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17 April 2026

The Genome-Wide Identification and Expression Profiling of the HSF Gene Family in Ganoderma lucidum Under Temperature Stress

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Zhejiang Province Key Laboratory of Plant Secondary Metabolism and Regulation, College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China
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Author to whom correspondence should be addressed.
Genes2026, 17(4), 473;https://doi.org/10.3390/genes17040473
This article belongs to the Section Plant Genetics and Genomics
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Abstract

Objective: In this study, the heat shock transcription factor (HSF) gene family in Ganoderma lucidum was systematically characterized. Using genomic and transcriptomic data, we identified HSF family members and investigated their expression patterns under temperature stress and their potential regulatory roles in triterpenoid biosynthesis. Methods: A genome-wide identification of HSF genes in G. lucidum was performed using bioinformatic approaches. A phylogenetic tree was constructed, and conserved motifs, gene structures, and protein tertiary structures were predicted. The relative expression levels of HSF genes and key mevalonate (MVA) pathway enzyme genes were examined by a quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) in mycelia subjected to temperature stress. Total triterpenoid content in fermented mycelia under temperature stress was determined using the vanillin–glacial acetic acid method. Results: Eight HSF family members (GlHSF1–GlHSF8) were identified in G. lucidum. Phylogenetic analysis revealed that GlHSF proteins were closely related to PoHSF from Pleurotus ostreatus. Transcriptomic analysis showed that HSF genes exhibited relatively high expression levels during the mature stage while being barely expressed during the mycelial stage. Under heat stress (42 °C), most GlHSF genes peaked at 18 h, with GlHSF2 showing the most pronounced response (approximately 13-fold upregulation). Downstream MVA pathway genes, including IDI, PMK, and MVD, were significantly upregulated at 24 h, whereas the upstream rate-limiting enzyme gene HMGR was continuously suppressed. Despite HMGR suppression, total triterpenoid content did not decrease significantly, likely due to the activation of downstream genes. Under cold stress (14 °C), the expression of most GlHSF and MVA pathway genes decreased, accompanied by a significant reduction in total triterpenoid content. Conclusions: The HSF gene family was identified in the G. lucidum genome. Based on expression analysis, GlHSF2 showed the strongest response under heat stress, and its expression peak was correlated with the sequential activation of downstream genes in the MVA pathway. This suggests that GlHSF2 acts as a potential key regulatory node, differentially regulating upstream and downstream MVA pathway genes to influence triterpenoid biosynthesis under heat stress. These findings provide a theoretical basis for future research on the biological functions of GlHSF homeostasis.

1. Introduction

Ganoderma lucidum is a traditional precious medicinal fungus that is both edible and medicinal in China. However, the HSF gene family in G. lucidum has not yet been systematically characterized, and its expression patterns under temperature stress and regulatory relationship with triterpenoid biosynthesis remain unclear. Therefore, the main objectives of this study were to: (1) identify HSF family members at the genome-wide level and analyze their physicochemical properties, phylogeny, gene structures, conserved motifs, and promoter cis-acting elements; (2) characterize the spatiotemporal expression patterns of GlHSF genes based on transcriptomic data from six major developmental stages (mycelium, primordium, cap opening, maturity, fruiting body, and spore powder); and (3) investigate the association between GlHSF expression and the expression of key mevalonate (MVA) pathway enzyme genes as well as triterpenoid accumulation under temperature stress.
G. lucidum has a long history of application in the traditional medical systems of China and southeastern Asian countries [1]. According to the Shennong Bencao Jing (Shennong’s Classic of Materia Medica), G. lucidum is classified as a “superior herb”—a category for non-toxic substances that are beneficial for reinforcing vital energy and consolidating the constitution, thus earning its reputation as a “miraculous medicine” [2]. G. lucidum is rich in bioactive components such as polysaccharides, triterpenoids, and sterols, with ganoderma triterpenoids exhibiting anti-tumor [3], anti-carcinogenic [4], hepatoprotective [5], and antioxidant [6] activities. The completion of the genome sequencing of G. lucidum has facilitated functional genomic research. For example, Li et al. [7] identified Zn2Cys6_61 as a key positive regulator of ganoderic acid synthesis through omics analysis; Li et al. [8] reported that GlbHLH members exhibit a dual regulatory role in the upstream pathway of ganoderic acid biosynthesis; Wang et al. [9] found that GlPRMT5 negatively regulates the biosynthesis of bioactive metabolites. Abiotic stresses, particularly temperature stress, severely inhibit mycelial growth and ganoderic acid biosynthesis [10], but the molecular mechanisms remain poorly understood.
HSFs are highly conserved core transcription factors that maintain protein homeostasis and counteract thermal and oxidative stresses [11]. The DNA-binding domain (DBD) of HSF specifically recognizes heat shock elements (HSEs) with the conserved motif nGAAn or nTTCnnGAAnnTTCn [11] and adopts a winged helix–turn–helix structure [11,12]. The DBD, hydrophobic heptad repeat (HR-A/B), and exon–intron boundaries define HSF phylogeny [13]. The HSF protein was first identified in Drosophila melanogaster in 1984 [14]. Subsequently, in 1988, a heat-inducible, sequence-specific DNA-binding protein was identified in yeast, leading to the cloning of HSF and the discovery of its temperature-dependent phosphorylation [15]. In 1993, the monomer-to-trimer conversion was uncovered as a key activation mechanism [16]. Upon heat stress, HSF monomers trimerize, translocate to the nucleus, bind to target sequences, and activate transcription. After cellular homeostasis is restored, negative feedback returns HSF to its monomeric state. In fungi, HSF maintains homeostasis by regulating the expression of molecular chaperones such as heat shock proteins (HSPs) [17], and the HSF gene family has been identified and its expression patterns analyzed in model fungi like Saccharomyces cerevisiae [15,18].
G. lucidum triterpenoids, which are primarily lanostane-type triterpenoids, represent one of the most abundant and pharmacologically active constituents of G. lucidum [19]. The key enzymes in the MVA [20] pathway by which G. lucidum produces ganoderic acids are AACT [21], LS [22], HMGR [23], HMGS [24], MVD [25], IDI [26], FPS [27], and SQS [28]. Heat stress often upregulates the MVA pathway by activating specific signaling cascades, thereby promoting the synthesis of secondary metabolites, including triterpenoids with antioxidant or membrane-stabilizing functions [10,29,30,31].
The main findings of this study are as follows: Eight HSF family members were identified. Under heat stress (42 °C), most GlHSF genes reached peak expression at 18 h, with GlHSF2 showing the most pronounced upregulation (approximately 13-fold). Downstream MVA pathway genes were significantly upregulated at 24 h, whereas the upstream rate-limiting enzyme gene HMGR was continuously suppressed. These results suggest that GlHSF2 is a candidate core responsive factor under heat stress, and its expression peak is temporally correlated with the activation of downstream MVA pathway genes, implying a possible role for GlHSF2 in the differential regulation of MVA pathway genes and, consequently, in triterpenoid biosynthesis. This study provides a theoretical basis and data support for the further functional analysis of GlHSF under temperature stress.

2. Materials and Reagents

2.1. Materials

The G. lucidum strain Xianzhi No. 1 (Zhejiang (Non-major) Approved Mushroom Variety 2009003) was obtained from the Zhejiang Province Key Laboratory of Plant Secondary Metabolism and Regulation. Three G. lucidum strains with consistent growth status were selected in this study and cultured independently as biological replicates (n = 3). Samples were collected at six distinct developmental stages (Figure S1): mycelium, primordium, cap opening, maturity, fruiting body, and sporulation (spore powder). One sample was collected from each strain, yielding a total of three independent biological replicates at each developmental stage. Samples from different growth stages were immediately frozen in liquid nitrogen and subsequently stored at −80 °C until further analysis. For subsequent experiments, G. lucidum mycelia were grown on potato dextrose agar (PDA) medium at 28 °C in the dark.

