1. Metabolomic Assessment of Key Maize Resources: GC-MS and NMR Profiling of Grain from B73 Hybrids of the Nested Association Mapping (NAM) Founders and of Geographically Diverse Landraces.
- Author
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Venkatesh TV, Chassy AW, Fiehn O, Flint-Garcia S, Zeng Q, Skogerson K, and Harrigan GG
- Subjects
- Alleles, Genetic Variation, Genotype, Geography, Seeds classification, Seeds genetics, Seeds metabolism, Zea mays classification, Zea mays genetics, Zea mays metabolism, Gas Chromatography-Mass Spectrometry methods, Magnetic Resonance Imaging methods, Metabolomics methods, Seeds chemistry, Zea mays chemistry
- Abstract
The present study expands metabolomic assessments of maize beyond commercial lines to include two sets of hybrids used extensively in the scientific community. One set included hybrids derived from the nested association mapping (NAM) founder lines, a collection of 25 inbreds selected on the basis of genetic diversity and used to investigate the genetic basis of complex plant traits. A second set included 24 hybrids derived from a collection of landraces representative of native diversity from North and South America that may serve as a source of new alleles for improving modern maize hybrids. Metabolomic analysis of grain harvested from these hybrids utilized gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) and (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) techniques. Results highlighted extensive metabolomic variation in grain from both hybrid sets, but also demonstrated that, within each hybrid set, subpopulations could be differentiated in a pattern consistent with the known genetic and compositional variation of these lines. Correlation analysis did not indicate a strong association of the metabolomic data with grain nutrient composition, although some metabolites did show moderately strong correlations with agronomic features such as plant and ear height. Overall, this study provides insights into the extensive metabolomic diversity associated with conventional maize germplasm.
- Published
- 2016
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