Next Article in Journal
Mining Genetically Encoded Biosensors from Filamentous Fungi
Previous Article in Journal
Screening and Validation of Interacting Proteins of Receptor-like Cytoplasmic Kinase OsRLCK118 Involved in Rice Blast Resistance
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Transcriptomic and Physiological Profiling Reveals Metabolic Determinants and Key Regulatory Hubs of Fruiting Body Degeneration in Lentinula edodes

1
The Key Laboratory of Development and Utilization of Edible and Medicinal Mushroom Resources, Lishui Institute of Agriculture and Forestry Sciences, Lishui 323000, China
2
Lishui Municipal Administration for Market Regulation, Lishui 323000, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Fungi 2026, 12(2), 149; https://doi.org/10.3390/jof12020149
Submission received: 20 January 2026 / Revised: 11 February 2026 / Accepted: 13 February 2026 / Published: 19 February 2026
(This article belongs to the Section Fungal Cell Biology, Metabolism and Physiology)

Abstract

Frequent strain degeneration during subcultivation, characterized by impaired sporulation and fruiting body formation, represents a major constraint in fungal agricultural production. Our study systematically investigated two naturally degenerated Lentinula edodes strains classified as abortive (Abt: L808-13, L808-14) and malformed (Abn: L808-18) fruiting-body phenotypes, through comprehensive phenotypic characterization, enzymatic profiling, thermotolerance assessment, and transcriptomic analysis. While vegetative growth remained unaffected, degenerated strains exhibited premature hyphal knotting, significantly reduced thermotolerance, and Abn-specific suppression of carboxymethyl cellulase (CMCase) activity. Comparative transcriptomics revealed 1239 and 582 differentially expressed genes (DEGs) in Abt and Abn groups, respectively, accompanied by a global dysregulation in carbohydrate catabolism, phospholipid metabolism, and redox homeostasis. Furthermore, protein–protein interaction (PPI) networks and RT-qPCR data highlighted 12 core hub genes enriched in glycoside hydrolysis, cytochrome P450 signaling, and membrane lipid dynamics. These findings provide mechanistic insights into the molecular basis of fruiting body degeneration and establish a foundation for developing diagnostic indicators to screen for early-stage degeneration in industrial mushroom production.

1. Introduction

Edible mushrooms, particularly Lentinula edodes (shiitake), represent a valuable global food source, with shiitake ranking among the most widely cultivated species [1,2,3]. Beyond its distinctive flavor and low-calorie profile, L. edodes is renowned for diverse bioactive compounds including polysaccharides, phenolics, essential amino acids, vitamins, and ergosterol [4,5], which confer antitumor activity, antiviral, immunomodulatory, and hypocholesterolemic effects [6,7,8,9,10].
High-quality strains underpin stable cultivation and sustainable development of the mushroom industry, yet intensive farming has exacerbated strain degeneration, manifesting as reduced mycelial growth, abnormal browning, impaired fruiting body development, and decreased yield and inferior quality, with substantial economic losses [11,12,13]. The fruiting body serves as both the primary edible organ and a key reproductive structure, progressing from simple to complex multicellularity via primordium initiation, stipe and cap differentiation, pileus expansion with lamella formation, and basidiospore maturation [14,15,16,17,18]. This process is regulated by intrinsic genetic programs and environmental cues such as light, temperature, nutrition, humidity, and ventilation, alongside genetic factors like mating-type genes [19]. Model basidiomycetes have revealed key regulators, including ICH1, EXP1, ELN2, ELN3, DST1, and DST2 in Coprinopsis cinerea [20,21,22,23,24] and FST3, FST4, WC-1, WC-2, BRI1, HOM1, and HOM2 in Schizophyllum commune [25,26,27].
Omics advances have elucidated gene dynamics in fruiting body development across species like Coprinopsis cinerea [28], Agaricus bisporus [29], Flammulina velutipes [30], Hypsizygus marmoreus [31], and Lentinula edodes [32], implicating a diverse array of biological processes such as hydrophobin synthesis, F-box protein-mediated ubiquitination, cytochrome P450-catalyzed biotransformation, septin regulation, ribosomal translation, kinase-mediated signal transduction, DNA damage repair, transmembrane transport, polysaccharide metabolism, heat shock responses, sterol biosynthesis, amino acid metabolism, mTOR signaling, fatty acid metabolism, and cell wall remodeling [28,33,34].
For shiitake, the research on fruiting body development remains at an exploratory stage, with current work largely focused on primordium formation and the development of the stipe and cap [32]. Notably, PRIB, Le.hyd1, and Le.hyd2 are highly expressed during the primordium stage [35,36,37], Le.CDC5 is abundantly expressed in both mycelium and early maturation stages of fruiting bodies [38]. MFBC and EXG1 are specifically expressed in fruiting bodies [36,39], UCK1 shows enriched expression in gill tissue, and LeTYR is associated with gill browning [40]. Additionally, TLG1 is activated during fruiting body senescence and polysaccharide degradation [41]. To date, most studies interrogate normal developmental trajectories, while mechanisms underlying mutant or degenerate phenotypes remain sparse and limited to a few morphogenetic abnormalities like dysgenetic cap edge development [42]. The complexity of basidiomycete development and genetic intractability continue to hinder mechanistic resolution [28,29,30].
In this study, we employed comparative transcriptome analysis to identify the functional genes and regulatory networks underlying abnormal fruiting body development in L. edodes. Integrated analyses of the abortive (Abt: L808-13 and L808-14) and malformed (Abn: L808-18) phenotypes uncovered key pathways and molecular mechanisms associated with reproductive development, as well as three novel missense mutations that may act as potential genetic drivers. These findings advance the understanding of fungal reproductive biology and provide actionable targets for breeding strategies aimed at mitigating strain degeneration and enhancing the economic sustainability of mushroom cultivation.

2. Materials and Methods

2.1. Materials and Growth Conditions

The dikaryotic L. edodes strain L808 was obtained from the Edible Fungi Research Institute of Lishui Academy of Agricultural and Forestry Sciences. For cultivation, L808 was grown in permeable polypropylene bags (15 cm × 55 cm) containing 1800 g of autoclaved substrate composed of 78% hardwood sawdust, 20% wheat bran, 1% brown sugar, 1% gypsum, with water added to achieve a final moisture content of 60%. Fruiting was induced using an autumn high-shed layer cultivation system in Songyang, Zhejiang, with the system maintained under ambient environmental conditions. From the cultivation cycles of strain L808, three strains exhibiting distinct and stable phenotypes were isolated via tissue culture, including normal control strains (Nle: L808-6, L808-9), abortive fruiting body strains (Abt: L808-13, L808-14), and malformed fruiting body strains (Abn: L808-18). All sub-strains have been confirmed to reproducibly exhibit their respective phenotypes.

