De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morphological development

De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morphological development

Journal Pre-proofs De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morp...

2MB Sizes 0 Downloads 35 Views

Journal Pre-proofs De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morphological development Jinqiu Wang, Xuefei Wen, Bowen Yang, Dayu Liu, Xiang Li, Fang Geng PII: DOI: Reference:

S0141-8130(19)36671-1 BIOMAC 13506

To appear in:

International Journal of Biological Macromolecules

Received Date: Revised Date: Accepted Date:

20 August 2019 14 September 2019 17 September 2019

Please cite this article as: J. Wang, X. Wen, B. Yang, D. Liu, X. Li, F. Geng, De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morphological development, International Journal of Biological Macromolecules (2019), doi: 10.1016/j.ijbiomac.2019.09.210

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier B.V.

De novo transcriptome and proteome analysis of Dictyophora indusiata fruiting bodies provides insights into the changes during morphological development

Jinqiu Wang, Xuefei Wen, Bowen Yang, Dayu Liu, Xiang Li, Fang Geng*

College of Pharmacy and Biological Engineering, Key Laboratory of Coarse Cereal Processing (Ministry of Agriculture and Rural Affairs), Chengdu University, No. 2025 Chengluo Avenue, Chengdu, 610106, P. R. China


Corresponding authors:

Dr. Fang Geng, E-mail: [email protected]

Abstract De novo transcriptome assembly and shotgun proteome analysis of Dictyophora indusiata fruiting bodies were performed. A total of 19704 unigenes were sequenced, and 4380 proteins were identified. Annotation and functional analysis of the identified proteins were significantly enriched in small molecule synthetic and metabolic processes, protein modification regulation (phosphorylation and ubiquitination), and vesicle transport. Furthermore, quantitative developmental transcriptome analysis was performed between the peach-shaped and mature fruiting bodies, and the results revealed that the metabolism and transport activities were upregulated in the mature stage, while protein translation was downregulated; this regulation is likely the main reason for the significant changes in the nutrients of fruiting bodies. Furthermore, the cell wall stress-dependent MAPK sub-pathway was activated in the mature stage, and fungal cell wall degradation-related genes were upregulated, which could promote reconstruction of the cell wall and might play a key role in the morphological development of D. indusiata fruiting bodies.

Keywords Dictyophora indusiata; transcriptome; proteome; carbohydrate-active enzymes; morphological development

1. Introduction The fruiting body of Dictyophora indusiata, also known as bamboo fungus, is an edible mushroom prized in the world market for its beautiful appearance, distinctive flavor, high nutritive value and healthcare benefits [1-6]. In recent years, many reports have proved the antimicrobial, antioxidant, antitumor, and immunomodulation effects of the bioactive ingredients from D. indusiata fruiting bodies, such as polysaccharides, flavonoids, proteins and others [7-12]. Therefore, D. indusiata fruiting bodies have become more valuable because of their great potential as a functional food and medicines. For a long time, D. indusiata fruiting bodies were only collected in the wild, so the yield was low, and the price was high. Recently, the artificial cultivation of D. indusiata has been studied, some cultivation techniques have been promoted and applied in China, and the output has increased year by year. Correspondingly, the processing and consumption of D. indusiata fruiting body has developed rapidly. However, as a kind of edible fungus rich in water, D. indusiata fruiting body will undergo vigorous physiological processes during post-harvest processing and storage, which lead to the shortening of its shelf life and greatly restrict its consumption and trade. Currently, artificial drying of D. indusiata fruiting body is the most common and effective process to extend its shelf life. However, this process is not only time-consuming and energy-consuming but also results in the loss of nutrition and unrecoverable changes in the texture of the fruiting body. Post-harvest management is one of the effective ways to extend the shelf life of fresh fruiting bodies. Therefore, it is very important to understand the post-harvest physiological processes of D. indusiata fruiting body. In the industrialized cultivation cycle, the developmental process of D. indusiata can be divided into five major stages: undifferentiated mycelia, primordia, ball-shaped stage, peach-shaped stage and the

mature stage. At the peach-shaped stage, D. indusiata fruiting body has completely differentiated and is edible. Under suitable circumstances (such as high humidity, good ventilation), the peach-shaped D. indusiata fruiting body can rapidly (in several hours) extend to its full length coupled with the expansion of its veil, and the mature fruiting body is developed. The mature fruiting bodies of D. indusiata are the main form for consumption; however, peach-shaped fruiting bodies are easier to transport and have a longer storage period. Therefore, it is an alternative to harvest the peach-shaped fruiting body for storage and transport. Accordingly, it is urgent to explore and reveal the differences in nutrition and quality between these two morphological fruiting bodies of D. indusiata, as well as the underlying physiological and molecular mechanisms of the formation of differences during morphological development, for the post-harvest management, processing and utilization of D. indusiata. However, these issues have not yet attracted attention and have not been studied. The morphological development of D. indusiata from the peach-shaped stage to mature stage involves systematic physiological changes, so it is appropriate to explore them through systematic research methods, such as high-throughput omics technologies. For edible mushrooms, transcriptome and proteome analyses have been used for systematic exploration of the comprehensive differences between multiple samples. For example, a comparative transcriptomic analysis conducted in the Bailinggu (Pleurotus tuoliensis) mushroom revealed that genes involved in morphogenesis, primary carbohydrate metabolism, cold stimulation and blue-light response were important to fruiting body formation [13]. For shiitake (Lentinula edodes), comparative transcriptome analysis of mycelium grown under three different conditions revealed that candidate genes for light-induced BF formation encoded

proteins linked to light reception, light signal transduction pathways and pigment formation [14]. In our previous studies, de novo transcriptome, proteome and metabolome analyses were employed to investigate the eating qualities of the morel (Morchella importuna), and total of 8495 unigenes, 4047 proteins and 30 metabolites were identified in morel fruiting body; the results provided insights into the taste formation, texture regulation and color changes of morel fruiting body [15, 16]. These findings suggested that omics technologies are effective tools to find critical information from complex systems. Therefore, de novo transcriptome and proteome analyses of D. indusiata fruiting body were conducted, and a comparative analysis of the transcriptome between the peach-shaped fruiting body and mature fruiting body was further carried out in the present study, aiming to obtain a comprehensive and systematic understanding of the physiological processes and underlying molecular mechanisms in D. indusiata fruiting bodies during morphological development.

