Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.

Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissecting the Genetic Architecture of Mineral Compositions and Yield-Related Traits Under Different N Conditions in Maize

Semra Palali Delen, University of Nebraska - Lincoln


Micronutrients and macronutrients, although only required for small amounts in plants, have a profound impact on plant development and human health. However, the genetic architecture and molecular mechanisms in controlling micronutrient and macronutrient compositions in maize remain largely unclear. In the first chapter, I focus on two essential micronutrients, zinc (Zn) and iron (Fe), and a hazardous heavy metal, cadmium (Cd). I conducted a literature review to illustrate the assimilation, transport, and accumulation pathways for Zn, Fe, and Cd in various cereal crops. Because of the chemical similarities of Cd with Zn and Fe, and the shared molecular pathways, it is challenging to increase essential micronutrients Zn/Fe and reduce the Cd in the maize grain. In the second chapter, I presented a genetic study using the maize diversity panel and identified several trait-specific loci to break down the genetic linkage between toxic metal Cd and essential minerals Zn and Fe. In addition to the micronutrient, nitrogen (N) as an essential macronutrient, is important to achieve high yields under modern agriculture systems. However, extensive application of inorganic N fertilizers creates a series of environmental burdens. It is a long-standing goal to increase the N use efficiency in maize production. In the third chapter, I conducted a field experiment to understand the N response of six yield component traits. I phenotyped 230 diverse maize lines from the same population mentioned above under low N (LN) and high N (HN) field conditions for two years and analyzed the data using two complementary statistical approaches. Here, we focused not only on statistically significant SNPs estimated by GWAS but also on non-zero effect SNPs inferred from a Bayesian-based approach, GCTB (genome-wide complex trait Bayesian). These statistical approaches allow us to estimate complex genetic parameters such as field-based and SNP-based heritability, trait-associated SNPs and loci, polygenicity, and mode of selection. Our results showed that large-effect SNPs controlling for NR traits tend to be rare, likely because these rare SNPs were deleterious and, therefore, were maintained in low frequencies to increase the plant fitness in responding to different N conditions.

Subject Area

Plant sciences|Genetics|Bioinformatics

Recommended Citation

Delen, Semra Palali, "Dissecting the Genetic Architecture of Mineral Compositions and Yield-Related Traits Under Different N Conditions in Maize" (2022). ETD collection for University of Nebraska-Lincoln. AAI30000169.