Construction of sRNA Regulatory Network for Infecting Rice Based on Multi-Omics Data.

Studies have shown that fungi cause plant diseases through cross-species RNA interference mechanism (RNAi) and secreted protein infection mechanism. The small RNAs (sRNAs) of use the RNAi mechanism of rice to realize the infection process, and different effector proteins can increase the autotoxicity by inhibiting pathogen-associated molecular patterns triggered immunity (PTI) to achieve the purpose of infection. However, the coordination of sRNAs and proteins in the process of infecting rice is still poorly understood. Therefore, the combination of transcriptomics and proteomics to study the mechanism of infecting rice has important theoretical significance and practical value for controlling rice diseases and improving rice yields. In this paper, we used the high-throughput data of various omics before and after the infecting rice to screen differentially expressed genes and sRNAs and predict protein interaction pairs based on the interolog and the domain-domain methods. We were then used to construct a prediction model of the -rice interaction proteins according to the obtained proteins in the proteomic network. Finally, for the differentially expressed genes, differentially expressed sRNAs, the corresponding mRNAs of rice and , and the interacting protein molecules, the -rice sRNA regulatory network was built and analyzed, the core nodes were selected. The functional enrichment analysis was conducted to explore the potential effect pathways and the critical infection factors of sRNAs and proteins were mined and analyzed. The results showed that 22 sRNAs of , 77 secretory proteins of were used as effect factors to participate in the infection process of . And many significantly enriched GO modules were discovered, which were related to the infection mechanism of .