2. Materials and methods 2.1. D. indusiata Samples Fresh peach-shaped and mature fruiting body of D. indusiata were collected from a cultivated field in Guizhou, Guangxi province of China. After harvest, the samples were delivered immediately to the laboratory. The fruiting bodies without any physical damage and uniform in size were selected for further experiments. For transcriptome and proteome analyses, the selected fruiting bodies were longitudinally cut along the central axis, and approximately 2-mm-thick sliced tissue was tacked, then frozen and ground to power in liquid nitrogen. Samples from 10 fruiting bodies were merged together as a biological repeat, and three biological replicates of each

stage of D. indusiata were prepared for omics analysis. For nutrient determination, the selected fruiting bodies were homogenized with ice, and the homogenates from 3 fruiting bodies were merged together as a biological repeat; five biological replicates of each stage of D. indusiata were prepared and used for the determination of nutrients. 2.2. Determination of nutrients The moisture content of D. indusiata fruiting bodies was determined by the “forced draft oven” method at 105 °C; the Kjeldahl nitrogen method and Soxhlet method were employed to determine protein content and total lipid content, respectively [17-19]. Water-soluble polysaccharide was extracted by ultrasonic extraction using water at a ratio of 1:50 (dry fruiting body: water, w/v) and then determined by the phenol-sulfuric acid method [20, 21]. The crude fiber was estimated using the traditional Van Soest method [22]. All measurements were carried out with five replicates. The data are presented as the mean values with standard deviations (mean ± SD). Statistical analyses were performed using the statistical program GraphPad Prism 7.00 (GraphPad Software Inc., La Jolla, CA, US) by t-test. 2.3. RNA extraction and de novo assembly of D. indusiata transcriptome The total RNA was extracted from D. indusiata samples using TRIzol (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocols. The RNA concentration and integrity were determined by using a Nanodrop2000 (Thermo Fisher Scientific, Waltham, MA, USA) and Agilent Technologies 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA), respectively. The cDNA libraries were prepared by using the Illumina TruSeq RNA sample preparation kit according to the manufacturer’s instructions and then were sequenced using Illumina HiSeq 4000 (Illumina, San Diego, CA, USA). Before assembly, the raw data were filtered using





( with default parameters to remove adaptors, low-quality reads, reads with ambiguous bases ‘N’, and reads of less than 30 bp. No reference genome was available for D. indusiate; therefore, de novo assembly of the clean reads was performed using Trinity ( The longest assembled transcripts were defined as unigenes and then were subjected to further functional annotation by aligning against protein sequence databases including NR, Swiss-Prot and COG using DIAMOND. Meanwhile, unigenes were also annotated by Pfam using HMMER 3.0, by Kyoto Encyclopedia of Genes and Genomes (KEGG) using KOBAS, and by Gene Ontology (GO) using Blast2GO. Furthermore, unigenes were annotated using dbCAN for carbohydrate-active enzyme (CAZyme) families (based on CAZyDB 07/15/2016). Three biological replicates were performed for each stage. 2.4. Analysis of differentially expressed genes (DGEs) To identify the differentially expressed genes (DEGs) between the fresh peach-shaped and mature fruiting body of D. indusiata, the mapping read counts to every assembled unigene was calculated by the program RSEM and normalized to FPKM for gene expression analysis. Then, DEGseq2 was used to statistically analyze the raw counts obtained by RSEM and to screen the differentially expressed genes whose q-values were less than 0.05 and for which there was an absolute value of log2 Ratio ≥ 1 between the two samples. Further, the identified DEGs were subjected to GO and KEGG pathway analysis. 2.5. Total protein extraction and 2D-LC-MS/MS proteomic analysis A standard protein extraction process was employed [23, 24], and the protein concentration was determined with a BCA kit according to the manufacturer’s

instructions. The mixture of extracted proteins (200 μg) was used for the following analysis. The extracted D. indusiata proteins were alkylated with 50 mmol/L of iodoacetamide for 40 min at room temperature in the dark and were subsequently were digested using trypsin (Sigma-Aldrich) at a 1:50 trypsin-to-protein mass ratio for the first digestion overnight and a 1:100 trypsin-to-protein mass ratio for a second 4-h digestion [25, 26]. Three biological replicates were performed to ensure protein reproducibility. The peptide mixture resulting from the mixing of three biological replicates was fractionated using an off-line high-pH reversed-phase liquid chromatography (RPLC) fractionation protocol with an Agilent 300Extend C18 column (5 μm, 4.6×250 mm) on a Waters ACQUITY UPLC (Dionex, Sunnyvale, CA, USA). Elution buffers were adjusted to a pH of 9.0 with ammonium hydroxide. The fractionation was carried out with a gradient of 8% to 32% acetonitrile for 60 min. A total of 60 concatenated fractions were collected according to the elution time, and then those fractions were randomly pooled into 18 samples. Following rotation vacuum concentration (Christ RVC 2-25, Christ, Germany), the 18 samples were dissolved in the loading buffer for LC-MS/MS [27, 28]. The 18 samples resulting from the high-pH reversed-phase fractionation were analyzed with an Easy-nLC1000 (Thermo scientific, Proxeon, Odense, Denmark) coupled to a Q-Exactive mass spectrometer (Thermo Scientific, San Jose, CA, USA) [25]. 2.6. Database search and bioinformation analysis of the identified proteins The acquired MS/MS spectra were searched using the Maxquant search engine (v. against the de novo sequenced transcriptome concatenated with a reverse decoy database. Trypsin/P was specified as cleavage enzyme allowing up to 2 missing cleavages. The mass tolerance for precursor ions was set as 20 ppm in First search and

5 ppm in Main search, and the mass tolerance for fragment ions was set as 0.02 Da. Carbamidomethyl on Cys was specified as fixed modification, oxidation on Met was specified as variable modifications, and peptide and protein false discovery rate (FDR) ≤ 0.01 [29]. The subcellular localization of the D. indusiata proteome was predicted using WoLF PSORT ( [30]. GO annotations of the D. indusiata proteome







(www. InterProScan ( was used to annotate protein GO functions based on the protein sequence alignment method. Based on the GO annotation categories, a two-tailed Fisher’s exact test was used to test the enrichment of all identified D. indusiata proteins against all proteins from databases, and a GO term with a corrected p-value < 0.05 was considered significantly enriched.[31]

3. Results and discussion 3.1. Nutrient differences between peach-shaped and mature fruiting bodies of D. indusiate The moisture contents in the peach-shaped and mature fruiting bodies were 86.83% and 88.62%, respectively. This was consistent with most mushrooms: the fruit body absorbs a large amount of water during the maturation process and becomes more moist and sparse [32]. The major nutrient contents of these two samples were determined based on the dry weight. Generally, the peach-shaped fruiting body was significantly higher in protein, water-soluble polysaccharide, crude fiber and ash contents but was lower in total lipid contents (Table 1, p < 0.01). In detail, water-soluble polysaccharide of the peach-shaped fruiting body was 43.9% higher and

crude fiber was 54.1% higher than that of mature fruiting body. These results indicated that polysaccharides and cellulose undergo extensive metabolism or degradation during the morphological development of D. indusiate fruiting body. Accompanying the increase in lipid content in mature fruiting body, a partial conversion from carbohydrates to lipids was implied. These nutrient changes were consistent with the observed characteristics of mature fruiting bodies: fragile texture, stronger odor, and intense respiration. 3.2. Overview of D. indusiata fruiting body transcriptome High-throughput Illumina sequencing was performed for the cDNA derived from the fruiting bodies according to the transcriptome analysis workflow. A total of 48395514 - 51954318 raw reads were obtained from the 6 sequencings (3 biological replicates were performed for each stage). After data filtering and trimming, the numbers of high-quality clean reads ranged from 48080756 to 51618294, corresponding 7185197965 to 7724506990 bp of clean nucleotides with a Q20 percentage over 97% and a GC percentage between 47.39-47.67% (Table 2). In conclusion, all statistics illustrated that the quality of sequencing was high enough for further analysis. The reference genome for D. indusiata is not available yet; therefore, the sequencing data was de novo assembled using Trinity. These clean reads were assembled into 39177 transcripts and subsequently assembled into 19704 unigenes with an average length of 1454 bp and an N50 of 2290 bp. The unigene size distribution showed that almost three-quarters of the unigenes (74.4%) had lengths ranging from 0 to 1500 bp. (Figure 2A). 3.3. Annotation and analysis of the sequenced D. indusiata unigenes For functional annotation, all sequenced D. indusiata unigenes were searched

