Here I present three studies on the characterization and utilization of historical maize (Zea maize L.) inbreds for genomewide association mapping. In the first study, I characterized a collection of 284 maize inbreds, most of which were developed by the University of Minnesota between the 1910s and 1980s. My objective was to relate these inbreds to known heterotic patterns and identify unique groups of inbreds, if any, represented by the Minnesota germplasm. The inbreds were genotyped with 56,110 single nucleotide polymorphism markers. Model-based clustering identified five subpopulations, with the A321 subpopulation containing more than 60% of the Minnesota inbreds, some of which formed groups unique to the Minnesota inbreds. In the second study, I investigated the influence of the xenia effect on the evaluation of maize inbreds for kernel composition. My objective was to determine the influence of xenia on kernel composition traits among self- and open-pollinated plots of inbreds that were unadjusted and spatially and temporally adjusted. Pollination treatment was not significant for any kernel composition trait and simple and rank correlations were high between self- and open-pollinated treatments indicating that kernel oil, protein, and starch can be evaluated in open-pollinated plots without confounding differences among entries. In the third study, association mapping was used to identify major quantitative trait loci (QTL) for less-complex traits using historical inbreds. My objectives were to (i) characterize genomewide linkage disequilibrium and (ii) assess variation and map QTL for flowering time, kernel composition, and resistance to northern corn leaf blight (caused by Setosphaeria turcica) and Goss` wilt and blight (caused by Clavibacter michiganensis sups. nebraskensis). Linkage disequilibrium was high among all pairwise marker combinations and among adjacent markers. The A321 subpopulation had inbreds with either or both the minimum and maximum inbred mean value for all traits except protein concentration. I identified 54 QTL across six traits, which accounted for 24% to 61% of the phenotypic variation for a given trait. To my knowledge, this was the first attempt to utilize high-density markers and association mapping to mine QTL among historical maize inbreds.
University of Minnesota Ph.D. dissertation. February 2013. Major; Applied plant science. Advisor: Rex Bernardo. 1 computer file (PDF);
vii, 129 pages, appendix p. 81-129.
Schaefer, Christopher Michael.
Historical Minnesota maize inbreds: relatedness, diversity and marker associations for flowering time, kernel composition and disease resistance.
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