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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #204137

Title: Genetic and physiological analysis of iron content and bioavailability in maize kernels

item LUNG'AHO, MERCY - Cornell University
item MWANIKI, ANGELA - Cornell University
item Szalma, Stephen
item HART, JONATHAN - Cornell University
item RUTZKE, MICHAEL - Cornell University
item Kochian, Leon
item Glahn, Raymond
item Hoekenga, Owen

Submitted to: PLOS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/20/2011
Publication Date: 6/8/2011
Citation: Lung'Aho, M., Mwaniki, A., Szalma, S.J., Hart, J., Rutzke, M., Kochian, L.V., Glahn, R.P., Hoekenga, O. 2011. Genetic and physiological analysis of iron content and bioavailability in maize kernels. PLoS One. 6(6):e20429. DOI:10.1371/journal.pone.0020429.

Interpretive Summary: Iron deficiency is a worldwide problem that is directly correlated with poverty and food insecurity. Approximately 1/3 of the world’s population suffers from Fe deficiency-induced anemia, 80 percent of which are in developing countries. In developing countries, intervention strategies aimed alleviating micronutrient deficiencies are often too expensive and difficult to sustain. About 75 percent of the world’s poor households live in rural areas and the majority is small-scale farmers. The resource-poor typically consume what they grow and are dependent upon a small number of staple crops for the vast majority of their nutrition, including Fe. Hence there is considerable interest in agricultural approaches that improve Fe content and bioavailability in staple food crops. In this study, we used a statistical genetics approach known as quantitative trait loci (QTL) analysis with a set of corn varieties to identify regions of the corn genome associated with altered (up or down) corn seed Fe content and bioavailability. Fe bioavailability was determined by using an in vitro system that mimics the human intestine, based on a unique intestinal cell line (Caco2 cells). Using this approach, we identified three discrete regions of the corn genome associated with increased seed Fe bioavailability and three other regions associated with increased seed Fe content. This work sets the stage for subsequent genomics and biochemical research aimed at identifying the compounds in the seed influencing Fe bioavailability, and the genes underlying increased seed Fe bioavailability and content.

Technical Abstract: Maize is a major cereal crop widely consumed in developing countries, which have a high prevalence of iron (Fe) deficiency including anemia. The major cause of Fe deficiency in these countries is inadequate intake of bioavailable Fe, of which poverty is a major contributing factor. Therefore, biofortification of maize has great potential to alleviate this deficiency. Maize is also a model system for genetic and genomic research and thus allows the opportunity for gene discovery. Here we describe an integrated genetic and physiological analysis of Fe nutrition in maize kernels, to determine the genes and molecular processes that influence seed Fe content and bioavailability. Quantitative trait locus (QTL) analysis was used to dissect seed Fe concentration (FeSC) and Fe bioavailability (FeSB) from the Intermated B73 x Mo17 (IBM) recombinant inbred (RI) set of maize. FeSB was determined by an in vitro digestion/Caco-2 cell line bioassay. Loci associated with increased Fe bioavailability were identified on chromosomes 3, 6 and 9 while those associated with increased seed Fe content were identified on chromosomes 1, 2 and 5. Models obtained explained ~25% of the variance in Fe bioavailability and ~20% of the variance in seed Fe content. Seed Fe concentration was not correlated with Fe bioavailability. Iron bioavailability was also not correlated with the levels of seed phytate, as estimated by testing RI at the extremes of the observed Fe bioavailability. Comparative genomic analysis identified several candidate genes for each of the observed QTL, which will be briefly discussed.