against public databases, and a total of 14911 unigenes (75.7%) were annotated and functionally classified in Swiss-Prot (12516), Nr (10978), KEGG (9106), GO (4985), and COG (3481) database (Figure 2B). The E-value distribution, similarity distribution and species distribution of D. indusiata unigenes matched to the NR database were analyzed (Figure S1). The E value distribution illustrated that 85.4% of the unigenes exhibited high homology (<1e-10). For the similarity distribution, most of the unigenes (72.7%) had a similarity greater than 60%. For the species distribution, the annotated D. indusiata unigenes showed greatest similarity to Sphaerobolus stellatus SS14, with 3968 matching genes (36.6%), illustrating the closely related relationship between these two species. GO analysis was performed to classify the functions of the annotated unigenes. These unigenes were categorized into three main GO categories; in the “biological process” category, cellular process (2590, 52.0%), metabolic process (2546, 51.1%) and single-organism process (1587, 31.8%) were dominant. In terms of the “molecular function” category, catalytic activity (2,434; 48.8%) and binding (2,126; 42.6%) were the most common terms. For “cellular component” category, cell (2429, 48.7%), cell part (2422, 48.6%) and organelle (1663, 33.4%) were the most highly represented (Figure 2C). The annotations of unigenes involved in COG classifications were searched by the software program DIAMOND (Figure S1D). The largest COG category was associated with “posttranslational modification, protein turnover, chaperones” (O, 558 unigenes), followed by “function unknown” (S, 472); “general function prediction only” (R, 446); “translation, ribosomal structure and biogenesis” (J, 424). Compared with other mushrooms, there were more D. indusiate unigenes represented in the categories of “posttranslational modification, protein turnover, chaperones” and

“intracellular trafficking, secretion, and vesicular transport” [33], indicating that protein structure regulation and transport activities were more vigorous in the fruiting body of D. indusiate. The KEGG annotated D. indusiate unigenes were classified into 6 main categories with 22 subcategories (123 pathways) (Figure 2D). According to these results, it was suggested that pathways involved in metabolism and genetic information processing were most active in the fruiting body of D. indusiate, which was similar to the transcriptome analyses of other mushroom such as Ganoderma lucidum [34]. With respect to the detailed subcategories, the results showed that the pathways that contained the most unigenes were translation (921, 10.1%), carbohydrate metabolism (792, 8.70%), folding, sorting and degradation (704, 7.73%), transport and catabolism (664, 7.29%), amino acid metabolism (584, 6.41%), energy metabolism (467, 5.13%) and lipid metabolism (398, 4.37%). Those pathways were all involved in the maintenance of basic biological processes of D. indusiate and the main biosynthetic routes of the major nutrients. Expressed sequence tag-simple sequence repeats (EST-SSR) markers are useful for genetic map construction, cultivar identification, molecular marker-assisted selection in breeding, and other related studies. Therefore, EST-SSR screening was performed based on the do novo sequenced transcriptome of D. indusiata fruiting bodies. A total of 2846 potential EST-SSR markers distributed among 2095 unigenes were identified. Among those EST-SSR markers, mono-nucleotide repeats (1456), tri-nucleotide repeats (883) and di-nucleotide repeats (400) accounted for 51.16%, 31.03% and 14.05%, respectively. Only a small number of tetra-nucleotide repeats (60, 2.11%), hexa-nucleotide repeats (40, 1.41%) and penta-nucleotide repeats (7, 0.25%) were identified. The most dominant mono-nucleotide repeats were tandem A

and T (1375, 48.31%), in which 6-10 tandem repeats were over-represented. Additionally, 518 and 835 EST-SSR markers were located in the coding sequence regions and untranslated regions, respectively. These findings were similar to the studies of other mushrooms, such as P. tuoliensis, V. volvacea and A. polytricha [13, 35]. Moreover, the most abundant repeat motif in the coding sequence regions was the tri-nucleotide repeats (302, 58.30%). The high frequency of tri-nucleotide repeats located in coding sequence regions was a common phenomenon, which could reduce the incidence of frameshift mutations in coding regions [36]. The D. indusiata fruiting body commodity currently is derived both from wild picking and artificial cultivation; therefore, the identification of the genetic background is important, and the differences between regions and influences of cultivation are marked. Thus, these identified EST-SSR markers were important information for further studies, such as the construction of a genetic evolutionary tree and product traceability system. 3.4. Overview of D. indusiata fruiting body proteome The transcriptome of D. indusiata fruiting bodies was the collection of RNAs transcribed in it, including coding RNAs and noncoding RNAs. Coding RNAs can be further translated into proteins and then perform specific functions directly involved in physiological processes. Therefore, high-throughput proteome workflow was performed to identify the translated proteins in D. indusiata fruiting bodies. To increase the throughput of identification, the total proteins of D. indusiata fruiting bodies were separated into 18 fractions by a high-pH reversed-phase fractionation protocol before loading for the LC-MS/MS analysis. A total of 295543 spectra produced by the mass spectrometer, after searching against the putative proteins translated from the de novo transcriptome, yielding 25,641 peptides which identified and accepted with a peptide FDR of 0.01. All the peptides were identified

with high precision, and the mass tolerance of the peptide ions was less than 5 ppm (Figure S2A). The majority of peptide lengths are distributed between 8-20 amino acid residues (Figure S2B), consistent with the common trypsin-digested pattern. After clearing the repeated sequence, a total of 4380 proteins were identified (Figure 3A). The detailed information of the identified proteins is summarized in Table S1. The statistical results show that the sequence coverage of most of the D. indusiata proteins (66.1%) was higher than 10%, indicating that the overall identification quality was higher. The theoretical molecular weight of the identified protein was statistically analyzed, and results showed that more than half of the identified proteins (70.9%) were distributed between 10-60 kDa (Figure S2C). The number of identified proteins accounted for 22.2% of the total sequenced unigenes, which was similar to our previous results on morel fruiting body (Morchella importuna) (14637 unigenes and 4047 proteins) [15, 16]. Over the past decade, several advances have been made in shotgun proteomics technology, which is based on the LC-MS/MS, to improve the accuracy and throughput of the identification of proteins [23, 24]. In recent years, multidimensional (usually two-dimensional) LC separation has demonstrated great resolving power and enables the throughput of the deep proteome beyond 3000~ proteins. For the first-dimension separation, high-pH RPLC is increasingly being used due to its rapid fractionation and the low-salt buffers with broad adaptability [27, 28]. Such pH-modulated two-dimensional RPLC separations have been applied to the study of morel (Morchella importuna) and tartary buckwheat (Fagopyrum tataricum) proteome and shown a high identification throughput (4047 and 3363 proteins, respectively) [16, 37]. Here, a similar workflow was employed for the analysis of the D. indusiata proteome, and 4380 proteins were identified with an extremely high

