A rapid approach to investigate spatiotemporal distribution of phytohormones in rice. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Cai, Wen-Jing; Ye, Tian-Tian; Wang, Qing; Cai, Bao-Dong; Feng, Yu-Qi
• Is Part Of: Plant methods. Volume 12:Issue 1(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-12
• Subjects: UPLC–MS/MS -- Phytohormones -- Spatiotemporal distribution -- Rice; Botany -- Methodology -- Periodicals; 572.2
• DOI: 10.1186/s13007-016-0147-1
• Languages: English
• ISSNs: 1746-4811

Abstract

Abstract Background Phytohormones play crucial roles in almost all stages of plant growth and development. Accurate and simultaneous determination of multiple phytohormones enabled us to better understand the physiological functions and the regulatory networks of phytohormones. However, simultaneous determination of multiple phytohormones in plant is still a challenge due to their low concentrations, structural and chemical diversity, and complex matrix of plant tissues. Therefore, development of a simple and selective method for the simultaneous determination of multiple phytohormones is highly needed. Results We developed a clean-up strategy for profiling of multiple phytohormones, which can overcome the challenge of structural and chemical diversity. By using a one-step dispersive solid-phase extraction (DSPE) combined with UPLC–MS/MS, 54 phytohormones including auxins, ABA, SA, JA, GAs and CKs were simultaneously analyzed from a single rice sample extract. Using the developed method, we investigated the spatiotemporal distribution of phytohormones in rice. The profiling of various tissues of rice at different growth stages revealed the complexity of metabolic regulation and allocations of phytohormone species. Conclusion A rapid one-step method was developed for the simultaneous analysis of six groups of phytohormones, including cytokinins, auxins, salicylic acid, jasmonates, abscisic acid and gibberellins in a single run, using UPLC–ESI–MS/MS. The proposed method was successfully applied to investigate spatiotemporal distribution of multiple phytohormones in rice. The spatiotemporal information obtained may be helpful for better understanding of phytohormones functions throughout life cycle of rice when integrated into transcriptome and other omics data.