Literature DB >> 30611782

Comprehensive metabolomic and proteomic analysis in biochemical metabolic pathways of rice spikes under drought and submergence stress.

Qiangqiang Xiong1, Chaohao Cao1, Tianhua Shen1, Lei Zhong1, HaoHua He2, Xiaorong Chen3.   

Abstract

Drought and submergence are the main adverse factors affecting plant growth and yield formation in parts of China, especially in the Yangtze River region. In this study, T1 (drought duration: 10 d), T2 (submergence duration: 8 d) and CK (control) treatments were applied. This work aimed to study the changes in metabolic pathways of rice under drought and submergence stress during the panicle differentiation stage. The identification and analysis of differential metabolites and differentially expressed proteins functions indicate that drought and submergence mainly promoted the energy metabolism pathway, carbon fixation in photosynthetic organism pathway, carbohydrate metabolic process, and reactive oxygen species (ROS) metabolic process functions. Under drought stress, the inhibition of photosynthetic rate is mainly through stomatal conductance restriction, and flavonoid pathway regulates the metabolic process of ROS. Under submergence stress, the electron transfer chain was destroyed to inhibit the photosynthetic rate, and the antioxidant system was activated to regulate the metabolism of ROS. The changes in related enzymes or proteins in metabolic regulatory networks are analyzed, which will be conducive to understanding the response mechanism of rice drought and submergence more deeply and provide a scientific basis for rice drought and submergence prevention and mitigation, and the breeding of drought- and submergence-resistant varieties.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Drought; Metabolic pathways; Metabolome; Proteome; Rice (Oryza sativa L.); Submergence

Mesh:

Substances:

Year:  2019        PMID: 30611782     DOI: 10.1016/j.bbapap.2019.01.001

Source DB:  PubMed          Journal:  Biochim Biophys Acta Proteins Proteom        ISSN: 1570-9639            Impact factor:   3.036


  9 in total

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Journal:  Front Plant Sci       Date:  2022-01-27       Impact factor: 5.753

4.  Poplar's Waterlogging Resistance Modeling and Evaluating: Exploring and Perfecting the Feasibility of Machine Learning Methods in Plant Science.

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Review 7.  Review: Proteomic Techniques for the Development of Flood-Tolerant Soybean.

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Journal:  Int J Mol Sci       Date:  2020-10-12       Impact factor: 5.923

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Authors:  Yaqiong Wu; Tongli Wang; Yue Xin; Guibin Wang; Li-An Xu
Journal:  Molecules       Date:  2020-10-20       Impact factor: 4.411

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Authors:  Zhilin Zhou; Jun Tang; Qinghe Cao; Zongyun Li; Daifu Ma
Journal:  PLoS One       Date:  2022-03-10       Impact factor: 3.240

  9 in total

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