|KANDIANIS, CATHERINE - Children'S Nutrition Research Center (CNRC)|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/15/2012
Publication Date: 6/17/2012
Citation: Kandianis, C.B., Yan, W., Grusak, M.A. 2012. Genome wide search for variation associated with micronutrient density of developing rice grains [abstract]. Proceedings, XVI International Symposium on Iron Nutrition and Interactions in Plants, June 17-21, 2012, Amherst, Massachusetts. p. 108.
Technical Abstract: “Omic” tools are rapidly being employed to delineate the biological framework controlling phenotypes of interest in crop species. An advanced understanding of the genetic basis for quantitative trait variation has been made possible through genome wide association studies (GWAS) that make use of genomic data sampled from geographically diverse and genotypically rich germplasm collections. In the present study, 195 genotypically diverse inbred lines (Oryza spp.) from the USDA Rice Minicore Collection were employed to identify quantitative trait loci (QTL) associated with variation in grain mineral density; for this presentation, we focus specifically on Fe, Zn, and Mg content and concentration. Because grain mineral density arises from the integration of many temporal and spatial processes, we assessed two seed mineral phenotypes: (1) cumulative mineral concentration and/or content determined at seed maturity (harvest endpoint); and (2) the temporal profile of seed mineral accumulation during the grain filling period. Quantitative variation in cumulative grain Fe, Zn, and Mg content and concentration mapped to relatively few, strong effect loci of unknown and possibly novel biological function. Several mineral density QTL were found to co-localize with seed biomass QTL, suggesting that the regulation of source-sink dynamics contributing to seed growth could be of similar importance in controlling the dynamics of micronutrient accumulation in grains during seed fill. We employed non-linear modeling of mineral and seed biomass data from a developmental time-course to estimate genotype-specific model parameters representing rate and duration of seed biomass and seed mineral accumulation. Reliable parameter estimates were obtained, representing a wide range of mineral or biomass accumulation rates and duration across genotypes. We report the results of GWAS with these developmental phenotypes, compare QTL identified in cumulative versus developmental analyses, and discuss implications of the dependence of seed mineral density on seed biomass.