Comparative response of SOD in different plants against cadmium and drought stress at the molecular level

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Xiao-Zhang Yu, Li Yang, Yu-Xi Feng

Abstract


Abiotic stress like drought and heavy metal imposes a negative impact on exposed plants’ growth and development, commences over production of reactive oxygen species (ROS) inside plant cells resulting in oxidative stress at the cellular level. After that, plants activate multiple defense mechanisms, within which the superoxide dismutase (SOD) family acts as the first line of defense to eliminate ROS. From the literature, it is evident that fewer studies have been carried out in combination with molecular evolution and phylogenetics, and expression profile of the SOD genes amidst dicot and the monocot at subcellular level against drought stress and cadmium (Cd) metal exposure. In the present study, SOD isogenes are identified in purposely elected two dicot plants i.e. Arabidopsis thaliana (9 genes), Solanum lycopersicum (8 genes) and two monocot plants namely Triticum aestivum (11 genes), and Oryza sativa (7 genes), respectively. Based on the amino acids sequence similarities, the identified proteins are classified into three subfamilies in accordance to their phylogenetic relationships, namely Cu/ZnSOD, FeSOD, and MnSOD. High variability observed between Cu/ZnSOD with other two groups i.e. FeSOD and MnSOD which showed lesser variation within them by using secondary structure predication. Subcellular localization suggested that genes encoding FeSOD, MnSOD and Cu/ZnSOD are predominant in chloroplasts, mitochondria, and cytoplasm, respectively in studied plants. The expression profiling through microarray analysis showed varied strategies of SOD isogenes against drought stress and Cd exposure individually. From the perspective of evolution, this study would expand our knowledge for vividly understanding the role of distinctive SOD isogenes in detoxifying ROS in different plants under various abiotic stresses.


Keywords


plants, superoxide dismutase, ROS, abiotic stress, bioinformatic analysis

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References


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DOI: http://dx.doi.org/10.26789/AEB.2020.01.003

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