Abstract Botryosphaeria dothidea is the main fungal pathogen responsible for causing Chinese hickory (Carya cathayensis) dry rot disease, posing a serious threat to the Chinese hickory industry. Understanding the molecular basis of B. dothidea infection and the host’s resistance mechanisms is crucial for controlling and managing the ecological impact of Chinese hickory dry rot disease. This study utilized ultrastructural observations to reveal the process of B. dothidea infection and colonization in Chinese hickory, and investigated the impact of B. dothidea infection on Chinese hickory biochemical indicators and plant hormone levels. Through high-throughput transcriptome sequencing, the gene expression profiles associated with different stages of B. dothidea infection in Chinese hickory and their corresponding defense responses were described. Additionally, a series of key genes closely related to non-structural carbohydrate metabolism, hormone metabolism, and plant-pathogen interactions during B. dothidea infection in Chinese hickory were identified, including genes encoding DUF, Myb_DNA-binding, and ABC transporter proteins. These findings provide important insights into elucidating the pathogenic mechanisms of B. dothidea and the resistance genes in Chinese hickory. Supplementary Information The online version contains supplementary material available at 10.1186/s12870-024-05664-7. Keywords: Botryosphaeria dothidea, Carya cathayensis, Dry rot disease, Transcriptome, Plant hormones, Non-structural carbohydrates Background B. dothidea (Botryosphaeria dothidea)is a widely distributed plant pathogenic fungus with a global presence, being a major causative agent of plant diseases such as canker and dieback [[38]1]. It is particularly renowned for posing a serious threat to economically important crops like Apples (Malus pumila), Pistachios (Pistacia vera) and English walnuts (Juglans regia) [[39]2–[40]4]. Infection by B. dothidea results in various symptoms, including stem cankers, branch wilting, and fruit rot, which significantly impact the quality of timber and fruits, causing direct economic losses to agricultural systems. Common management practices involve regular inspection, pruning of infected parts, and the use of appropriate fungicides. However, due to the fungus’s ability to release spores at infection sites and its dormancy under unfavorable conditions, complete eradication is challenging. For farmers and horticulturists, a comprehensive understanding of the infection mechanisms of B. dothidea is crucial for developing targeted control strategies to protect plant health and ensure the sustainability of the agricultural industry. Chinese hickory (Carya cathayensis) is an important oilseed nut crop in the family Juglandaceae, widely cultivated in Zhejiang and Anhui provinces, and plays a significant role in supporting the local agricultural economy [[41]5]. However, improper fertilization practices over an extended period have led to severe soil acidification and a decline in fertility. Additionally, due to the over-reliance on a limited number of cultivars, the resistance of Chinese hickory trees to diseases has become extremely vulnerable, resulting in the widespread dissemination of diseases [[42]6]. Canker disease caused by B. dothidea has emerged as a highly threatening and contagious disease in the Chinese hickory industry, especially during the spring when rainfall facilitates the massive spread of spores of the fungus [[43]7]. Upon spore settlement, several black canker spots rapidly develop, catastrophically spreading and making it challenging to prevent the occurrence of canker disease [[44]8, [45]9]. In the process of plant-pathogen interactions, pathogen-associated molecular patterns-triggered immunity (PTI) and effector-triggered immunity (ETI) are two critical stages of the plant immune system [[46]10]. Plants initiate immune responses by recognizing pathogen-associated molecular patterns (PAMPs) and triggering PTI as the initial defense mechanism against pathogen invasion. PTI activates a series of signaling pathways, leading to the induction of plant defense responses such as reactive oxygen species burst and cell wall thickening [[47]11, [48]12]. However, pathogens may evade PTI through diverse mechanisms, such as secreting effectors to target and disrupt plant immune responses [[49]13]. Compared to PAMP-triggered immunity (PTI), effector-triggered immunity (ETI) is a more specific and specialized immune response, typically mediated by NOD-like receptors (NLRs) [[50]13]. During ETI, plant cells may employ programmed cell death (PCD) to prevent the spread of pathogens [[51]14]. Additionally, plant hormones play a crucial role in defending against pathogen infections. Salicylic acid (SA), a key endogenous plant hormone, is essential in immune responses, inducing the expression of various disease-resistance genes, and enhancing both local defenses and systemic acquired resistance (SAR) [[52]15, [53]16]. Jasmonic acid (JA) works in synergy with SA, forming a complex hormonal regulatory network to build a more robust immune defense [[54]17, [55]18]. Recent studies have shown that during the resistance of potatoes to the necrotrophic pathogen Alternaria solani, the role of JA is limited, whereas SA signaling is critical [[56]19]. In Arabidopsis, pathogen-induced SA and its receptors NPR3/4 can activate the JA signaling pathway, promoting effector-induced immunity-related programmed cell death [[57]20]. A deeper understanding of these plant hormones and their roles in defense responses can help elucidate how plants regulate defense signaling to cope with different pathogenic pressures. This study systematically investigates the effects of fungal canker disease in Chinese hickory caused by B. dothidea through interaction transcriptome analysis, non-structural carbohydrate measurements, and plant hormone assays. The aim is to elucidate the physiological and molecular defense responses of Chinese hickory. Additionally, this study reported for the first time the qualitative and quantitative transcriptomic profiling of Chinese hickory in response to B. dothidea infection. Initially, quantification of non-structural carbohydrates, JA, and SA was conducted to explore their impact on the progression of canker disease in Chinese hickory. Subsequently, the transcriptional response of Chinese hickory to B. dothidea inoculation was deeply investigated, focusing