基于RNA-seq筛选番茄防御南方根结线虫病的差异基因与RPP13的表达特征分析

doi:10.13560/j.cnki.biotech.bull.1985.2025-0657

摘要/Abstract

摘要：

目的通过对抗、感番茄材料接种南方根结线虫后进行RNA-seq和加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA），关注和抗病相关的信号通路及基因，验证目标基因的根部表达模式，为后续上述基因分子功能研究提供理论依据。方法对抗病番茄材料‘18060’和感病材料‘Moneymaker’进行线虫接种，收集未接种、接种后2 d和4 d的根部进行RNA-seq和WGCNA协同分析，对可能参与抗病的主要信号通路及抗病相关基因进行筛选，并完成目标基因的组织特异性表达和根部表达水平测定。结果随着接种时间延长，不同阶段的差异表达基因（differential expressed genes, DEGs）数量逐渐增多，抗、感材料的组间比较在接种第2天筛选出1 900个DEGs，在第4天，DEGs数量增加至3 012个；KEGG分析显示，在抗、感材料组内和组间比较中，“植物‒病原菌互作”均被显著富集。在组间比较中，被富集到该通路的DEGs主要编码包括类受体蛋白/激酶、钙信号相关蛋白、热激蛋白以及转录因子等，其中还有编码RPP13蛋白的5个R基因亦被筛选到；聚焦接种时期的DEGs，WGCNA筛选出了具有较强显著性的模块MEbrown，依据in degree和out degree数量分别筛选出数值前10的nodes作为核心基因，发现其中有2个编码RPP13的DEGs；组织特异性和根部表达模式鉴定进一步表明，Solyc07g039410.3在番茄防卫南方根结线虫入侵中可能发挥关键作用。结论筛选出番茄抗南方根结线虫病进程中可能发挥作用的6个RPP13基因，其中，Solyc07g039420.1和Solyc07g039410.3在根部存在特异性表达特征，4 dpi时期，作为hub基因的Solyc07g039410.3被显著诱导并提升至6.23倍，该基因很可能在番茄防御南方根结线虫病的进程中发挥关键功能。

关键词: 番茄, 根结线虫, 抗病, RPP13基因, RNA-seq, WGCNA, 根部表达模式

Abstract:

Objective By conducting RNA-seq and weighted gene co-expression network analysis on resistant and susceptible tomato materials inoculated with root-knot nematodes (RKNs) ( Meloidogyne incognita), we aim to focus on the signaling pathways and genes related to disease resistance, verify the root expression patterns of target genes, and provide theoretical basis for subsequent molecular function research on these genes. Method The resistant lines ‘18060’ and susceptible lines ‘Moneymaker’ were used for inoculation, and root samples were collected for transcriptome sequencing and WGCNA at the time points of no inoculation, 2 d and 4 d after inoculation The main pathways and regulatory genes that might be involved in disease resistance were screened, and the determination of the tissue-specific expression and root expression of these target genes were completed. Result As the inoculation time prolonged, the number of differentially expressed genes (DEGs) gradually increased. In the comparison between the resistant and susceptible groups at 2 dpi, 1 900 DEGs were screened out, and at 4 dpi the number of DEGs increased to 3 012. KEGG analysis showed that the “plant-pathogen interaction” was significantly enriched in both the within-group and between-group comparisons. In the between-group comparison, the DEGs enriched in this pathway mainly encoded receptor-like proteins/kinase, calcium signaling-related proteins, heat shock proteins, and transcription factors, etc. Among which 5 R genes encoding RPP13 protein were also screened out. Focusing on the DEGs during the inoculation period, the significant module MEbrown was screened out via the WGCNA, and the top 10 nodes based on the in degree and out degree were selected as hub genes based on the in degree and out degree. Two DEGs encoding RPP13 were found among them. The tissue-specific expression and root expression pattern identification further indicated that Solyc07g039410.3 might play a key role in tomato defense against the invasion of M. incognita. Conclusion Six RPP13 genes potentially involved in the process of resisting M. incognita are screened out. Among them, Solyc07g039420.1 and Solyc07g039410.3 demonstrate specific expression characteristics in the roots. At 4 dpi, the hub gene Solyc07g039410.3 is significantly induced and its expression increases by 6.23 times, indicating this gene plays a critical role in the defense of tomato against M. incognita.

Key words: tomato, root-knot nematode, disease resistance, RPP13 gene, RNA-seq, WGCNA, root expression pattern

冯成蒿, 党雨乐, 王志泽, 聂蔚丹, 杨中敏, 杜崇. 基于RNA-seq筛选番茄防御南方根结线虫病的差异基因与RPP13的表达特征分析[J]. 生物技术通报, 2026, 42(4): 141-152.

FENG Cheng-hao, DANG Yu-le, WANG Zhi-ze, NIE Wei-dan, YANG Zhong-min, DU Chong. Screening of Differentially Expressed Genes in Tomato Defense against Meloidogyne incognita Based on RNA-seq and Expression Characteristics Analysis of RPP13 Gene[J]. Biotechnology Bulletin, 2026, 42(4): 141-152.

