Ionomic Profiling of Rice Genotypes and Identification of Varieties with Elemental Covariation Effects |
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| Authors: | Zhang Chengming Nobuhiro Tanaka Maria Stefanie Dwiyanti Matthew Shenton Hayato Maruyama Takuro Shinano Chu Qingnan Xie Jun Toshihiro Watanabe |
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| Institution: | 1.Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589, Japan;2.Institute of Crop Science, National Agriculture and Food Research Organization, Tsukuba 305-8518, Japan;3.Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan;4.College of Resources and Environment, Southwest University, Chongqing 400715, China |
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| Abstract: | Ionomic profiles are primarily influenced by genetic and environmental factors. Identifying ionomic responses to varietal effects is necessary to understand the ionomic variations among species or subspecies and to potentially understand genetic effects on ionomic profiles. We cultivated 120 rice (Oryza sativa) varieties to seedling stage in identical hydroponic conditions and determined the concentrations of 26 elements (including 3 anions) in the shoots and roots of rice. Although the subspecies effects were limited by the genus Oryza pre-framework and its elemental chemical properties, we found significant differences in ionomic variations in most elements among the aus, indica and japonica subspecies. Principal component analysis of the correlations indicated that variations in the root-to-shoot ionomic transport mechanisms were the main causes of ionomic differences among the subspecies. Furthermore, the correlations were primarily associated with the screening of varieties for elemental covariation effects that can facilitate breeding biofortified rice varieties with safe concentrations of otherwise toxic elements. The japonica subspecies exhibited the strongest elemental correlations and elemental covariation effects, therefore, they showed greater advantages for biofortification than the indica and aus subspecies, whereas indica and aus subspecies were likely safer in metal(loid) polluted soils. We also found that geographical and historical distribution significantly defined the ionomic profiles. Overall, the results of this study provided a reference for further association studies to improve the nutritional status and minimize toxicity risks in rice production. |
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| Keywords: | Ionomic profile Rice genotype Elemental covariation Correlation Principal component analysis |
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