Co-expression network analysis and identification of core genes in the interaction between wheat and Puccinia Striiformis f. sp. tritici

Abstract The epidemic of stripe rust, caused by the pathogen Puccinia Striiformis f. sp. tritici (Pst), would reduce wheat (Triticum aestivum) yields seriously. Traditional experimental methods are difficult to discover the interaction between wheat and Pst. Multi-omics data analysis provides a new idea for efficiently mining the interactions between host and pathogen. We used 140 wheat-Pst RNA-Seq data to screen for differentially expressed genes (DEGs) between disease-resistant and disease-susceptible samples, and carried out Gene Ontology (GO) enrichment analysis. Based on this, we constructed a gene co-expression network, identified the core genes and interacted gene pairs from the conservative modules. Finally, we checked the distribution of Nucleotide-binding and leucine-rich repeat (NLR) genes in the co-expression network and drew the wheat NLR gene co-expression network. In order to provide accessible information for related researchers, we built a web-based visualization platform to display the data. Based on the analysis, we found that various heat shock proteins (HSPs), protein kinases, and glycosidases frequently appeared in the network. They were likely to be involved in the biological processes of Pst infecting wheat. We also found that HSPs was significantly co-expressed in wheat and Pst, suggesting that there might be direct or indirect interactions between them. This study can assist scholars in conducting studies on the pathogenesis and help to advance the investigation of wheat-Pst interaction patterns.