Research Article

Identification of Rice Blast Resistance-related Co-expression Modules in Near Iso-genic Lines by WGCNA  

Xiang Li1,2 , Linna Ma1,2 , Liwei Guo1,2 , Yixiang Liu1,2 , Min Yang1,2 , Shusheng Zhu1,2 , Xiahong He2,3 , Youyong Zhu1,2 , Huichuan Huang1,2
1 College of Plant Protection, Yunnan Agricultural University, Kunming, 650201, China
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
© 2022 BioPublisher Publishing Platform
This article was first published in Molecular Plant Breeding in Chinese, and here was authorized to translate and publish the paper in English under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

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)

Abstract

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.

Keywords
WGCNA; Rice; Rice blast; Broad-spectrum resistance gene; Near isogenic lines
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. Xiang Li
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. Huichuan Huang
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