Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt - Li, Fang; Chen, Xi; Yang, Bo; Guang, Yingjie; Wu, Dandan; Shi, Zunji; Li, Yanzhong (Frontiers in Plant Science, 2022)
Following infestation by Verticillium wilt, alfalfa (Medicago sativa L.) often shows symptoms such as disease spots, leaf loss, stem and leaf yellowing, resulting in the decline of alfalfa yield and quality and causing significant losses to the alfalfa industry. The popularization and planting of disease-resistant varieties is the most effective method to prevent and control Verticillium wilt of alfalfa. Therefore, it is particularly important to reveal the resistance mechanism of Verticillium wilt resistant varieties of alfalfa. In this study, the physiological and biochemical indexes were measured on days 7, 14, 21 and 28 after inoculation with Verticillium alfalfae for investigating the response mechanisms of two alfalfa varieties, high resistant WL343HQ and low resistant Dryland. Transcriptome sequencing of alfalfa samples infected with Verticillium alfalfae and uninfected alfalfa samples was performed to analyze the potential functions and signaling pathways of differentially expressed genes (DEGs) by GO classification and KEGG enrichment analysis. Meanwhile, WGCNA algorithm was used to construct a co-expression network of DEGs. Inoculation with Verticillium alfalfae significantly affected net photosynthetic rate, stomatal conductance, chlorophyll content, MDA content, JA and SA concentrations, and NO and H2O2 contents in both WL343HQ and Dryland inoculated with Verticillium alfalfae. Most of the transcription factors in plants were classified in the WRKY, NAC and bHLH families. WGCNA analysis showed that the number of transcription factors related to plant growth and disease resistance was higher in the corresponding modules of WL343HQ disease groups on days 7 and 28 (WVa) and (WVd) than in the corresponding modules of Dryland disease groups on days 7 and 21 (HVa) and (HVc). These findings provide data for further gene function validation and also provide a reference for in-depth studies on interactions between plants and pathogens.