2.2. Strain Characterization and Phenotypic Analysis

Mycelial morphology was evaluated on potato dextrose agar (PDA) plates after incubation at 25 °C for 30 days. Mycelial growth rate was determined in tubes with sawdust-based medium (78% hardwood sawdust, 20% wheat bran, 1% brown sugar, 1% gypsum; substrate-to-water ratio, 1:1.2), incubating at 25 °C, and calculating daily growth rate based on distances between marked growth lines. Yield per bag was recorded when the veils had cracked but not yet fully detached.

2.3. Heat Stress Tolerance Assessment

Mycelium in sawdust medium tubes was incubated at 25 °C for 7–10 days, with initial growth lines marked. Following 4 h heat stress at 42 °C, incubation resumed at 25 °C until mycelium reached 1 cm from the tube bottom, when final growth lines were marked. Growth rate after heat stress was calculated from measured distances.

2.4. Enzyme Assays

The relative activities of laccase and carboxymethyl cellulase (CMCase) were assessed with plate-based assays. For laccase activity, mycelial plugs were inoculated on PDA plates supplemented with 0.04% (w/v) guaiacol and incubated at 25 °C for 8–12 days. Activity was evaluated by measuring the diameter of the resulting brownish-red oxidation zone. For CMCase activity, mycelia were cultured on CMC-Na plates (containing 0.5% CMC, 0.1% MgSO4, 0.2% KH2PO4, 0.2% yeast extract, and 1.5% agar) at 25 °C for 7 days. Subsequently, the plates were stained with 1 mg/mL Congo red for 15 min and destained with 1 M NaCl for another 15 min, after which the diameter of the hydrolysis halo was recorded. Enzyme activity was quantified based on the size of the oxidation zone (laccase) or hydrolysis halo (CMCase), with larger zones indicating higher activity.

2.5. RNA Sequencing and Differential Expression Analysis

Total RNA was extracted from the mycelium of L. edodes L808 strains using the MiniBEST Plant RNA Extraction Kit (Takara, Dalian, China) according to the manufacturer’s instructions. RNA integrity was assessed by 1% agarose gels and RNA Nano 6000Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA). RNA purity and concentration were determined by NanoPhotometer® spectrophotometer (IMPLEN, Westlake Village, CA, USA) and Qubit® RNA Assay Kit in Qubit®2.0 Flurometer (Life Technologies, Carlsbad, CA, USA), respectively. Sequencing libraries were prepared with the NEBNext Ultra™ RNA Library Prep Kit (New England Biolabs, Beijing, China) and subjected to paired-end (150 bp) sequencing on an Illumina NovaSeq 6000 platform at Novogene Co., Ltd. (Beijing, China).
Raw reads were processed with fastp to remove adapter sequences, duplicates, and low-quality bases. Clean reads were aligned to the L. edodes reference genome (GenBank accession GCA_015476405.1) using HISAT2 (v2.0.5). The genome annotation file was updated and refined by Novogene Co., Ltd. (Beijing, China) through the integration of the newly generated transcriptomic data with the original genomic sequence (File S1). Gene expression levels were quantified as FPKM (fragments per kilobase per million mapped reads) using featureCounts (Subread v1.6.4). Read counts were normalized via DESeq2 (v1.26.0), which models fragment distribution using a negative binomial model. Differentially expressed genes (DEGs) were defined with thresholds of |log2(fold change)| ≥ 1 and adjusted p-value < 0.05 after multiple-testing correction. Use GATKv4.1.9.0 to analyze and annotate the variant sites. Functional annotation and enrichment analyses of DEGs for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed with clusterProfiler (v3.14.3) to identify relevant metabolic and signaling pathways. Use GATKv4.1.9.0 to analyze the variant sites, and use annovar to annotate the variant sites. Protein–protein interactions among differentially expressed genes were analyzed using the STRING database to identify functional associations and potential biological networks.

2.6. Real-Time PCR Analysis of Gene Expression

To validate the transcriptomic results, quantitative real-time PCR (qRT-PCR) was performed on selected differentially expressed genes (DEGs). Total RNA (1 μg) isolated from the mycelium of L. edodes strain L808 was reverse-transcribed into cDNA with the PrimeScript™ RT Master Mix (Takara, Dalian, China). qRT-PCR was performed on a LightCycler® 480 II system (Roche, Rotkreuz, Switzerland) using TB Green® Premix Ex Taq™ II (Takara, Dalian, China). According to experimental screening, the Actin gene was used for normalization [43]. Relative gene expression levels were calculated using the 2−ΔΔCT method. Each experiment included three independent biological replicates. All primer sequences are listed in Table S1.

2.7. Statistical Analysis

All experiments were conducted in triplicate. Data are expressed as mean ± SD. Statistical analysis used one-way ANOVA with Duncan’s test (p < 0.05). Different letters denote significant differences.

3. Results

3.1. Fruiting-Body Development Is Specifically Disrupted in Spontaneous L808 Degenerates

Naturally degenerated L. edodes L808 strains (L808-13, L808-14, L808-18) displayed normal vegetative growth and browning processes but exhibited distinct defects in fruiting body development. During reproductive development, L808-13 and L808-14 showed severe impairment in fruiting body formation with nearly undetectable yields, while L808-18 produced undifferentiated, tumor-like structures that lacked the typical morphology of stipe, pileus, and gills (Figure 1A,B). After 40-day incubation at 25 °C, the degenerated strains of L808-13, L808-14 and L808-18 exhibited significant hyphal knotting (Figure 1C), indicating premature initiation of reproductive development (primordia formation). Agronomic analysis revealed negligible yields of fruiting bodies in the degenerated strains, despite their mycelial growth rates being comparable to those of the normal control strains L808-6 and L808-9 (Figure 1D). These results suggested that developmental defects of degenerate strains were mainly concentrated in fruiting body formation, especially primordium formation and differentiation stages.

3.2. Extracellular Enzyme Activities and Heat Tolerance in Degenerated Strains

Extracellular enzyme activities and thermotolerance responses were assessed to evaluate the physiological status of degenerated L. edodes L808 strains. Laccase and carboxymethyl cellulase (CMCase), key enzymes involved in lignocellulose and cellulose metabolism, play essential roles in fruiting body formation [44,45].
In our assay, laccase activity showed no significant differences in the diameter of the halo zone among the three degenerated strains (L808-13, L808-14, L808-18) and the normal controls (Figure 2A,C). However, a lighter coloration in the oxidation zone was observed in strain L808-14, indicating a slight decrease in laccase secretion or enzymatic activity. In contrast, the malformed-fruiting strain L808-18 displayed a visibly smaller and statistically significant reduction in halo size compared to both the other degenerated strains and the normal controls (Figure 2B,C), suggesting substantially diminished CMCase activity. These results preliminarily indicate that laccase-mediated capacity was largely retained with only minor variations, whereas the reduced CMCase activity may reflect a strain-specific impairment in cellulose metabolism.
Thermotolerance analysis following 42 °C heat treatment revealed significantly reduced mycelial growth rates in both non-fruiting (L808-13, L808-14) and malformed-fruiting (L808-18) degenerated strains compared to normal controls (Figure 2D). The compromised heat stress response indicates impaired high-temperature adaptation mechanisms as a common physiological defect in degenerated strains, independent of their specific fruiting body phenotype.

