ABSTRACT
BACKGROUND: The seedling stage has received little attention in maize breeding to identify genotypes tolerant to water deficit. The aim of this study is to evaluate incorporation of seed weight (expressed as hundred kernel weight, HKW) as a covariate into genomic association and prediction studies for three biomass traits in a panel of elite inbred lines challenged by water withholding at seedling stage. METHODS: 109 genotyped-by-sequencing (GBS) elite maize inbreds were phenotyped for HKW and planted in controlled conditions (16/8 day/night, 25 °C, 50% RH, 200 µMol/m2/s) in trays filled with soil. Plants in control (C) were watered every two days, while watering was stopped for 10 days in water withholding (WW). Fresh weight (FW), dry weight (DW), and dry matter content (DMC) were measured. RESULTS: Adding HKW as a covariate increased the power of detection of associations in FW and DW by 44% and increased genomic prediction accuracy in C and decreased in WW. CONCLUSIONS: Seed weight was effectively incorporated into association studies for biomass traits in maize seedlings, whereas the incorporation into genomic predictions, particularly in water-stressed plants, was not worthwhile.
ABSTRACT
Detecting genes that influence biofortification traits in cereal grain could help increase the concentrations of bioavailable mineral elements in crops to solve the global mineral malnutrition problem. The aims of this study were to detect the quantitative trait loci (QTLs) for phosphorus (P), iron (Fe), zinc (Zn), and magnesium (Mg) concentrations in maize grain in a mapping population, as well as QTLs for bioavailable Fe, Zn, and Mg, by precalculating their respective ratios with P. Elemental analysis of grain samples was done by coupled plasma-optical emission spectrometry in 294 F(4) lines of a biparental population taken from field trials of over 3 years. The population was mapped using sets of 121 polymorphic markers. QTL analysis revealed 32 significant QTLs detected for 7 traits, of which some were colocalized. The Additive-dominant model revealed highly significant additive effects, suggesting that biofortification traits in maize are generally controlled by numerous small-effect QTLs. Three QTLs for Fe/P, Zn/P, and Mg/P were colocalized on chromosome 3, coinciding with simple sequence repeats marker bnlg1456, which resides in close proximity to previously identified phytase genes (ZM phys1 and phys2). Thus, we recommend the ratios as bioavailability traits in biofortification research.
