Proteomic Analysis of Rapeseed Root Response to Waterlogging Stress.

ABSTRACT

The overall health of a plant is constantly affected by the changing and hostile environment. Due to climate change and the farming pattern of rice (Oryza sativa) and rapeseed (Brassica napus L.), stress from waterlogging poses a serious threat to productivity assurance and the yield of rapeseed in China's Yangtze River basin. In order to improve our understanding of the complex mechanisms behind waterlogging stress and identify waterlogging-responsive proteins, we firstly conducted iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomic analysis of rapeseed roots under waterlogging treatments, for both a tolerant cultivar ZS9 and sensitive cultivar GH01. A total of 7736 proteins were identified by iTRAQ, of which several hundred showed different expression levels, including 233, 365, and 326 after waterlogging stress for 4H, 8H, and 12H in ZS9, respectively, and 143, 175, and 374 after waterlogging stress for 4H, 8H, and 12H in GH01, respectively. For proteins repeatedly identified at different time points, gene ontology (GO) cluster analysis suggested that the responsive proteins of the two cultivars were both enriched in the biological process of DNA-dependent transcription and the oxidation⁻reduction process, and response to various stress and hormone stimulus, while different distribution frequencies in the two cultivars was investigated. Moreover, overlap proteins with similar or opposite tendencies of fold change between ZS9 and GH01 were observed and clustered based on the different expression ratios, suggesting the two genotype cultivars exhibited diversiform molecular mechanisms or regulation pathways in their waterlogging stress response. The following qRT-PCR (quantitative real-time polymerase chain reaction) results verified the candidate proteins at transcription levels, which were prepared for further research. In conclusion, proteins detected in this study might perform different functions in waterlogging responses and would provide information conducive to better understanding adaptive mechanisms under environmental stresses.