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- W2892854172 abstract "Abstract Saline-alkaline stress is one of the primary abiotic stresses that limits crop yields worldwide. The early seedling stage of plants is the most vulnerable stage to stress conditions. In this study, the physiological and phenotypic changes induced by alkali treatments (Na2CO3 and NaHCO3 mixtures) were analyzed for alfalfa (Medicago sativa L. cv. Zhongmu-3) and barrel medic (Medicago truncatula line R108) seedlings. As expected, Zhongmu-3, which is alkali tolerant, and R108, which is alkali sensitive, responded differently to alkaline stress. To characterize the protein expression profiles of these two Medicago species in response to alkaline stress, an iTRAQ-based quantitative proteomic analysis was applied to detect alkali-responsive proteins. A total of 467 differentially changed alkali-responsive proteins were identified from Zhongmu-3 and R108. Compared with their levels in untreated control seedlings, the abundance of 349 proteins increased and 38 proteins decreased in alkali-treated Zhongmu-3 seedlings, whereas 142 proteins increased and 35 proteins decreased in R108 seedlings. Zhongmu-3 and R108 shared 97 common differentially changed proteins, but a large percentage of them showed different change patterns between Zhongmu-3 and R108. Subsequent functional annotation indicated these proteins influenced diverse processes, such as catalytic activity, signaling, and antioxidant activity. The transcript levels of genes encoding 10 differentially changed proteins were determined by quantitative PCR. The data provide new insights into the regulatory mechanisms responsible for alkali stress responses in leguminous plants and have potential implications for breeding of alkaline-resistant alfalfa and other crops." @default.
- W2892854172 created "2018-10-05" @default.
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- W2892854172 date "2019-01-01" @default.
- W2892854172 modified "2023-09-26" @default.
- W2892854172 title "Identification of alkali-responsive proteins from early seedling stage of two contrasting Medicago species by iTRAQ-based quantitative proteomic analysis" @default.
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- W2892854172 doi "https://doi.org/10.1016/j.envexpbot.2018.09.021" @default.
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