on hormone and sugar metabolism pathways. Furthermore, a series of key structural genes involved in B. dothidea infection and the resistance response of Chinese hickory to B. dothidea infection were identified. The expression of these genes was validated through qRT-PCR experiments. In summary, these findings provide preliminary insights into the infection mechanisms of B. dothidea, contributing to a deeper understanding of plant defense mechanisms against fungal invasion and identifying candidate genes associated with hickory’s tolerance to B. dothidea. Materials and methods Plant materials and growth conditions The plant material used in this experiment is Chinese hickory, with two-year-old Hunan hickory (Carya hunanensis) serving as the rootstock. Scions were taken from one-year-old grafted seedlings of Chinese hickory and cultivated in a controlled-environment greenhouse at the Pan Mubang Nursery, Zhejiang A&F University. The cultivation environment was maintained at a temperature of 25 ± 2 °C, relative humidity of 75%, and a light/dark cycle of 12 h each, with a light intensity of 2000 lx [[58]21]. Fungal material The pathogenic material for the Chinese hickory dieback disease (B. dothidea) was obtained from infected tree trunk tissues at the infection margins in a Chinese hickory orchard located in Wucun, Taiyang Town, Lin’an District, Hangzhou City, Zhejiang Province. These samples were collected, isolated, and identified by the Microbiology Laboratory at Zhejiang A&F University and were properly preserved [[59]22]. Subsequently, the isolated strains were cultured on potato dextrose agar at 28 °C and stored at 4 °C for use in subsequent inoculation experiments. Inoculation of B. Dothidea The B. dothidea isolates were inoculated using the stem wound method, where agar blocks containing fungal mycelium were applied to wounded stems. The control group was treated with agar blocks without mycelium [[60]23]. Sampling was performed on 5, 10, and 15 days post-treatment. Non-inoculated stems (treated with agar blocks without mycelium) served as the control. At each time point (5, 10, and 15 days), wood chips from the inoculation and lesion development sites were collected using sterile surgical knives, immediately frozen in liquid nitrogen, and stored at -80 °C for subsequent transcriptome analysis. Each treatment included 3 biological replicates, with each biological replicate consisting of 3 technical replicates. Determination of non-structural carbohydrates After the infection of Chinese hickory leaves by B. dothidea, the analysis of non-structural carbohydrate content was conducted days 5, 10, and 15. For this purpose, the 6th mature leaf from the top of each Chinese hickory seedling in each treatment was selected as the sample for analysis. Post-collection, the samples were immediately placed in an oven and heated at 110 °C for 30 min to halt biological activity. Subsequently, the samples were dried at 65 °C for 4 h until a constant weight was achieved, followed by grinding into fine powder and filtering through a 100-mesh sieve. The concentrations of soluble sugars and starch were determined using the Plant Soluble Sugar Assay Kit and Starch Assay Kit (Solarbio Life Sciences, Beijing, China), respectively. Measurements were taken at a wavelength of 620 nm using a microplate reader (Dynamax, USA) [[61]24]. Each treatment included 3 biological replicates, with each biological replicate consisting of 3 technical replicates. The results are expressed as mg/g dry weight. Measurement of SA and JA After inoculating with B. dothidea, wood chip samples were collected from the inoculation sites or control plants at three time points, rapidly frozen in liquid nitrogen, and then stored at -80 °C for subsequent plant hormone extraction. Salicylic acid (SA) and jasmonic acid (JA) were extracted according to previously described methods [[62]25]. The contents of SA and JA were then measured using a triple quadrupole liquid chromatography-mass spectrometry system (1290 Infinity II-6470, Agilent Technologies, USA), following the protocol outlined by Bao-jia Gao et al. [[63]26]. Each treatment included 6 biological replicates, with each biological replicate consisting of 3 technical replicates. The results are expressed as mg/g dry weight. Transcriptome analysis of Interaction On 5, 10, and 15 days post-inoculation with B. dothidea on Chinese hickory, we conducted transcriptome sequencing of the infected tissues. The three treatment groups were designated as SGDB (5 days), SGTB (10 days), and SGQB (15 days), while healthy Chinese hickory seedlings at each time point served as control groups, named CKDB (5 days), CKTB (10 days), and CKQB (15 days). Additionally, the B. dothidea strain cultured on PDA agar plates was used as a control group, designated as SGFA, to investigate the transcriptional expression changes of B. dothidea in Chinese hickory. Each treatment included 3 biological replicates, with each biological replicate consisting of 3 technical replicates. Total RNA from the infected Carya cathayensis tissue wood chips was extracted using the TRIzol method [[64]27]. RNA purity was assessed using a NanoDrop spectrophotometer, with a 260/280 ratio greater than 2.0, indicating high RNA quality. Further evaluation of RNA quality was performed using 1.5% agarose gel electrophoresis, where 1 µL of RNA sample exhibited clear bands, confirming its suitability for RNA sequencing. High-quality RNA from three biological replicates of each treatment group was pooled for subsequent experiments. Sequencing libraries were prepared using the True-Seq RNA Sample Preparation Kit (Illumina, San Diego, USA), following Illumina’s standard protocol for library construction and sequencing [[65]28]. The final libraries were sequenced on the Illumina HiSeq X-ten platform, yielding raw data that, after filtering and quality control, resulted in clean data of 7.10 GB per sample. After removing low-quality and adapter sequences from the raw data, the clean reads were aligned to the reference genomes of Chinese hickory [[66]29] and B. dothidea [[67]1]. Gene functions were annotated using the eggNOG-mapper database ([68]http://eggnog-mapper.embl.de/). The expression levels of genes were quantified using the Hisat2 software with FPKM (fragments per kilobase per million mapped reads) values [[69]30]. Differential expression genes (DEGs) were identified using DESeq2 [[70]31], with parameters set as |log2(fold