2.2. Reagents

Polysaccharides and Polyphenols Plant RNA Extraction Kit (RC411, Vazyme Biotech, Nanjing, China); EvoM-MLV Reverse Transcription Kit for qPCR (AG11728, Accurate Biotechnology, Hangzhou, China); SYBR® Green Pro Taq HS Premix qPCR Kit (AG11718, Accurate Biotechnology); oleanolic acid standard (CAS: 508-02-1, Shanghai Yuanye Bio-Technology, Shanghai, China); vanillin (CAS: 121-33-5, TCI, Tokyo, Japan); and glacial acetic acid, ethyl acetate, and perchloric acid (analytical grade). Primers were synthesized by Tsingke Biotechnology (Beijing, China).

2.3. Culture Media

PDA medium (PM0520) was obtained from Coolaber Technology (Beijing, China).
Liquid seed medium: 35 g/L glucose, 5 g/L tryptone, 2.5 g/L yeast extract, 0.5 g/L MgSO4·7H2O, 1 g/L KH2PO4, and 0.05 g/L vitamin B1.

3. Methods

3.1. Identification and Physicochemical Characterization of GlHSF Genes

The genome-wide data of G. lucidum (GCA_000271565.1) [32] were retrieved from the NCBI database (https://www.ncbi.nlm.nih.gov; version 268.0, August 2025; accessed on 9 December 2025) [33]. The hidden Markov model (HMM) profile of the HSF transcription factor family (PF00096) was obtained from the Pfam database (http://pfam.xfam.org/; version 37.4, January 2025; accessed on 9 December 2025) [34]. Candidate genes containing the HSF domain were initially screened from the G. lucidum genome using the hmmsearch program from the HMMER software suite (version 3.3.2, November 2020) [35] with an E-value threshold of ≤0.01. Subsequently, BLASTP (version 2.17.0, July 2025) [36] searches against the NCBI database were performed to identify additional candidate genes by reverse-deducing gene sequences from protein sequences, using an E-value cut-off of ≤1 × 10−5. The genes identified by both methods were retained as candidate HSF genes. The molecular weight (MW) and theoretical isoelectric point (pI) of the candidate proteins were calculated using the Peptides package [37] in R software (version 4.5.2, October 2025). The subcellular localization of the GlHSF family members was predicted using the WoLF PSORT online tool (https://wolfpsort.hgc.jp/; version 0.2, September 2006; accessed on 10 December 2025) [38].

3.2. Chromosomal Localization and Phylogenetic Analysis of GlHSF Genes

The genomic locations of GlHSF genes were visualized using TBtools (version 1.130, July 2023) [39] software based on the G. lucidum genome assembly and structural annotation files. A chromosomal distribution map of GlHSF genes was generated by integrating their genomic positions with corresponding annotation information. For phylogenetic analysis, HSF protein sequences from Pleurotus ostreatus, S. cerevisiae, Schizosaccharomyces pombe, and other fungal species were retrieved from the NCBI and Pfam databases. These sequences, together with the identified GlHSF protein sequences from G. lucidum, were aligned using the Muscle program (version 3.8.31, August 2016) [40]. A maximum likelihood (ML) phylogenetic tree was constructed using IQ-TREE (version 2.1.3, June 2021) [41] with 1000 bootstrap replicates. The resulting phylogenetic tree was visualized and refined using the online tool iTOL (Interactive Tree of Life, https://itol.embl.de/; accessed on 12 December 2025) [42].

3.3. Sequence Analysis and Protein Structure Prediction of GlHSF Genes

The conserved motifs of the GlHSF proteins were predicted using the MEME online suite (http://meme-suite.org/index.html; version 5.5.1, February 2023; accessed on 12 December 2025) [43] with the following parameters: the number of motifs to identify was set to 10, and all other parameters were kept at their default values. A gene structure analysis of GlHSF genes was performed using the GSDS 2.0 (Gene Structure Display Server, http://gsds.gao-lab.org/; version 2.0, April 2015) [44] online tool. The three-dimensional (3D) structures of GlHSF proteins were predicted using the AlphaFold 3 [45] server (https://alphafoldserver.com; version 3, May 2024; accessed on 15 December 2025). For cis-acting element analysis, the 2000 bp upstream promoter sequences of GlHSF genes were extracted using TBtools software (version 1, June 2020). These sequences were then submitted to the PlantCARE [46] online platform (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/; version 1.0, January 2002; accessed on 15 December 2025) for the prediction and analysis of cis-acting regulatory elements. All results obtained from the above analyses were visualized using TBtools software.

3.4. Expression Profile Analysis of GlHSF Genes at Different Developmental Stages of Ganoderma lucidum

Raw transcriptomic data from six developmental stages of G. lucidum (mycelium, primordium, cap opening, maturity, fruiting body, and sporulation) were processed using Fastp (version 0.21.0, February 2021) [47] for quality control and read trimming.
(1) Data quality control: The raw image data generated by high-throughput sequencing were converted into raw sequencing reads through base calling. Subsequently, Fastp was used to filter the raw data by removing reads shorter than 30 bp, contaminant sequences, low-quality reads, and reads with an excessively high proportion of ambiguous bases (N), thereby generating high-quality clean data. FastQC (version 0.11.9, March 2019) was then applied to evaluate the quality of the filtered clean data. (2) Alignment to the reference genome: Clean reads were aligned to the G. lucidum reference genome [48] using STAR (version 2.7.9a, October 2020) [49], and alignment statistics were calculated. (3) Gene expression quantification: featureCounts (version 1.5.0-p3, November 2014) [50] was used to count the reads mapped to each gene. The expression level of each gene was then calculated as FPKM (Fragments Per Kilobase of transcript per Million mapped reads). (4) Differential expression analysis: Differential expression analysis was performed using DESeq2 (version 1.46.0, October 2023) [51]. Low-expression genes were filtered based on CPM (counts per million) values, and the read count data were normalized. The base mean for each sample group was calculated, and the fold change was determined. Dispersion values were estimated using a negative binomial distribution model, followed by p-value calculation and Benjamini–Hochberg correction to obtain q-values. (5) Enrichment analysis: GO enrichment analysis and KEGG enrichment analysis were performed on the differentially expressed genes using topGO (version 2.56.0, October 2023) [52] and clusterProfiler (version 3.14.3, October 2020) [53], respectively.
Subsequently, the RSEM (version 1.3.3, October 2025) [54] and Trinity (version 2.15.2, May 2025) [55] software packages were used in combination to generate the expression matrix of GlHSF family genes. The resulting count data were normalized within samples using the TMM (trimmed mean of M-values) [56] method. A heatmap of GlHSF gene expression levels was then generated using the R programming language.

3.5. Expression Analysis of GlHSF and Key MVA Pathway Enzyme Genes in Response to Temperature Stress by qRT-PCR

Mycelial plugs were excised from vigorously growing colonies on the same plate and inoculated onto fresh potato dextrose agar (PDA) medium. The cultures were incubated at 28 °C in the dark until the mycelia covered approximately two-thirds of the plate. Subsequently, for each temperature treatment (14 °C, 28 °C, and 42 °C), three independent biological replicates (each from a separate mycelial culture) were prepared. Mycelia were harvested at 0, 6, 12, 18, and 24 h after temperature treatment.
Total RNA was extracted from the stressed mycelia using an RNA extraction kit and reverse-transcribed into cDNA using a reverse transcription kit. The expression levels of GlHSF family genes and key enzyme genes in the MVA pathway were quantified by qRT-PCR. The primers used are listed in Table 1. The G. lucidum 18S rRNA gene was used as an internal reference; the reaction system consisted of TB Green Premix Ex Taq (with ROX) 5.0 μL, PCR Forward Primer 0.2 μL, PCR Reverse Primer 0.2 μL, cDNA 1.0 μL, and ddH2O 3.6 μL. The PCR program was as follows: 95 °C for 30 s, followed by 40 cycles of 95 °C for 10 s and 60 °C for 34 s. All primers used for qPCR were designed to span exon–exon junctions where possible and validated by melting curve analysis to ensure a single specific amplicon. Standard curves were generated using serial dilutions of pooled cDNA to calculate amplification efficiency (E) for each primer pair according to the formula E = (10^(−1/slope) − 1) × 100%. Primer pairs exhibiting amplification efficiencies between 90% and 110% and a correlation coefficient (R2) greater than 0.99 were accepted. Each qPCR was performed in three technical replicates per biological replicate. The mean cycle threshold (Ct) of the technical replicates was used for subsequent calculations. Relative gene expression levels were calculated using the 2−ΔΔCt method. Graphs were generated using GraphPad Prism 10 software, and a statistical analysis of relative expression levels was performed by an analysis of variance (ANOVA) using SPSS software (version 31.0.0, June 2025); differences were considered statistically significant at p < 0.05.
Table 1. Primers of genes in qRT-PCR.

