期刊
AGRICULTURE-BASEL
卷 13, 期 1, 页码 -出版社
MDPI
DOI: 10.3390/agriculture13010053
关键词
rice; protein-protein interaction; coexpression network; drought stress gene; random walk with restart
类别
This study introduces a random walk with restart algorithm (RWR) to identify potential drought stress-related genes in rice. By integrating protein-protein interaction data and gene coexpression network, a set of 13 genes were identified, 5 of which have been reported to be involved in drought stress resistance mechanisms.
Drought stress-related gene identification is vital in revealing the drought resistance mechanisms underlying rice and for cultivating rice-resistant varieties. Traditional methods, such as Genome-Wide Association Studies (GWAS), usually identify hundreds of candidate stress genes, and further validation by biological experiements is then time-consuming and laborious. However, computational and prioritization methods can effectively reduce the number of candidate stress genes. This study introduces a random walk with restart algorithm (RWR), a state-of-the-art guilt-by-association method, to operate on rice multiplex biological networks. It explores the physical and functional interactions between biological molecules at different levels and prioritizes a set of potential genes. Firstly, we integrated a Protein-Protein Interaction (PPI) network, constructed by multiple protein interaction data, with a gene coexpression network into a multiplex network. Then, we implemented the RWR on multiplex networks (RWR-M) with known drought stress genes as seed nodes to identify potential drought stress-related genes. Finally, we conducted association analysis between the potential genes and the known drought stress genes. Thirteen genes were identified as rice drought stress-related genes, five of which have been reported in the recent literature to be involved in drought stress resistance mechanisms.
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