change)| > 1 and q-value < 0.05. Weighted gene co-expression network analysis We inputted the transcriptome read counts of 18 Chinese hickory samples and 12 B. dothidea samples into the R package WGCNA (v3.2.2) to construct a co-expression network. Initially, hierarchical clustering was performed on all samples to analyze their similarity. For Chinese hickory samples, a soft threshold power of 11 was chosen based on the scale-free topology criterion, while for B. dothidea samples, a soft threshold power of 15 was selected. Using the topological overlap dissimilarity measure, genes were hierarchically clustered, and module detection was conducted utilizing the dynamic tree-cutting method with the gene dendrogram. During this process, mergeCutHeight was set to 0.25, and minModuleSize was set to 30 for both datasets. We calculated the correlation coefficients between module eigengenes and the contents of starch (ST), sucrose (SUC), SA, and JA. Additionally, we computed the correlation coefficients between B. dothidea module eigengenes and the lesion area. In WGCNA, gene connectivity, reflecting the strength of connections between genes, is determined based on edge weights (ranging from 0 to 1) determined by topological overlap measurements. Finally, we visualized the connectivity among genes within specific modules in Cytoscape (v3.9.0). Validation by Real-Time Quantitative Polymerase Chain Reaction (qRT-PCR) To validate the accuracy of the RNA-seq data, we conducted qRT-PCR to confirm the expression levels of the selected differentially expressed genes (DEGs). Under the experimental conditions where Chinese hickory seedlings were inoculated with B. dothidea, we collected the infected tissues at 5, 10, and 15 days post-inoculation. After culturing for five days, we observed that the mycelium of B. dothidea had fully grown and reached a suitable stage for experimentation. Therefore, we chose to use a 5-day-old B. dothidea culture on PDA plates for our experiments. RNA was extracted from the aforementioned sample groups using the same method as described in Sect. [71]2.6, followed by reverse transcription. The Takara PrimeScriptTM RT reagent Kit with gDNA Eraser was used for the reverse transcription experiments following the kit instructions, and the obtained cDNA was stored at -20 °C for subsequent qPCR as templates. Translation elongation factor 1-alpha was chosen as the housekeeping gene for normalization. A total of 6 relevant DEGs were selected for analysis to compare the expression levels of DEGs in each treatment group under B. dothidea infection in Chinese hickory. Based on the selected DEG sequences, qRT-PCR primers were designed using the Primer-BLAST online tool on the NCBI platform, and these primers were synthesized by Beijing Qingke Biotechnology Co., Ltd. The specific information for primer design is provided in Table S1. Data Analysis In this study, we utilized R language and Origin 2021 software to calculate and process data on the Non-structural carbohydrate (ST and SUC) and plant hormone (SA and JA) contents of Chinese hickory. The obtained data underwent one-way ANOVA or Pearson correlation analysis, with a significance level set at 5%. All data are expressed as mean ± standard deviation (SD), with carbohydrates based on three independent biological replicates and plant hormones based on six independent biological replicates. For graphical representation, we employed R Studio software (v4.2.1) for visualization. Electron Microscopy Observation of B. dothidea infection in Hickory stems Based on the infection time points, tissue samples of B. dothidea infected Chinese hickory stems were prepared for scanning electron microscopy. First, the samples were immersed in 2.5% glutaraldehyde and 0.1 M PBS buffer at pH 7.0. Subsequently, they underwent a graded series of washes with ethanol solutions at concentrations of 30%, 50%, 70%, 80%, 90%, and 95%. Finally, the samples were dehydrated using absolute ethanol and isoamyl acetate. The processed samples were then mounted on sample stubs with conductive adhesive and left in a freeze-dryer for 12 h. Afterward, they were gold-coated at the critical point and observed using a scanning electron microscope. Results The infection process of B. Dothidea in Chinese hickory To investigate the damage caused by B. dothidea (Figure S1) infection in Chinese hickory, we performed inoculation experiments with B. dothidea strains on Chinese hickory seedlings, using untreated plants as controls (Fig. [72]1A). On the 5th day post-inoculation (S1), the seedlings showed black lesions; by the 10th day (S2), the lesions had significantly enlarged; and by the 15th day (S3), the blackening of the stem base had become more pronounced. Over time, the lesion area continued to expand and spread in all directions along the stem (Fig. [73]1B). Fig. 1. [74]Fig. 1 [75]Open in a new tab Illustrates the infection process of B. dothidea in Chinese hickory and the impact of B. dothidea infection on biochemical indices (non-structural carbohydrates and plant hormones) in Chinese hickory. (A) Displays time-lapse photographs of Chinese hickory samples that were not inoculated with B. dothidea. (B) Shows the progression of lesions over time at the infection site in Chinese hickory samples after inoculation with B. dothidea. (C) Scanning electron micrographs depict the infection process of B. dothidea in Chinese hickory. (D) Demonstrates the changes in the lesion area of Chinese hickory after infection by B. dothidea. (E-H) Illustrate the changes in sucrose (SUC), starch (ST), salicylic acid (SA), and jasmonic acid (JA) levels. The blue circle indicates the inoculation site, while the red circle marks the lesion area on the Chinese hickory seedlings as B. dothidea infection progresses over time. CK represents the control group; SG represents the infected group; SEM: Scanning Electron Microscope; The red arrows indicate the location of B. dothidea; S1 represents Day 5 of the B. dothidea infection experiment on Chinese hickory, S2 represents Day 10, and S3 represents Day 15.Values are expressed as means ± SD of three determinations from four separate experiments. Values not sharing the same letter are significantly different at P < 0.05 To further analyze the colonization process of B. dothidea in Chinese hickory, we performed ultrastructural observations of stem samples collected on the 5th, 10th, and 15th days post-inoculation to assess the extent