G3 Genes Genomes GeneticsGeneticsPeer-reviewed journal article
Genome-wide association study suggests an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels
Matheus BaseggioiD, Matthew Murray, Di WuiD, Greg ZiegleriD, Nicholas S. Kaczmar, James Chamness, John P. HamiltoniD, C. Robin BuelliD, Olena K. VatamaniukiD, Edward S. BuckleriD, Margaret Elizabeth SmithiD, Ivan R. BaxteriD, William F. TracyiD, Michael A. GoreiD
Abstract
Despite being one of the most consumed vegetables in the United States, the elemental profile of sweet corn (Zea mays L.) is limited in its dietary contributions. To address this through genetic improvement, a genome-wide association study was conducted for the concentrations of 15 elements in fresh kernels of a sweet corn association panel. In concordance with mapping results from mature maize kernels, we detected a probable pleiotropic association of zinc and iron concentrations with nicotianamine synthase5 (nas5), which purportedly encodes an enzyme involved in synthesis of the metal chelator nicotianamine. Additionally, a pervasive association signal was identified for cadmium concentration within a recombination suppressed region on chromosome 2. The likely causal gene underlying this signal was heavy metal ATPase3 (hma3), whose counterpart in rice, OsHMA3, mediates vacuolar sequestration of cadmium and zinc in roots, whereby regulating zinc homeostasis and cadmium accumulation in grains. In our association panel, hma3 associated with cadmium but not zinc accumulation in fresh kernels. This finding implies that selection for low cadmium will not affect zinc levels in fresh kernels. Although less resolved association signals were detected for boron, nickel, and calcium, all 15 elements were shown to have moderate predictive abilities via whole-genome prediction. Collectively, these results help enhance our genomics-assisted breeding efforts centered on improving the elemental profile of fresh sweet corn kernels.
- organism: zebrafish
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 17
- FWCI
- 1.27
- Field percentile
- top 22%
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