throughput, providing systematic and comprehensive proteome information for further functional analysis of D. indusiata. 3.5. Annotation and analysis of the identified D. indusiata proteins For the performance of complex biological functions in eukaryotic cells, the proteins are elaborately subdivided into functionally subcellular structure. The WoLF PSORT software was used to predict and classify the subcellular localization of the identified D. indusiata proteins. The results showed that identified proteins localized in a wide variety of subcellular structures, mainly including the nucleus, mitochondria, cytoplasm, extracellular, plasma membrane, cytoplasm (nucleus), and cytoskeleton (Figure 3B). A total of 1470 identified proteins were annotated to the discrete nucleus, accounting for 33.6%, indicating that the cell division, proliferation and development of D. indusiata fruiting body are vigorous. Moreover, the maturity of the fruiting body is accompanied by the generation of spores, which also requires a large amount of protein to work in the nucleus for the subtraction. Additionally, the results were consistent with the complex morphological developmental process of D. indusiata fruiting body: from a spherical structure (5-7 cm) growing to a stretched mature fruiting body (15-20 cm). Along with the dramatic changes in the mature process, a large amount of energy needs to be consumed, and thus a large number of the identified proteins were localized to the mitochondria (1004 proteins, accounting for 22.9%), working for the metabolism of energy. As the main location for metabolism, 815 identified proteins (18.6%) localized to the cytoplasm, suggesting that numerous metabolic/synthesis activities occur in the harvested D. indusiata fruiting-body. The identified D. indusiata proteins were annotated and classified by GO analysis. The GO classification of D. indusiata proteome is highly similar to the GO classification of the transcriptome. For the categories of “molecular function” and

“cell component”, the top 5 GO terms were completely consistent, but there was a slight difference in the category “biological process”, (Figure 2 B and Figure S2 D-F). If a “translation rate” was estimated as “the number of proteins” divided by the “number of unigene” in the same GO term, then the GO terms with the highest translation rate were: “molecular function regulator” (82.0%, with 41 proteins and 50 unigenes), “binding” (71.4%, with 1518 proteins and 2434 unigenes), and “catalytic activity” (57.6%, with 1402 proteins and 2126 unigenes). These results indicated that the rate of protein translation varied with the functions. Further GO functional enrichment analysis showed that D. indusiata proteins were mostly enriched in the synthesis, metabolism and transport processes, especially the synthesis and metabolism of small molecule polar metabolites (Figure 3C). As an edible mushroom, D. indusiata fruiting-body are tasty and flavored. The taste and flavor come from the metabolites, such as amino acids, oligosaccharides, organic acids, and volatile small molecules. Therefore, the vast majority of enriched biological processes are involved in the metabolism and synthesis of these small molecule metabolites. Among these enriched processes, “sulfur compound metabolic process” (GO:0006790) needed to be valued, because sulfur compounds are a class of molecules with a low odor threshold, which could have an important influence on the flavor of D. indusiata fruiting-body. In addition to metabolism and synthesis, two processes (“vesicle-mediated transport” and “intracellular transport”) involved in transport were enriched, suggesting that intracellular transport is active. In the classification of “molecular function”, the identified proteins were mainly enriched in protein kinase activity (GO:0004674), GTPase activity (GO:0003924), and metal ion binding (GO:0051540, GO:0051536). A total of 21 proteins were enriched in the GO term “protein serine/threonine kinase activity”. These kinases should be explored in a

future study of D. indusiata postharvest storage and processing because phosphorylation pathways are important in the processes by which fruiting bodies cope with the postharvest environment. Additionally, “ubiquitin-like protein transferase activity” (GO:0019787) was enriched, indicating that ubiquitination plays an important role in the physiological regulation of D. indusiata. For the “cellular component” aspect, tethering complex (GO:0099023), cytosol (GO:0005829), and exocyst (GO:0000145) were the most significantly enriched. Both tethering complexes and exocyst complexes are involved in vesicle trafficking, which is responsible for the secretion (exocytosis), uptake (endocytosis) and transport of materials








(endoplasmic reticulum, golgi, etc.). These two kinds of complexes mainly mediate the initial contact between vesicle and the membranes of organelles and participate in the tethering, docking and fusion during the vesicle trafficking [38, 39]. These results indicated that the material transport between organelles was busy along with the exuberant synthesis and metabolism in the D. indusiata fruiting body. 3.6. Overview of DEGs between peach-shaped and mature fruiting bodies Results of transcriptome and proteome analyses provided plentiful and important information for understanding the molecular mechanisms of the physiological characteristics of D. indusiata. However, comparative analysis was necessary to reveal the difference between peach-shaped and mature fruiting bodies. Therefore, the unigenes were quantified. The expression abundance of unigenes were normalized to those in peach-shaped D. indusiata samples, and a threshold value of fold change ≥ 2 and adjusted p-value ≤ 0.05 were set to determine the DEGs. A total of 1954 unigenes were identified as differentially expressed (Table S2). Most of the DEGs were co-expressed in both the peach-shaped and mature stages, and only 15 and 3 genes

were specifically expressed in peach-shaped fruiting body and mature fruiting body, respectively. Among the co-expressed DEGs, 1,248 genes were upregulated, and 706 genes were downregulated (mature stage vs peach-shaped stage) (Figure S3). 3.7. GO and KEGG Analysis of DEGs According to the GO annotation and classification analysis, 302 upregulated expression genes and 224 downregulated expression genes were classified in 36 GO terms (Figure 4A). There is a large contrast between the number of upregulated and downregulated DEGs for several GO terms, such as “localization” (64 up vs 22 down), “response to stimulus” (24 up vs 12 down), “macromolecular complex” (10 up vs 53 down), “membrane” (116 up vs 48 down), “transporter activity” (30 up vs 7 down), “structural molecule activity” (0 up vs 33 down). Furthermore, GO enrichment analysis was conducted (p-value < 0.05) to obtain more detailed information (Table S3). The results showed that the number of enriched GO terms upregulated in the mature stage (66 GO terms) was much higher than that in the peach-shaped stage (7 GO terms). Most of the enriched terms with the upregulated DEGs belonged to the “biological process” category. Two of the enriched terms, “transport” and “metabolic process”, were highlighted and further classified. In the subcategories of “metabolic process”, “macromolecule metabolic process”, “organic substance biosynthetic process”, “nitrogen compound metabolic process”, “protein metabolic process”, “organic cyclic compound metabolic process” and “small molecule metabolic process” were enriched. In the subcategories of “transport” term, “macromolecular complex subunit organization”, “amino acid transport”, “carboxylic acid transport”, “organic acid transport” and “anion transmembrane transport” were represented. Consistent with the above results, enriched GO terms in the “molecular function” category were all related to transporter activity, such as

“transmembrane transporter activity”, “substrate-specific transmembrane transporter activity” and so on. All of the enriched GO terms with the downregulated DEGs were relevant