of damage (Fig. [76]1C). On the 5th day after inoculation, distinct black lesions appeared in the cortex, with a small number of hyphae attaching to the cortex surface. These hyphae tightly adhered to the openings and crevices of the cortex, preparing for further invasion and beginning to spread to the surrounding areas. By the 10th day, electron microscopy revealed that the hyphae had penetrated the cortex surface and proliferated extensively within the cortex, leading to an expansion and worsening of the lesion area. By the 15th day, electron micrographs showed dense growth of hyphae within the cortex, with some hyphae beginning to colonize the surface of the xylem, making the affected areas more pronounced. Significant differences in lesion size were observed among the three time points (Fig. [77]1D) (P < 0.05). In summary, we observed the complete invasion and colonization process of B. dothidea. Impact of B. dothidea Infection on Biochemical Indices (non-structural carbohydrates) and Plant Hormones in Chinese hickory Sucrose (SUC) and starch (ST), as the primary non-structural carbohydrates, are key indicators of plant damage. In Chinese hickory samples infected with B. dothidea, SUC levels increased during the early stages of infection but gradually declined in the later stages (Fig. [78]1E) (P < 0.05). In contrast, ST exhibited a slight decreasing trend across different infection stages (Fig. [79]1F). In uninfected Chinese hickory samples, the changes in SUC and ST levels were relatively stable, indicating the significant role of non-structural carbohydrates in the interaction between plants and pathogens. Additionally, salicylic acid (SA) and jasmonic acid (JA) are crucial components of the plant defense system that help combat pathogen attacks. In Chinese hickory samples infected with B. dothidea, SA levels significantly decreased (Fig. [80]1G) (P < 0.05), while JA levels showed a notable decline during the mid-infection stage but increased again in the later stage (Fig. [81]1H) (P < 0.05). In uninfected samples, the variations of these two compounds were relatively stable. This indicates that as B. dothidea continues to infect the plants, both types of plant hormones play important roles in defending against the pathogen. Transcriptome sequencing data statistics and gene functional annotation Transcriptome sequencing was performed on the lesion tissues of Chinese hickory infected with B. dothidea, with three treatment groups designated as SGDB (5th day), SGTB (10th day), and SGQB (15th day). Botryosphaeria dothidea cultured on PDA medium served as the control group, labeled as SGFA. Healthy Chinese hickory seedlings at each time point were used as control groups and named CKDB, CKTB, and CKQB. Each treatment group included three replicates. Transcriptome sequencing of B. dothidea was completed for 12 cDNA libraries. After quality assessment and filtering of raw data, the transcriptome comprised 411,577,567 clean reads with an average Q30 of 93.99%, indicating high sequencing quality (Table S2). All reads from each sample were mapped to the B. dothidea (GenBank: GCA_011503125.2) reference genome. Due to the samples originating from Chinese hickory cambium tissues in the early infection stages, the sequence mapping rates were relatively low in SGDB and SGTB, while the mapping rate in SGQB reached 75.84% (Table S3). The number of reads in each treatment group met the requirements for further analysis, with over 70% of transcriptome sequences in the SGQB group aligning to the reference genome, indicating accurate sequencing results. Transcriptome sequencing of Chinese hickory was completed for 18 cDNA libraries. After quality assessment and filtering of raw data, the average Q30 of the transcriptome was 48.26%, indicating high sequencing quality (Table S2). All reads from each sample were mapped to the Chinese hickory (10.5524/100571) reference genome, and the average mapping rate across sample groups was 80.21%, confirming the accuracy of the sequencing results (Table S4). Good consistency was observed among the three biological replicates, validating the reliability of the transcriptome data used in subsequent analyses. Correlation analysis further confirmed the close association of the global gene expression patterns with different stages of B. dothidea infection in Chinese hickory (Figure S2-S3). Functional annotation of B. dothidea protein sequences and Chinese hickory protein sequences was performed using the eggnog-mapper database, providing functional annotation information for subsequent analysis of DEGs (Table S5-S6). Transcriptomic analysis of Chinese hickory inoculated with B. dothidea To further analyze the transcriptome data, we conducted hierarchical clustering analysis of differentially expressed genes (DEGs) for B. dothidea (Fig. [82]2A; Table S7) and Chinese hickory (Fig. [83]2B; Table S8), and generated heatmaps and line charts. KEGG pathway analysis was performed for each cluster. Fig. 2. [84]Fig. 2 [85]Open in a new tab Overview of Transcriptomic Analysis of Chinese hickory Inoculated with B. dothidea (Chinese hickory Transcriptomic Analysis and B. dothidea Transcriptomic Analysis). (A) The figure illustrates the temporal expression patterns of differentially expressed genes (DEGs) in B. dothidea samples. The left section shows line graphs representing the expression trends of ten subclusters (C1-C10) obtained from hierarchical clustering analysis of B. dothidea samples at different time points. The central section presents a heatmap of gene expression, where each row represents a gene and each column represents a sample. The color scale in the heatmap indicates the normalized gene expression levels, with colors ranging from blue to white to red representing low, medium, and high expression levels, respectively. The right section displays the KEGG pathway names associated with each subcluster. (B) The figure illustrates the temporal expression patterns of differentially expressed genes (DEGs) in Chinese hickory samples. The blue group (Group 1) shows the expression trend line graphs of ten subclusters (C1-C10) obtained from hierarchical clustering analysis of Chinese hickory samples not inoculated with B. dothidea at different time points, while the red group (Group 2) displays the same analysis results for Chinese hickory samples inoculated with B. dothidea. The central section features a heatmap of gene expression, where each row represents