Autor: |
Liu Zhu, Hongyan Zhang, Dan Cao, Yalan Xu, Lanzhi Li, Zilan Ning, Lei Zhu |
Jazyk: |
angličtina |
Rok vydání: |
2022 |
Předmět: |
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Zdroj: |
Agriculture, Vol 13, Iss 1, p 53 (2022) |
Druh dokumentu: |
article |
ISSN: |
2077-0472 |
DOI: |
10.3390/agriculture13010053 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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