3.6. Determination of Total Triterpenoid Content in Ganoderma lucidum Mycelia Under Temperature Stress

Mycelial plugs excised from a vigorously growing colony were inoculated into primary liquid seed medium and incubated at 28 °C with shaking at 120 rpm for 7 days. Then, 2 mL of the primary culture was transferred into nine separate secondary liquid medium flasks (three independent biological replicates for each temperature condition) and incubated under the same conditions for an additional 3 days. After three days, the nine flasks were divided into three groups (three flasks per group) and subjected to static incubation at 14 °C, 28 °C, or 42 °C for 24 h. Subsequently, all flasks were transferred back to 28 °C for static incubation until a mycelial pellicle formed. After 10 days of static fermentation, the mycelial pellicles were harvested individually from each flask. Total triterpenoid content was subsequently determined using the vanillin–glacial acetic acid method [57] as described below.
An accurately weighed 1 mg of oleanolic acid reference standard was placed into a foil-wrapped glass test tube and dissolved in anhydrous ethanol, and the volume was adjusted to 10 mL to prepare a standard stock solution (0.1 mg·mL−1). Aliquots of 0, 0.2, 0.4, 0.6, 0.8, and 1.0 mL of the stock solution were transferred into separate 10 mL glass test tubes. The solvent was evaporated to dryness in a boiling water bath (100 °C). After cooling to room temperature, 0.1 mL of 5% (w/v) vanillin–glacial acetic acid solution and 0.4 mL of perchloric acid were added to each tube and mixed thoroughly. The mixtures were incubated in a 70 °C water bath for 15 min, followed by cooling in an ice bath for 5 min to terminate the reaction. Subsequently, 2 mL of ethyl acetate was added and mixed well. The absorbance of each solution was measured at 548 nm. A standard curve was constructed by plotting the absorbance (Y) against the mass of oleanolic acid (X, mg).
The linear regression equation of the standard curve was as follows:
Y = 13.477X + 0.0562 (R2 = 0.9991), where Y represents the absorbance and X represents the mass of oleanolic acid (mg).
Lyophilized mycelial samples were ground into a fine powder using a liquid nitrogen grinding mill. An accurately weighed amount of 25 mg of the powder was transferred into a 2 mL centrifuge tube, and 1.5 mL of 95% ethanol was added. The mixture was extracted at room temperature for 2 h with vortexing every 30 min, followed by ultrasonic extraction for 30 min. After centrifugation at 4000 rpm for 15 min, 200 µL of the supernatant was transferred into a glass test tube (three replicates per sample). The solvent was evaporated to dryness in a boiling water bath (100 °C). The subsequent color development and absorbance measurement steps were performed as described for the standard curve method. Total triterpenoid content in the samples was calculated based on the regression equation obtained from the standard curve.
The total triterpenoid content was calculated using the following formula:
Total triterpenoid content (mg/100 mg cell dry weight) = [(Y − 0.0562)/13.477] × 30, where Y is the absorbance of the sample.

4. Results and Analysis

4.1. Identification and Physicochemical Characterization of GlHSF Genes

Based on the screening results from hmmsearch and BLASTP, the overlapping candidate gene sequences identified by both methods were selected. A total of eight HSF genes were identified from the G. lucidum genome and were designated as GlHSF1 to GlHSF8. As shown in Table 2, the deduced amino acid sequences ranged from 247 to 1352 residues in length. The corresponding molecular weights ranged from 27,307.1 Da to 147,221.35 Da, and the theoretical isoelectric points (pIs) ranged from 5.24 to 10.62. The instability index of all GlHSF proteins was greater than 40, indicating that they are all unstable hydrophilic proteins. Subcellular localization prediction suggested that most GlHSF proteins are localized to the cytoplasm and nucleus, with some possibly localized to mitochondria and a few potentially localized to the plasma membrane.
Table 2. Physicochemical properties of HSF gene family members in Ganoderma lucidum.

4.2. Chromosomal Localization and Phylogenetic Analysis of GlHSF Genes

Based on the chromosomal localization map of GlHSF genes (Figure 1), the eight GlHSF family members were found to be distributed across five different chromosomes. Chromosomes GLA01, GLA03, and GLA08 each contained only one HSF gene, while chromosome GLA06 harbored two GlHSF genes. Chromosome GLA10 contained the highest number of HSF genes, with three GlHSF family members.
Figure 1. The chromosomal localization of HSF gene family members in Ganoderma lucidum. Eight GlHSF genes were mapped to five chromosomes (GLA01, GLA03, GLA06, GLA08, and GLA10). The vertical scale bar on the left indicates the chromosome length in megabases (Mb). Gene names and their corresponding positions are labeled alongside each chromosome.
To elucidate the evolutionary characteristics of the GlHSF gene family, multiple sequence alignment was performed on 41 HSF genes, including eight from G. lucidum (GlHSF1–GlHSF8) and 33 from other fungal species such as P. ostreatus, S. cerevisiae, and S. pombe. A phylogenetic tree was subsequently constructed (Figure 2). Based on the topological structure of the tree, the 41 HSF genes were classified into four major groups (Groups I–IV).
Figure 2. A phylogenetic analysis of HSF gene family members in Ganoderma lucidum and other fungi. The phylogenetic tree was constructed using the maximum likelihood method with 1000 bootstrap replicates in IQ-TREE. The tree was rooted and divided into four major groups (I–IV), with groups indicated by colored arcs. Po. Pleurotus ostreatus; Sc. Saccharomyces cerevisiae; Ca. Candida albicans; Sp. Schizosaccharomyces pombe; Kl. Kluyveromyces lactis; Mp. Monascus purpureus; Tr. Trichophyton rubrum; Ba. Blastomyces adeninivorans; Zp. Zygosaccharomyces parabailii; Ng. Nakaseomyces glabratus; Lt. Lobosporangium transversale; Rt. Rhodotorula toruloides; Ah. Aspergillus homomorphus; Aa. Aspergillus awamori; Fo. Fusicolla oligoseptata; Zm. Zygosaccharomyces mellis; Tru. Talaromyces rugulosus.
Group I and Group III each contained one GlHSF gene, GlHSF3 and GlHSF2, respectively. Both genes exhibited close homology with HSF genes from P. ostreatus (PoHSF), suggesting that these genes are evolutionarily conserved. Group II contained four GlHSF genes (GlHSF5–GlHSF8), which formed a highly clustered evolutionary branch, indicating close phylogenetic relationships among them. This branch was evolutionarily close to PoHSF3 but distant from RtHSF of Rhodotorula toruloides. Group IV contained two GlHSF genes (GlHSF1 and GlHSF4), which also clustered with PoHSF genes but were evolutionarily distant from TrHSF of Trichophyton rubrum.