图/表 12

图1 抗病番茄‘18060’和感病番茄‘Moneymaker’接种后根结数量统计A：供试番茄材料接种后的根部酸性品红溶液染色结果；B：抗、感材料各10株供试番茄根部的根结数量统计

Fig. 1 Statistics of root galls numbers after inoculation of disease-resistant tomato '18060' and disease-susceptible tomato 'Moneymaker'A: The staining results of the root parts of the tested tomato materials after inoculation with acid fuchsin solution. B: Number statistics of root-knots on the roots of 10 tested tomato plants for both resistant and susceptible materials

表1 转录组测序数据统计与质量评估

Table 1 Statistics and quality assessment of transcriptome sequencing data

样本Sample	干净数据Clean data （Gb）	Q30 （%）	GC含量 GC content （%）	总比对率Total mapped reads	唯一映射的读段Unique mapped reads	基因区间Intergenic （%）	外显子Exon（%）
MM-0d-1	5.88	96.29	42.35	97.11	94.01	5.95	88.38
MM-0d-2	6.16	95.50	42.19	97.14	94.26	6.21	87.17
MM-0d-3	5.74	96.37	42.37	97.38	94.42	5.69	88.99
MM-2d-1	6.08	95.65	42.19	96.96	94.18	5.97	87.66
MM-2d-2	5.98	95.62	42.34	97.16	94.55	5.86	87.97
MM-2d-3	6.54	96.54	42.33	97.58	94.94	5.41	89.42
MM-4d-1	5.87	96.32	42.33	96.60	93.88	5.72	89.04
MM-4d-2	5.76	96.50	42.27	97.60	95.10	5.55	89.74
MM-4d-3	6.05	96.17	42.32	97.03	94.51	5.89	89.19
XH-0d-1	6.03	96.50	42.30	95.98	93.72	6.10	88.70
XH-0d-2	6.10	96.10	42.29	95.87	93.65	6.18	88.21
XH-0d-3	6.07	96.27	42.22	94.94	92.70	6.31	87.35
XH-2d-1	6.21	95.78	42.36	95.29	93.21	6.39	87.50
XH-2d-2	6.29	95.56	42.17	94.96	92.97	6.58	86.90
XH-2d-3	5.98	95.89	42.26	95.30	92.81	6.16	88.18
XH-4d-1	6.43	96.39	42.35	96.58	94.26	5.90	88.63
XH-4d-2	6.42	96.04	41.95	95.90	93.85	6.14	87.90
XH-4d-3	6.10	95.95	42.20	96.21	93.99	5.95	88.32

图2 供试番茄18个样本基于RNA-seq的PCA分布不同坐标表示不同主成分，百分比表示相应主成分对样品差异的贡献值，每个点表示1个样品，不同分组的样本用不同颜色和形状表示

Fig. 2 PCA distribution of 18 samples of the tested tomatoes based on RNA-seqThe different coordinates refer to different principal components, and the percentages refer to the contribution value of the corresponding principal component to the sample’s variance. Each point indicate a sample, and samples in different groups are marked by different colors and shapes

图3 不同比较策略下DEGs统计（A）及抗、感病组内共表达趋势分析（B）

Fig. 3 Statistical analysis of DEGs under different comparison strategies (A) and analysis of the co-expression trend within the resistant and susceptible groups (B)

图4 不同比较组DEGs的KEGG富集通路

Fig. 4 KEGG enrichment pathway of DEGs in different comparison groups

图5 XH组富集到植物‒病原菌互作途径中DEGs的FPKM聚类分析热图表示XH组不同处理阶段DEGs的FPKM值，模块颜色代表FPKM的大小，绿色箭头代表共同筛选的DEGs

Fig. 5 Cluster analysis of FPKM values of DEGs enriched in the plant-pathogen interaction pathway in the XH groupThe heatmap shows the FPKM values of DEGs in the XH group at different treatment stages, the colors of the modules indicate the size of FPKM, and the green arrows indicate the DEGs that were jointly selected

图6 组间比较MM_vs_XH中富集到植物‒病原菌互作途径DEGs的log2FC聚类分析聚类热图代表组间比较MM_vs_XH中不同接种阶段DEGs的log2FC统计，圆圈颜色和大小代表FPKM的数值高低，绿色箭头代表共同筛选的DEGs

Fig. 6 Cluster analysis of log2FC values for DEGs enriched in the plant-pathogen interaction pathway during inter-group comparisons (MM_vs_XH)The cluster heatmap indicates the statistical log2FC values of DEGs in the MM_vs_XH group comparison at different inoculation stages, the colors and sizes of the circles indicate the numerical values of FPKM, and the green arrows indicate the DEGs that are jointly selected

图7 层次聚类及模块划分A：最佳软阈值的选择；B：DEGs的系统聚类树和基因模块划分，不同颜色代表不同的模块

Fig. 7 Hierarchical clustering and module divisionA: Selection of the optimal soft threshold. B: The system clustering tree of DEGs and the division of gene modules, with different colors indicating different modules

图8 模块与不同样本之间的相关性分析横坐标代表不同材料各接种时期，纵坐标代表模块名称，模块颜色越深代表相关性越强

Fig. 8 Correlation analysis between the module and different samplesThe horizontal axis indicates different materials and different inoculation periods, the vertical axis indicates the module name, and the darker the color of the module, the stronger the correlation

图9 共表达网络构建图结点的颜色越深代表in degree数量越多，圆圈越大代表out degree数量越多，虚线框内的nodes分别代表in degree和out degree数量排名前10的hub genes

Fig. 9 Construction diagram of co-expression networkThe darker the color of a node, the greater the number of in degree. The larger the circle, the greater the number of out degree. The nodes within the dotted box indicate the top ten hub genes in terms of in degree and out degree respectively

图10 RPP13基因的组织特异性表达分析ns：显著性差异（one-way ANOVA，P>0.05），* P<0.05，** P<0.01，*** P<0.001。下同

Fig. 10 Analysis of the tissue-specific expressions of the RPP13 genesns: Significant difference (one-way ANOVA, P>0.05), *:P<0.05, **P<0.01, *** P<0.001. The same below

图11 RPP13基因的根部表达模式鉴定

Fig. 11 Identification of the root expression pattern of the RPP13 genes

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