The gummosis-susceptible peach variety ‘Spring snow’ was grafted onto wild peach rootstocks and maintained at the experimental orchard of the institute of Fruit and Tea, Hubei Academy of Agricultural Sciences (Wuhan, China). Current-year shoots were used for the experiments. The N. parvum strain JSZ01 was deposited in the Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees (Wuhan, China). Prior to infection, JSZ01 was cultured on potato dextrose agar (PDA) medium at 26°C for 3 d.

The inoculation method followed the (Zhang et al., 2022) with minor modifications. Current-year shoots were defoliated and gently rinsed with flowing water to remove surface dust. The shoots were then cut into approximately 15 cm segments, sterilized with 75% alcohol for 30 s, and washed three times with sterile water. The shoot segments were wounded with a sterile needle and inoculated with N. parvum strain JSZ01. As a control, shoots were inoculation with PDA medium. Both treated shoots were placed in a clean plastic box with wet gauzes at the bottom, covered with plastic wrap, and transferred to a light incubator (12 h light/12 h dark, 75% relative humidity) at 26 °C. After inoculation, tissues within 2 cm of the lesion were collected at 12, 24, 36, 48 and 60 h. Each treatment had three replicates, with each replicate consisting of 15 shoot segments. All samples were immediately frozen in liquid nitrogen and stored at -80°C for further analyses.

Total RNA from peach shoots was isolated using the Plant Total RNA Kit (Simgen, 5103050, Hangzhou, China) according to the manufacturer’s protocols. The RNA samples were then sent to Biomarker Technologies company (Beijing, China) for paired-end RNA sequencing. The cDNA library was constructed using the NEBNext^® Ultra™ RNA Library Prep Kit (NEB, USA) and sequenced using the Illumina Novaseq6000.

To obtain high-quality reads, raw reads were filtered using the default parameters of the fastp software to remove adapter sequences and low-quality reads (Chen et al., 2018). Clean reads were then mapped to the reference genome of Prunus persica v2.0 (Verde et al., 2017) using HISAT2. Gene expression levels were calculated using the FPKM method by Feature Counts and R software.

Differential expression of genes (DEGs) between different samples was screened by using DESeq2, with |log2fold changes| ≥ 1 and false discovery ratios (FDR) < 0.05 as the threshold. The DEGs were then subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis (Kanehisa et al., 2008; Young et al., 2010). GO and KEGG pathways with a q value < 0.05 were considered significantly enriched. The visualization of the heatmap and Bubble Chart was drawn using R language (Gu, 2022; Villanueva and Chen, 2019).

First-strand cDNA was synthesized using a commercial kit (Simgen, 7306100, Hangzhou, China) according to the manufacturer’s instructions. qPCR was performed on the QuantStudio 7 Flex instrument (Applied Biosystems, Foster City, CA, USA) using MonAMP™ SYBR Green qPCR Mix (Monad, MQ10201, Wuhan, China). Each reaction consisted of 5 μL of SYBR qPCR master mix, 0.2 μM of forward and reverse primers, and 200 ng of cDNA in a final volume of 10 μL.

The cycling conditions were as follows: 95°C for 5 min, followed by 40 cycles of 95°C for 15 s and 60°C for 30 s. PpTEF2 (Translation elongation factor 2) was used as the normalizing internal control. Relative gene expression levels were quantified according to the 2^–ΔΔCT method (Livak and Schmittgen, 2001). Three independent replicates were used for the experiments. The gene-specific primers for qPCR analysis are listed in Supplementary Table S4 .

Sugar content was measured according to the previous protocol described by (Umer et al., 2020) with minor modifications. The same fresh shoot samples used for transcriptome analysis were employed for metabolome analysis. Each sample was ground with liquid nitrogen, and 0.02 g of tissue powder was vortexed with 0.5 mL extraction agent (methanol-isopropanol-water, 3: 3: 2; v/v/v) for 3 min. The mixture was then subjected to ultrasound in an ice water bath for 30 min.

Following centrifugation at 14000 r/min for 3 min, 50 μL of the supernatants was transferred to a 2 mL tube and mixed with 20 μL of internal standard (0.1 mg/mL ribitol). The mixtures were dried in a Speed Vac (Labconco, Kansas City, MO, USA), and then vortexed with 100 μL of methoxyamine hydrochloride (15 mg/mL). The samples were incubated at 37°C for 2 hours, followed by the addition of 100 μL BSTFA to each tube. The tubes were then incubated at 37°C for 30 minutes to obtain the derivative solution. The GC-MS assay was performed using a gas chromatograph coupled to a mass spectrometer (Agilent 8890-5977B, CA, USA) to quantify the sugar contents.

