Physiological and Transcriptomic Insights Into Adaptive Responses of Seriphidium transiliense Seedlings to Drought Stress

2021 
Abstract Drought is the most challenging environmental stress factor for grassland ecosystems as the climate change. Seriphidium transiliense, a typical plant in the desert steppe, is widely distributed in northern Xinjiang Region of China. In this study, we analyzed the phenotypic traits, physiological responses, and transcriptional changes in the leaves and roots of S. transiliense, exposed to different levels of drought stress. The morphology of the aboveground and underground portions of S. transiliense changed significantly under drought stress. Additionally, the antioxidants activity and content in leaves and roots increased dramatically. Based on the weighted gene co-expression network analysis (WGCNA) method, we performed a correlation analysis between physiological traits and differentially expressed genes (DEGs) to characterize the key genes and regulatory pathways involved in drought resistance in S. transiliense. A total of 135 and 120 DEGs associated with drought resistance were identified in leaves and roots, respectively. These genes included 38 responsive TFs belonged to WRKY, AP2/ERF, C2H2, bHLH, MYB, bZIP, NAC, LEA, MADS, and GRAS families that play critical roles in plant responses to abiotic stresses. Furthermore, many receptor protein kinase encoding genes including CBL, CIPK, LRR-RLK, CRK, PI3K, CML, and PP2C involved in the stress signaling responses such as ABA signaling pathway, MAPK signaling pathway, and Ca2+ signal transduction, were significantly upregulated under different levels of drought stresses. Moreover, more responsive genes participated in multiple carbohydrate metabolic pathways in roots. Our study provided new insights into the regulatory mechanism of the acclimation responses to drought stress in S. transiliense and suggested that these genes may be used in molecular breeding to develop new varieties tolerant to drought stress.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    76
    References
    0
    Citations
    NaN
    KQI
    []