4.3. Sequence Analysis and Protein Structure Prediction of GlHSF Genes

Based on the MEME motif analysis (Figure 3A), all eight GlHSF members contained Motif 1 and Motif 3, suggesting that these two motifs are critical for GlHSF function. These motifs are likely associated with the DNA-binding domain or the oligomerization domain, which are essential for target sequence binding and for the monomer-to-trimer transition required for functional activation, respectively. Among the remaining motifs, Motif 2, Motif 6, Motif 8, and Motif 5 were present in four, three, three, and two GlHSF members, respectively. GlHSF1, GlHSF2, GlHSF3, and GlHSF4 shared similar motif compositions. Similarly, GlHSF5, GlHSF6, and GlHSF7 exhibited comparable motif distributions, consistent with their close phylogenetic relationships, indicating high structural similarity among them. GlHSF8 contained the fewest motifs but retained two motifs common to all GlHSF members. Among these, Motif 2 appears critical for its function, maintaining its close evolutionary relationship with the other members. Sequence logo analysis (Figure 3D) revealed that Motif 2 and Motif 6 are highly conserved, suggesting that they play key functional roles in HSF genes. Genes containing these two motifs exhibited closer phylogenetic relationships. As shown in Figure 3C, the eight GlHSF genes contained 3–11 introns and 4–11 coding sequences (CDSs), classifying them as intron-rich genes among fungi. This suggests a high level of structural complexity within this gene family. Furthermore, all eight GlHSF proteins contained the hallmark conserved domains of the HSF gene family, namely the HSF_DNA-bind superfamily and the HSF1 superfamily (Figure 3B). This further confirms their identity as heat shock transcription factor family genes in G. lucidum.
Figure 3. Structural characterization of HSF family members in Ganoderma lucidum. (A) Distribution of 10 conserved motifs in GlHSF proteins, as identified by MEME suite with number of motifs set to 10. (B) Distribution of conserved functional domains in GlHSF proteins. (C) Exon–intron structure of GlHSF genes, analyzed by GSDS 2.0 online tool. Green boxes represent coding sequences (CDSs), and black lines represent introns. (D) Sequence logos of six major conserved motifs in GlHSF proteins. Height of each stack reflects level of sequence conservation at that position.
Based on the three-dimensional (3D) protein structure predictions obtained via the AlphaFold 3 online platform (Figure 4), the structural predictions for the blue and yellow regions exhibit higher confidence. As previously demonstrated, the DNA-binding domain of HSF proteins is characterized by a winged helix–turn–helix (wHTH) motif. Consistently, all eight predicted GlHSF structures conformed to this description, confirming that this motif serves as the critical functional region enabling the specific recognition of target DNA sequences.
Figure 4. The tertiary structure prediction of the Ganoderma lucidum HSF family. The eight GlHSF proteins (GlHSF1–GlHSF8) exhibit conserved folding patterns, with α-helices (blue), β-sheets (yellow), and random coils (red) shown. The conserved DBD is highlighted, revealing its structural conservation across all members.
To explore the potential transcriptional regulation of GlHSF genes, the 2000 bp upstream promoter regions were analyzed for cis-acting elements (Figure 5). As a highly evolutionarily conserved family of transcription factors, HSFs exhibit a high degree of homology in their regulatory elements across plants and fungi; therefore, the HSF regulatory elements in the PlantCARE database are also relevant for G. lucidum. The upstream regions of GlHSF promoters contain 10 cis-acting elements, which can be classified into four categories: abiotic stress-responsive, hormone-responsive, light-responsive, and general/structural regulatory elements. Among these, three were associated with light responsiveness, suggesting that the GlHSF family mediates the regulation of light signals on G. lucidum growth or bioactive compounds. Three are general or basic regulatory elements that maintain baseline transcription efficiency and participate in enhancer or hypoxia regulation. Two are related to hormone or signaling molecule responses, specifically abscisic acid (ABA) and methyl jasmonate (MeJA) responsiveness, which correspond to the HSF family’s role in counteracting temperature stress. Two are associated with abiotic stress responses, specifically low-temperature and drought stress, and are present in all eight GlHSF genes, suggesting that GlHSF may confer potential drought and cold tolerance. In summary, these results suggest that the eight GlHSF genes may be involved in G. lucidum growth, metabolism, and temperature stress resistance.
Figure 5. The 2000 bp promoter sequences of eight GlHSF genes were submitted to the PlantCARE database for cis-element prediction. Different colored boxes represent distinct cis-acting elements: light responsiveness (light green), abscisic acid responsiveness (yellow), regulatory element (pink), light-responsive element (cyan), common elements in promoter and enhancer regions (red), part of a light-responsive element (gray), MeJA responsiveness (pale green), enhancer-like element involved in anoxic specific inducibility (orange), low-temperature responsiveness (purple), and MYB binding sites involved in drought inducibility (beige). The positions of the 5′ and 3′ ends of the promoter sequences are indicated, and the scale bar represents nucleotide length.

4.4. Expression Profile Analysis of GlHSF Genes at Different Developmental Stages of Ganoderma lucidum

The gene expression heatmap (Figure 6) shows gene expression levels in G. lucidum under normal growth conditions at 28 °C without temperature stress. Through cluster analysis, we found that the expression levels of GlHSF8, GlHSF6, and GlHSF7 were nearly zero across all six growth stages, suggesting that the expression of these three GlHSF genes is associated with extreme temperature stress. In contrast, GlHSF1 showed low expression levels during the first five stages but exhibited a sudden surge in expression during the spore powder stage. This suggests a potential association with spore formation. Given that the spore powder stage is the most stress-sensitive and requires the greatest stress resistance in the life cycle of G. lucidum, GlHSF1 may play a protective role during spore formation.
Figure 6. Heatmap of HSF gene expression in Ganoderma lucidum at different growth stages. Data represent three independent biological replicates, with red indicating high expression and blue indicating low expression. JS, mycelium; YJ, primordium; KS, cap opening; CS, maturity; F0, fruiting body; FR, spore powder.

4.5. Expression Analysis of GlHSF and Key Mva Pathway Enzyme Genes in Response to Temperature Stress by qRT-PCR

To investigate the response of GlHSF genes to temperature stress and their possible role in ganoderic acid biosynthesis, mycelia were treated at 14 °C and 42 °C, and gene expression was analyzed by qRT-PCR. GlHSF1, GlHSF6, GlHSF7, and GlHSF8 had very low basal expression in mycelia (FPKM < 1) and showed no significant stress-induced changes in preliminary assays. Thus, only GlHSF2, GlHSF3, GlHSF4, and GlHSF5, which displayed detectable basal expression and clear stress responsiveness, were selected for the further analysis of their expression dynamics and potential link to the MVA pathway.
As shown in Figure 7, under low-temperature stress (14 °C), the expression levels of GlHSF genes and key enzyme genes in the MVA pathway showed relatively minor changes, with relative expression levels ranging from 0.5- to 1.5-fold. In contrast, under high-temperature stress (42 °C), the relative expression levels of GlHSF2, GlHSF3, GlHSF4, and GlHSF5 all peaked at 18 h. Notably, GlHSF2 exhibited the most pronounced response, remained highly expressed from 6 to 24 h, and showed an approximately 13-fold upregulation at 18 h, suggesting that it is a candidate core factor in the heat stress response under the conditions tested. The downstream MVA pathway genes IDI, PMK, and MVD were significantly upregulated at 24 h, whereas the upstream rate-limiting enzyme genes HMGR and HMGS remained continuously suppressed throughout the stress period.
Figure 7. The relative expression levels of GlHSF genes and key mevalonate (MVA) pathway genes in Ganoderma lucidum under different temperature treatments. The expression levels of four GlHSF genes (GlHSF2, GlHSF3, GlHSF4, and GlHSF5) and six MVA pathway genes (HMGS, HMGR, MK, PMK, MVD, and IDI) were analyzed by qRT-PCR at 0, 6, 12, 18, and 24 h after exposure to 14 °C and 42 °C. Relative expression levels were calculated using the 2−ΔΔCt method with 18S as the internal reference gene. Bars represent the mean ± standard deviation (SD) of three biological replicates. Different lowercase letters (a, b, c, d, e) above the bars indicate statistically significant differences between groups (one-way ANOVA, Tukey’s test, p < 0.05). For 42 °C, GlHSF2 (F (4, 10) = 80.02, p < 0.0001); GlHSF3 (F (4, 10) = 319.6, p < 0.0001); GlHSF4 (F (4, 10) = 83.09, p < 0.0001); GlHSF5 (F (4, 10) = 23.60, p < 0.0001); HMGS (F (4, 10) = 49.53, p < 0.0001); HMGR (F (4, 10) = 7.434, p = 0.0048); MK (F (4, 10) = 6.643, p = 0.0071); IDI (F (4, 10) = 23.49, p < 0.0001); PMK (F (4, 10) = 9.260, p = 0.0021); and MVD (F (4, 10) = 14.59, p = 0.0004).

