Browsing by Author "Dorn, Kevin, committee member"
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Item Open Access Genome-wide association study and genomic prediction for end-use qualities in hard winter wheat(Colorado State University. Libraries, 2024) Wondifraw, Meseret A., author; Mason, R. Esten, advisor; Haley, Scott D., advisor; Rhodes, Davina, committee member; Dorn, Kevin, committee memberWheat (Triticum aestivum L.) is a widely cultivated crop used primarily for human food, animal feed, and industrial products. Numerous wheat-based products have unique nutritional and functional requirements. In the global market, wheat quality is one of the determining factors of wheat's price and baked product characteristics. Thus, after grain yield, improving these qualities is one of the major breeding objectives in wheat. Chapter One: This chapter outlines wheat's origins and global production. It explores major quality traits like water absorption and dough rheological properties, plus their measurement methods. Factors impacting wheat quality and pertinent genes are discussed. Finally, key challenges and opportunities around breeding for improved wheat quality are addressed. Chapter Two: This chapter presents a genome-wide association study of water absorption capacity in hard winter wheat. Lines were phenotyped using the solvent retention capacity test and genotyped via genotyping-by-sequencing. Forty-three marker-trait associations were identified across 17 chromosomes, especially on chromosome 1B, indicating polygenic influence. Co-localization between identified marker-trait associations and the genes that have effects on water absorption was done, and some quantitative trait nucleotides (QTNs) were located near gluten glutenin, gliadin, and glycosyltransferase genes, confirming water absorption is a complex trait affected by different flour components. Chapter Three: This chapter presents genome-wide prediction models to predict water absorption capacity using a training population of 497 hard winter wheat genotypes. Univariate models were compared to multivariate genomic prediction models using two validation approaches - cross-validation with 100 permutations and a 20-80 split and forward validation utilizing three years of data (2019-2021) from the CSU ELITE Trial. Multivariate genomic prediction models integrating highly correlated traits like break flour yield or all traits as covariates showed improved accuracy compared to univariate models in both validation approaches, demonstrating that incorporating related phenotypic traits as covariates in multivariate models can substantially improve the accuracy of predicting water absorption capacity. Chapter Four: This chapter evaluates genomic prediction models for bread-baking quality traits in 790 wheat genotypes over the 2014-2022 growing seasons. Marker-trait associations identified via genome-wide association study (GWAS) were incorporated as fixed effects. Three models were compared using cross-validation and forward validation: a model without fixed effect, with Glu-B1al allele (Bx7OE + 8 subunit) kompetitive allele-specific PCR (KASP) marker data as a fixed effect, and with GWAS-identified markers as fixed effects. Overall, the model with GWAS-identified markers as fixed effects showed the highest prediction accuracy. However, prediction accuracy decreased for bake loaf volume prediction specifically, suggesting that trait-specific tuning is needed to optimize genomic prediction models for different baking quality traits. These chapters reinforce the genetic complexity of water absorption capacity and baking quality traits in wheat. Polygenic inheritance was revealed for water absorption capacity. Genomic prediction that incorporates phenotypic covariates and GWAS-derived markers is the best approach to selecting water absorption and baking traits.Item Open Access Mapping Rhizoctonia root and crown rot resistance from sugar beet germplasm FC709-2 using new genomic resources(Colorado State University. Libraries, 2024) Metz, Nicholas, author; Mason, Esten, advisor; Dorn, Kevin, committee member; Richards, Christopher, committee member; Gaines, Todd, committee memberSugar beet (Beta vulgaris subsp. Vulgaris) provides about 35% of the refined sugar globally, and over half of the domestic production in the United States. Sugar beet are primarily grown in temperate climates from plantings in late spring and harvest in the fall. In the United States sugar beets are grown in four diverse regions: the upper Midwest (Minnesota and North Dakota), the far west (California, Idaho, Oregon, and Washington, the Great Plains (Colorado, Nebraska, Montana, and Wyoming), and the Great Lakes (Michigan). Multiple pests and pathogens continue to threaten tonnage and recoverable sugar yields. These are controlled through planting genetically resistant cultivars, agronomic cultural practices and chemical applications throughout the growing season. With a shrinking set of chemical and cultural control options to manage these production threats, the need for continued improvement upon host plant resistance is important. Decades of global breeding efforts to improved disease tolerance in sugar beet has been effective, but molecular and genomic guided breeding and disease resistance characterization in sugar beet is only now emerging. The most important root pathogen in sugar beet is Rhizoctonia Root and Crown Rot (RRCR) caused by the fungal pathogen Rhizoctonia solani. This disease is estimated to cause up to 50% localized losses, and regularly causes 57 million dollars in economic losses per year despite the use of tolerant varieties, chemical control, and cultural practices. Public sugar beet