3.3. Transcriptomic Alterations in L808 Strain Degeneration

RNA sequencing was performed with three biological replicates for both normal (L808-6 and L808-9) and degenerated strains (L808-13, L808-14, and L808-18). After quality control, each sample generated 5.96–7.36 Gb of clean reads, with Q20 ≥ 99.20%, Q30 ≥ 93.10%, and GC content ranging from 48.34% to 48.68%, confirming high data quality.
Principal component analysis (PCA) showed clear segregation between normal and degenerated strains. Furthermore, the abortive (L808-13, L808-14) and malformed (L808-18) degenerated strains formed distinct clusters, indicating significantly altered gene expression patterns in degeneration strains (Figure 3A).
Based on the PCA results, two comparison groups were defined: Nle_vs_Abt (normal vs. abortive fruiting body: L808-6/L808-9 vs. L808-13/L808-14) and Nle_vs_Abn (normal vs. malformed fruiting body: L808-6/L808-9 vs. L808-18). Using thresholds of |log2FC| ≥ 1 and p ≤ 0.05, we identified 1239 differentially expressed genes (DEGs) in the Nle_vs_Abt group (594 up- and 645 down-regulated) and 582 DEGs in the Nle_vs_Abn group (278 up- and 304 down-regulated), respectively (Figure 3B,C).

3.4. Enrichment Analysis of DEGs

Functional enrichment analysis of DEGs revealed significant metabolic reprogramming in degenerated L. edodes strains. In the GO analysis, DEGs from both the abortive and malformed comparison groups were significantly enriched in biological processes related to carbohydrate metabolic processes, polysaccharide metabolic processes, carbohydrate catabolic processes, and polysaccharide catabolic processes. For molecular function, enriched terms included monooxygenase activity, hydrolase activity acting on glycosyl bonds, and hydrolase activity hydrolyzing O-glycosyl compounds. Cellular component analysis showed enrichment in extracellular region and cell wall components (Figure 4). Notably, down-regulated genes substantially outnumbered up-regulated ones within these enriched terms, suggesting potential suppression of these metabolic pathways (Figure 4).
KEGG pathway analysis demonstrated that DEGs in the abortive group were notably enriched in metabolic pathways, starch and sucrose metabolism, steroid biosynthesis, glycine-serine-threonine metabolism, amino sugar and nucleotide sugar metabolism, and glycerophospholipid metabolism. In the malformed group, significant enrichment was observed in metabolic pathways, ascorbate and aldarate metabolism, cyanoamino acid metabolism, and glycerophospholipid metabolism (Figure 5).
Collectively, the enrichment analyses demonstrate that DEGs from both abortive and malformed groups share significant enrichment in carbohydrate catabolism and polysaccharide degradation pathways, indicating potential impairment of extracellular polysaccharide hydrolysis capacity essential for normal fruiting body development. Furthermore, the distinct metabolic profiles observed between abortive and malformed groups suggest differential molecular mechanisms underlying these two degeneration phenotypes.

3.5. Identification of WGCNA Modules Associated with Degeneration

A weighted gene co-expression network analysis (WGCNA) was performed with the transcriptomic data, leading to the identification of 17 co-expression modules (Figure 6A). Analysis of the module-trait relationships revealed that the turquoise module comprising 3350 genes was highly correlated with yield (r = 0.94, p < 0.01) and negatively correlated with degeneration (r = −0.94, p < 0.01), while the tan module of 131 genes exhibited opposite correlation patterns (r = −0.85, p < 0.01 for yield; r = 0.85, p < 0.01 for degeneration) (Figure 6B). Gene significance tightly tracked module membership in both modules (turquoise: r = 0.89, p < 1 × 10−200; tan: r = 0.87, p = 1.9 × 10−41), indicating the robustness of these module-trait associations (Figure 6C). Expression analysis demonstrated global downregulation of the turquoise module and predominant upregulation of the tan module in degenerated strains (Figure S1). These findings delineate trait-associated transcriptional programs and nominate hub genes within the turquoise and tan modules as mechanistic candidates for fruit body degeneration and yield determination.

3.6. Core Genes and Coordinated Metabolic Disruption in Degenerated Strains

Intersection analysis of DEGs from the abortive and malformed comparison groups identified 231 shared DEGs (Figure 7A). A secondary intersection between these DEGs and genes from the degeneration-associated WGCNA modules (turquoise and tan) yielded 111 overlapping candidates (Figure 7B). KEGG enrichment of these 111 genes highlighted glycerophospholipid metabolism, biosynthesis of secondary metabolites, starch and sucrose metabolism, and metabolic pathways (Figure 7C). Heatmap profiling revealed 22 key genes within the four enriched pathways that were consistently downregulated in degenerate strains (Figure 7D). Protein–protein interaction (PPI) network analysis of the 22 genes using STRING revealed that the interactions centered around 12 core genes (Table S2), forming four distinct functional modules (Figure 7E): a carbohydrate metabolism network (3 glycoside hydrolases, 2 α-amylases), a cytochrome P450 cluster (3 CYP450 family proteins), a phospholipid metabolism node (2 phosphatidylserine decarboxylases), and an ALDH/ACAT processing unit (aldehyde dehydrogenase, acetyl-CoA acetyltransferase). These findings suggest coordinated dysregulation of carbon source utilization, membrane integrity maintenance, and systemic metabolite synthesis in fruiting body degeneration.

3.7. RT-qPCR Validation of Transcriptomic Data

RT-qPCR was performed on six DEGs to experimentally validate the transcriptome sequencing results. Six hub genes were selected from the protein–protein interaction network (Figure 7E), including GH1 (evm.TU.Scaffold10.351), GH20 (evm.TU.Scaffold4.774), AMY1 (evm.TU.Scaffold4.1138), CYP450 (evm.TU.Scaffold3.156), ALDH (evm.TU.Scaffold2.1051), PSD (evm.TU.Scaffold5.1233). As shown in Figure 8, the gene expression profiles of these genes were consistent with the RNA-Seq results, with reduced transcript abundance in the DEGs from the interaction network. The results confirm the reliability of our transcriptomic analyses.

4. Discussion

4.1. Morphological Divergence and Developmental Defects in Degenerate Strains

Strain degeneration during subcultivation represents a polygenic and complex physiological process that severely hinders the industrial production of L. edodes [11,13]. Our investigation integrated phenotypic, physiological, and transcriptomic analyses to elucidate the mechanism of two distinct degeneration phenotypes, namely the abortive type (Abt; L808-13 and L808-14) and the malformed phenotype (Abn; L808-18). While previous reports regarding Cordyceps militaris, Flammulina filiformis, and Lentinula edodes documented degeneration symptoms such as low yields or slight morphological abnormalities [11,42,46], the nodular, tumor-like, and completely undifferentiated tissue observed in the Abn phenotype appears unprecedented (Figure 1). Such divergence between abortive and malformed types suggests that fruiting body degeneration may occur at various developmental stages. Specifically, the Abt strain represents an early-stage arrest in primordium development, whereas the Abn phenotype indicates a profound breakdown in metabolic pathways required for cap and stipe differentiation. Consequently, the degenerate materials provide a comprehensive biological framework for deciphering the molecular mechanisms governing mushroom morphogenesis.