4.6. Determination of Total Triterpenoid Content in Ganoderma lucidum Mycelia Under Temperature Stress

A one-way ANOVA revealed a statistically significant main effect of temperature stress on total triterpenoid content in G. lucidum mycelia (F (2,6) = 5.334, p = 0.0466), followed by Tukey’s post hoc test for pairwise comparisons (Figure 8). The total triterpenoid content in G. lucidum mycelia varied to different degrees under different temperature stresses. Compared with the control group (approximately 2.0 mg/100 mg DW), cold stress significantly reduced total triterpenoid content to approximately 1.5 mg/100 mg DW (p < 0.05). Under heat stress, the content decreased to approximately 1.6 mg/100 mg DW, but this difference was not significant (p > 0.05). These results indicate that both low-temperature and high-temperature stress inhibit triterpenoid synthesis, with the inhibitory effect of cold stress reaching a significant level.
Figure 8. Total triterpenoid content graph of strain under temperature stress. Total triterpenoid content in Ganoderma lucidum mycelia under different temperature stresses. Total triterpenoid content was measured at 28 °C (control), 14 °C (low temperature), and 42 °C (high temperature). Data are presented as the mean ± standard deviation (SD) of three biological replicates. The asterisk (*) indicates a significant difference compared to the control (28 °C) at p < 0.05, while “ns” denotes no significant difference, as determined by the one-way ANOVA followed by Tukey’s post hoc test. The content is expressed in milligrams per 100 milligrams of dry weight (mg/100 mg DW).
Under cold stress, the expression of most GlHSF genes showed an overall downward trend, particularly GlHSF2 and GlHSF5. The expression levels of genes in the MVA pathway, such as HMGR and HMGS, also decreased. However, there were no significant differences in the expression of some key enzyme genes in the MVA pathway. This trend is consistent with the significant reduction in total triterpene content observed under cold stress. In contrast, under high-temperature stress, although the expression of most GlHSF genes and some key enzyme genes in the MVA pathway increased significantly, the expression of the gene encoding HMGR—the most critical rate-limiting enzyme in the MVA pathway—decreased significantly, thereby inhibiting the MVA pathway from the upstream. Although HMGR expression was significantly suppressed, limiting the upstream carbon flux into the triterpene synthesis pathway, the activation of GlHSF simultaneously promoted the expression of downstream genes such as IDI, MK, and MVD. This “upstream–downstream decoupling” regulatory pattern partially mitigated the synthetic defects caused by HMGR downregulation, resulting in a slight decrease in total triterpene content but no significant difference.

5. Discussion

In this study, eight HSF family members were systematically identified in the G. lucidum genome. Similarly, only seven HSF family members have been identified in Flammulina filiformis [58]. Although this number is higher than that found in Saccharomyces species, it remains considerably lower than that in plants, which possess much larger HSF families—for example, 52 in soybean and 21 in Arabidopsis thaliana [12]. Ascomycete fungi such as Beauveria bassiana [59] and Candida albicans [60] typically harbor three HSF members (HSF1, SKN7, and SFL1), which appear to be a relatively common set of HSFs across the fungal kingdom. Phylogenetic analysis placed GlHSF proteins close to those of P. ostreatus, indicating the evolutionary conservation of the HSF family within Agaricomycetes. Four members (GlHSF5–GlHSF8) formed a tightly clustered branch (Group II), suggesting a possible lineage-specific expansion via gene duplication. Chromosomal localization further supported this: the eight genes are distributed across five chromosomes, with three members on GLA10 (GlHSF1, GlHSF2, and GlHSF4). Notably, GlHSF1 and GlHSF4 are closely linked on GLA10 and belong to the same phylogenetic group (Group IV), pointing to a tandem duplication event. In contrast, GlHSF2 resides on the same chromosome but in a different group (Group III), implying distinct evolutionary origins. Likewise, GlHSF7 and GlHSF8 on GLA06 are phylogenetically close (Group II) but not tightly linked, suggesting an older duplication followed by intrachromosomal rearrangement. These observations align with documented cases of local gene duplications driving transcription factor family expansion in fungi [61,62].
The eight GlHSF genes contain 3–11 introns, classifying them as intron-rich compared to many other fungal genes. In fungi, a reduction in intron number is generally an evolutionary trend that enhances transcription and splicing efficiency, thereby enabling faster stress responses [63,64]. Therefore, the high intron load in GlHSF genes may lead to longer splicing processing times, potentially contributing to a relatively slower transcriptional response—a hypothesis that could be tested in future time-course experiments. Fungi contain various types of cis-acting elements, such as promoters, enhancers, and silencers [65], all of which participate in the regulation of fungal development and metabolism. Promoter analysis (2 kb upstream) revealed 10 cis-acting elements, classified into four categories: abiotic stress-responsive (low-temperature, drought), hormone-responsive (ABA, MeJA), light-responsive, and general/structural elements. The presence of ABA and MeJA response elements in GlHSF promoters is noteworthy, as these hormones are known to mediate temperature stress adaptation in plants and fungi [66,67,68,69,70]. For example, ABA is involved in cold and drought signaling, while MeJA enhances cold tolerance via Ca2+ signaling and protects photosystem II under heat stress. These findings suggest that GlHSF expression may be modulated by upstream hormonal signals, though direct evidence is required.
Transcriptomic profiling across six stages showed that GlHSF6, GlHSF7, and GlHSF8 were barely expressed under normal conditions, while GlHSF1 peaked specifically at the spore powder stage, suggesting a possible role in spore formation. Under cold stress (14 °C), qRT-PCR detected only minor changes in the expression of GlHSF and MVA pathway genes (0.5- to 1.5-fold). In contrast, heat stress (42 °C) induced a strong upregulation of GlHSF2, GlHSF3, GlHSF4, and GlHSF5, all peaking at 18 h. Among them, GlHSF2 showed the most pronounced response, remaining highly expressed from 6 to 24 h and reaching an approximately 13-fold increase at 18 h. A clear temporal cascade was observed: the peak of GlHSF expression (18 h) preceded the upregulation of downstream MVA pathway genes IDI, PMK, and MVD (24 h), whereas the upstream rate-limiting enzyme genes HMGR and HMGS remained continuously suppressed throughout the stress period. Consistent with this expression pattern, total triterpenoid content decreased slightly but not significantly under heat stress, whereas cold stress caused a significant reduction.
One of the core findings of this study is the strong response of GlHSF2 under heat stress and its temporal correlation with the expression of downstream genes in the MVA pathway. As the most important rate-limiting enzyme known in the MVA pathway, the expression of HMGR is continuously suppressed under heat stress, which contrasts sharply with the activation of downstream genes such as IDI. Under high-salt stress, the MVA pathway is upregulated at the transcriptional level, and key enzymes, including ACAT, HMGR and IDI, are significantly induced, thereby promoting the flow of carbon to squalene synthesis. Despite the downregulation of SQS, squalene still accumulated and increased, which was attributed to the increased supply of precursors and the reduced flux to the downstream sterol pathway [71]. Under heat stress, this dynamic change shows a significant time cascade effect: the peak expression of GlHSF (18 h) occurs earlier than the upregulation of the downstream MVA gene (24 h), while the upstream gene remains in an inhibited state all the time. From this, it can be inferred that the mechanism logic is similar under high-temperature stress. We hypothesize that GlHSF2 may differentially regulate the MVA pathway under thermal stress; that is, while inhibiting the upstream HMGR and HMGS, it activates the downstream IDI, PMK, and MVD to maintain the potential ability of downstream precursors (such as IPP and DMAPP) to transform. This is a speculative regulatory (Figure 9) approach by which G. lucidum prioritizes survival under heat stress (inhibiting major metabolic pathways) while maintaining basic secondary metabolism (activating terminal enzymes).
Figure 9. A hypothetical model illustrating the regulatory role of GlHSF2 in the MVA pathway under heat stress. Upon heat stress, GlHSF2 expression is upregulated, and the GlHSF2 protein is translated. GlHSF2 then suppresses the upstream rate-limiting enzymes HMGR and HMGS while simultaneously activating the downstream genes IDI, PMK, and MVD. This redirection of carbon flux leads to increased flow into the tricarboxylic acid (TCA) cycle and fatty acid biosynthesis, thereby providing energy for protein synthesis, cellular repair under heat stress, and basic cellular activities. Meanwhile, the activation of downstream MVA genes ensures the sustained supply of precursors for basal secondary metabolism.
However, this study is mainly based on bioinformatic prediction and correlation analysis. If the function of GlHSF is to be further verified, future research should mainly focus on using yeast single-hybrid (Y1H) or electrophoretic mobility shift assay (EMSA) and other experiments to verify whether GlHSF2 specifically binds to HSF binding sites in the promoter regions of key enzyme genes in the MVA pathway, such as IDI and MK, and whether it can directly participate in regulation. And overexpression or gene knockout techniques could be used to modify the strains, and the growth of the modified strains under heat stress, the expression of key genes, and the accumulation of metabolites could be observed. The quantification of individual ganoderic acids by LC-MS will help identify the precise metabolic nodes modulated by GlHSF. In addition, in combination with the cis-element of the GlHSF promoter region, taking ABA and MeJA response elements as examples, the existence of exogenous hormones or their inhibitors was verified by observing the changes in gene expression after adding them to the mycelial medium, and their impact on subsequent regulation was investigated. Expanding and integrating these contents will facilitate the analysis of the functions and regulatory modalities of GlHSF and help increase the accumulation of secondary metabolites such as ganoderic acid.

