Transcriptomic analysis of different resistant leaves infected by Colletotrichum gloeosporioides in grape

Abstract: 【Objective】Grape anthracnose is a fungal disease caused by Colletotrichum gloeosporioides. It is one of the four major diseases of grapes due to its wide distribution and great harm. Grape anthracnose has a great negative impact on the yield of grape berries. At present, there are many researches on the prevention and control methods of grape anthracnose, but there are few reports on grape anthracnose disease resistance genes. In this study, RNA-seq was used to screen the differentially expressed genes(DEGs) caused by C. gloeosporioides in grapes to further analyze the molecular mechanism of grape anthracnose resistance.【Methods】The experimental materials were collected from the Zhengzhou Grape Garden of the National Fruit Species Fund of the Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences. The anthracnose-susceptible progeny 7-2-6 strains and the anthracnose-resistant progeny 7-1-8 strains selected from the hybrid progeny through resistance identification were used as the research materials; the C. gloeosporioides were inoculated on the PDA medium and placed in a thermotank at a constant temperature of 28 ℃ for two to three weeks, and the leaves were inoculated by the method of bacterial cake inoculationand placed in a 28 ℃ incubator under moisturizing conditions. Simultaneously, the leaves sprayed with pure water on the stab wound were used as controls. The leaves were collected at 0, 24, 48 and 72 h after inoculation. Three biological replicates were set for samples at all periods. They were frozen by liquid nitrogen and stored in a refrigerator at -80 ℃ for later use. The high-throughput second-generation sequencing technology RNA-seq was used for sequencing, and the grape genome 12×PN40024 was used as the reference gene for comparison. Bowtie2 clean reads were aligned to the reference sequence to calculate the gene alignment rate,and RSEM was used to calculate the expression level of genes and transcripts. DEGseq algorithm detected DEGs, and selected genes with a multiple of more than twice the difference and Q-value ≤ 0.001as significant DEGs, and DEGs were used in KEGG enrichment analysis, transcription factor family analysis, and WGCNA was used to selecte genes of interest, and carry out a comprehensive screening of these key genes, select disease resistance candidate genes, and use q RT-PCR to verify.【Results】Through the analysis of transcriptome sequencing data, the average output of each sample was 6.65 Gb data. The average genome comparison rate was 86.08%, and the average gene set comparison rate was79.39%. A total of 25 545 genes were detected, of which 23 220 were known genes and 2403 were predicted new genes. At 0, 24, 48 and 72 h, there were 5527, 5924, 5451 and 7977 DEGs between the resistant strain and the susceptible strain, respectively. The numbers of up-regulated genes were 1468, 1801,1528 and 1893, and the numbers of down-regulated genes were 4059, 4123, 3923 and 6084, respectively. Among them, the number of down-regulated DEGs between resistant and susceptible strains was much greater than that of up-regulated genes. The number of DEGs up-regulated at 24 h and 72 h was significantly higher than that at 0h; the number of down-regulated DEGs at 72 h was 1.5 times higher than that of other periods. KEGG enrichment analysis showed that in the response process of pathogen infection, metabolite synthesis and signal transduction pathways were very active. Plant-pathogen interaction, flavonoid biosynthesis and mitogen-activated protein kinase signal pathways-plant was the most significant. Transcription factor family analysis found that AP2-EREBP, MYB, bHLH, NAC and WRKY families had the largest number of DEGs, and most of the transcription factors were down-regulated, but programmed cell death-related transcription factors were up-regulated. Weighted Gene Co-Expression Network Analysis(WGCNA) obtained modules related to disease resistance traits. Among them, Medrakgree and MEred were most related to disease resistance traits. Most of the genes were enriched in the biosynthesis of secondary metabolites, plant pathogen interactions, and MAPK signaling pathways—plant. Continuous DEGs analysis revealed that a total of 2592 DEGs were continuously expressed in the three periods of 24 h, 48 h and 72 h after anthracnose inoculation. Most of these DEGs came from the biosynthesis of secondary metabolites, plant pathogen interactions, MAPK signaling pathways-plant, protein processing in the endoplasmic reticulum, and spliceosome pathways. Based on various analysis, 9 DEGs were selected for qRT-PCR verification, and the expression trends of 8 genes were consistent with the results of transcriptome sequencing.【Conclusion】C. gloeosporioides infection caused anthracnose symptoms on grape leaves and also caused DEGs in different resistant strains. Transcriptome sequencing analysis obtained the DEGs of grapes in response to C. gloeosporioides infection.It was found that DEGs were significantly enriched in the three pathways of plant-pathogen interaction,flavonoid biosynthesis, and mitogen-activated protein kinase signaling pathway-plant, and 8 disease-resistant candidate genes were screened out, including MLO protein; WRKY, ERF transcription factors,etc.