To identify the key barrier parts and relevant elements during Cd/As transport into brown rice, 16 elements were measured in 14 different parts of 21 rice genotypes; moreover, transcriptomic of different nodes was analyzed. Cd/As contents in root and nodes were significantly higher than those other parts. Node I had the highest Cd content among nodes, leading an increase in gene expressions involved in glycolytic and Cd detoxification. The Cu/Zn/Co distribution and transport to various parts was similar to that of Cd, and Fe/Sb distribution and transport to various parts was similar to that of As. Moreover, Cu/Zn/Co/Mg was correlated with Cd in root and nodes, as well as Fe with As. Besides, the ionomic profile showed the different parts of an organ were closely related, and the spatial distribution of different organs was consistent with the growth morphology of rice. Therefore, root and nodes are two key barriers to Cd/As transport into brown rice. Moreover, Node I has the highest Cd accumulation capacities among nodes. The ionomic profile reflects relationships among plant parts and correlations between the elements, suggesting that nodes are hubs for element distribution, as well as the correlation between Cd with Zn/Cu/Co/Mg, between Fe with As.
Selenium (Se) is an important trace element that mainly occurs in the form of selenocysteine in selected proteins. In prokaryotes, Se is also required for the synthesis of selenouridine and Se-containing cofactor. A large number of selenoprotein families have been identified in diverse prokaryotic organisms, most of which are thought to be involved in various redox reactions. In the last decade or two, computational prediction of selenoprotein genes and comparative genomics of Se metabolic pathways and selenoproteomes have arisen, providing new insights into the metabolism and function of Se and their evolutionary trends in bacteria and archaea. This review aims to offer an overview of recent advances in bioinformatics analysis of Se utilization in prokaryotes. We describe current computational strategies for the identification of selenoprotein genes and generate the most comprehensive list of prokaryotic selenoproteins reported to date. Furthermore, we highlight the latest research progress in comparative genomics and metagenomics of Se utilization in prokaryotes, which demonstrates the divergent and dynamic evolutionary patterns of different Se metabolic pathways, selenoprotein families, and selenoproteomes in sequenced organisms and environmental samples. Overall, bioinformatics analyses of Se utilization, function, and evolution may contribute to a systematic understanding of how this micronutrient is used in nature.
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