6. Conclusions

In summary, eight GlHSF genes were identified in the G. lucidum genome, and their structural features, expression patterns under temperature stress, and potential regulatory functions in the MVA pathway were comprehensively analyzed. Among these, GlHSF2 displayed a marked response to heat stress and is regarded as a candidate core factor in the heat stress response, warranting further functional investigation. The eight GlHSF genes play distinct or synergistic potential roles in regulating growth, development, secondary metabolite biosynthesis, and stress responses across the six developmental stages of G. lucidum. These findings provide a theoretical foundation for further functional studies of genes in G. lucidum.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/genes17040473/s1, Figure S1: Figures of the six distinct developmental stages of Ganoderma lucidum.

Author Contributions

Y.L., L.L. and J.H. conceived the study and designed the experiment. J.H., J.Z. and L.L. performed the experiments and collected the data. J.H., L.L. and S.W. analyzed the data and prepared the figures. J.H. drafted the manuscript. W.L., R.Z., Z.L., D.Y. and Z.Y. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (No. LHZSZ24H280003), Natural Science Foundation of Zhejiang Province (No. LD25H280001 and LQN25H280001) and National Natural Science Foundation of China (U25A20163). The APC was funded by the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (No. LHZSZ24H280003).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are largely available within the article and its Supplementary Materials. The raw transcriptome sequencing datasets generated during the current study are not publicly available due to a combination of internal laboratory confidentiality policies and ongoing commercial collaboration agreements. Requests for access to the restricted datasets should be directed to the corresponding author and will be considered on a case-by-case basis, subject to the approval of the involved commercial partners and the institutional review board.

Acknowledgments

We thank the journal editor and anonymous reviewers for their valuable time and constructive comments, which will help improve the quality of this manuscript.

Conflicts of Interest

The authors declare that they have no conflict of interest regarding the submission of this manuscript and its probable publication.