a gene and each column represents a sample. The color scale in the heatmap indicates the normalized gene expression levels, with colors ranging from blue to white to red representing low, medium, and high expression levels, respectively. The right section displays the KEGG pathway names associated with each subcluster For the 14,017 DEGs in the B. dothidea samples (Fig. [86]2A), hierarchical clustering divided these genes into ten subclusters (C1-C10). In the early stages of infection, DEGs related to “metabolic regulation pathways” and “biological process regulation pathways” () showed higher expression in subclusters C5 and C10 (Fig. [87]2A). This likely indicates that the pathogen requires substantial energy resources to invade the Chinese hickory stem at the early stage. In the mid-infection stage, DEGs associated with “cellular biological regulation pathways” and “biological process and development pathways” exhibited higher expression in subclusters C3 and C4 (Fig. [88]2A). This may reflect the interaction between the host and pathogen, suggesting biological responses taken by the pathogen during further invasion. In the late infection stage, DEGs related to “biological processes and developmental pathways” were highly expressed in subcluster C8 (Fig. [89]2A). This could represent the pathogen’s adaptation to the host environment, utilizing host resources and impacting host biological processes and development pathways to sustain survival and reproduction within the host. For the 44,903 DEGs in the Chinese hickory samples (Fig. [90]2B), hierarchical clustering similarly defined ten transcript clusters (C1-C10). During the resistance of Chinese hickory seedlings to B. dothidea infection, DEGs associated with “morphogenesis pathways,” “metabolism and growth development pathways,” and “biological development process-related pathways” showed higher expression in subclusters C6, C7, C8, and C9 (Fig. [91]2B). These highly expressed KEGG pathways may represent physiological or pathological responses of the plant to pathogen invasion, indicating crucial roles in the plant’s immune system, cellular signaling, metabolic regulation, and biological development to combat pathogen intrusion and maintain growth and survival. Through the analysis of the interaction transcriptome data, we revealed the biological responses of B. dothidea at different infection stages, as well as the physiological or pathological responses of Chinese hickory to pathogen invasion. These results provide significant data for understanding the response mechanisms of Chinese hickory to B. dothidea infection and offer key insights into the pathogenesis of Chinese hickory canker disease. Transcriptomic analysis of the interaction between chinese hickory and B. dothidea In order to gain deeper insights into the molecular mechanisms underlying the interaction between Chinese hickory and B. dothidea, we identified genes expressed by B. dothidea during the infection of Chinese hickory at different time points. We compared DEGs between B. dothidea inoculated (S) and PDA medium-cultured (CK) samples. Compared to CK, at day 5 post-inoculation, 2601 DEGs were identified, with 1174 upregulated and 1426 downregulated; at day 10, 3387 DEGs were detected, with 1493 upregulated and 1894 downregulated; at day 15, 4683 DEGs were detected, with 2453 upregulated and 2230 downregulated (Figure S4). This indicates a shift in the balance between induced and suppressed genes in the pathogen from day 5 to 15, further confirming the enhanced pathogenicity of B. dothidea at the 15th day of infection. To comprehensively understand the pathogenicity of B. dothidea on Chinese hickory, we conducted the KEGG analysis to explore the functions of these DEGs. In the S1 vs. CK, S2 vs. CK, and S3 vs. CK comparisons, a total of 1904 common DEGs were identified, potentially associated with the pathogenicity of B. dothidea infection in Chinese hickory. Functional analysis of these DEGs revealed significant enrichment in four main aspects: carbohydrate metabolism, amino acid metabolism, lipid metabolism, and plant signal transduction (Fig. [92]3A–B, Table S9). Enrichment in these four aspects could substantially contribute to the pathogenicity of B. dothidea. Fig. 3. [93]Fig. 3 [94]Open in a new tab Identification and KEGG Enrichment Analysis of Differentially Expressed Genes during the Interaction between B. dothidea and Chinese hickory. (A) Venn diagram illustrating DEGs in B. dothidea treated samples compared to PDA-cultivated B. dothidea samples. S1 vs. CK (SGDB vs. SGFA): DEGs after 5 day of treatment. S2 vs. CK (SGTB vs. SGFA): DEGs after 10 day of treatment. S3 vs. CK (SGQB vs. SGFA): DEGs after 15 day of treatment. (B) KEGG enrichment analysis of common DEGs from the Venn diagram in Fig. 3A. (C) Venn diagram depicting DEGs in Chinese hickory treated samples compared to mock-inoculated Chinese hickory samples. S1 vs. CK1 (SGDB vs. CKDB): DEGs after 5 day of treatment. S2 vs. CK2 (SGTB vs. CKTB): DEGs after 10 day of treatment. S3 vs. CK3 (SGQB vs. CKQB): DEGs after 15 day of treatment. (D) KEGG enrichment analysis of common DEGs from the Venn diagram in Fig. 3C Simultaneously, to gain a more comprehensive understanding of the infection mechanism of B. dothidea on Chinese hickory, we identified genes involved in Chinese hickory response to B. dothidea. We compared the expression of differentially changed genes (statistically significant, p ≤ 0.05) between B. dothidea inoculated (S) and mock-inoculated (CK) Chinese hickory. By comparing the transcriptome data of three groups: S1 vs CK1, S2 vs CK2, S3 vs CK3 (Fig. [95]3C), we observed a decrease in the gene expression changes in Chinese hickory with the progression of B. dothidea infection. The defense mechanisms of Chinese hickory against B. dothidea decreased continuously with the sustained invasion of the pathogen, and Chinese hickory primarily exerted its defense mechanisms in the early stages of infection. Furthermore, using KEGG pathway enrichment analysis for the common DEGs (19,134) in S1 vs CK1, S2 vs CK2, S3 vs CK3, the results showed that these DEGs were mainly concentrated in four aspects: ‘secondary metabolism and biosynthesis’, ‘metabolic pathways’, ‘cellular functions’, and ‘immune response’ (Fig. [96]3D, Table S10). Among them, ‘secondary metabolism and biosynthesis’ and ‘metabolic pathways’ are directly related to the synthesis and metabolism of non-structural carbohydrates (ST and SUC) and plant hormones (SA and JA). This suggests their potential role in the defense mechanisms of Chinese hickory to B. dothidea during disease development. As ‘secondary metabolism and biosynthesis’ and ‘metabolic pathways’ play crucial roles in plant defense against pathogens, the down regulation of genes in these enriched pathways in Chinese hickory may contribute to the development of the disease. Analysis of co-expression networks for DEGs To gain deeper insights into the role of non-structural carbohydrates (ST and SUC) and plant hormones (SA and JA) in the infection process of B. dothidea on Chinese hickory, we conducted WGCNA using all DEGs under various treatments. A total of 33 gene co-expression modules related to all treatments were identified (Fig. [97]4A), containing gene numbers ranging from 36 to 2311. The correlation network between these modules and traits (Fig. [98]4B) indicated that highly correlated modules might be involved in similar biological processes. Notably, four co-expression modules (MEskyblue, MEgreen, MEroyalblue, and MEyellow) showed high correlation (p < 0.01) with traits (Fig. [99]4B, C), suggesting their crucial roles in the infection process of B. dothidea on Chinese hickory. Specifically, MEskyblue, MEgreen, MEyellow, and MEroyalblue modules included 104, 664, 807 and 218 identified genes, respectively, which were highly correlated with lesion size, non-structural carbohydrates, and plant hormone synthesis and metabolism. These genes represented DEGs induced by B. dothidea during the infection process. Fig. 4. [100]Fig. 4 [101]Open in a new tab Co-expression Analysis of DEGs during B. dothidea Infection of Chinese hickory. (A) Hierarchical clustering dendrogram of co-expressed genes based on WGCNA method. (B) Correlation analysis between key modules and non-structural carbohydrates, plant hormones, and lesion area. (C) Gene count statistics for each key module. (D-G) Network diagrams of gene modules most correlated with non-structural carbohydrates, plant hormones, and lesion area Hub genes within MEskyblue, MEroyalblue, MEyellow, and MEgreen modules were visualized using Cytoscape software (Fig. [102]4D-G). As hub genes, CIA, DUF, Fungal_trans, and Sugar_tr in the MEskyblue module exhibited co-expression correlation with ‘Glycosylphosphatidylinositol (GPI) anchor biosynthesis,’ ‘Unsaturated fatty acid biosynthesis,’ ‘Glycine, serine, and threonine metabolism,’ ‘Oxidative phosphorylation,’ and ‘Fatty acid biosynthesis and metabolism’ pathways (Figure S5A). Hub genes DUF and Mannosyl_trans2 in the MEroyalblue module showed co-expression correlation with ‘Ubiquinone and other terpenoid-quinone biosynthesis,’ ‘Tryptophan metabolism,’ ‘Lysine degradation,’ ‘Fatty acid degradation,’ and ‘Starch and sucrose metabolism’ pathways (Figure S5B). FMN, NAD, and Methyltransf_16 in the MEyellow module displayed co-expression correlation with ‘Carbon metabolism,’ ‘Amino sugar and nucleotide sugar metabolism,’ ‘Glycolysis / Gluconeogenesis,’ ‘Oxidative phosphorylation,’ and ‘Starch and sucrose metabolism’ pathways (Figure S5C). zf-RING_UBOX, RNA_pol_Rbc25, and HAD_2 in the MEgreen module exhibited co-expression correlation with ‘Proteasome,’ ‘Ubiquitin-mediated proteolysis,’ ‘Endoplasmic reticulum protein processing,’ ‘MAPK signaling pathway,’ and ‘Carbon metabolism’ pathways (Figure S5D). Subsequently, a total of 37 genes were screened from the four color modules, forming a complex regulatory network with strong associations between genes related to ‘Non-structural carbohydrate biosynthesis and metabolism’ and ‘Plant-pathogen interaction’ pathways (Table S11-12). The hub gene (gene-GTA08_BOTSDO03209) in the MEyellow module suggests a previously unknown function, indicating its potential as a gene for further investigation. To gain a deeper understanding of the role of non-structural carbohydrates (ST, SUC) and plant hormones (SA, JA) in the defense process of Chinese hickory against B. dothidea infection, we conducted WGCNA using DEGs under various treatments. Ultimately, 37 co-expressed modules related to all treatments were detected, with gene numbers ranging from 44 to 8819 (Fig. [103]5A). The correlation network between these modules and traits (Fig. [104]5B) suggests that highly correlated modules may participate in similar biological processes. Notably, three co-expressed modules (MEpurple, MElightcyan, and MElightgreen) showed high correlation (p < 0.05) with traits (Fig. [105]5B, C), indicating their significant roles in Chinese hickory defense against B. dothidea infection. The MEpurple, MElightcyan, and MElightgreen modules comprised 1,202,898, and 765 identified genes, respectively, highly correlated with the synthesis and metabolism of structural carbohydrates and plant hormones. These genes were identified as DEGs induced by Chinese hickory in response to B. dothidea infection. Fig. 5. [106]Fig. 5 [107]Open in a new tab Co-expression analysis of DEGs during the defense process of Chinese hickory against B. dothideainfection. (A) Hierarchical clustering tree of co-expressed genes based on the WGCNA method. (B) Correlation analysis between key modules and non-structural carbohydrates and plant hormones. (C) Gene count statistics for each key module. (D-F) Network diagrams of gene modules most correlated with non-structural carbohydrates and plant hormones Hub genes in the MEpurple, MElightcyan, and MElightgreen modules were visualized using Cytoscape software (Fig. [108]5D-F). As hub genes, those in the MEskyblue module, such as cNMP_binding, DUF, Myb_DNA-binding, and ABC_membrane, exhibited co-expression correlations with pathways related to plant disease resistance (‘Plant-pathogen interaction’, ‘MAPK signaling pathway - plant’, and ‘Plant hormone signal transduction’) and starch metabolism pathways (‘Starch and sucrose metabolism’, ‘Fructose and mannose metabolism’, and ‘Carbon metabolism’) (Figure S6A). Hub genes in the lightcyan module, including Pkinase, Cyclin, and CRAL, showed co-expression correlations with the starch metabolism pathway ‘Phenylpropanoid biosynthesis’ (Figure S6B). Hub genes in the lightgreen module, such as ABC2_membrane, DUF, and Sugar_tr, exhibited co-expression correlations with pathways related to plant disease resistance (‘Plant-pathogen interaction’, ‘NF-kappa B signaling pathway’, ‘MAPK signaling pathway’, ‘Toll-like receptor signaling pathway’, and ‘NOD-like receptor signaling