“organonitrogen compound biosynthetic process”, “peptide biosynthetic process”, “translation”, “ribosome” and “structural constituent of ribosome”. KEGG analysis of the DEGs showed that total of 333 DEGs (189 upregulated and 144 downregulated) were classified into 20 subcategories (Figure 5B). The subcategories with more upregulated DEGs were mainly related to nutrient metabolism, including “carbohydrate metabolism” (29 up vs 13 down), “amino acid metabolism” (22 up vs 13 down), “metabolism of other amino acids” (19 up vs 7 down), “lipid metabolism” (12 up vs 5 down), “energy metabolism” (9 up vs 5 down), and “transport and catabolism” (21 up vs 9 down). These results indicated that nutrient metabolism became exuberant with the maturity of fruiting bodies. The downregulated DEGs dominated the subcategory of “translation” (7 up vs 45 down). These results were fully compatible with the results of GO enrichment. KEGG pathway enrichment analysis was further conducted. The results showed that “MAPK signaling pathway-yeast” was significantly enriched as the upregulated pathway in the mature fruiting body (Figure S4A). In detail, 10 upregulated DEGs and 3 downregulated DEGs were mapped in MAPK signaling pathway. For those downregulated DEGs, they were significantly enriched in five pathways, including “ribosome”, “meiosis-yeast”, “cell cycle-yeast”, “mismatch repair” and “DNA replication” (Figure S4B). In particular, 42 DEGs matched in “ribosome” pathway, which occupied almost one-third of ribosomal proteins. This result was in accordance with the GO enrichment analysis, which showed that the enriched GO terms by downregulated DEGs were all related to protein translation. Actually, previous studies

also showed that transcription and translation metabolism-related genes were downregulated after harvest of mushroom [40, 41], suggesting that it is a common phenomenon that translation and protein metabolism are drastically altered in the post-harvest maturity process. The other four downregulated DEGs enriched pathways were all associated with the DNA replication processes. In the “DNA replication” pathways, the downregulated DEGs included genes encoding subunits of DNA polymerase delta complex and helicase, such as DNA polymerase delta subunit-4, replication factor C subunit 2/4 of clamp loader, DNA replication licensing factor MCM6 and MCM7, as well as DNA replication ATP-dependent helicase. In the “cell cycle” and “meiosis” pathways, the downregulated DEGs were involved in multi-pathways and multienzyme complex such as origin recognition complex (Orc2, Orc5), mini-chromosome maintenance complex (Mcm6, Mcm7), cohesion (Smc1), condensing









cell-cycle-regulating enzymes. Previous studies have also shown that DNA replication-related pathways are upregulated in the fruiting body growth period and downregulated after the maturity of fruiting body or post-harvest [13, 42-44]. GO and KEGG analysis of DEGs suggested that the consumption of main nutrients and energy were more active, while DNA replication and repair, protein translation were drastically weakened in the mature fruiting body of D. indusiata. These findings were consistent with the basic physiological functions of the fruiting body: the mission of the fruiting body is reproduction for D. indusiata, spores are produced along with the growth of fruiting bodies and are diffused with the expansion of the fruiting body, so the mission of the fruiting bodies is completed, then rapidly turns to senescence and deterioration. Therefore, during the process of maturity from the peach-shaped stage to the mature stage, metabolic and transport-related pathways

were activated to decompose nutrients to provide energy for the morphological development of fruiting body; meanwhile, DNA replication and protein translation became unimportant because of the completion of sporulation. Accordingly, the nutrient determination results (Table 1) showed that total proteins, water-soluble polysaccharide, and crude fiber were all decreased in the mature fruiting body. These results were also consistent with the previous studies of Lentinula edodes, in which the mature fruiting body of L. edodes had fewer up-regulated genes (7) enriched in the "translation" KEGG pathway than the mycelium (34) [45]; and the genes involved in the GO classification of “developmental process” and “reproduction” were up-regulated in the early bud stage than fully developed stage of L. edodes [46]. 3.8. Identified DEGs and Proteins Involved in MAPK Pathways MAPK pathways are important signal transduction pathways conserved in essentially all eukaryotes and involved in regulating a wide variety of physiological activities such as cell wall integrity maintenance, fruiting body development, stress response, conidiation and so on [47-49]. Previous studies have also found genes in MAPK pathways that regulated the development and metabolism in many species of fungus, such as Coprinopsis cinereal, Tuber melanosporum, Neurospora crassa, and P. ostreatus and so on.[14, 50-52] The DEGs were mapped in four MAPK sub-pathways and corresponded to different environmental stimulation: pheromone, cell wall stress, high osmolarity, and starvation. Interestingly, it was found that upregulated DEGs in the mature stage of D. indusiata were only mapped in the cell wall stress-dependent MAPK sub-pathway (Figure 5), including RHO1 GDP-GTP exchange protein 1/2 (Rom1,2), Ras homolog gene family member A (Rho 1), classical protein kinase C alpha type(Pkc1), GTPase-activating protein SAC7 (Sac 7), mitogen-activated protein kinase 7 (Slt 2) and tyrosine-protein phosphatase 2/3

(Ptp2,3). Based on these results, it was speculated that the cell wall stress-related MAPK pathway was activated during the maturity of D. indusiate fruiting body. 3.9. Identified CAZy Families The activated MAPK signaling pathway stimulates downstream related enzymes to perform functions. In the above results, the cell wall stress-related MAPK pathway were most stimulated, so enzymes related to cell wall synthesis and metabolism were examined. CAZymes are enzymes that are involved in the cleavage, biosynthesis, and modification of complex carbohydrates. They have a primary responsibility in cell wall remodel and degradation and inevitably play important roles in the morphological changes of D. indusiate. On the other hand, CAZymes are equally important for the nutrient absorption of D. indusiate because they are essential enzymes to degrade the culture substrate. By searching against the CAZyme database using the transcriptome data, a total of 1173 CAZymes-related unigenes were identified in the D. indusiate transcriptome. Based on catalytic activities associated conserved domains, 497 glycosyl hydrolases (GHs), 244 glycosyl transferases (GTs), 182 carbohydrate esterases (CEs), 133 auxiliary activities (AAs), 101 carbohydrate-binding modules (CBMs) and 16 polysaccharide lyases (PLs) were identified. Furthermore, the differential expression of these CAZymes unigenes between the peach-shaped stage and mature stage was evaluated and summarized in Table S4. According to the results, 58 CAZyme unigenes were significantly upregulated in the mature fruiting body, including 24 GHs, 8 CEs, 7 GTs, 16 AAs, and 3 CBMs, while 34 CAZymes unigenes were significantly downregulated, including 12 GHs, 7 CEs, 7 GTs, 4 AAs, 3 CBMs and 1 PLs. The upregulated CAZymes unigenes were divided into two groups. One group mainly comprised plant cell wall degradation-related

genes, including 1 cellulase, 3 hemicellulose, 2 lignin oxidase and 11 lignin-degrading auxiliary enzymes.