References

  1. Joseph, S.; Sabulal, B.; George, V.; Antony, K.R.; Janardhanan, K.K. Antitumor and anti-inflammatory activities of polysaccharides isolated from Ganoderma lucidum. Acta Pharm. 2011, 61, 335–342. [Google Scholar] [CrossRef] [Scilit]
  2. Lin, Z. Ganoderma (Lingzhi) in Traditional Chinese Medicine and Chinese Culture. Adv. Exp. Med. Biol. 2019, 1181, 1–13. [Google Scholar]
  3. Liu, C.; Chen, F.; Fan, X.; Liu, B.; Chai, X.; He, S.; Huang, T.; Wang, X.; Liu, L.; Liu, H.; et al. Combined NMR and MS-based metabonomics and real-time PCR analyses reveal dynamic metabolic changes of Ganoderma lucidum during fruiting body growing. Food Res. Int. 2024, 180, 114056. [Google Scholar] [CrossRef] [Scilit]
  4. Das, A.; Alshareef, M.; Henderson, F., Jr.; Martinez Santos, J.L.; Vandergrift, W.A., 3rd; Lindhorst, S.M.; Varma, A.K.; Infinger, L.; Patel, S.J.; Cachia, D. Ganoderic acid A/DM-induced NDRG2 over-expression suppresses high-grade meningioma growth. Clin. Transl. Oncol. 2020, 22, 1138–1145. [Google Scholar] [CrossRef] [Scilit]
  5. Liu, L.Y.; Chen, H.; Liu, C.; Wang, H.Q.; Kang, J.; Li, Y.; Chen, R.Y. Triterpenoids of Ganoderma theaecolum and their hepatoprotective activities. Fitoterapia 2014, 98, 254–259. [Google Scholar] [CrossRef] [Scilit]
  6. Mau, J.L.; Lin, H.C.; Chen, C.C. Antioxidant properties of several medicinal mushrooms. J. Agric. Food Chem. 2002, 50, 6072–6077. [Google Scholar] [CrossRef] [Scilit]
  7. Li, Y.; Liu, L.; Li, M.; Xu, J.; Yang, J.; He, X.; Yang, W.; Li, W.; Zhang, R.; Mao, L.; et al. Multiomics Analysis across the Life Cycle Identifies Zn2Cys6_61 as a Target for Enhancing Triterpenoid Production in Ganoderma lucidum. J. Agric. Food Chem. 2026, 74, 10585–10602. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  8. Li, J.; Zhu, X.; Du, Y.; Chen, W.; Xu, J.; Wang, Y.; Zhou, S.; Xu, Z.; Ma, S.; Li, Z.; et al. Comprehensive genomic identification and functional analysis of bHLH transcription factors in Ganoderma lucidum. Chin. Herb. Med. 2026, 18, 200–211. [Google Scholar] [CrossRef] [Scilit]
  9. Wang, Z.; Qiu, H.; Li, Y.; Zhao, M.; Liu, R. GlPRMT5 inhibits GlPP2C1 via symmetric dimethylation and regulates the biosynthesis of secondary metabolites in Ganoderma lucidum. Commun. Biol. 2024, 7, 241. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  10. Liu, Y.N.; Chen, Y.L.; Zhang, Z.J.; Wu, F.Y.; Wang, H.J.; Wang, X.L.; Liu, G.Q. Phosphatidic acid directly activates mTOR and then regulates SREBP to promote ganoderic acid biosynthesis under heat stress in Ganoderma lingzhi. Commun. Biol. 2024, 7, 1503. [Google Scholar] [CrossRef] [Scilit]
  11. Akerfelt, M.; Morimoto, R.I.; Sistonen, L. Heat shock factors: Integrators of cell stress, development and lifespan. Nat. Rev. Mol. Cell Biol. 2010, 11, 545–555. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  12. Scharf, K.D.; Berberich, T.; Ebersberger, I.; Nover, L. The plant heat stress transcription factor (Hsf) family: Structure, function and evolution. Biochim. Biophys. Acta 2012, 1819, 104–119. [Google Scholar] [CrossRef] [Scilit]
  13. Zhou, L.; Yu, X.; Wang, D.; Li, L.; Zhou, W.; Zhang, Q.; Wang, X.; Ye, S.; Wang, Z. Genome-wide identification, classification and expression profile analysis of the HSF gene family in Hypericum perforatum. PeerJ 2021, 9, e11345. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  14. Wu, C.; Wilson, S.; Walker, B.; Dawid, I.; Paisley, T.; Zimarino, V.; Ueda, H. Purification and properties of Drosophila heat shock activator protein. Science 1987, 238, 1247–1253. [Google Scholar] [CrossRef] [Scilit]
  15. Sorger, P.K.; Pelham, H.R. Yeast heat shock factor is an essential DNA-binding protein that exhibits temperature-dependent phosphorylation. Cell 1988, 54, 855–864. [Google Scholar] [CrossRef] [Scilit]
  16. Zhong, M.; Orosz, A.; Wu, C. Direct sensing of heat and oxidation by Drosophila heat shock transcription factor. Mol. Cell 1998, 2, 101–108. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  17. Pessa, J.C.; Joutsen, J.; Sistonen, L. Transcriptional reprogramming at the intersection of the heat shock response and proteostasis. Mol. Cell 2024, 84, 80–93. [Google Scholar] [CrossRef] [Scilit]
  18. Wiederrecht, G.; Seto, D.; Parker, C.S. Isolation of the gene encoding the S. cerevisiae heat shock transcription factor. Cell 1988, 54, 841–853. [Google Scholar] [CrossRef] [Scilit]
  19. Baby, S.; Johnson, A.J.; Govindan, B. Secondary metabolites from Ganoderma. Phytochemistry 2015, 114, 66–101. [Google Scholar] [CrossRef] [Scilit]
  20. Dinday, S.; Ghosh, S. Recent advances in triterpenoid pathway elucidation and engineering. Biotechnol. Adv. 2023, 68, 108214. [Google Scholar] [CrossRef] [Scilit]
  21. Fang, X.; Shi, L.; Ren, A.; Jiang, A.-L.; Wu, F.-L.; Zhao, M.-W. The cloning, characterization and functional analysis of a gene encoding an acetyl-CoA acetyltransferase involved in triterpene biosynthesis in Ganoderma lucidum. Mycoscience 2013, 54, 100–105. [Google Scholar] [CrossRef] [Scilit]
  22. Shang, C.H.; Shi, L.; Ren, A.; Qin, L.; Zhao, M.W. Molecular cloning, characterization, and differential expression of a lanosterol synthase gene from Ganoderma lucidum. Biosci. Biotechnol. Biochem. 2010, 74, 974–978. [Google Scholar] [CrossRef] [Scilit]
  23. Shang, C.H.; Zhu, F.; Li, N.; Ou-Yang, X.; Shi, L.; Zhao, M.W.; Li, Y.X. Cloning and characterization of a gene encoding HMG-CoA reductase from Ganoderma lucidum and its functional identification in yeast. Biosci. Biotechnol. Biochem. 2008, 72, 1333–1339. [Google Scholar] [CrossRef] [Scilit]
  24. Ren, A.; Ouyang, X.; Shi, L.; Jiang, A.L.; Mu, D.S.; Li, M.J.; Han, Q.; Zhao, M.W. Molecular characterization and expression analysis of GlHMGS, a gene encoding hydroxymethylglutaryl-CoA synthase from Ganoderma lucidum (Ling-zhi) in ganoderic acid biosynthesis pathway. World J. Microbiol. Biotechnol. 2013, 29, 523–531. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  25. Shi, L.; Qin, L.; Xu, Y.; Ren, A.; Fang, X.; Mu, D.; Tan, Q.; Zhao, M. Molecular cloning, characterization, and function analysis of a mevalonate pyrophosphate decarboxylase gene from Ganoderma lucidum. Mol. Biol. Rep. 2012, 39, 6149–6159. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  26. Wu, F.L.; Shi, L.; Yao, J.; Ren, A.; Zhou, C.; Mu, D.S.; Zhao, M.W. The cloning, characterization, and functional analysis of a gene encoding an isopentenyl diphosphate isomerase involved in triterpene biosynthesis in the Lingzhi or reishi medicinal mushroom Ganoderma lucidum (higher Basidiomycetes). Int. J. Med. Mushrooms 2013, 15, 223–232. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  27. Fei, Y.; Li, N.; Zhang, D.H.; Xu, J.W. Increased production of ganoderic acids by overexpression of homologous farnesyl diphosphate synthase and kinetic modeling of ganoderic acid production in Ganoderma lucidum. Microb. Cell Fact. 2019, 18, 115. [Google Scholar] [CrossRef] [Scilit]
  28. Zhou, J.-S.; Ji, S.-L.; Ren, M.-F.; He, Y.-L.; Jing, X.-R.; Xu, J.-W. Enhanced accumulation of individual ganoderic acids in a submerged culture of Ganoderma lucidum by the overexpression of squalene synthase gene. Biochem. Eng. J. 2014, 90, 178–183. [Google Scholar] [CrossRef] [Scilit]
  29. Tao, Y.; Han, X.; Ren, A.; Li, J.; Song, H.; Xie, B.; Zhao, M. Heat stress promotes the conversion of putrescine to spermidine and plays an important role in regulating ganoderic acid biosynthesis in Ganoderma lucidum. Appl. Microbiol. Biotechnol. 2021, 105, 5039–5051. [Google Scholar] [CrossRef] [Scilit]
  30. Shangguan, J.; Li, H.; Han, X.; Qiao, J.; Qiu, H.; Liu, H.; Shi, L.; Zhu, J.; Liu, R.; Ren, A.; et al. Hydrogen sulfide maintains redox homeostasis and suppresses ganoderic acids biosynthesis under heat stress via persulfidating thioredoxin 1 in Ganoderma lucidum. Int. J. Biol. Macromol. 2026, 336, 149427. [Google Scholar] [CrossRef] [Scilit]
  31. Shangguan, J.; Wu, T.; Tian, L.; Liu, Y.; Zhu, L.; Liu, R.; Zhu, J.; Shi, L.; Zhao, M.; Ren, A. Hydrogen sulfide maintains mitochondrial homeostasis and regulates ganoderic acids biosynthesis by SQR under heat stress in Ganoderma lucidum. Redox Biol. 2024, 74, 103227. [Google Scholar] [CrossRef] [Scilit]
  32. Chen, S.; Xu, J.; Liu, C.; Zhu, Y.; Nelson, D.R.; Zhou, S.; Li, C.; Wang, L.; Guo, X.; Sun, Y.; et al. Genome sequence of the model medicinal mushroom Ganoderma lucidum. Nat. Commun. 2012, 3, 913. [Google Scholar] [CrossRef] [Scilit]
