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Construction of sRNA Regulatory Network for Magnaporthe oryzae 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 Magnaporthe oryzae use the RNAi mechanism of rice to realize the infection process, and different effector proteins can incre...

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Autores principales: Zhao, Enshuang, Zhang, Hao, Li, Xueqing, Zhao, Tianheng, Zhao, Hengyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633311/
https://www.ncbi.nlm.nih.gov/pubmed/34868245
http://dx.doi.org/10.3389/fgene.2021.763915
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author Zhao, Enshuang
Zhang, Hao
Li, Xueqing
Zhao, Tianheng
Zhao, Hengyi
author_facet Zhao, Enshuang
Zhang, Hao
Li, Xueqing
Zhao, Tianheng
Zhao, Hengyi
author_sort Zhao, Enshuang
collection PubMed
description 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 Magnaporthe oryzae 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 M. oryzae infecting rice is still poorly understood. Therefore, the combination of transcriptomics and proteomics to study the mechanism of M. oryzae 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 M. oryzae 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 M. oryzae-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 M. oryzae, and the interacting protein molecules, the M. oryzae-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 M. oryzae sRNAs and proteins were mined and analyzed. The results showed that 22 sRNAs of M. oryzae, 77 secretory proteins of M. oryzae were used as effect factors to participate in the infection process of M. oryzae. And many significantly enriched GO modules were discovered, which were related to the infection mechanism of M. oryzae.
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spelling pubmed-86333112021-12-02 Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data Zhao, Enshuang Zhang, Hao Li, Xueqing Zhao, Tianheng Zhao, Hengyi Front Genet Genetics 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 Magnaporthe oryzae 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 M. oryzae infecting rice is still poorly understood. Therefore, the combination of transcriptomics and proteomics to study the mechanism of M. oryzae 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 M. oryzae 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 M. oryzae-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 M. oryzae, and the interacting protein molecules, the M. oryzae-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 M. oryzae sRNAs and proteins were mined and analyzed. The results showed that 22 sRNAs of M. oryzae, 77 secretory proteins of M. oryzae were used as effect factors to participate in the infection process of M. oryzae. And many significantly enriched GO modules were discovered, which were related to the infection mechanism of M. oryzae. Frontiers Media S.A. 2021-11-12 /pmc/articles/PMC8633311/ /pubmed/34868245 http://dx.doi.org/10.3389/fgene.2021.763915 Text en Copyright © 2021 Zhao, Zhang, Li, Zhao and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Zhao, Enshuang
Zhang, Hao
Li, Xueqing
Zhao, Tianheng
Zhao, Hengyi
Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title_full Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title_fullStr Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title_full_unstemmed Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title_short Construction of sRNA Regulatory Network for Magnaporthe oryzae Infecting Rice Based on Multi-Omics Data
title_sort construction of srna regulatory network for magnaporthe oryzae infecting rice based on multi-omics data
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633311/
https://www.ncbi.nlm.nih.gov/pubmed/34868245
http://dx.doi.org/10.3389/fgene.2021.763915
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