4.4 Article

Genome-wide association mapping of iron homeostasis in the maize association population

Journal

BMC GENETICS
Volume 16, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/s12863-014-0153-0

Keywords

Fe-efficiency; Association mapping population; Fine-mapping; Genome-wide association; Marker assisted selection

Funding

  1. Deutsche Forschungsgemeinschaft [STI596/4-1, WI1728/16-1]
  2. Max Planck Society

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Background: Iron (Fe) deficiency in plants is the result of low Fe soil availability affecting 30% of cultivated soils worldwide. To improve our understanding on Fe-efficiency this study aimed to (i) evaluate the influence of two different Fe regimes on morphological and physiological trait formation, (ii) identify polymorphisms statistically associated with morphological and physiological traits, and (iii) dissect the correlation between morphological and physiological traits using an association mapping population. Results: The fine-mapping analyses on quantitative trait loci (QTL) confidence intervals of the intermated B73xMo17 (IBM) population provided a total of 13 and 2 single nucleotide polymorphisms (SNPs) under limited and adequate Fe regimes, respectively, which were significantly (FDR = 0.05) associated with cytochrome P450 94A1, invertase beta-fructofuranosidase insoluble isoenzyme 6, and a low-temperature-induced 65 kDa protein. The genome-wide association (GWA) analyses under limited and adequate Fe regimes provided in total 18 and 17 significant SNPs, respectively. Conclusions: Significantly associated SNPs on a genome-wide level under both Fe regimes for the traits leaf necrosis (NEC), root weight (RW), shoot dry weight (SDW), water (H2O), and SPAD value of leaf 3 (SP3) were located in genes or recognition sites of transcriptional regulators, which indicates a direct impact on the phenotype. SNPs which were significantly associated on a genome-wide level under both Fe regimes with the traits NEC, RW, SDW, H2O, and SP3 might be attractive targets for marker assisted selection as well as interesting objects for future functional analyses.

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