4.2. Metabolic Breakdown and Carbohydrate Dysregulation in Degenerate Strains

The transition from vegetative growth to reproductive development necessitates a profound metabolic shift to support rapid morphogenesis. Analysis of Morchella species demonstrated that fluctuations in carbohydrate metabolism pathways, including starch and sucrose metabolism, are critical for the progression from primordia to mature sporophores [47,48]. In our research, the malformed strain L808-18 exhibited a specific inhibition of CMCase activity while laccase levels remained stable (Figure 2). Such physiological defects suggest that the formation of nodular tissue may arise from an inability to liberate sufficient glucose for differentiation. A similar dependence on glycoside hydrolases for stipe elongation has been established in Volvariella volvacea [49], implying that the L808-18 phenotype suffers from a kinetic bottleneck where the energy supply cannot sustain the differentiation of cap and stipe.
In contrast, the abortive strains L808-13 and L808-14 retained laccase and CMCase activities to a considerable extent, yet failed to produce primordia (Figure 1 and Figure 2). Interestingly, transcriptomic profiling revealed that the abortive strains shared significant downregulation of carbohydrate degradation genes with the malformed strain, suggesting that metabolic imbalance may occur at the level of carbon flux redirection or regulatory coordination rather than absolute enzymatic capacity (Figure 4 and Figure 5). Similar to Ganoderma lucidum, the upregulation of carbohydrate metabolism genes is essential to provide structural energy during reproductive development [50]. Our work proposes that in the abortive strains, transcriptional repression of carbohydrate and polysaccharide metabolism prevents the supply of energy required for primordium initiation. Consequently, the failure of the malformed strain may be attributable to a limited supply of hydrolysis products, whereas the abortive strains may fail to form primordia due to inadequate or improper activation of the metabolic program required for resource utilization.

4.3. Stress Adaptation and Membrane Homeostasis in Degenerate Strains

Beyond energy metabolism, strain degeneration in L. edodes is fundamentally linked to a breakdown in stress adaptation and membrane homeostasis. The universal but variable reduction in thermotolerance across all degenerate strains serves as a primary physiological indicator of an impaired stress response (Figure 2), especially considering that temperatures can affect the formation of normal fruiting bodies [42]. Our findings suggest that such vulnerability appears to be driven by the coordinated downregulation of the cytochrome P450 (CYP) superfamily (Figure 7 and Figure 8), which comprises essential regulators of stipe elongation and secondary metabolism in Coprinopsis cinerea and L. edodes [21,51]. Furthermore, the significant enrichment of monooxygenase-related genes in degenerated strains indicates a systemic failure to maintain redox homeostasis (Figure 4). Such disruption likely leads to the defective accumulation of reactive oxygen species (ROS), a physiological stressor previously identified as a key driver of developmental abnormalities and mycelial senescence in Volvariella volvacea [52,53]. Consistent with broader observations, fungal degeneration in our study was also coupled with markers of oxidative stress [12].
Concomitantly, the significant enrichment of DEGs in glycerophospholipid metabolism and cell wall components suggests a compromised membrane system (Figure 5, Figure 7 and Figure 8). The downregulation of phosphatidylserine decarboxylase (PSD) is particularly critical because the enzyme catalyzes the formation of phosphatidylethanolamine, a major determinant of membrane fluidity and intracellular signaling [54]. Our hypothesis suggests that the dysregulation of phospholipid homeostasis in degenerate strains results in rigid or unstable membranes, which in turn impairs the localized secretion of extracellular enzymes and the perception of morphogenetic signals from the extracellular domain. Furthermore, the downregulated ALDH and ACAT likely fail to coordinate the metabolic cascade necessary for secondary metabolite synthesis and cell wall remodeling (Figure 7 and Figure 8). Together, these factors create a deleterious cascade where impaired stress adaptation and defective cell-cell communication prevent the complex tissue organization necessary for normal sporophore development.

4.4. Diagnostic Utility of Hub Genes for Strain Degeneration

Our study revealed a substantial number of DEGs in degenerated Lentinula edodes strains and identified 12 hub genes through network analysis. Although these core genes, including glycoside hydrolases, cytochrome P450 proteins, and membrane lipid-related genes, likely represent the physiological consequences triggered by specific genetic events rather than the primary pathogenic mutations, they provide significant value as diagnostic tools for early quality control. In agricultural practice, strain stability is frequently compromised during repeated subcultivation, while phenotypic abnormalities often remain latent at the mycelial level. By monitoring the expression levels of these hub genes, mycelium with impaired physiological status can be proactively identified before fruiting trials, providing a basis for the timely elimination of degenerated strains, thereby optimizing strain preservation processes and reducing production risks.

5. Conclusions

In summary, strain degeneration in L. edodes, manifesting as non-fruiting or malformed phenotypes, is driven by a coordinated collapse of carbohydrate mobilization, membrane lipid homeostasis, and stress resilience. Analysis of the protein–protein interaction network highlighted 12 hub genes associated with carbon metabolism, glycoside hydrolases, and P450 proteins that strictly correlate with fruiting body yield. Our findings elucidate the molecular mechanisms underlying fungal reproductive failure and identify candidate hub genes that function as diagnostic indicators for early detection of strain degeneration during mycelial propagation, thereby supporting quality control in industrial mushroom production.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/jof12020149/s1. File S1: Updated reference genome annotation for Lentinula edodes L808 (GenBank: GCA_015476405.1). Figure S1: Heatmap of gene expression in turquoise and tan modules. Table S1: Primers used for RT-qPCR. Table S2: The information of genes in protein–protein interaction network.

Author Contributions

Conceptualization, L.L. and K.L.; methodology, H.Y. and K.L.; validation, H.Y., X.S., X.L. and J.J.; formal analysis, H.Y. and X.S.; investigation, H.Y., X.L. and J.T.; resources, K.L. and J.J.; data curation, H.Y. and J.T.; writing—original draft preparation, H.Y.; writing—review and editing, K.L. and L.L.; visualization, H.Y.; supervision, L.L. and J.T.; project administration, K.L. and L.L.; funding acquisition, K.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Research and Development Projects of Lishui City, grant number 2025zdyf16. This work was partially supported by the earmarked fund for China Agriculture Research System, grant number CARS-20.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw sequencing data of RNA-seq are available at the National Genomics Data Center, China National Center for Bioinformation, under BioProject ID PRJCA055520 (https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA055520, accessed on 9 January 2026).