The other group mainly contained fungal



degradation-related genes, including 4 chitinase, 1 endo-1,6-beta-D-glucanase, and 2 exo-1,3-beta-glucanase. For the downregulated CAZymes unigenes, it was noteworthy that half of them were involved in plant cell wall degradation: 5 cellulase, 8 hemicellulose and 2 lignin degrading enzymes. In addition, in the 92 CAZymes DEGs, 53 of them translated, and then were identified in the proteome analysis; the proportion of translation reached 57.6%, which was much higher than the average translation rate (22.2%). It is well known that the main components of bamboo-based culture substrate are cellulose, hemicellulose and lignin. The above results showed that the numbers of upand downregulated CAZymes unigenes associated with these components were comparable. However, in detail, there were more cellulases and hemicelluloses that were downregulated, while more lignin degrading enzymes were upregulated in the mature fruiting body. It was implied that the main substrates of D. indusiate fruiting body changed from cellulose and hemicellulose to lignin during development from the peach-shaped stage to mature stage. One possible speculation was that as the fruiting body continued to absorb nutrients, the components of the bamboo-based culture substrate changed, and then the types of enzymes secreted by the fruiting bodies adjusted accordingly. Interestingly, fungal cell wall degradation-related CAZymes unigenes were all upregulated in the mature fruiting body. It is well known that the fungal cell wall structure is highly dynamic, changing constantly during its life cycle. From the peach-shaped stage to mature stage, the fruiting bodies of D. indusiata undergone great morphological changes, such as rapid stipe elongation, without further cell

division. Therefore, the cell wall must be stretched and reconstructed in the process of morphological development of D. indusiata, and a certain degree of hydrolysis of the main component of the fungal cell wall (chitin and glucan) is needed. These findings were also consistent with previous reports, which showed that β-1,3-glucanases, β-1,6-glucanase, chitinase and chitosanase were implicated in the maintenance of wall plasticity [42, 43, 53, 54]. Those hydrolytic enzymes acted on their own cell walls and contributed to breakage and re-forming of bonds within and between polymers, leading to reconstruction of the cell wall. In addition, the mature fruiting body rapidly turns to senescence and deterioration, and these upregulated glucanases and chitinases also would contribute to the degradation of the degenerated fruiting body. In addition to the cell wall degradation-related CAZymes, other CAZymes, which are involved in the hydrolysis of nutrients, glycoprotein modification, and glycan biosynthesis, were identified and differentially expressed in the two stages of D. indusiata fruiting bodies. Several CAZyme unigenes involved in starch, sucrose and







phosphorylceramide glucuronosyltransferase, neutral trehalase, trehalose 6-phosphate synthase).







downregulated in the mature stage fruiting body. It was reported that a water extract of










1,4-beta-N-acetylmuramidase might play an important role in the antimicrobial effects on bacteria. 3.10. Identified DEGs and Proteins Involved in Browning Once reaching the maturation stage, the fruiting body of D. indusiata rapidly undergoes the senescence process. Browning of the fruiting body is one of the most important changes in the senescence process and leads to the loss of nutrition and the

irreversible changes in texture and color of fruiting body. Tyrosinase, laccase and peroxidase (POD) are the main enzymes that catalyze the browning of mushroom fruiting bodies. Tyrosinase belongs to the monophenol monooxygenases, which catalyze monophenol tyrosine to corresponding quinones, and then the generated quinone forms melanin by nonenzymatic reactions. Laccases belongs to polyphenol oxidases that catalyze the oxidation of polyphenolic substrates to quinones, which then spontaneously polymerize into dark-colored pigments. Glutathione S-transferases (GSTs), which could eliminate reactive oxygen species and preserve the integrity of cell membrane, were also important for the delay of browning. Numerous studies have revealed that the browning of the mushroom fruiting body after maturity is associated with increased tyrosinase and laccase activities [42, 55]. Therefore, the DEGs and their encoded proteins involved in those browning-related enzymes were important in this study. After searching, it was found that 2 laccase, 1 tyrosinase, 8 peroxidase and 3 GSTs were significantly upregulated in mature fruiting body, while only 1 laccase and 2 peroxidases were downregulated. Of the above 14 DEGs, 9 encoded proteins were identified in the proteome analysis (Table S5). According to these results, it was inferred that those upregulated unigenes might be important for the browning of the D. indusiata fruiting body after harvest, and the related enzymes should be highlighted in future research.

Abbreviations Used AAs, Auxiliary activities; FDR, False discovery rate; CEs, Carbohydrate esterases; CAZyme, Carbohydrate-active enzyme; CBMs, Carbohydrate-binding modules; DGEs, Differentially expressed genes; EST-SSR, Expressed sequence tag-simple sequence repeats; GHs, Glycosyl hydrolases; GO, Gene Ontology; GTs, Glycosyl





of Genes

and Genomes;


Polysaccharide lyases; RPLC, Reversed-phase liquid chromatography.

Funding National Natural Science Foundation of China (31701655); Science and Technology Research Program of Chengdu (2019-YF05-00117-SN).

Supporting Information Description Supporting information for the identified D. indusiata unigenes and proteins is shown in Figure S1 and S2, respectively; the detailed information for the identified D. indusiata proteins and DEGs is shown in Table S1 and S2, respectively; the scatter plot of total unigenes is shown in Figure S3; GO enrichment and KEGG results of DEGs are shown in Table S3 and Figure S4, respectively; CAZymes related DEGs and browning related DEGs are shown in Table S4 and S5, respectively.

Declaration of Competing Interest There are no conflicts of interest among the authors.

References [1] Y. Hua, Q. Gao, L. Wen, B. Yang, J. Tang, L. You, M. Zhao, Structural characterisation of acid- and alkali-soluble polysaccharides in the fruiting body of Dictyophora indusiata and their immunomodulatory activities, Food Chemistry 132(2) (2012) 739-743. [2] Y.B. Ker, K.C. Chen, C.C. Peng, C.L. Hsieh, R.Y. Peng, Structural Characteristics and Antioxidative Capability of the Soluble Polysaccharides Present in Dictyophora indusiata (Vent.









Medicine,2011,(2011-06-15) 2011(1) (2011) 396013. [3] J.H. Yang, H.C. Lin, J.L. Mau, Antioxidant properties of several commercial mushrooms, Food Chemistry 35(6) (2002) 519-526. [4] D.I.O. Oyetayo, Antioxidant and Antimicrobial Properties of Aqueous Extract from Dictyophora indusiata, Open Mycology Journal 3(1) (2009) 20-26. [5] I.K. Lee, B.S. Yun, G. Han, D.H. Cho, Y.H. Kim, I.D. Yoo, Dictyoquinazols A, B, and C, new neuroprotective compounds from the mushroom Dictyophora indusiata, Journal of Natural Products 65(12) (2002) 1769. [6] C. Deng, H. Fu, L. Teng, Z. Hu, X. Xu, J. Chen, T. Ren, Anti-tumor activity of the regenerated triple-helical polysaccharide from Dictyophora indusiata, International Journal of Biological Macromolecules 61(10) (2013) 453-458. [7] D. Ishiyama, Y. Fukushi, M. Ohnishi-Kameyama, T. Nagata, H. Mori, T. Inakuma, Y. Ishiguro, J. Li, H. Kawagishi, Monoterpene-alcohols from a mushroom Dictyophora indusiata, Phytochemistry 50(6) (1999) 1053-1056. [8] V.K. Sharma, J. Choi, N. Sharma, M. Choi, S.Y. Seo, In vitro anti‐tyrosinase activity of 5‐ (hydroxymethyl)‐2‐furfural isolated from Dictyophora indusiata, Phytotherapy Research 18(10) (2004) 841-4. [9] W. Liao, Z. Yu, Z. Lin, Z. Lei, Z. Ning, J.M. Regenstein, J. Yang, J. Ren, Biofunctionalization of Selenium Nanoparticle withDictyophora IndusiataPolysaccharide and Its Antiproliferative Activity through Death-Receptor and Mitochondria-Mediated Apoptotic Pathways, Scientific Reports 5 (2015) 18629.

