Transboundary Regulation Of Magnaporthe Oryzae Srna On Rice-based On High-throughput Data

In recent years,studies have shown that phytopathogenic fungi possess the ability of transboundary regulation of host plants through small RNAs(sRNAs).Magnaporthe oryzae,a causative agent of rice blast,causes disease by penetrating the rice tissues through infection structures.However,little is known about the transboundary regulation of M.oryzae sRNA on rice in current studies.Therefore,it is of great theoretical and practical significance to study the transboundary regulation of rice by sRNA in the process of infection of M.oryzae.In this paper,based on the high-throughput data of M.oryzae sRNAs and the mixed sRNAs during infection,the model based on a single algorithm and multiple data sets and the fusion model based on various algorithm and multiple data sets were constructed.In addition,the differential expressions of sRNAs in M.oryzae before and during infection were compared,it was found that expression levels of 366 M.oryzae sRNAs were up-regulated significantly during infection.Functional enrichment analysis was performed on target genes of differentially expressed sRNAs,and nine biological processes and a KEGG pathway related to rice growth and defense responses were obtained.These functions correspond to thirteen rice genes.A total of fourteen M.oryzae sRNAs targeting the rice genes were identified by data analysis,and their authenticity was verified in the database of M.oryzae sRNAs.The fourteen M.oryzae sRNAs may participate in the transboundary regulation process and act as sRNA effectors to manipulate the rice blast process.The model constructed in this paper is the optimal model selected after analyzing and comparing the performance of different models.This model can be used for the prediction of differentially expressed sRNAs,and has some reference value for predicting differentially expressed sRNAs of the homologous species of M.oryzae.In addition,it will also play an important role in the related research on M.oryzae in the future.At present,no research has been reported to analyze the pathogenic mechanismof rice blast from the perspective of sRNA transboundary regulation.In this paper,computational methods are used for the research on the transboundary regulation of M.oryzae sRNAs.Futhermore,big data analysis and machine learning are also applied to this field.Compared with previous biological methods,this method has higher efficiency and lower cost.The results of this article provide a data analysis basis for studying the infection mechanism of M.oryzae and a reliable biological data analysis scheme for the study of the transboundary regulation of fungal sRNAs.In addition,this study provides new ideas for innovative study on the processes of plant infection by other phytopathogenic fungi,and it is great significance to understand the interaction mechanism between fungi and plants.