Acknowledgments

During manuscript preparation, the authors used Gemini 3.0 and DeepSeek V3 for grammar checking and language polishing. The authors have reviewed and edited all content and take full responsibility for the final publication.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Yoo, S.; Lee, H.-Y.; Markkandan, K.; Moon, S.; Ahn, Y.J.; Ji, S.; Ko, J.; Kim, S.-J.; Ryu, H.; Hong, C.P. Comparative Transcriptome Analysis Identified Candidate Genes Involved in Mycelium Browning in Lentinula edodes. BMC Genom. 2019, 20, 121. [Google Scholar] [CrossRef]
  2. Royse, D.J.; Baars, J.J.P.; Tan, Q. Current Overview of Mushroom Production in the World. In Edible and Medicinal Mushrooms: Technology and Applications; Wiley: Hoboken, NJ, USA, 2017; p. 2. [Google Scholar]
  3. Özçelik, E.; Pekşen, A. Hazelnut Husk as a Substrate for the Cultivation of Shiitake Mushroom (Lentinula edodes). Bioresour. Technol. 2007, 98, 2652–2658. [Google Scholar] [CrossRef]
  4. Ponnusamy, C.; Uddandrao, V.V.S.; Pudhupalayam, S.P.; Singaravel, S.; Periyasamy, T.; Ponnusamy, P.; Prabhu, P.; Sasikumar, V.; Ganapathy, S. Lentinula edodes (Edible mushroom) as a Nutraceutical: A Review. Biosci. Biotechnol. Res. Asia 2022, 19, 1–11. [Google Scholar] [CrossRef]
  5. Shi, D.; Yin, C.; Fan, X.; Yao, F.; Qiao, Y.; Xue, S.; Lu, Q.; Feng, C.; Meng, J.; Gao, H. Effects of Ultrasound and Gamma Irradiation on Quality Maintenance of Fresh Lentinula edodes during Cold Storage. Food Chem. 2022, 373, 131478. [Google Scholar] [CrossRef] [PubMed]
  6. Soković, M.; Ćirić, A.; Glamočlija, J.; Stojković, D. The Bioactive Properties of Mushrooms. In Wild Plants, Mushrooms and Nuts; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2016; pp. 83–122. [Google Scholar]
  7. Zhuang, H.; Chen, Z.; Feng, T.; Yang, Y.; Zhang, J.; Liu, G.; Li, Z.; Ye, R. Characterization of Lentinus edodes β-Glucan Influencing the in Vitro Starch Digestibility of Wheat Starch Gel. Food Chem. 2017, 224, 294–301. [Google Scholar] [CrossRef]
  8. Philippoussis, A.; Zervakis, G.; Philippoussis, A.; Zervakis, G. Cultivation of Edible Mushrooms in Greece: Presentation of the Current Status and Analysis of Future Trends. Sci. Cultiv. Edible Fungi. 2000, 2, 843–848. [Google Scholar]
  9. Wang, Y.; Zeng, X.; Liu, W. De Novo Transcriptomic Analysis during Lentinula edodes Fruiting Body Growth. Gene 2018, 641, 326–334. [Google Scholar] [CrossRef]
  10. Roncero-Ramos, I.; Delgado-Andrade, C. The Beneficial Role of Edible Mushrooms in Human Health. Curr. Opin. Food Sci. 2017, 14, 122–128. [Google Scholar] [CrossRef]
  11. Yin, J.; Xin, X.; Weng, Y.; Gui, Z. Transcriptome-Wide Analysis Reveals the Progress of Cordyceps militaris Subculture Degeneration. PLoS ONE 2017, 12, e0186279. [Google Scholar] [CrossRef]
  12. Danner, C.; Mach, R.L.; Mach-Aigner, A.R. The Phenomenon of Strain Degeneration in Biotechnologically Relevant Fungi. Appl. Microbiol. Biotechnol. 2023, 107, 4745–4758. [Google Scholar] [CrossRef]
  13. Chen, X.; Zhang, Z.; Liu, X.; Cui, B.; Miao, W.; Cheng, W.; Zhao, F. Characteristics Analysis Reveals the Progress of Volvariella Volvacea Mycelium Subculture Degeneration. Front. Microbiol. 2019, 10, 2045. [Google Scholar] [CrossRef] [PubMed]
  14. Nagy, L.G.; Kovács, G.M.; Krizsán, K. Complex Multicellularity in Fungi: Evolutionary Convergence, Single Origin, or Both? Biol. Rev. Camb. Philos. Soc. 2018, 93, 1778–1794. [Google Scholar] [CrossRef]
  15. Kuratani, M.; Tanaka, K.; Terashima, K.; Muraguchi, H.; Nakazawa, T.; Nakahori, K.; Kamada, T. The dst2 Gene Essential for Photomorphogenesis of Coprinopsis cinerea Encodes a Protein with a Putative FAD-Binding-4 Domain. Fungal Genet. Biol. FG B 2010, 47, 152–158. [Google Scholar] [CrossRef]
  16. Ohm, R.A.; de Jong, J.F.; de Bekker, C.; Wösten, H.A.B.; Lugones, L.G. Transcription Factor Genes of Schizophyllum commune Involved in Regulation of Mushroom Formation. Mol. Microbiol. 2011, 81, 1433–1445. [Google Scholar] [CrossRef] [PubMed]
  17. Kües, U. Life History and Developmental Processes in the Basidiomycete Coprinus cinereus. Microbiol. Mol. Biol. Rev. MMBR 2000, 64, 316–353. [Google Scholar] [CrossRef]
  18. Voisey, C.R. Intercalary Growth in Hyphae of Filamentous Fungi. Fungal Biol. Rev. 2010, 24, 123–131. [Google Scholar] [CrossRef]
  19. Manachère, G. Conditions Essential for Controlled Fruiting of Macromycetes—A Review. Trans. Br. Mycol. Soc. 1980, 75, 255–270. [Google Scholar] [CrossRef]
  20. Muraguchi, H.; Kamada, T. The ich1 Gene of the Mushroom Coprinus cinereus Is Essential for Pileus Formation in Fruiting. Dev. Camb. Engl. 1998, 125, 3133–3141. [Google Scholar] [CrossRef]
  21. Muraguchi, H.; Kamada, T. A Mutation in the eln2 Gene Encoding a Cytochrome P450 of Coprinus cinereus Affects Mushroom Morphogenesis. Fungal Genet. Biol. FG B 2000, 29, 49–59. [Google Scholar] [CrossRef]
  22. Arima, T.; Yamamoto, M.; Hirata, A.; Kawano, S.; Kamada, T. The eln3 Gene Involved in Fruiting Body Morphogenesis of Coprinus cinereus Encodes a Putative Membrane Protein with a General Glycosyltransferase Domain. Fungal Genet. Biol. FG B 2004, 41, 805–812. [Google Scholar] [CrossRef]
  23. Muraguchi, H.; Fujita, T.; Kishibe, Y.; Konno, K.; Ueda, N.; Nakahori, K.; Yanagi, S.O.; Kamada, T. The exp1 Gene Essential for Pileus Expansion and Autolysis of the Inky Cap Mushroom Coprinopsis cinerea (Coprinus cinereus) Encodes an HMG Protein. Fungal Genet. Biol. FG B 2008, 45, 890–896. [Google Scholar] [CrossRef]
  24. Kamada, T.; Sano, H.; Nakazawa, T.; Nakahori, K. Regulation of Fruiting Body Photomorphogenesis in Coprinopsis cinerea. Fungal Genet. Biol. FG B 2010, 47, 917–921. [Google Scholar] [CrossRef]
