Research Article
Identification of Rice Blast Resistance-related Co-expression Modules in Near Iso-genic Lines by WGCNA
2 State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan Agricultural University, Kunming, 650201, China
3 Southwest Forestry University, Kunming, 650233, China
Author Correspondence author
Molecular Pathogens, 2022, Vol. 13, No. 1 doi: 10.5376/mp.2022.13.0001
Received: 17 Jan., 2022 Accepted: 25 Jan., 2022 Published: 14 Mar., 2022
Li X., Ma L.N., Guo L.W., Liu Y.X., Yang M., Zhu S.S., He X.H., Zhu Y.Y., and Huang H.C., 2022, Identification of rice blast resistance-related co-expression modules in near iso-genic lines by WGCNA, Molecular Pathogens, 13(1): 1-10 (doi: 10.5376/mp.2022.13.0001)
Weighted gene co-expression network analysis (WGCNA) is often used to analyze multi-sample (>15) data, identify co-expressed gene modules, and explore the relationship between co-expression modules and target traits in systematic biology. In order to explore the gene co-expression network in response to Magnaporthe oryzae infection in rice near iso-genic lines (NIL) carrying different broad-spectrum resistance genes. We analyzed the expression pattern of genes by WGCNA based on the data of GSE117030 form the GEO database and identified 23 co-expression modules. Combining expression patterns with phenotypes, we chose tan module and midnightblue module as target modules. GO enrichment analysis showed that most of the genes in the target module were related to cell components. A co-expression network was constructed for the genes in the target module, and some hub genes were screened out. These results provide new insights into further understanding the mechanism of broad-spectrum resistance genes and breeding rice varieties with disease resistance.
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