Identification of abiotic stress-related gene co-expression networks in maize by WGCNA.

Weighted Gene Co-expression Network Analysis (WGCNA) is a classic systems biology analysis method, which can be used to identify coexpressed gene modules and explore the biological correlation between modules and target traits, and mine core genes in module networks. In this study, 58 transcriptome data of roots, stems, leaves, and other tissues under low temperature stress, high temperature stress, drought stress, and salt stress in maize (Zea mays L.) were collected, and the gene co-expression network of maize abiotic stress was identified by WGCNA method. After filtering the 12,552 low-expression genes from transcriptome data, the co-expression network was constructed using the remaining 27,204 high-expression genes, and 25 modules were obtained. According to the distribution of abiotic stress-related genes and different expression genes in the modules reported in maize, the mediumpurple4, ivory, coral2, darkseagreen4 modules most related to low temperature stress, high temperature stress, drought and salt stresses, and green modules responding to various stresses were screened out. Subsequently, GO enrichment of the genes in these five modules revealed that genes with functions related to abiotic stress were significantly enriched in these modules, such as stress response, peroxidase activity. Correlation analysis showed that 10 abiotic stress-related core genes were predicted, including Zm00001eb072870, Zm00001eb320970, Zm00001eb037640, Zm00001eb423300, and Zm00001eb265310. This study provides new ideas for the mining of abiotic stress-related genes and the research of abiotic stress regulatory networks in maize. [ABSTRACT FROM AUTHOR]