Browsing by Subject "Quantitative genetics"
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Item Genetic analysis to improve drought and low nitrogen tolerance of corn in monoculture and in a kura clover intercropping system(2012-12) Ziyomo, CathrineDirect selection for grain yield under stress conditions is often inefficient because the heritability for grain yield is greatly reduced under stress. The objectives of the first study described in this thesis were to determine the efficiency of indirect selection for corn (Zea mays L.) grain yield under drought and low N conditions using secondary traits or molecular markers. Testcrosses of 238 intermated B73 x Mo17 recombinant inbreds were evaluated under drought and low N stress conditions. Results indicated that direct selection for grain yield in the targeted stress environment is more efficient than using secondary traits under both drought stress and low N stress. Using significant markers only was not more efficient than direct phenotypic selection for grain yield. The relative efficiency of genomewide selection was significantly greater than 1.0 for grain yield under drought stress but not for grain yield under low N stress. The results suggest that selection based on molecular markers is more efficient than phenotypic selection alone for the improvement of grain yield under drought stress, while for grain yield under low N stress, selection based on markers alone can only be more efficient if gains per unit time and cost are considered. In addition to the genetic improvement of corn for stress tolerance, the use of drought tolerant corn in a kura clover (Trifolium ambiguum M. Bieb.) intercropping system can reduce the competition for moisture between the grain crop and the cover crop. The objectives of the second study were to determine if drought tolerant corn can minimize the yield losses incurred when corn is intercropped with kura clover. Results indicate that drought-tolerant corn can maintain high yields and allow sufficient regrowth of kura clover and therefore significantly reduce the risk associated with intercropping corn with living mulch.Item Heritability and genetic correlations in the dental dimensions of Saguinus fuscicollis and Macaca mulatta(2018-06) Hardin, Anna M.The genetic inheritance of dental traits in primates is of interest to biological anthropologists due to the high-quality preservation of dental remains in the primate fossil record and, as a result, the frequent use of dental morphology in the study of primate evolution. Adaptive hypotheses for morphological evolution in the primate dentition often discuss individual teeth as independent characters, yet the dentition may be best described as an organ composed of serially homologous parts. Previous studies have shown that dental dimensions are both highly heritable and frequently genetically correlated with other dental features in human and baboon populations, yet it remains to be seen whether tooth size heritabilities and patterns of genetic correlation differ in primate populations with different living conditions or evolutionary histories. This dissertation uses quantitative genetic parameters estimated in the dental dimensions of brown-mantled tamarins (Saguinus fuscicollis) and rhesus macaques (Macaca mulatta) to address these blank spaces in our understanding of the genetic inheritance and integration of primate tooth size. The findings of this research further our knowledge of the genetic inheritance of tooth size in primates and generate new hypotheses about the impact of genetic integration on the evolution of the canine-premolar honing complex and the dentition more broadly.Item The oat-crown rust pathosystem: an interaction of a plant, a pathogen, and time(2020-12) McNish, IanPlant diseases are often described as the interaction of a plant, a pathogen, and the environment. For a disease to develop, there must be a susceptible plant, a virulent pathogen, and an environment amenable to disease. This concept is useful to explain the presence or absence of a disease, but many important questions and ideas in plant pathology, plant genomics, plant phenomics, and plant cultivar development are also dependent on time. A pathogen population changes over time, by a process of selection, to defeat the resistances deployed in crop cultivars. The genetic architecture of disease resistance changes as a plant grows from a seedling to an adult plant, matures, and dies. The visual and spectral signature of plant stress and disease also changes as the plant grows and the disease develops. Finally, plant breeders attempt to limit the damage diseases cause by quickly improving plant populations and deploying disease resistant plant cultivars. The dimension of time has been well-explored in some areas of plant science such as gene expression, but time is often overlooked in plant breeding, quantitative genetics, and phenomics. Crown rust, caused by the fungal pathogen Puccinia coronata f. sp. avenae Erikss. (Pca), is a dynamic and devastating disease of cultivated oat (Avena sativa L.). In this research, I found that the North American Pca population has gained many virulences over the past thirty years and that the Pca isolates collected in recent years are capable of defeating a surprisingly high number of crown rust resistance genes. I found that the genetic architecture of crown rust resistance changed throughout the growing season. Many resistance loci were detected briefly, sometimes just for a couple of days, and few loci were detected at many points in time. I found that the spectral signature of disease and plant stress changed throughout the season and that the predictive value of the collected data was greatest for adult plants before senescence. Finally, I found that quantitative resistance to crown rust could be rapidly improved in an oat population, but the race-specificity of that resistance was difficult to determine. If plant breeders understand how time influences the composition of pathogen populations, the observations they make, the analyses they perform, and the technologies they develop, then they will be more capable of improving complex plant traits like disease resistance.Item The Road From Variants To Traits: How Regulatory Variants Affect Gene Expression & Organismal Phenotypes(2024-03) Renganaath, KaushikNature hosts an incredible amount of diversity and beneath such diversity lies fascinating genetics that we have spent years trying to decode. Differences in our DNA sequences lead to variation in organismal traits. Most of these variants have been found to reside in noncoding portions of the genome, implying that a lot of organismal trait variation arises from variation in gene expression levels. Advances in sequencing technology have over the years allowed us to map hundreds of genomic loci underlying gene expression variation, and these loci are called expression quantitative trait loci (eQTLs). These eQTLs are of two types, local and trans, depending on their proximity to the genes they regulate. Local eQTLs regulate expression of genes in close genomic proximity while trans eQTLs regulate distant genes. Today, we possess a vast catalog of eQTLs across multiple taxa. Yet, we don’t fully understand the mechanisms by which eQTLs affect organismal traits. In this dissertation, I computationally dissect the mechanisms connecting genetic variation, gene expression and organismal traits in yeast Saccharomyces cerevisiae. As the first eukaryotic organism to have its genome fully sequenced, S.cerevisiae has over the years been a workhorse for understanding the genetics underlying complex traits. We today have comprehensive sets of QTLs underlying traits like gene expression and growth in yeast that account for most of heritable variation in these traits, allowing us to investigate the mechanisms by which eQTLs lead to organismal trait variation. In this dissertation, I characterize causal variants underlying local eQTLs in yeast (Chapter II) and the mechanisms by which eQTLs influence growth in different conditions (Chapter III). My work unravels fundamental principles by which eQTLs influence complex organismal traits.