The WGCNA package (v4.0.2) was used to assess the similarities of expression patterns among the samples based on transcriptome data. During data preprocessing, expression values with a mean less than 1 and a coefficient of variation less than 0.1 were excluded to minimize noise and focus on robust signals. In the networkType identification process, the network type was specified as ‘unsigned’, and the soft threshold power (β value) was determined automatically to optimize the network construction. The minimum module size was set to 30, and the minimum kME to stay was set to 0.3 to ensure robust module detection. The network of these relationships was further elucidated using Cytoscape software (v3.9.1, https://cytoscape.org).

All experiments were repeated at least three times for each study to ensure reliability and accuracy. Statistical differences were calculated using analysis of variance (ANOVA) in SPSS13.0 (IBM, USA), followed by a t-test to determine significant differences between means. The significance levels were set at * P < 0.05, ** P < 0.01, and *** P < 0.001.

The development of gummosis spots was observed on the shoots of ‘Spring snow’ peach trees with and without inoculation with N. parvum ( Figure 1A ). Compared to the mock group, the N. parvum-inoculated shoots exhibited visible necrotic lesion at 12 hours post inoculation (hpi), with a lesion length of approximately 0.7 cm. The lesions on peach shoots gradually expanded over time, reaching approximately 2.6 cm in length by 60 hpi ( Figure 1B ). Moreover, another typical symptom of gummosis was observed, as the lesions began releasing gum at 36 hpi ( Figure 1A ). In contrast, the mock treatment did not display any lesions or gum exudation. These results indicate that N. parvum inoculation induces peach gummosis.

RNA-seq was performed on samples from both the mock and N. parvum treatments at five time points. The number of total clean reads ranged from 38, 915, 380 to 58, 094, 244, with an average Q30 value of 95.42% and the GC content ranging from 45.43% to 46.34% ( Supplementary Table S1 ). Principal component analysis (PCA) results (PC1 variance explained 25.27% and PC2 14.57%, R=0.1207) showed that each group sample has good repeatability, and the mock treatment groups have distinct global expression patterns ( Supplementary Figure S1 ). A total of 8,136 differentially expressed genes (DEGs, log₂fold≥1 with P-value≤ 0.05) were identified ( Supplementary Table S2 ). Volcano plots showed upregulation of 295, 274, 817, 983, and 938 genes and downregulation of 1025, 318, 1054, 1272 and 1160 genes in comparisons between T12 vs. C12, T24 vs. C24, T36 vs. C36, T48 vs. C48, and T60 vs. C60, respectively ( Figure 2A ).

GO enrichment analyses revealed significant enrichment of DEGs in ‘xyloglucan metabolic process (GO:0010411)’, and ‘cell wall (GO:0005618)’ processes during the earlier periods of infection (12 hpi and 24hpi) ( Figure 2B ). Further analysis showed decreased expressions of XTHs (encoding for xyloglucan endotransglucosylase/hydrolases) and increased expressions of EXPs (encoding for expansin) and BGALs (encoding for beta-galactosidase) under N. parvum infection at 12 hpi and 24hpi ( Figure 2C ). At 12 hpi, the log₂Fold change in the transcript level of Prupe.1G088900 decreased by 2.6 times, while that of Prupe.6G075100 increased by 2.58 times compared to the mock group ( Supplementary Table S2 ). Moreover, DEGs were enriched in sugar metabolism-related processes, including ‘UDP-glycoyltransferase activity (GO:0008194)’, ‘gluconeogenesis (GO:0006094)’, and ‘Transcription factor activity (GO:0003700)’ process ( Figure 2B ). Collectively, these results demonstrated that cell wall metabolism, sugar metabolism, and transcription factors in peach shoots play important roles in responding to N. parvum infection.