pre-breeding has developed hundreds of widely utilized lines with novel traits and combinations of traits, including for RRCR resistance. One such line, FC709-2, displayed exceptional tolerance to Rhizoctonia solani released from the United States Department of Agriculture sugar beet breeding program in Fort Collins, Colorado. This germplasm line is base for many RRCR resistant cultivars used by growers around the world. In this study, new germplasm, genetic, and genomic resources revolving around FC709-2 were developed. These resources include a new germplasm line derived from the purification of FC709-2. By using stricter selection pressure and single seed decent a more homogenous seed lot was created to be used by other breeding programs. A new reference genome created from a single highly RRCR resistant plant using the most recent sequencings and bioinformatic technologies will be used to discover genes that are responsible for a wide array of plant interactions. Last, novel QTLs associated with RRCR resistance were discovered using a bi-parental mapping population and bulk segregate analysis. Collectively, these results show that discovering novel RRCR resistance genes in a highly resistant germplasm line using a purpose-built reference genome is a streamlined and accurate method. With these new resources in place researchers around the world can use them to discover the genes responsible for RRCR resistance, create markers for more accurate selections, and follow the methods described to be implemented in other plant breeding programs.Item Embargo Sweet surprise: the search for genes conferring beet curly top virus resistance(Colorado State University. Libraries, 2023) Withycombe, Jordan, author; Nachappa, Punya, advisor; Nalam, Vamsi, committee member; Nishimura, Marc, committee member; Dorn, Kevin, committee memberSugar beets (Beta vulgaris L.) are grown across the western United States and suffer economic loss annually to curly top disease. Curly top disease is caused by the beet curly top virus (BCTV) and is spread by the only known insect vector the beet leafhopper, Circulifer tenellus Baker (BLH). Current management strategies for BCTV include chemical control using neonicotinoid seed treatments and foliar insecticidal sprays, as well as the use of BCTV-resistant sugar beet varieties. However, the underlying genetic mechanism surrounding resistance in sugar beet is unknown. The overarching goal of this study was to identify the mechanism of resistance in sugar beet to BCTV and identify potential genes conferring resistance. The objectives for this study were: 1) classify the nature of BCTV resistance in a resistant (EL10) and susceptible (FC709-2) genotype of sugar beet using host suitability and host preference insect assays, as well as assess viral load within each genotype and 2) characterize the transcriptional response to BCTV infection using RNA-sequencing. To classify the nature of BCTV resistance in each genotype of sugar beet, host suitability and preference assays were conducted using virus infected and uninfected BLH. In host suitability assays, the percentage of surviving BLH adults and the number of nymphs produced when reared on a single plant of either genotype was determined over a 3-week period. There was no difference in adult survival, or the number of nymphs produced on either genotype for the virus infected or uninfected leafhoppers. Host preference assays were used to assess settling behavior of BLH over time when given a choice between the two genotypes. It was concluded that virus infected leafhoppers had a clear choice to settle on the susceptible genotype at all timepoints after 4 hours, while uninfected leafhoppers did not make as strong of a settling choice. Average viral load for each genotype across three timepoints was estimated using qPCR. The results showed that the average viral load increased in each genotype over time, yet there was no difference in the average viral load between the genotypes at any individual timepoint. The global transcriptional response to BCTV infection over time for a resistant and susceptible genotype of sugar beet was conducted using RNA-sequencing technology. Mock-inoculated and BCTV-inoculated plants from each genotype were sampled on day 1, 7 or 14 post inoculation resulting in the preparation of 36 mRNA sequencing libraries. Comparison between mock-inoculated and BCTV-inoculated plants of each genotype and timepoint were conducted separately to generate six list of differentially expressed transcripts (DETs). Each transcript was annotated with a description and further classified for its role in the plant biological, cellular or molecular processes. The results showed that both genotypes of sugar beet had a dynamic response to BCTV infection over time, although there was minimal overlap between the responses to one another. EL10, the resistant genotype, had DETs associated with phytohormone production including jasmonic acid and abscisic acid, along with proteins linked to stress reduction and the downregulation of plant primary metabolic processes. In contrast FC709-2, the susceptible genotype, was found to produce opposing phytohormones like salicylic acid and auxins, as well as the production of volatile organic compounds and an increase of primary plant metabolic processes. These opposing responses shed light on the differences in the transcriptional response of a resistant and susceptible genotype of sugar beet. Understanding and classifying the mechanisms of resistance or susceptibility to BCTV infection in sugar beet is beneficial to researchers and plant breeders as it provides a basis for further exploration of the host plant-virus-vector interactions.