Document Type

Dissertation - Open Access

Award Date

2021

Degree Name

Doctor of Philosophy (PhD)

Department

Agronomy, Horticulture, and Plant Science

First Advisor

Sunish Sehgal

Keywords

Disease resistance, Fine mapping, Genomic selection, GWAS, Wheat landrace, Wheat yield

Abstract

A steady increase in wheat yield is vital to feed the continuously rising world population. Systematic exploitation of wheat germplasm and a better understanding of the underlying genetic control could be pivotal in accelerating the genetic gain for yield and disease management. Various modern techniques such as genome-wide association study (GWAS), genomic selection (GS), fine mapping, and cloning can expedite wheat improvement and broaden our understanding of the complex wheat genome. In the first objective of this study, we evaluated the Watkins core set of 121 landrace cultivars (LCs) to identify novel sources of resistance against the tan spot, Stagonospora nodorum blotch (SNB), and Fusarium Head Blight (FHB). The phenotypic evaluation identified 13 LCs with multiple resistance to tan spot and SNB, while five other LCs were found to be a potential source for FHB resistance. A total of 30 significant marker-trait associations (MTAs) were identified in a GWAS for response to tan spot and SNB. In the second objective, we performed GWAS in a panel of 297 hard red winter wheat lines from the US Great Plains region to identify QTLs for various spike and kernel-related traits and evaluated the prediction accuracy (PA) of GS models for these traits. Most of the MTAs (47) were identified for spike-related traits, where 16, 15, 11, and 5 MTAs were identified for spike length, spikelet per spike, spike density, and kernel per spike, respectively, while only 6 MTAs were identified for three kernel-related traits (kernel weight, kernel area, and thousand kernel weight). Fourteen MTAs were identified at two or more individual environments were considered stable QTLs. Univariate genomic selection (GS) models like genomic best linear unbiased prediction (GBLUP) were compared with multivariate models like Bayesian multi-trait multi-environment (BMTME) and we found that the multi-trait model (BMTME) outperformed the singletrait model (GBLUP) in terms of PA. In the last objective, we developed a fine map of a grain yield QTL on chromosome 7DS introgressed into bread wheat from Aegilops tauschii (D-Genome donor of wheat). Heterogeneous inbred families (HIFs) were developed. Eleven high-quality SNP markers were developed and mapped to the target region (3-17 Mb) on chromosome 7DS using recombination breakpoints (recombinants). A total of 29 homozygous recombinants (7 haplotype groups) were identified and evaluated in the greenhouse and field. KASP markers spanning to the QTL region can be used for marker-assisted selection of 7DS yield QTL. Overall, the finding of this study can be used for genetic improvement of wheat and accelerate the genetic gain.

Number of Pages

220

Publisher

South Dakota State University

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Rights Statement

In Copyright