Transcriptome changes associated with apple (Malus domestica) root defense response after Fusarium proliferatum f. sp. malus domestica infection

Abstract

Background Apple replant disease is a soilborne disease caused by Fusarium proliferatum f. sp. malus domestica strain MR5 (abbreviated hereafter as Fpmd MR5) in China. This pathogen causes root tissue rot and wilting leaves in apple seedlings, leading to plant death. A comparative transcriptome analysis was conducted using the Illumina Novaseq platform to identify the molecular defense mechanisms of the susceptible M.26 and the resistant M9T337 apple rootstocks to Fpmd MR5 infection. Results Approximately 518.1 million high-quality reads were generated using RNA sequencing (RNA-seq). Comparative analysis between the mock-inoculated and Fpmd MR5 infected apple rootstocks revealed 28,196 significantly differentially expressed genes (DEGs), including 14,572 up-regulated and 13,624 down-regulated genes. Among them, the transcriptomes in the roots of the susceptible genotype M.26 were reflected by overrepresented DEGs. MapMan analysis indicated that a large number of DEGs were involved in the response of apple plants to Fpmd MR5 stress. The important functional groups identified via gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were responsible for fundamental biological regulation, secondary metabolism, plant-pathogen recognition, and plant hormone signal transduction (ethylene and jasmonate). Furthermore, the expression of 33 up-regulated candidate genes (12 related to WRKY DNA-binding proteins, one encoding endochitinase, two encoding beta-glucosidases, ten related to pathogenesis-related proteins, and eight encoding ethylene-responsive transcription factors) were validated by quantitative real-time PCR. Conclusion RNA-seq profiling was performed for the first time to analyze response of apple root to Fpmd MR5 infection. We found that the production of antimicrobial compounds and antioxidants enhanced plant resistance to pathogens, and pathogenesis-related protein (PR10 homologs, chitinase, and beta-glucosidase) may play unique roles in the defense response. These results provide new insights into the mechanisms of the apple root response to Fpmd MR5 infection.

Transcriptome Characterization and Gene Changes Induced by Fusarium solani in Sweetpotato Roots

“…DEGs in different pathways of the comparisons indicated that sweetpotato was challenged with F. solani via a complex network to stimulate plant immune system responses and regulate the expression of defense-related genes [26,28]. More than 12,000 DEGs were detected in CK-32 vs. T-6h, CK-32 vs. T-24h, CK-32 vs. T-3d, and CK-32 vs. T-5d comparisons, and these DEGs were enriched into different GO entries and KEGG metabolic pathways, reflecting that some genes in sweetpotato play an important role in the resistance to pathogens [42,43]. The number of downregulated genes was higher than that of upregulated genes.…”

MIR390 Is Involved in Regulating Anthracnose Resistance in Apple

“…Active oxygen metabolism effectively prevented pathogens from stimulating membrane lipid peroxidation, causing the loss of cellular compartmentalization and the inhibition of photosynthetic electron transport [ 51 , 52 ]. PR genes were induced by pathogen infection and PR proteins may act as antimicrobial components in the plant defense response [ 36 , 57 ]. We found a remarkable upregulation of PR genes in MIR390b -overexpressing plants compared with ‘GL-3′ plants ( Figure 7 ).…”

Phenomics and transcriptomic profiling of fruit development in distinct apple varieties

“…Although some studies have been conducted on gene expression and phenotype variations in apples 6 – 8 , 11 – 16 . there are several limitations in terms of data quality and completeness.…”

“…The reference genome version (GDDH13 v1.1) utilized for sequence mapping is a widely recognized resource in apple genome research 16 , 19 , 27 – 30 , encompassing transcript information for 45,116 protein-coding genes. To normalize the transcript quantities of each coding gene, the mapping results was normalized using TPM (Transcripts Per Million) and FPKM (Fragments Per Kilobase of transcript per Million mapped reads).…”