[10] Y. Hua, B. Yang, J. Tang, Z. Ma, Q. Gao, M. Zhao, Structural analysis of water-soluble polysaccharides in the fruiting body of Dictyophora indusiata and their in vivo antioxidant activities, Carbohydrate Polymers 87(1) (2012) 343-347. [11] W. Liao, Z. Luo, D. Liu, Z. Ning, J. Yang, J. Ren, Structure characterization of a novel polysaccharide from Dictyophora indusiata and its macrophage immunomodulatory activities, Journal of Agricultural & Food Chemistry 63(2) (2015) 535. [12] H. Chen, B. Sun, H. Tian, X. Chen, M. Huang, Isolation and identification of antibiotic albaflavenone from Dictyophora indusiata (Vent:Pers.) Fischer, Journal of Chemical Research 35(11) (2011) -. [13] Y. Fu, Y. Dai, C. Yang, P. Wei, B. Song, Y. Yang, L. Sun, Z.W. Zhang, Y. Li, Comparative Transcriptome Analysis Identified Candidate Genes Related to Bailinggu Mushroom Formation and Genetic Markers for Genetic Analyses and Breeding, Scientific Reports 7(1) (2017). [14] L.H. Tang, H.H. Jian, C.Y. Song, D.P. Bao, X.D. Shang, D.Q. Wu, Q. Tan, X.H. Zhang, Transcriptome analysis of candidate genes and signaling pathways associated with light-induced brown film formation in Lentinula edodes, Applied Microbiology & Biotechnology 97(11) (2013) 4977-4989. [15] J. Wang, H. Ye, D. Liang, D. Liu, F. Geng, X. Li, De Novo Sequencing and Transcriptome Analysis of Morchella importuna Fruiting Body, Shipin Kexue/Food Science 39(18) (2018) 81-87. [16] J. Wang, J. Xiao, F. Geng, X. Li, J. Yu, Y. Zhang, Y. Chen, D. Liu, Metabolic and proteomic analysis of morel fruiting body (Morchella importuna), Journal of Food Composition

and Analysis 76 (2019) 51-57. [17] S.S. Nielsen, Moisture Content Determination, Food Analysis Laboratory Manual, Springer International Publishing, Cham, 2017, pp. 105-115. [18] S.S. Nielsen, Protein Nitrogen Determination, Food Analysis Laboratory Manual, Springer International Publishing, Cham, 2017, pp. 131-135. [19] S.S. Nielsen, C. Carpenter, Fat Content Determination, Food Analysis Laboratory Manual, Springer International Publishing, Cham, 2017, pp. 121-129. [20] M. Meng, D. Cheng, L. Han, Y. Chen, C. Wang, Isolation, purification, structural analysis and immunostimulatory activity of water-soluble polysaccharides from Grifola Frondosa fruiting body, Carbohydrate Polymers 157 (2017) 1134-1143. [21] C.-H. Su, M.-N. Lai, L.-T. Ng, Effects of different extraction temperatures on the physicochemical properties of bioactive polysaccharides from Grifola frondosa, Food Chemistry 220 (2017) 400-405. [22] Z. Li, C. Li, Y. Gao, W. Ma, Y. Zheng, Y. Niu, Y. Guan, J. Hu, Identification of oil, sugar and crude fiber during tobacco (Nicotiana tabacum L.) seed development based on near infrared spectroscopy, Biomass and Bioenergy 111 (2018) 39-45. [23] M.P. Washburn, D. Wolters, J.R. Yates, Large-scale analysis of the yeast proteome by multidimensional protein identification technology, Nature Biotechnology 19(3) (2001) 242-247. [24] J.R. Wisniewski, A. Zougman, N. Nagaraj, M. Mann, Universal sample preparation method for proteome analysis, Nature Methods 6(5) (2009) 359-U60. [25] F. Geng, J.Q. Wang, D.Y. Liu, Y.G. Jin, M.H. Ma, Identification of N-Glycosites in Chicken

Egg White Proteins Using an Omics Strategy, Journal of Agricultural and Food Chemistry 65(26) (2017) 5357-5364. [26] F. Geng, Y.X. Xie, J.Q. Wang, K. Majumder, N. Qiu, M.H. Ma, N-Glycoproteomic Analysis of Chicken Egg Yolk, J. Agric. Food Chem. 66(43) (2018) 11510-11516. [27] F. Yang, Y.F. Shen, D.G. Camp, R.D. Smith, High-pH reversed-phase chromatography with fraction concatenation for 2D proteomic analysis, Expert Review of Proteomics 9(2) (2012) 129-134. [28] T.S. Batth, C. Francavilla, J.V. Olsen, Off-Line High-pH Reversed-Phase Fractionation for In-Depth Phosphoproteomics, Journal of Proteome Research 13(12) (2014) 6176-6186. [29] S. Li, X. Wang, S. He, J. Li, Q. Huang, T. Imaizumi, L. Qu, G. Qin, L.J. Qu, H. Gu, CFLAP1 and CFLAP2 Are Two bHLH Transcription Factors Participating in Synergistic Regulation of AtCFL1-Mediated Cuticle Development in Arabidopsis, Plos Genetics 12(1) (2016). [30] P. Horton, K.J. Park, T. Obayashi, N. Fujita, H. Harada, C.J. Adamscollier, K. Nakai, WoLF PSORT: protein localization predictor, Nucleic Acids Research 35(Web Server issue) (2007) 585-7. [31] D.W. Huang, B.T. Sherman, R.A. Lempicki, Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists, Nucleic Acids Research 37(1) (2009) 1-13. [32] J.H. Yang, H.C. Lin, J.L. Mau, Non-volatile taste components of several commercial mushrooms, Food Chemistry 72(4) (2001) 465-471. [33] H.Y. Song, D.H. Kim, J.M. Kim, Comparative transcriptome analysis of dikaryotic mycelia and mature fruiting bodies in the edible mushroom Lentinula edodes, Scientific Reports 8(1)

(2018). [34] G.J. Yu, M. Wang, J. Huang, Y.L. Yin, Y.J. Chen, S. Jiang, Y.X. Jin, X.Q. Lan, B.H. Wong, Y. Liang, Deep insight into the Ganoderma lucidum by comprehensive analysis of its transcriptome, Plos One 7(8) (2012) e44031-e44031. [35] Y. Zhou, L. Chen, X. Fan, Y. Bian, De novo assembly of Auricularia polytricha transcriptome using Illumina sequencing for gene discovery and SSR marker identification, Plos One 9(3) (2014) e91740. [36] Y. Dai, W. Su, C. Yang, B. Song, Y. Li, Y. Fu, Development of Novel Polymorphic EST-SSR Markers in Bailinggu (Pleurotus tuoliensis) for Crossbreeding, Genes 8(11) (2017) 325. [37] J. Wang, J. Xiao, X. Liu, F. Geng, Q. Huang, J. Zhao, D. Xiang, G. Zhao, Analysis of tartary buckwheat (Fagopyrum tataricum) seed proteome using offline two-dimensional liquid chromatography and tandem mass spectrometry, Journal of Food Biochemistry 43(7) (2019) e12863. [38] R. Ravikumar, A. Steiner, F.F. Assaad, Multisubunit tethering complexes in higher plants, Current Opinion in Plant Biology 40 (2017) 97-105. [39] M.R. Heider, M. Munson, Exorcising the Exocyst Complex, Traffic 13(7) (2012) 898-907. [40] C.H. de Moor, H. Meijer, S. Lissenden, Mechanisms of translational control by the 3' UTR in development and differentiation, Seminars in Cell & Developmental Biology 16(1) (2005) 49-58. [41] G.W.R. Jr, A.A. Komar, W.C. Merrick, eIF4A: The godfather of the DEAD box helicases, Progress in Nucleic Acid Research & Molecular Biology 72 (2002) 307.