  25. Ohm, R.A.; Aerts, D.; Wösten, H.A.B.; Lugones, L.G. The Blue Light Receptor Complex WC-1/2 of Schizophyllum commune Is Involved in Mushroom Formation and Protection against Phototoxicity. Environ. Microbiol. 2013, 15, 943–955. [Google Scholar] [CrossRef] [PubMed]
  26. Ohm, R.A.; de Jong, J.F.; Lugones, L.G.; Aerts, A.; Kothe, E.; Stajich, J.E.; de Vries, R.P.; Record, E.; Levasseur, A.; Baker, S.E.; et al. Genome Sequence of the Model Mushroom Schizophyllum commune. Nat. Biotechnol. 2010, 28, 957–963. [Google Scholar] [CrossRef]
  27. Pelkmans, J.F.; Patil, M.B.; Gehrmann, T.; Reinders, M.J.T.; Wösten, H.A.B.; Lugones, L.G. Transcription Factors of Schizophyllum commune Involved in Mushroom Formation and Modulation of Vegetative Growth. Sci. Rep. 2017, 7, 310. [Google Scholar] [CrossRef] [PubMed]
  28. Muraguchi, H.; Umezawa, K.; Niikura, M.; Yoshida, M.; Kozaki, T.; Ishii, K.; Sakai, K.; Shimizu, M.; Nakahori, K.; Sakamoto, Y.; et al. Strand-Specific RNA-Seq Analyses of Fruiting Body Development in Coprinopsis cinerea. PLoS ONE 2015, 10, e0141586. [Google Scholar] [CrossRef]
  29. Gehrmann, T.; Pelkmans, J.F.; Ohm, R.A.; Vos, A.M.; Sonnenberg, A.S.M.; Baars, J.J.P.; Wösten, H.A.B.; Reinders, M.J.T.; Abeel, T. Nucleus-Specific Expression in the Multinuclear Mushroom-Forming Fungus Agaricus bisporus Reveals Different Nuclear Regulatory Programs. Proc. Natl. Acad. Sci. USA 2018, 115, 4429–4434. [Google Scholar] [CrossRef]
  30. Park, Y.-J.; Baek, J.H.; Lee, S.; Kim, C.; Rhee, H.; Kim, H.; Seo, J.-S.; Park, H.-R.; Yoon, D.-E.; Nam, J.-Y.; et al. Whole Genome and Global Gene Expression Analyses of the Model Mushroom Flammulina velutipes Reveal a High Capacity for Lignocellulose Degradation. PLoS ONE 2014, 9, e93560. [Google Scholar] [CrossRef]
  31. Zhang, J.; Ren, A.; Chen, H.; Zhao, M.; Shi, L.; Chen, M.; Wang, H.; Feng, Z. Transcriptome Analysis and Its Application in Identifying Genes Associated with Fruiting Body Development in Basidiomycete Hypsizygus marmoreus. PLoS ONE 2015, 10, e0123025. [Google Scholar] [CrossRef] [PubMed]
  32. Song, H.-Y.; Kim, D.-H.; Kim, J.-M. Comparative Transcriptome Analysis of Dikaryotic Mycelia and Mature Fruiting Bodies in the Edible Mushroom Lentinula edodes. Sci. Rep. 2018, 8, 8983. [Google Scholar] [CrossRef]
  33. Krizsán, K.; Almási, É.; Merényi, Z.; Sahu, N.; Virágh, M.; Kószó, T.; Mondo, S.; Kiss, B.; Bálint, B.; Kües, U.; et al. Transcriptomic Atlas of Mushroom Development Reveals Conserved Genes behind Complex Multicellularity in Fungi. Proc. Natl. Acad. Sci. USA 2019, 116, 7409–7418. [Google Scholar] [CrossRef] [PubMed]
  34. Almási, É.; Sahu, N.; Krizsán, K.; Bálint, B.; Kovács, G.M.; Kiss, B.; Cseklye, J.; Drula, E.; Henrissat, B.; Nagy, I.; et al. Comparative Genomics Reveals Unique Wood-decay Strategies and Fruiting Body Development in the Schizophyllaceae. New Phytol. 2019, 224, 902–915. [Google Scholar] [CrossRef] [PubMed]
  35. Endo, H.; Kajiwara, S.; Tsunoka, O.; Shishido, K. A Novel cDNA, priBc, Encoding a Protein with a Zn(II)2Cys6 Zinc Cluster DNA-Binding Motif, Derived from the Basidiomycete Lentinus edodes. Gene 1994, 139, 117–121. [Google Scholar] [CrossRef]
  36. Miyazaki, Y.; Sakuragi, Y.; Yamazaki, T.; Shishido, K. Target Genes of the Developmental Regulator PRIB of the Mushroom Lentinula edodes. Biosci. Biotechnol. Biochem. 2004, 68, 1898–1905. [Google Scholar] [CrossRef]
  37. Ng, W.L.; Ng, T.P.; Kwan, H.S. Cloning and Characterization of Two Hydrophobin Genes Differentially Expressed during Fruit Body Development in Lentinula edodes. FEMS Microbiol. Lett. 2000, 185, 139–145. [Google Scholar] [CrossRef]
  38. Nakazawa, T.; Miyazaki, Y.; Kaneko, S.; Shishido, K. Developmental Regulator Le.CDC5 of the Mushroom Lentinula edodes: Analyses of Its Amount in Each of the Stages of Fruiting-Body Formation and Its Distribution in Parts of the Fruiting Bodies. FEMS Microbiol. Lett. 2006, 261, 60–63. [Google Scholar] [CrossRef] [PubMed]
  39. Sakamoto, Y.; Irie, T.; Sato, T. Isolation and Characterization of a Fruiting Body-Specific Exo-Beta-1,3-Glucanase-Encoding Gene, exg1, from Lentinula edodes. Curr. Genet. 2005, 47, 244–252. [Google Scholar] [CrossRef]
  40. Sato, T.; Takahashi, M.; Hasegawa, J.; Watanabe, H. Overexpression and Repression of the Tyrosinase Gene in Lentinula edodes Using the pChG Vector. J. Biosci. Bioeng. 2019, 128, 1–7. [Google Scholar] [CrossRef]
  41. Sakamoto, Y.; Watanabe, H.; Nagai, M.; Nakade, K.; Takahashi, M.; Sato, T. Lentinula edodes tlg1 Encodes a Thaumatin-like Protein That Is Involved in Lentinan Degradation and Fruiting Body Senescence. Plant Physiol. 2006, 141, 793–801. [Google Scholar] [CrossRef]
  42. Yan, D.; Gao, Q.; Rong, C.; Liu, Y.; Song, S.; Yu, Q.; Zhou, K.; Liao, Y. Comparative Transcriptome Analysis of Abnormal Cap and Healthy Fruiting Bodies of the Edible Mushroom Lentinula edodes. Fungal Genet. Biol. 2021, 156, 103614. [Google Scholar] [CrossRef]
  43. Zhao, X.; Yang, H.; Chen, M.; Song, X.; Yu, C.; Zhao, Y.; Wu, Y. Reference Gene Selection for Quantitative Real-Time PCR of Mycelia from Lentinula edodes under High-Temperature Stress. BioMed Res. Int. 2018, 2018, 1670328. [Google Scholar] [CrossRef]
  44. Kumar, A.S.; Sharma, V.P.; Kumar, S.; Barh, A.; Banayal, S.; Kamal, S. Enzyme Profile of Shiitake Mushroom Strains Grown on Wheat Straw. Indian J. Hortic. 2018, 75, 475. [Google Scholar] [CrossRef]
  45. Cesur, A.; Yamamoto, R.; Asada, Y.; Watanabe, A. Relationship between Fruiting Body Development and Extracellular Laccase Production in the Edible Mushroom Flammulina velutipes. Biochem. Biophys. Rep. 2022, 29, 101204. [Google Scholar] [CrossRef] [PubMed]
  46. Wang, C.; Sun, Y.; Yang, X.; Wang, Z.; Xiang, S.; Huang, Z.; Liang, Y. Transcriptional Analysis Provides Molecular Insights into Degeneration of the Edible Fungus Flammulina filiformis. J. Appl. Microbiol. 2025, 136, lxaf039. [Google Scholar] [CrossRef] [PubMed]
