Comparison of gene co-networks analysis provide a systems view of rice (Oryza sativa L.) response to Tilletia horrida infection.

Aijun Wang,Peng Ai,Wenjuan Zhao,Aiping Zheng,Xianyu Niu,Xinyue Shu,Ping Li,Zonghua Wang

doi:10.1371/journal.pone.0202309

Aijun Wang, Peng Ai + Show 6 more

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https://doi.org/10.1371/journal.pone.0202309

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Abstract

The biotrophic soil-borne fungus Tilletia horrida causes rice kernel smut, an important disease affecting the production of rice male sterile lines in most hybrid rice growing regions of the world. There are no successful ways of controlling this disease and there has been little study of mechanisms of resistance to T. horrida. Based on transcriptional data of different infection time points, we found 23, 782 and 23, 718 differentially expressed genes (fragments per kilobase of transcript sequence per million, FPKM >1) in Jiangcheng 3A (resistant to T. horrida) and 9311A (susceptible to T. horrida), respectively. In order to illuminate the differential responses of the two rice male sterile lines to T. horrida, we identified gene co-expression modules using the method of weighted gene co-expression network analysis (WGCNA) and compared the different biological functions of gene co-expression networks in key modules at different infection time points. The results indicated that gene co-expression networks in the two rice genotypes were different and that genes contained in some modules of the two groups may play important roles in resistance to T. horrida, such as DTH8 and OsHop/Sti1a. Furthermore, these results provide a global view of the responses of two different phenotypes to T. horrida, and assist our understanding of the regulation of expression changes after T. horrida infection.

Highlights

Rice kernel smut (RKS), caused by the soil-borne basidiomycete fungus Tilletia horrida, is the most devastating disease during the production of rice male sterile lines in most hybrid rice growing regions of the world [1]
In order to identify the mechanisms involved in RKS response and search for the major modules and key genes that have important roles in the resistance of the two male sterile lines to T. horrida, we constructed the gene co-expression network
This was done using weighted gene co-expression network analysis (WGCNA) and different modules were identified according to transcriptome data as to how the two male sterile lines were affected by T. horrida infection at different time points

Summary

Introduction

Rice kernel smut (RKS), caused by the soil-borne basidiomycete fungus Tilletia horrida, is the most devastating disease during the production of rice male sterile lines in most hybrid rice growing regions of the world [1]. With the development of sequencing techniques, transcriptome analysis and genomics have promoted the study of the molecular mechanisms of disease resistance and tolerance to stress [7] These processes often involve multiple biological function genes; the analysis of multiple function genes using traditional biological methods is difficult [8]. The identification of candidate genes that related to biological phenotype was mainly based on comparing gene expression levels of differentially expressed genes between different experimental groups [9,10,11] This method mainly focused on single model research, nowadays, the study of molecular interactions in dynamic network changes has been extended [12]. Of these four biological networks, gene co-expression networks analysis has many advantages [16]

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