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GERWR: Identifying the Key Pathogenicity- Associated sRNAs of Magnaporthe Oryzae Infection in Rice Based on Graph Embedding and Random Walk With Restart.
Article em En | MEDLINE | ID: mdl-38153818
ABSTRACT
Rice blast, caused by Magnaporthe oryzae(M.oryzae), is a destructive rice disease that reduces rice yield by 10% to 30% annually. It also affects other cereal crops such as barley, wheat, rye, millet, sorghum, and maize. Small RNAs (sRNAs) play an essential regulatory role in fungus-plant interaction during the fungal invasion, but studies on pathogenic sRNAs during the fungal invasion of plants based on multi-omics data integration are rare. This paper proposes a novel approach called Graph Embedding combined with Random Walk with Restart (GERWR) to identify pathogenic sRNAs based on multi-omics data integration during M.oryzae invasion. By constructing a multi-omics network (MRMO), we identified 29 pathogenic sRNAs of rice blast fungus. Further analysis revealed that these sRNAs regulate rice genes in a many-to-many relationship, playing a significant regulatory role in the pathogenesis of rice blast disease. This paper explores the pathogenic factors of rice blast disease from the perspective of multi-omics data analysis, revealing the inherent connection between pathogenic factors of different omics. It has essential scientific significance for studying the pathogenic mechanism of rice blast fungus, the rice blast fungus-rice model system, and the pathogen-host interaction in related fields.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ascomicetos / Oryza / Magnaporthe Idioma: En Revista: ACM Trans Comput Biol Bioinform / ACM trans. comput. biol. bioinform. (Online) / ACM transactions on computational biology and bioinformatics (Online) Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ascomicetos / Oryza / Magnaporthe Idioma: En Revista: ACM Trans Comput Biol Bioinform / ACM trans. comput. biol. bioinform. (Online) / ACM transactions on computational biology and bioinformatics (Online) Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article