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Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
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Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
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Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula

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Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula
Journal Article

Identification of QTL affecting seed mineral concentrations and content in the model legume Medicago truncatula

2009
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Overview
Increasing the amount of bioavailable micronutrients such as iron and zinc in plant foods for human consumption is an international goal, intended especially for developing countries where micronutrient deficiencies are an ongoing health risk. Legume seeds have the potential to provide the essential nutrients required by humans, but concentrations of several minerals are low when compared to other foods. In order to increase seed mineral concentrations, it is important to understand the genes and processes involved in mineral distribution within the plant. The main objectives of this study were to use a Medicago truncatula recombinant inbred population (Jemalong-6 × DZA 315.16) to determine loci governing seed mineral concentrations, seed mineral content, and average seed weight, and to use these loci to propose candidate genes whose expression might contribute to these traits. Ninety-three lines in 2004 and 169 lines in 2006 were grown for seed harvest and subsequent analysis of seed Ca, Cu, Fe, K, Mg, Mn, P, and Zn concentrations and content. Quantitative trait loci (QTL) cartographer was used to identify QTL using composite interval mapping (CIM). CIM identified 46 QTL for seed mineral concentration, 26 for seed mineral content, and 3 for average seed weight. At least one QTL was detected for each mineral trait, and colocation of QTL for several minerals was found in both years. Results comparing seed weight with seed mineral concentration and content QTL demonstrate that seed size can be an important determinant of seed mineral concentration. The identification, in this model legume, of transgressive segregation for nearly all the minerals suggests that allelic recombination of relevant mineral-related genes in agronomic legumes could be a successful strategy to increase seed mineral concentrations above current levels.