (Bednarczyk-Cwynar and Zaprutko 2015, Tingting 2017). Pharmacological tests have demonstrated their efficacy in various domains, including but not limited to anticancer, antiviral, antibacterial, hepatoprotective, cardiovascular, antihyperlipidemic, antioxidant, anti-inflammatory, antiulcer, analgesic, antinociceptive, and antidiabetic effects (Bednarczyk-Cwynar and Zaprutko 2015, Tingting 2017). Triterpenes are crucial secondary metabolites found in I. hispidus (Dongchao 2022). Research has established that triterpenes secreted by I. hispidus possess various biological activities, including antiviral, hypoglycemic, and hypolipidemic properties (Dongchao 2022). In the genome of I. hispidus CDMR, the terpene category had the highest count of secondary metabolism gene clusters, comprising 10 clusters and 58 genes. This result is consistent with previous reports, in which secondary metabolic gene clusters involved in terpene regulation were most frequently identified in the genomes of the Xiajin strain (Shandong Province) and the Aksu Prefecture strain (Xinjiang Province) of I. hispidus. Specifically, 8 of 15 secondary metabolism gene clusters were found to be associated with terpene regulation in the Xiajin strain and 12 of 20 in the Aksu Prefecture strain (Zhang, Feng et al. 2022, Wang, Bao et al. 2023). Hence, triterpenes serve as significant secondary metabolites in I. hispidus and play important roles in biological functions that promote human health.

To the best of our knowledge, our study is the first in which the whole genome of I. hispidus CDMR has been sequenced. We accomplished this by using a combination of the Illumina NovaSeq and PacBio Sequel platforms. After data filtering and assembly, the genome size was determined to be 34.22 Mb. We identified 7,723 coding genes, 8,100 repetitive sequences, 91 tRNAs, 13 rRNAs, and 15 snRNAs in the genome. Furthermore, through comprehensive annotation, we annotated 5,012 genes using the GO database, 5,714 genes using the KEGG database, 1,209 genes using the COG database, 6,576 genes using the NR database, 297 genes using the TCDB database, 5,012 genes using the InterPro database, and 1,639 genes using the Uniprot database. Moreover, we discovered significant associations with various functional categories, including 313 genes related to carbohydrate-active enzymes, 340 genes associated with secretory proteins, 128 genes involved in secondary metabolism, 116 genes related to Cytochrome P450, and 728 genes implicated in pathogen–host interactions. Our findings offer comprehensive insights into the genome of I. hispidus CDMR, fostering the exploration of genomic and functional variances among I. hispidus populations from diverse regions in China. Moreover, this study holds promise for advancing the genetic and genomic investigations of the nutritional and therapeutic attributes of I. hispidus.

Supplementary information Supplemental figures and supplemental tables are available online at GENETICA.

Acknowledgements This study was supported by the Key R&D Program of Hebei Province (20326327D).

Authors contributions Yongxue Song and Chunzheng Fu conceived and designed this project. Donghao Zhang, Xiuling Chen and Hui Wang collected and cultivated the sample; Chunzheng Fu analyzed the data and drafted the manuscript; Yongxue Song and Jisheng Li provided supervision and revised the manuscript. All authors read and approved the final manuscript.

Funding Not applicable.

Data availability Sequencing data of the Inonotus hispidus genome of this study have been deposited at NCBI BioProject (http://www.ncbi.nlm.nih.gov/bioproject) under the accession number PRJNA1100408.

Conflict of interest No potential conflict of interest was reported by the author(s).

Ethical approval Samples were collected under the supervision of the Science and Technology Department of Hebei Province.

Consent to participate Not applicable.

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Whole genome sequencing and analysis of Inonotus hispidus isolated from the Chengde Mountain Resort, China

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Abstract

Figures

Introduction

Materials and Methods

Sample collection

DNA extraction and sequencing

Genome assembly and component prediction

Gene function annotation

Results

Genome sequencing, assembly, and component prediction

Gene function annotation

Carbohydrate-active enzymes analysis

Secretory proteins analysis

Secondary metabolism gene clusters analysis

Cytochrome P450 analysis

Pathogen–host interactions analysis

Discussion

Comparison of genomic information

Gene function analysis

Declarations

References

Additional Declarations

Supplementary Files

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