  47. Fan, T.; Ren, R.; Tang, S.; Zhou, Y.; Cai, M.; Zhao, W.; He, Y.; Xu, J. Transcriptomics Combined with Metabolomics Unveiled the Key Genes and Metabolites of Mycelium Growth in Morchella importuna. Front. Microbiol. 2023, 14, 1079353. [Google Scholar] [CrossRef]
  48. Feng, W.; Guo, Z.; Jin, Q.; Xu, F.; Shen, Y.; Song, T.; Wang, M.; Zhang, J.; Fan, L.; Huang, X.; et al. A Preliminary Exploration of Transcriptome and Proteomic Changes during the Young and Harvest Periods in Morchella sextelata. J. Fungi 2025, 11, 192. [Google Scholar] [CrossRef]
  49. Tao, Y.; Xie, B.; Yang, Z.; Chen, Z.; Chen, B.; Deng, Y.; Jiang, Y.; van Peer, A.F. Identification and Expression Analysis of a New Glycoside Hydrolase Family 55 Exo-β-1,3-Glucanase-Encoding Gene in Volvariella volvacea Suggests a Role in Fruiting Body Development. Gene 2013, 527, 154–160. [Google Scholar] [CrossRef]
  50. Cai, M.; Liang, X.; Liu, Y.; Hu, H.; Xie, Y.; Chen, S.; Gao, X.; Li, X.; Xiao, C.; Chen, D.; et al. Transcriptional Dynamics of Genes Purportedly Involved in the Control of Meiosis, Carbohydrate, and Secondary Metabolism during Sporulation in Ganoderma lucidum. Genes 2021, 12, 504. [Google Scholar] [CrossRef]
  51. Miyazaki, Y.; Nakamura, M.; Babasaki, K. Molecular Cloning of Developmentally Specific Genes by Representational Difference Analysis during the Fruiting Body Formation in the Basidiomycete Lentinula edodes. Fungal Genet. Biol. FG B 2005, 42, 493–505. [Google Scholar] [CrossRef]
  52. Zhao, F.; Wang, Q.; An, X.; Tan, Q.; Yun, J.; Zhang, Y. Oxidative Damage from Repeated Tissue Isolation for Subculturing Causes Degeneration in Volvariella volvacea. Front. Microbiol. 2023, 14, 1210496. [Google Scholar] [CrossRef]
  53. Zhao, F.; Liu, X.; Chen, C.; Cheng, Z.; Wang, W.; Yun, J. Successive Mycelial Subculturing Decreased Lignocellulase Activity and Increased ROS Accumulation in Volvariella volvacea. Front. Microbiol. 2022, 13, 997485. [Google Scholar] [CrossRef] [PubMed]
  54. Schuiki, I.; Daum, G. Phosphatidylserine Decarboxylases, Key Enzymes of Lipid Metabolism. IUBMB Life 2009, 61, 151–162. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Phenotypic characteristics of Lentinula edodes L808 strains. (A) Normal strain L808-9 and degenerated strains L808-13, L808-14, L808-18 with abnormal fruiting body development. (B) Malformed, undifferentiated fruiting body of degenerated strain L808-18. (C) Hyphal morphology observation of L. edodes L808 strains. (D) Fruiting body yield per bag (left) and daily mycelial growth rate (right). Data are presented as mean ± SD (n = 3). Different lowercase letters indicate significant differences (p < 0.05). Scale bars: (A) = 5 cm; (B) = 20 mm; (D) = 10 cm.
Figure 1. Phenotypic characteristics of Lentinula edodes L808 strains. (A) Normal strain L808-9 and degenerated strains L808-13, L808-14, L808-18 with abnormal fruiting body development. (B) Malformed, undifferentiated fruiting body of degenerated strain L808-18. (C) Hyphal morphology observation of L. edodes L808 strains. (D) Fruiting body yield per bag (left) and daily mycelial growth rate (right). Data are presented as mean ± SD (n = 3). Different lowercase letters indicate significant differences (p < 0.05). Scale bars: (A) = 5 cm; (B) = 20 mm; (D) = 10 cm.
Jof 12 00149 g001
Figure 2. Analysis of enzymatic activities and thermotolerance in Lentinula edodes L808. (A) Determination of relative laccase activity. (B) Determination of relative carboxymethyl cellulase (CMCase) activity. (C) Statistical analysis of enzyme activities was quantified based on the diameter of the oxidation zone (laccase) or hydrolysis halo (CMCase). (D) Assessment of mycelial thermotolerance. Data are presented as mean ± SD (n = 3). Different lowercase letters indicate statistically significant differences (p < 0.05); ** p < 0.01. Bars = 10 cm in (A,B).
Figure 2. Analysis of enzymatic activities and thermotolerance in Lentinula edodes L808. (A) Determination of relative laccase activity. (B) Determination of relative carboxymethyl cellulase (CMCase) activity. (C) Statistical analysis of enzyme activities was quantified based on the diameter of the oxidation zone (laccase) or hydrolysis halo (CMCase). (D) Assessment of mycelial thermotolerance. Data are presented as mean ± SD (n = 3). Different lowercase letters indicate statistically significant differences (p < 0.05); ** p < 0.01. Bars = 10 cm in (A,B).
Jof 12 00149 g002
Figure 3. Transcriptomic analysis of normal and degenerated Lentinula edodes strains. (A) PCA analysis. (B) Volcano plots showing DEGs in Nle _vs_Abt (normal strains L808-6/L808-9 vs. abortive strains L808-13/L808-14) comparison groups. (C) Volcano plots showing DEGs in Nle_vs_Abn (normal strains L808-6/L808-9 vs. malformed strain L808-18) comparison groups.
Figure 3. Transcriptomic analysis of normal and degenerated Lentinula edodes strains. (A) PCA analysis. (B) Volcano plots showing DEGs in Nle _vs_Abt (normal strains L808-6/L808-9 vs. abortive strains L808-13/L808-14) comparison groups. (C) Volcano plots showing DEGs in Nle_vs_Abn (normal strains L808-6/L808-9 vs. malformed strain L808-18) comparison groups.
Jof 12 00149 g003
Figure 4. GO enriched pathway diagram of DEGs in Lentinula edodes L808.
Figure 4. GO enriched pathway diagram of DEGs in Lentinula edodes L808.
Jof 12 00149 g004
Figure 5. KEGG enriched pathway diagram of DEGs in Lentinula edodes L808. (A) Top 20 enriched KEGG bubble chart and annotation table for the DEGs in the abortive comparison group (Nle_vs_Abt). (B) Top 20 enriched KEGG bubble chart and annotation table for DEGs in the abnormal comparison group (Nle_vs_Abn). The size of the circles indicates the number of enriched genes. The orange line indicates the significance threshold (p-value = 0.05).
