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Title: Stability analysis of kernel quality traits in exotic-derived doubled haploid maize lines

Author
item VANOUS, ADAM - Iowa State University
item Gardner, Candice
item BLANCO, MICHAEL - Retired ARS Employee
item MARTIN-SCHWARZE, ADAM - Iowa State University
item WANG, JINYU - Iowa State University
item LI, XIANRAN - Iowa State University
item LIPKA, ALEXANDER - Iowa State University
item Flint-Garcia, Sherry
item BOHN, MARTIN - University Of Illinois
item Edwards, Jode
item LÜBBERSTEDT, THOMAS - Iowa State University

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/15/2018
Publication Date: 11/21/2018
Citation: Vanous, A., Gardner, C.A., Blanco, M., Martin-Schwarze, A., Wang, J., Li, X., Lipka, A.E., Flint Garcia, S.A., Bohn, M., Edwards, J.W., Lübberstedt, T. 2018. Stability analysis of kernel quality traits in exotic-derived doubled haploid maize lines. The Plant Genome. 12(1). https://doi.org/10.3835/plantgenome2017.12.0114.
DOI: https://doi.org/10.3835/plantgenome2017.12.0114

Interpretive Summary: Understanding maize (Zea mays) kernel composition is of increasing importance with the need to support the growing world population and greater industrial demands, such as using maize starch for biofuels. The main components that can be altered in the maize kernel are oil, protein, starch, and density. Oil resides chiefly in the embryo of the kernel, which starch is located in the endosperm. Insufficient understanding of the underlying genetic architecture of these kernel composition traits creates difficulty in manipulating them to achieve breeding goals. Double haploid lines are useful for genetic studies because they are 100% inbred and therefore genetically uniform. In this study, we used a diverse panel of doubled haploid lines derived from crosses of temperate and tropical (exotic) maize germmplasm, harvested seed from open-pollinated ears, and used Near Infrared Spectroscopy (NIRS) to analyze oil, starch, and protein content, as well as density of each sample. The same lines were genotyped using Genotyping by Sequencing (GBS) technology to obtain molecular information called SNPs (single nucleotide polymorphisms). The NIR data and SNP data was used in combination with multiple genome-wide association statistical analysis approaches to further explain the underlying genetic causes that affect kernel composition. Significant associations were discovered for all traits, with several coinciding with previously identified regions that correspond to 14 candidate genes. This study's findings aid in validating previously identified genomic regions and identified novel genomic regions effecting kernel composition traits.

Technical Abstract: Understanding maize (Zea mays) kernel composition is of increasing importance with the need to support the growing world population and greater industrial demands, such as using maize starch for biofuels. The main components that can be altered in the maize kernel are oil, protein, starch, and density; however, insufficient understanding of underlying genetic architecture creates difficulty in manipulating these kernel composition traits. In this study, we used a diverse panel of exotic derived doubled haploid lines, in conjunction with genome-wide association analysis to further explain the underlying genetic causes affecting kernel composition. Significant associations were discovered for all traits, with several coinciding with previously identified regions, corresponding to 14 candidate genes. The findings within this study aid in validating previously identified genomic regions and identified novel genomic regions effecting kernel composition traits.