pathway’) and starch metabolism pathways (‘Glucagon signaling pathway’, ‘Ovarian steroidogenesis’, ‘Flavonoid biosynthesis’, and ‘Zeatin biosynthesis’) (Figure S6C). Subsequently, a total of 26 genes were selected from the three color modules, forming a complex regulatory network, including genes such as ABC_membrane, DUF, Myb_DNA-binding, and Pkinase (Table S13-14). The results indicate a strong association among genes related to ‘Non-structural carbohydrate biosynthesis and metabolism’ and ‘Plant-pathogen interactions’. Real-time quantitative PCR (qPCR) Six differentially expressed genes were selected for fluorescence quantitative validation. The relative expression levels of these six genes within B. dothidea were assessed in infected tissues of Chinese hickory at 5, 10, and 15 days post-inoculation with stem canker, using B. dothidea cultured on PDA plates as a control. With the exception of the gene encoding the beta subunit of fatty acid synthase, all the selected DEGs exhibited expression trends consistent with the transcriptomic data across the three infection periods, thereby validating the reliability of the transcriptomic data in this experiment. The results are depicted in Figure S7. Discussion Dry rot disease poses a significant threat to the production of Chinese hickory, particularly impacting the Chinese hickory, crucial for the production of hickory kernels and other dried fruit products [[109]32]. With concerns over environmental hazards associated with chemical fungicides, there is an urgent demand for molecular breeding of resistant Chinese hickory varieties against dry rot disease. However, our understanding of the genes related to dry rot disease resistance and the pathogenic mechanism of its causal agent, B. dothidea, remains limited. Previous studies have identified B. dothidea as a major pathogenic fungus affecting various plants, including causing diseases such as Pistachio wilt disease [[110]33], Olive fruit rot [[111]34], Poplar canker [[112]35], and Apple ring rot [[113]36]. This study demonstrated that B. dothidea could colonize Chinese hickory as early as five days post-inoculation, possibly facilitated by favorable environmental conditions, leading to a brief latent period of the disease [[114]37, [115]38]. Plants employ various defense mechanisms, inducing the expression of defense-related genes to counteract pathogen invasion [[116]39]. Additionally, indicators related to non-structural carbohydrates and plant hormone metabolism showed varying changes in both inoculated and control groups of Chinese hickory after B. dothidea infection (Fig. [117]1E-H), suggesting their involvement in Chinese hickory’s resistance response to B. dothidea. To investigate the interaction mechanism between Chinese hickory and B. dothidea, this study utilized non-inoculated Chinese hickory as the control group and Chinese hickory inoculated with B. dothidea for 5, 10, and 15 days as treatment groups. RNA-Seq technology was employed for transcriptomic analysis to elucidate metabolic pathways and genes associated with resistance. The results confirmed significant reprogramming of the Chinese hickory transcriptome in response to B. dothidea infection, particularly involving non-structural carbohydrates and plant hormone metabolism pathways [[118]40]. With technological advancements, deep RNA sequencing has become increasingly feasible, enhancing our understanding of the transcriptome [[119]41] and facilitating quantitative analysis over a wide dynamic range [[120]42]. In this study, high-throughput RNA sequencing was utilized for differential gene analysis to explore the interaction mechanism between Chinese hickory and B. dothidea. The accuracy and reliability of the RNA sequencing data were validated through RT-qPCR analysis of the expression levels of select genes. Transcriptomic analysis of B. dothidea revealed up-regulation of DEGs in day 5, 10, and 15 inoculated groups, with 1174, 1493, and 2453 genes, respectively, compared to the control group. This suggests the heightened transcriptional activity of B. dothidea during the infection process, potentially enabling it to overcome the basic defenses of Chinese hickory. Transcriptomic levels of pathogens are seemingly positively correlated with their biomass and virulence [[121]43], and the observed high transcriptional activity of B. dothidea in this study may be associated with genetic variations in highly virulent strains [[122]44]. Furthermore, transcriptomics revealed localized cell death occurring after B. dothidea inoculation (Fig. [123]1B). Cell death-related defense mechanisms are crucial for limiting pathogen spread and nutrient acquisition by inducing local necrosis [[124]45, [125]46]. Cell death is also a common feature in highly grafting-resistant Chinese hickory species [[126]47]. Additionally, it has been reported that genes associated with pathogens confer resistance to dry rot disease in Chinese hickory by inducing cell death [[127]48]. Through DEGs analysis, genes associated with seedling stem development and resistance regulation were identified. Analysis of DEGs in B. dothidea inoculated and mock-inoculated samples revealed significant enrichment in KEGG pathways related to ‘secondary metabolism and biosynthesis,’ ‘metabolic pathways,’ ‘cellular functions,’ and ‘immune response.’ This finding is consistent with results from studies on other species, such as Potatoes (Solanum tuberosum ) [[128]49], Garlic (Allium sativum) [[129]50], and Melons (Cucumis melo) [[130]51]. It was also observed that genes associated with secondary metabolism or immune response were particularly sensitive to B. dothidea, especially those encoding DUF, Myb_DNA-binding, and ABC_membrane proteins.This study uncovers a new mechanism of interaction between B. dothidea and Chinese hickory, providing a theoretical basis for elucidating the pathogenic mechanism of B. dothidea and the resistance genes of Chinese hickory. Non-structural carbohydrates are crucial substances for plant growth and serve as carbon sources for key metabolic pathways such as the Calvin cycle and sugar fermentation [[131]52]. Under biotic stress, sugars can activate signal transduction, inducing the expression of defense genes [[132]53, [133]54]. Previous studies have suggested that pathways closely associated with sugar metabolism play a vital role in plant defense responses against fungal pathogens [[134]55]. It has been reported that critical genes