Figure 5. KEGG enriched pathway diagram of DEGs in Lentinula edodes L808. (A) Top 20 enriched KEGG bubble chart and annotation table for the DEGs in the abortive comparison group (Nle_vs_Abt). (B) Top 20 enriched KEGG bubble chart and annotation table for DEGs in the abnormal comparison group (Nle_vs_Abn). The size of the circles indicates the number of enriched genes. The orange line indicates the significance threshold (p-value = 0.05).
Jof 12 00149 g005
Figure 6. Weighted gene co-expression network analysis (WGCNA) of Lentinula edodes L808. (A) Hierarchical cluster tree. Each leaf represents a gene, and each major branch represents a co-expression module, with distinct colors indicating different modules. Genes not assigned to any module are shown in gray. (B) Module-trait correlation heatmap. The color scale on right shows module-trait correlation from −1 (blue) to 1 (red). The top and bottom numbers in each module represent the correlation coefficient and the corresponding p-value, respectively. (C) Scatter plot of module membership (MM) versus gene significance (GS) for the degeneration trait. Correlation coefficients for the turquoise and tan modules are 0.89 and 0.87, respectively.
Figure 6. Weighted gene co-expression network analysis (WGCNA) of Lentinula edodes L808. (A) Hierarchical cluster tree. Each leaf represents a gene, and each major branch represents a co-expression module, with distinct colors indicating different modules. Genes not assigned to any module are shown in gray. (B) Module-trait correlation heatmap. The color scale on right shows module-trait correlation from −1 (blue) to 1 (red). The top and bottom numbers in each module represent the correlation coefficient and the corresponding p-value, respectively. (C) Scatter plot of module membership (MM) versus gene significance (GS) for the degeneration trait. Correlation coefficients for the turquoise and tan modules are 0.89 and 0.87, respectively.
Jof 12 00149 g006
Figure 7. Identification and functional analysis of core genes associated with fruiting body degeneration. (A) Venn diagrams of DEGs from Nle vs. Abt and Nle vs. Abn; the overlap defines co_diff. (B) Venn diagram showing the intersection between common DEGs (co_diff) and genes from the turquoise and tan WGCNA modules. (C) KEGG pathway enrichment analysis of 111 shared genes identified from intersections in (B). (D) Heatmap of DEGs within the top four enriched KEGG pathways from (C). (E) Protein–protein interaction network for genes from the top four pathways, highlighting functional clusters: carbohydrate metabolism (GHs, α-AMYs), cytochrome P450 (CYP450), phospholipid metabolism (PSD), and aldehyde/acetyl-CoA processing (ALDH, ACAT). PSD, phosphatidylserine decarboxylase; ACAT, acetyl-CoA acetyltransferase; CYP450, cytochrome P450 family; GH, glycoside hydrolase; ALDH, aldehyde dehydrogenase; α-AMY, α-amylase.
Figure 7. Identification and functional analysis of core genes associated with fruiting body degeneration. (A) Venn diagrams of DEGs from Nle vs. Abt and Nle vs. Abn; the overlap defines co_diff. (B) Venn diagram showing the intersection between common DEGs (co_diff) and genes from the turquoise and tan WGCNA modules. (C) KEGG pathway enrichment analysis of 111 shared genes identified from intersections in (B). (D) Heatmap of DEGs within the top four enriched KEGG pathways from (C). (E) Protein–protein interaction network for genes from the top four pathways, highlighting functional clusters: carbohydrate metabolism (GHs, α-AMYs), cytochrome P450 (CYP450), phospholipid metabolism (PSD), and aldehyde/acetyl-CoA processing (ALDH, ACAT). PSD, phosphatidylserine decarboxylase; ACAT, acetyl-CoA acetyltransferase; CYP450, cytochrome P450 family; GH, glycoside hydrolase; ALDH, aldehyde dehydrogenase; α-AMY, α-amylase.
Jof 12 00149 g007
Figure 8. Verification of the relative expression levels of DEGs by RT-qPCR. Expression patterns of 6 DEGs were performed. Data are presented as mean ± SD (n = 3). Different lowercase letters indicate statistically significant differences (p < 0.05).
Figure 8. Verification of the relative expression levels of DEGs by RT-qPCR. Expression patterns of 6 DEGs were performed. Data are presented as mean ± SD (n = 3). Different lowercase letters indicate statistically significant differences (p < 0.05).
Jof 12 00149 g008
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yang, H.; Liu, K.; Jiang, J.; Song, X.; Lu, X.; Tan, J.; Li, L. Transcriptomic and Physiological Profiling Reveals Metabolic Determinants and Key Regulatory Hubs of Fruiting Body Degeneration in Lentinula edodes. J. Fungi 2026, 12, 149. https://doi.org/10.3390/jof12020149

AMA Style

Yang H, Liu K, Jiang J, Song X, Lu X, Tan J, Li L. Transcriptomic and Physiological Profiling Reveals Metabolic Determinants and Key Regulatory Hubs of Fruiting Body Degeneration in Lentinula edodes. Journal of Fungi. 2026; 12(2):149. https://doi.org/10.3390/jof12020149

Chicago/Turabian Style

Yang, Huiting, Kun Liu, Jun Jiang, Xiaoya Song, Xinyan Lu, Jianfei Tan, and Lingli Li. 2026. "Transcriptomic and Physiological Profiling Reveals Metabolic Determinants and Key Regulatory Hubs of Fruiting Body Degeneration in Lentinula edodes" Journal of Fungi 12, no. 2: 149. https://doi.org/10.3390/jof12020149

APA Style

Yang, H., Liu, K., Jiang, J., Song, X., Lu, X., Tan, J., & Li, L. (2026). Transcriptomic and Physiological Profiling Reveals Metabolic Determinants and Key Regulatory Hubs of Fruiting Body Degeneration in Lentinula edodes. Journal of Fungi, 12(2), 149. https://doi.org/10.3390/jof12020149

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop