Project description:MicroRNAs (miRNAs) play important roles by regulating the expression of target genes in plant and animal. However, little known about mechanism of fungal miRNA-like RNAs (milRNAs) regulating target gene restricts their functional exploration. In this study, multiple omics were used to identify the milRNAs and their target genes in a phytopathogenic fungus Valsa mali. Many candidate pathogenic factors were found to be regulated by milRNA-directed cleavage way. Absence or downregulated expression of Vm-milRNAs promote expression of candidate pathogenic factors during V. mali infection. Vm-milR16 is a significantly downregulated milRNA during V. mali infection, resulting in significantly upregulated expression of three target genes: VmSNF1, VmDODA, and VmHy1. Overexpression of Vm-milR16 significantly reduces the pathogenicity of V. mali. And all the three target genes of Vm-milR16 are required for the full pathogenicity of V. mali. Further analysis revealed that VmSNF1 regulates the pathogenicity by affecting the expression of pectinase genes during V. mali infection. And all the three target genes are essential for oxidative stress response during V. mali-host interaction. Vm-milRNAs may help V. mali to intelligently use limited resources and adaptively regulate pathogenicity by enhancing expression of pathogenic factors and fitness during infection.
Project description:In order to explore the role of LaeA in secondary metabolite biosynthetic gene clusters’ regulation, toxin production, and virulence of Valsa mali, TMT-based proteomic analysis of wildtype, LaeA deletion mutant and overexpression mutant were performed. Totally, 4,299 proteins (FDR < 0.01) were identified by searching against the Valsa mali protein sequence database.
Project description:To investigate changes in the INTS-11 distribution across different conditions, we peformed ChIP-seq using antibody against INTS11 in K562 cells at 4 days after modified allele expression We then performed coverage plot analyses using data obtained from ChIP-seq from IP fractions to investigate INTS11 distribution changes