involved in carbohydrate metabolism, photosynthesis, and secondary metabolism play a role in Chinese hickory resistance to anthracnose [[135]56]. In this study, KEGG analysis revealed significant enrichment of DEGs related to metabolic pathways such as “starch and sucrose metabolism,” “fructose and mannose metabolism,” and “tryptophan metabolism” in the B. dothidea inoculated group. Among these, 27 DEGs were associated with “starch and sucrose metabolism” (Table S8), which are known to play crucial roles in plant growth, stress response, and yield formation [[136]57, [137]58]. Studies have indicated that sugars not only serve as essential nutrients for plant growth but also act as a nutritional source for pathogenic fungi. Most fungi cannot directly utilize starch and sucrose and must first break them down into monosaccharides such as glucose and fructose [[138]59]. Consequently, fructose and glucose are considered key regulatory factors in plants’ resistance to fungal infections [[139]60]. In this study, we observed that following B. dothidea inoculation, the sucrose content in Chinese hickory seedlings increased, while the starch content decreased (Fig. [140]1E, F). This suggests a suppression of metabolic genes associated with starch accumulation and a reduction in monosaccharide levels, which may help restrict pathogen growth. As the infection progressed, monosaccharide levels increased, potentially providing favorable conditions for pathogen expansion (Fig. [141]1D). Furthermore, we detected the accumulation of sucrose at 10 days post-inoculation, and even after 15 days of B. dothidea inoculation, sucrose levels remained high in Chinese hickory seedlings. Simultaneously, the transcription levels of genes encoding sucrose transport proteins were up-regulated. This indicates that the high local sucrose content may originate from adjacent tissues transported to the lesion site, and new sucrose is synthesized through ABC transmembrane proteins. Plant hormones play a crucial role in response to various biotic and abiotic stresses. Upon detection of pathogen invasion, plants rapidly activate a complex hormonal signaling network for defense [[142]61]. Generally, SA mediates resistance to biotrophic and hemibiotrophic pathogens, while JA primarily defends against necrotrophic fungi [[143]62, [144]63]. Some studies suggest that, in certain cases, JA may not be effective, and SA is indispensable for resistance against necrotrophic fungi [[145]64], which aligns with our findings. In this study, we observed significant changes in SA levels in Chinese hickory tissues upon B. dothidea infection, while JA showed minor fluctuations (Fig. [146]1G, H). The roles of SA and JA in the interaction between plants and numerous pathogens are complex, and their effects on host plants’ resistance or susceptibility to pathogen infections may vary depending on the pathogen’s lifestyle and the plant genotype [[147]65]. In wheat (Triticum aestivum), inhibiting the SA and JA pathways weakened resistance against the hemibiotrophic pathogen Fusarium graminearum [[148]66]. We speculate that Chinese hickory resistance to B. dothidea may involve complex antagonistic and synergistic interactions between JA and SA, but further research is needed to elucidate their interplay mechanisms. In summary, we propose a model illustrating the interaction between B. dothidea and Chinese hickory during the infection process (Fig. [149]6). Initially, during the early stages of B. dothidea infection, the pathogen attaches to the phloem and spreads inward through epidermal gaps. Previous reports suggest that fungal pathogens invade the plant’s superficial cuticle through hyphal bodies, forming appressoria within it. Subsequently, hyphae penetrate epidermal cells to enter the parenchyma, expanding between the epidermal layer and parenchyma [[150]67]. Fungi may utilize cell wall hydrolytic enzymes to facilitate tissue penetration or induce osmotic pressure for hyphal entry into host cells [[151]68]. Fig. 6. [152]Fig. 6 [153]Open in a new tab Model depicting the interaction between B. dothidea and Chinese hickory during the infection process. (Sp: Secondary phloem; Pp: Primary phloem; X: Xylem; P: Pith; Vc: Vascular cambium; C: Cortex; Per: Periderm; B. dothidea: Botryosphaeria dothidea) Furthermore, by comparing transcriptomic changes in B. dothidea and Chinese hickory during their interaction, we have proposed the preliminary mechanism of pathogen invasion. B. dothidea synthesizes glycoside hydrolases and pectinases to hydrolyze plant cell walls, disrupting Chinese hickory’s surface defenses. The pathogen expresses β-fructofuranosidase to break down fructose for energy acquisition. In response to cell damage, excess reactive oxygen species are generated, prompting B. dothidea to express glutaminyl cyclase to maintain an appropriate oxidative environment. Chinese hickory’s response mechanisms include inducing lignin deposition to repair damaged cell walls and producing secondary metabolites such as triterpenoid saponins to directly inhibit the pathogen. Conclusion This study delves into the infection mechanism of the pathogenic fungus B. dothidea on Chinese hickory trees. We observed that the pathogen could establish colonization in Chinese hickory as early as five days post-inoculation. In comparison to the control group, significant changes occurred in biochemical indicators such as ST, SUC, SA, and JA in the inoculated group. Using transcriptomic analysis technology, we systematically investigated the transcriptomic response of Chinese hickory to B. dothidea. The results indicated substantial differential expression of genes related to metabolic pathways, sugar synthesis, and immune responses during the infection process by B. dothidea. Additionally, we established an interaction network for the invasion of Chinese hickory trees by the canker pathogen, identifying several key genes associated with non-structural sugar synthesis metabolism and plant-pathogen interactions, including genes encoding DUF, Myb_DNA-binding, and ABC transmembrane proteins. This study lays the theoretical foundation for a comprehensive understanding of the pathogenic mechanisms of B. dothidea and the resistance genes in Chinese hickory trees. Electronic supplementary material Below is the link to the electronic supplementary material. [154]Supplementary Material 1^ (15MB, xlsx) [155]Supplementary Material 2^ (4.9MB, docx) Acknowledgements