  33. Sayers, E.W.; Bolton, E.E.; Brister, J.R.; Canese, K.; Chan, J.; Comeau, D.C.; Connor, R.; Funk, K.; Kelly, C.; Kim, S.; et al. Database resources of the national center for biotechnology information. Nucleic Acids Res. 2022, 50, D20–D26. [Google Scholar] [CrossRef] [Scilit]
  34. Mistry, J.; Chuguransky, S.; Williams, L.; Qureshi, M.; Salazar, G.A.; Sonnhammer, E.L.L.; Tosatto, S.C.E.; Paladin, L.; Raj, S.; Richardson, L.J.; et al. Pfam: The protein families database in 2021. Nucleic Acids Res. 2021, 49, D412–D419. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  35. Eddy, S.R. Accelerated Profile HMM Searches. PLoS Comput. Biol. 2011, 7, e1002195. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  36. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  37. Osorio, D.; Rondón-Villarreal, P.; Torres, R. Peptides: A Package for Data Mining of Antimicrobial Peptides. R J. 2015, 7, 4–14. [Google Scholar] [CrossRef] [Scilit]
  38. Horton, P.; Park, K.J.; Obayashi, T.; Fujita, N.; Harada, H.; Adams-Collier, C.J.; Nakai, K. WoLF PSORT: Protein localization predictor. Nucleic Acids Res. 2007, 35, W585–W587. [Google Scholar] [CrossRef] [Scilit]
  39. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  40. Edgar, R.C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef] [Scilit]
  41. Nguyen, L.T.; Schmidt, H.A.; von Haeseler, A.; Minh, B.Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 2015, 32, 268–274. [Google Scholar] [CrossRef] [Scilit]
  42. Letunic, I.; Bork, P. Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021, 49, W293–W296. [Google Scholar] [CrossRef] [Scilit]
  43. Bailey, T.L.; Boden, M.; Buske, F.A.; Frith, M.; Grant, C.E.; Clementi, L.; Ren, J.; Li, W.W.; Noble, W.S. MEME SUITE: Tools for motif discovery and searching. Nucleic Acids Res. 2009, 37, W202–W208. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  44. Hu, B.; Jin, J.; Guo, A.Y.; Zhang, H.; Luo, J.; Gao, G. GSDS 2.0: An upgraded gene feature visualization server. Bioinformatics 2015, 31, 1296–1297. [Google Scholar]
  45. Abramson, J.; Adler, J.; Dunger, J.; Evans, R.; Green, T.; Pritzel, A.; Ronneberger, O.; Willmore, L.; Ballard, A.J.; Bambrick, J.; et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 2024, 630, 493–500. [Google Scholar] [CrossRef] [Scilit]
  46. Lescot, M.; Dehais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouze, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef] [Scilit]
  47. Chen, S.; Zhou, Y.; Chen, Y.; Gu, J. fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018, 34, i884–i890. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  48. Du, Y.; Peng, S.; Chen, H.; Li, J.; Huang, F.; Chen, W.; Wang, J.; Fang, X.; Liu, L.; Wei, L.; et al. Unveiling the Spatiotemporal Landscape of Ganoderma lingzhi: Insights into Ganoderic Acid Distribution and Biosynthesis. Engineering 2025, 121, 689–697. [Google Scholar] [CrossRef] [Scilit]
  49. Dobin, A.; Davis, C.A.; Schlesinger, F.; Drenkow, J.; Zaleski, C.; Jha, S.; Batut, P.; Chaisson, M.; Gingeras, T.R. STAR: Ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29, 15–21. [Google Scholar] [CrossRef] [Scilit]
  50. Liao, Y.; Smyth, G.K.; Shi, W. featureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 2014, 30, 923–930. [Google Scholar] [CrossRef] [Scilit]
  51. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [Scilit]
  52. Alexa, A.; Rahnenfuhrer, J.; Lengauer, T. Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics 2006, 22, 1600–1607. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  53. Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS J. Integr. Biol. 2012, 16, 284–287. [Google Scholar] [CrossRef] [Scilit]
  54. Li, B.; Dewey, C.N. RSEM: Accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 2011, 12, 323. [Google Scholar] [CrossRef] [Scilit]
  55. Grabherr, M.G.; Haas, B.J.; Yassour, M.; Levin, J.Z.; Thompson, D.A.; Amit, I.; Adiconis, X.; Fan, L.; Raychowdhury, R.; Zeng, Q.; et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 2011, 29, 644–652. [Google Scholar] [CrossRef] [Scilit]
  56. Robinson, M.D.; Oshlack, A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010, 11, R25. [Google Scholar] [CrossRef] [Scilit]
  57. Hou, M.; Shi, J.; Lin, C.; Zhu, L.; Bian, Z. Ultrasound-assisted extraction of triterpenoids from Chaenomeles speciosa leaves: Process optimization, adsorptive enrichment, chemical profiling, and protection against ulcerative colitis. Ultrason. Sonochem. 2024, 111, 107136. [Google Scholar] [CrossRef] [Scilit]
  58. Duan, X.; Han, X.; Zhao, R.; Gan, Y.; Chen, J.; Miao, R.; Lin, J.; Feng, R.; Tong, Z.; Gan, B.; et al. Genome-Wide Analysis of the Heat Shock Transcription Factor Gene Family in Flammulina filiformis and Its Response to CO2-Mediated Fruit Body Development. Horticulturae 2026, 12, 132. [Google Scholar]
  59. Zhou, G.; Ying, S.H.; Hu, Y.; Fang, X.; Feng, M.G.; Wang, J. Roles of Three HSF Domain-Containing Proteins in Mediating Heat-Shock Protein Genes and Sustaining Asexual Cycle, Stress Tolerance, and Virulence in Beauveria bassiana. Front. Microbiol. 2018, 9, 1677. [Google Scholar] [CrossRef] [Scilit]
  60. Spiering, M.J.; Moran, G.P.; Chauvel, M.; Maccallum, D.M.; Higgins, J.; Hokamp, K.; Yeomans, T.; d’Enfert, C.; Coleman, D.C.; Sullivan, D.J. Comparative transcript profiling of Candida albicans and Candida dubliniensis identifies SFL2, a C. albicans gene required for virulence in a reconstituted epithelial infection model. Eukaryot. Cell 2010, 9, 251–265. [Google Scholar] [CrossRef] [Scilit]
  61. Etxebeste, O. Transcription Factors in the Fungus Aspergillus nidulans: Markers of Genetic Innovation, Network Rewiring and Conflict between Genomics and Transcriptomics. J. Fungi 2021, 7, 600. [Google Scholar] [CrossRef] [Scilit]
  62. Stajich, J.E.; Wilke, S.K.; Ahren, D.; Au, C.H.; Birren, B.W.; Borodovsky, M.; Burns, C.; Canback, B.; Casselton, L.A.; Cheng, C.K.; et al. Insights into evolution of multicellular fungi from the assembled chromosomes of the mushroom Coprinopsis cinerea (Coprinus cinereus). Proc. Natl. Acad. Sci. USA 2010, 107, 11889–11894. [Google Scholar]
  63. Xu, G.; Guo, C.; Shan, H.; Kong, H. Divergence of duplicate genes in exon-intron structure. Proc. Natl. Acad. Sci. USA 2012, 109, 1187–1192. [Google Scholar] [CrossRef] [Scilit]
  64. Jeffares, D.C.; Mourier, T.; Penny, D. The biology of intron gain and loss. Trends Genet. 2006, 22, 16–22. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  65. Gasch, A.P.; Moses, A.M.; Chiang, D.Y.; Fraser, H.B.; Berardini, M.; Eisen, M.B. Conservation and evolution of cis-regulatory systems in ascomycete fungi. PLoS Biol. 2004, 2, e398. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  66. Chen, C.H.; Ringelberg, C.S.; Gross, R.H.; Dunlap, J.C.; Loros, J.J. Genome-wide analysis of light-inducible responses reveals hierarchical light signalling in Neurospora. EMBO J. 2009, 28, 1029–1042. [Google Scholar]
  67. Kim, T.H.; Bohmer, M.; Hu, H.; Nishimura, N.; Schroeder, J.I. Guard cell signal transduction network: Advances in understanding abscisic acid, CO2, and Ca2+ signaling. Annu. Rev. Plant Biol. 2010, 61, 561–591. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  68. Ma, Y.; Dai, X.; Xu, Y.; Luo, W.; Zheng, X.; Zeng, D.; Pan, Y.; Lin, X.; Liu, H.; Zhang, D.; et al. COLD1 confers chilling tolerance in rice. Cell 2015, 160, 1209–1221. [Google Scholar] [CrossRef] [Scilit]
  69. Guo, Y.; Li, J.; Liu, L.; Liu, J.; Li, C.; Yuan, L.; Wei, C.; Zhang, X.; Li, H. The Ca2+ channels CNGC2 and CNGC20 mediate methyl jasmonate-induced calcium signaling and cold tolerance. Plant Physiol. 2025, 198, kiaf219. [Google Scholar] [CrossRef] [Scilit]
  70. Fatma, M.; Iqbal, N.; Sehar, Z.; Alyemeni, M.N.; Kaushik, P.; Khan, N.A.; Ahmad, P. Methyl Jasmonate Protects the PS II System by Maintaining the Stability of Chloroplast D1 Protein and Accelerating Enzymatic Antioxidants in Heat-Stressed Wheat Plants. Antioxidants 2021, 10, 1216. [Google Scholar] [CrossRef] [Scilit]
  71. Zhao, Y.; Zhu, X.; Riaz, N.; Liu, X.; Li, J.; Wang, G. Salinity Modulates Carbon Flux to Promote Squalene and PUFA Biosynthesis in the Marine Protist Thraustochytrium. Mar. Drugs 2025, 23, 354. [Google Scholar] [CrossRef] [Scilit]
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