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Title:Genomic improvement of nitrogen utilization efficiency in maize
Author(s):Bubert, Jessica Marie
Director of Research:Moose, Stephen P
Doctoral Committee Chair(s):Moose, Stephen P
Doctoral Committee Member(s):Rayburn, A. Lane; Studer, Anthony; Tiffany, Jamann
Department / Program:Crop Sciences
Discipline:Crop Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Maize
Nitrogen
Nitrogen Use Efficiency
Nitrogen Utilization Efficiency
Genomic Selection
Genetics
Heterozygosity
Abstract:As available land for agricultural production has stabilized, farmers rely on fertilizer application rates to boost yields. Consequently, nitrogen (N) use in the United States has increased nearly six fold in the last fifty years to more than 13 million tons applied in 2014, an increase that mirrors worldwide trends. The production of N fertilizer is dependent on energy inputs to convert atmospheric dinitrogen to a form useable by plants, so as energy prices continue to climb the cost of N fertilizers will increase accordingly. Additionally, the detrimental environmental effects on water and air quality of nitrogen losses from denitrification, volatilization, and leaching are well documented. As such, improvements to nitrogen use efficiency (NUE) is an important target for future maize breeding efforts. The objectives of this research were to assess existing phenotypic and genotypic variation for NUE related traits, and leverage that variation to understand and improve hybrid performance. Historical and elite germplasm were grown as inbreds and hybrids in highly managed multi-year field trials under varying rates of applied nitrogen. Preliminary results supported previous research demonstrating N uptake efficiency may already be optimized, but there are opportunities to improve N utilization efficiency (NUtE). Field based trials were subjected to a phenotyping pipeline that estimates N utilization as a ratio of total biomass to total plant N. Measuring total NUtE on both hybrids and their inbred parents effectively controls for the impacts of relative maturity and heterosis on this trait. The results of this research indicate that available soil N in this geographical region is typically sufficient for inbreds to reach sink capacity, thereby limiting nitrogen response to supplemental N in inbreds. The lack of N response in inbreds indicates that making selections for NUtE in inbreds per se will not result in efficient genetic gain. Hybrids showed a consistent N response but do have a significant tester effect, so future research to understand the genetic mechanisms of heterosis is necessary in order to account for the hybrid combinations used in NUtE trials. The diversity that was identified through field testing and NUtE phenotyping was sufficient to support the use of genomic tools to increase NUtE in maize. Among many quantitative trait loci (QTL) detected in a prior genetic mapping experiment, nine robust intervals were determined to account for 5-15% of variation for multiple nitrogen utilization traits across years. The contribution of these previously identified QTL to NUtE among diverse maize hybrids was assessed using a genome-wide association study. Three of the nine QTL had significant marker-trait associations within their boundaries and an additional 12-24 significant SNPs were identified for NUtE related traits that may provide additional genes of interest that were not captured by the IBM mapping population used for QTL analysis. A genomic prediction approach was used to capture small genetic effects across the genome. Within year prediction accuracies for genomic prediction of grain nitrogen were 0.5 when the training population is 30% of the total population, while between-year accuracies with a one year training set were 0.28. Between year genomic predictions of hybrids using inbred data as a training set were 0.37 and 0.49 for NUtE and grain biomass, respectively. Similar to predictions of hybrid performance from inbred phenotypes, the ability to predict hybrid performance from inbred genotypes could be improved with a better understanding of the genetic mechanisms underlying heterosis. Including multi-year phenotypes in the training set and expanding the model beyond just additive effects could also significantly improve prediction accuracies in the future. It has long been known that heterosis is related to the degree of heterozygosity in a hybrid and recent advances in genome-scale genotyping enable detailed estimates of heterozygosity. Thus, in an effort to understand the genetic mechanisms underlying heterosis and how they impact complex traits, we conducted an experiment to investigate the influence of heterozygosity on nitrogen utilization efficiency and its component traits. Analysis of single nucleotide polymorphism (SNP) markers in more than 400 maize genes enriched for regulatory functions and control of N utilization showed divergent selection among the major germplasm groups for temperate maize production, indicating that heterozygosity is a preferred breeding goal to maximize N utilization and yield. In order to further test this preference, populations were created to maximize heterozygosity at three different levels: across the whole genome, within the previously known nine QTL regions, and at the SNP locations within the QTL that are also divergent between heterotic groups. Field testing of the populations for NUtE related traits indicated that heterozygosity is a preferred germplasm state for hybrid performance for grain biomass, stover biomass, and grain N. Additionally, selection for heterozygosity on a limited number of informed SNP markers can provide the same level of heterosis as selecting across the entire genome. This understanding of the importance of heterozygosity will be useful in guiding the selection of inbred parents to create future hybrids with better NUtE.
Issue Date:2018-12-05
Type:Thesis
URI:http://hdl.handle.net/2142/102942
Rights Information:Copyright 2018 Jessica Bubert
Date Available in IDEALS:2019-02-08
Date Deposited:2018-12


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