[42] Y. Sakamoto, K. Nakade, N. Konno, T. Sato, Senescence of the Lentinula edodes Fruiting Body After Harvesting, InTech2012. [43] Y. Sakamoto, K. Nakade, T. Sato, Characterization of the post-harvest changes in gene transcription in the gill of the Lentinula edodes fruiting body, Marine Biotechnology 15(2) (2013) 175-187. [44] M. Wang, B. Gu, J. Huang, S. Jiang, Y. Chen, Y. Yin, Y. Pan, G. Yu, Y. Li, B.H. Wong, Transcriptome and proteome exploration to provide a resource for the study of Agrocybe aegerita, Plos One 8(2) (2013) e56686. [45] H.Y. Song, D.H. Kim, J.M. Kim, Comparative transcriptome analysis of dikaryotic mycelia and mature fruiting bodies in the edible mushroom Lentinula edodes, Scientific Reports 8 (2018) 15. [46] Y.Z. Wang, X.L. Zeng, W.G. Liu, De novo transcriptomic analysis during Lentinula edodes fruiting body growth, Gene 641 (2018) 326-334. [47] R.E. Chen, J. Thorner, Function and regulation in MAPK signaling pathways: lessons learned from the yeast Saccharomyces cerevisiae, BBA - Molecular Cell Research 1773(8) (2007) 1311-1340. [48] B. Birkaya, A. Maddi, J. Joshi, S.J. Free, P.J. Cullen, Role of the cell wall integrity and filamentous growth mitogen-activated protein kinase pathways in cell wall remodeling during filamentous growth, Eukaryotic Cell 8(8) (2009) 1118-1133. [49] V. Valiante, T. Heinekamp, R. Jain, A. Härtl, A.A. Brakhage, The mitogen-activated protein kinase MpkA of Aspergillus fumigatus regulates cell wall signaling and oxidative stress response, Fungal Genetics & Biology 45(5) (2008) 618-627.

[50] L. Ramírez, J.A. Oguiza, G. Pérez, J.L. Lavín, A. Omarini, F. Santoyo, M. Alfaro, R. Castanera, A. Parenti, E. Muguerza, Genomics and transcriptomics characterization of genes expressed during postharvest at 4°C by the edible basidiomycete Pleurotus ostreatus, International Microbiology the Official Journal of the Spanish Society for Microbiology 14(2) (2011) 111. [51] E. Zampieri, R. Balestrini, A. Kohler, S. Abbà, F. Martin, P. Bonfante, The Perigord black truffle responds to cold temperature with an extensive reprogramming of its transcriptional activity, Fungal Genetics & Biology 48(6) (2011) 585-591. [52] G. Park, S. Pan, K.A. Borkovich, Mitogen-activated protein kinase cascade required for regulation of development and secondary metabolism in Neurospora crassa, Eukaryotic Cell 7(12) (2008) 2113-2122. [53] K. Minato, S. Kawakami, K. Nomura, H. Tsuchida, M. Mizuno, An exo beta-1,3-glucanase synthesized de novo degrades lentinan during storage of Lentinule edodes and diminishes immunomodulating activity of the mushroom, Carbohydrate Polymers 56(3) (2004) 279-286. [54] M.M. Zerillo, B.N. Adhikari, J.P. Hamilton, C.R. Buell, C.A. Lévesque, N. Tisserat, Carbohydrate-active enzymes in pythium and their role in plant cell wall and storage polysaccharide degradation, Plos One 8(9) (2013) e72572. [55] Y. Sakamoto, K. Nakade, S. Sato, K. Yoshida, K. Miyazaki, S. Natsume, N. Konno, Lentinula edodes Genome Survey and Postharvest Transcriptome Analysis, Applied & Environmental Microbiology 83(10) (2017) AEM.02990-16.


Table 1 Nutrient contents of peach-shaped and mature fruiting bodies of D. indusiate Peach-shaped fruiting body

Mature fruiting body

86.83 ± 0.37

88.62 ± 0.20**

Total proteins (g/100 g dry weight)

21.58 ± 0.04**

19.22 ± 0.07

Water-soluble polysaccharide (g/100 g dry weight)

24.12 ± 0.04**

16.76 ± 0.05

Crude fiber (g/100 g dry weight)

8.26 ± 0.12.**

5.36 ± 0.18

Total lipid (g/100 g dry weight)

7.41 ± 0.14

9.15 ± 0.11**


Water contents (g/100 g fresh weight)


p < 0.01, n = 5.

Table 2 Statistics and quality estimation of RNA-seq reads Sample

Raw reads

Clean reads

Clean bases

Error rate (%)


GC content (%)


51 954 318

51 618 294

7 724 506 990





51 588 574

51 276 776

7 675 654 881





50 039 168

49 738 930

7 447 363 676





49 388 786

49 078 670

7 341 985 410





48 395 514

48 080 756

7 185 197 965





51 523 832

51 208 436

7 661 197 246




Note: A1-A3 represent the 3 biological replicates of the peach-shaped fruiting body, and B1-B3 represent the 3 biological replicates of the mature fruiting body.

Figure Legends

Figure 1 Workflows of de novo transcriptome assembly and shotgun proteome analysis of Dictyophora indusiata fruiting body.

Figure 2


and functional annotation

of the D. indusiata

transcriptome. A, The length distribution of D. indusiata unigenes; B, functional annotations of D. indusiata unigenes in public databases; C, GO classification of the D. indusiata unigenes; D, KEGG classification of the D. indusiate unigenes.

Figure 3 Statistics and functional annotation of the D. indusiata proteome. A, Statistical information from tandem mass spectrometry and protein identification; B, subcellular localization of the identified D. indusiata proteins; C, GO enrichment analysis of the identified D. indusiata proteins.

Figure 4 GO analysis (A) and KEGG pathway analysis (B) of the differentially expressed genes (DEGs) between peach-shaped and mature D. indusiate fruiting body.

Figure 5 The matched unigenes in the cell wall stress-dependent MAPK sub-pathway.

A total of 19704 unigenes were sequenced and 4380 proteins were identified in D. indusiata fruiting bodies

The identified proteins were significantly enriched in small molecule synthetic and metabolic







ubiquitination), and vesicle transport.

Quantitative transcriptome analysis revealed that the metabolism and transport activities were upregulated in the mature stage, while protein translation was downregulated.

The cell wall stress-dependent MAPK sub-pathway was activated in the mature stage, and fungal cell wall degradation-related genes were upregulated and might play a key role in the morphological development of D. indusiata fruiting bodies.