Metabolome analysis was performed to investigate sugar levels in peach shoots during gum formation after N. parvum infection. A total of 13 sugar/alcohol metabolites were identified ( Supplementary Table S3 ). The Pearson’s correlation matrix and PCA revealed good repeatability and distinct separation (PC1 variance explained 41.6% and PC2 26.86%, R=0.1806) of mock and N. parvum infection treatments ( Figures 3A, B ), indicating suitable for further analysis. Based on |Fold Change| >1 and p-value < 0.05, 13 sugar/alcohol metabolites showed differential accumulation: 3 (1 up-regulated, 2 down-regulated) in T12 vs. C12, 4 (1 up-regulated, 3 down-regulated) in T24 vs. C24, 8 (1 up-regulated, 7 down-regulated) in T36 vs. C36, 8 (2 up-regulated, 6 down-regulated) in T48 vs. C48 and 7 (3 up-regulated, 4 down-regulated) T60 vs. C60 comparisons ( Figure 3C ). KEGG pathway enrichment analysis of the differentially abundant sugar (DAS) showed that the DASs were mainly involved in ‘galactose metabolism’ pathway, ‘biosynthesis of secondary metabolite’ pathway, and ‘starch and sucrose metabolism’ pathway ( Figure 3D ). Compared to the mock group, the N. parvum infection group exhibited higher contents of maltose and L-rhamnose at 12-60 hpi, with maltose increasing 1.72-fold and L-rhamnose increasing 1.40-fold at 60 hpi. Trehalose contents elevated at 36-60 hpi, especially 1.86-fold increase at 60 hpi. In contrast, the content of D-galactose, fructose and glucose decreased at 36-60 hpi, with the most significant reduction at 36 hpi: 22% for D-galactose, 39% for fructose, 33% for glucose ( Figure 3E ; Supplementary Table S3 ). These results suggest that peach can regulate sugar metabolism pathways in response to N. parvum infection.

To investigate the relationships between metabolites and genes in response to N. parvum-mediated peach gummosis, a sugar regulatory heatmap was generated to compare structural genes associated with sugar biosynthetic and decomposition pathways between N. parvum-infected and mock samples ( Figure 4 ). This analysis revealed that transcripts of AMY and PYG, encoding α-amylase and α-Glucan phosphorylases (α-GPs), were upregulated by N. parvum infection. Additionally, genes involved in the synthesis or decomposition of maltose (AMY, PYG), trehalose (TPS: trehalose-phosphate phosphatase, TRE: trehalase), sucrose (INV: invertase, SS: sucrose synthase), sorbitol (SDH: sorbitol dehydrogenase), D-Galactose (GOLS: galactinol synthase) were differentially expressed under N. parvum infection. As UDP-sugar metabolism is a crucial step in polysaccharide formation, an in-depth analysis of the DEGs associated with UDP-sugar biosynthesis was performed. This revealed that transcripts of HK (coding for hexokinase), PGM (coding for phosphoglucomutase), UGPase (coding for UTP-glucose-1-phosphate uridylyltransferase), UGE (coding for UDP-glucose 4-epimerase), UGDH (coding for UDP-glucose 6-dehydrogenase), UXS (coding for UDP-glucuronate decarboxylase), UXE (coding for UDP-arabinose 4-epimerase), and RHM (coding for UDP-rhamnose synthase) genes were induced to varying degrees by N. parvum inoculation compared to the mock treatment.

Transcription factors (TFs) play vital roles in plant disease response by directly targeting downstream genes. In this study, 277 TFs were differentially expressed in peach shoots inoculated with N. parvum at five time points compared to the mock group. These TFs were classified into 35 subfamilies based on the PlantTFDB databases. Notably, ERF TFs were the most numerous among these subfamilies. The heatmap analysis showed that 10 genes were significantly upregulated, while 28 genes were significantly downregulated in response to N. parvum infection ( Figures 5A, B ). In addition, WGCNA was performed to predict the key TFs and potential interacting genes. The identified genes were mainly concentrated in the blue, brown, grey, and turquoise modules ( Figure 6A ). ERF027 and bZIP9 were identified as the core TFs in the blue and turquoise modules, respectively ( Figure 6B, C ). Network analysis revealed different types of genes, including galactosyltransferase 1 (GALT1), xyloglucan endotransglycosylase 6 (XTH6), and CaLB, with high weight connected to ERF027, and bZIP9 was highly correlated with genes such as UDP-glucosyl transferase 88A1 (UGT88A1), ubiquitin-activating enzyme 1 (UBA1) and BRI1. These findings indicate that ERF027 and bZIP9 may cooperate with their connected genes in response to N. parvum infection, highlighting the importance of TFs in N. parvum-mediated gummosis in peach, particularly ERF027 and bZIP9.

To validate the gene expression results, 12 well-known pathogen stress-related genes involved in cell wall biogenesis (PpCel3 and PpExp2), flavonoid biosynthesis (PpCoA3 and PpPAL2), sugar metabolism (PpTRE13 and PpGH9C2), ROS scavenging process (PpPOD4 and PpGSTU17) and four TF (PpWRKY75, PpERF027, PpbZIP3 and PpbZIP9) of peach were evaluated using qPCR ( Figure 7 ). The correlation analysis of gene log₂Fold change between qRT-PCR and RNA-seq data yielded a determination coefficient (R²) of 0.8385 ( Supplementary Figure S2 ). These genes were induced to different extent by N. parvum infection, indicating that peach regulates a large number of stress-responsive genes to orchestrate its response to N. parvum infection.