Browsing by Subject "quantitative genetics"
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Item Advancing the Implementation of Genomics-Assisted Breeding in a Public Soybean Breeding Program(2023) Wartha, Cleiton AntonioThe usefulness of genomic selection (GS) for improvement of complex traits has been demonstrated in plant and animal breeding. While fully adopted in the livestock sector and commercial plant breeding, the implementation of GS in public-sector plant breeding programs lags. Challenges such as redesign of the breeding program and cost of genotyping still remain, and gaps exist between research and practical application in public programs. To address these challenges, there are several relevant tools that can be assembled in a framework to enhance the rate of genetic gain. For instance, we demonstrated the usefulness of historical multi-environment trial data from the Northern Uniform Soybean Tests (NUST) for trait mapping and as a publicly available training population for genomic selection models. Characterization of this relevant elite germplasm revealed regions of genetic differentiation mainly driven by maturity group differences and the lack of strong population structure evidenced the germplasm sharing among the public programs encouraged by the NUST organizers to maximize genetic diversity and local adaptation. We also investigated two forms of GS for cultivar development with potential for near term adoption: genomic mating and GS in the progeny rows. Given the large number of potential crosses, prediction tools for parental selection and cross design are valuable to create populations more likely to generate progenies that will exceed current cultivars. We validated in soybeans a methodology to predict the family mean, genetic variance, superior progeny mean, and genetic correlation based on modeling the segregation and recombination of genome-wide marker effects. Lastly, the integration of low-cost high-throughput phenotyping on canopy coverage and genomic prediction to reduce genotyping costs and enhance progeny row selections showed significant yield improvement over random selection in the main evaluation region but the results were not consistent across regions. Overall, the findings and publicly available data from this research will contribute towards genomics-assisted breeding efforts in plant breeding programs.Item Applications of Genomewide Selection in a New Plant Breeding Program(2019-07) Neyhart, JeffreyNewly established breeding programs must undergo population improvement and determine superior germplasm for deployment in diverse growing environments. More rapid progress towards these goals may be made by incorporating genomewide selection, or the use of genomewide molecular markers to predict the merit of unphenotyped individuals. Within the context of a new two-row barley (Hordeum vulgare L.) breeding program, my objectives were to i) investigate various methods of updating training population data and their impact on long-term genomewide recurrent selection, ii) assess genomewide prediction accuracy with informed subsetting of data across diverse environments, and iii) validate genomewide predictions of the mean, genetic variance, and superior progeny mean of potential breeding crossses. My first study relied on simulations to examine the impact on prediction accuracy and response to selection when updating the training population each cycle with lines selected based on predictions (best, worst, both best and worst), model criteria (PEVmean and CDmean), random sampling, or no selections. In the short-term, we found that updating with the best or both best and worst predicted lines resulted in high prediction accuracy and genetic gain; in the long-term, all methods (besides not updating) performed similarly. In an actual breeding program, a breeder may want phenotypic data on lines predicted to be the best and our results suggest that this method may be effective for long-term genomewide selection and practical for a breeder. In my second study, a 183-line training population and 50-line offspring validation population were phenotyped in 29 location-year environments for grain yield, heading date, and plant height. Environmental relationships were measured using phenotypic data, geographic distance, or environmental covariables. When adding data from increasingly distant environments to a training set, we observed diminishing gains in prediction accuracy; in some cases, accuracy declined with additional data. Clustering environments led to a small, but non-significant gain in prediction accuracy compared to simply using data from all environments. Our results suggest that informative environmental subsets may improve genomewide selection within a single population, but not when predicting a new generation under realistic breeding circumstances. Finally, my third study used genomewide marker effects from the same training population above to predict the mean (μ), genetic variance (VG), and superior progeny mean (μSP ; mean of the best 10% of lines) of 330,078 possible crosses for Fusarium head blight (FHB) severity, heading date, and plant height. Twenty-seven of these crosses were developed as validation populations. Predictions of μ and μSP were moderate to high in accuracy (rMP = 0.46 – 0.69), while predictions of VG were less accurate (rMP = 0.01 – 0.48). Predictive ability was likely a function of trait heritability, as rMP estimates for heading date (the most heritable) were highest and rMP estimates for FHB severity (the least heritable) were lowest. Accurate predictions of VG and μ are feasible, but, like any implementation of genomewide selection, reliable phenotypic data is critical.Item Estimating the capacity of Chamaecrista fasciculata to adapt to novel environments(2021-12) Peschel, AnnaTallgrass prairies are one of the most endangered ecosystems in North America with less than 1 percent of their original extent prior to European settlement remaining. Most tallgrass prairie has been razed for agriculture because they tend to exist on fertile soils. In Minnesota the tallgrass prairie once covered 18 million acres, but now only 200,000 acres remain—small, fragmented patches in a matrix of corn and soybean fields (Minnesota Prairie Plan Working Group 2018).Climate change poses new management challenges for extant tallgrass prairies. Given that the remaining prairies are small and severed from gene flow, they may lack sufficient genetic variation to adapt to climate change. If the standing genetic diversity within a population is insufficient for adaptive evolution, seed may need to be sourced from other populations to introduce alleles adaptive in environments predicted for the future. However, how tallgrass prairie plant populations will respond to climate change, and if they possess the capacity to adapt to climate change in situ, are open questions. With insight from prior research (Etterson 2004a,b; Sheth et al. 2018; Kulbaba et al. 2019), we investigate the capacity of the annual prairie legume, Chamaecrista fasciculata, to adapt to environments predicted for the future. The overarching aims of this research are to 1) estimate adaptive capacity in a population of C. fasciculata, 2) test fundamental evolutionary theory predicting a populations’ rate of adaptation, and 3) identify how key plant traits may respond to, and modulate a population’s response to, future climate change. Along with increasing temperatures, climate change in the Midwest is expected to increase the frequency and intensity of rainstorms (Angel et al. 2018). In Chapter 1, we asked if C. fasciculata has sufficient additive genetic variance for fitness to adapt to extreme rain. We also investigated how extreme rain affects plasticity of, selection on, and heritability of specific leaf area (SLA), a trait thought to mitigate water loss. We manipulated rainfall over a pedigreed population of C. fasciculata using rain shelters and found C. fasciculata possessed a significant capacity to adapt to anomalously wet environments. We also found plants to have thinner leaves in wet environments while selection favored thicker leaves, but fitness remained above replacement (mean lifetime fitness > 1, indicating population growth). In Chapter 2 we asked if C. fasciculata possesses the capacity to adapt to climate change, and how well predictions of the rate of adaptation match what is realized in the field. We planted a pedigreed population of C. fasciculata into three sites along an east to west aridity gradient. The eastern (home) site is predicted to have climate similar to the current climate of the western sites in 25-50 years, so comparisons of the rate of adaptation between the home and western sites will give insight into the capacity of this population to adapt to future climates. We detected significant additive genetic variance for fitness in all sites, which implies this population possesses the capacity to adapt to future climates. Predictions of progeny generation mean fitness were greater than what was realized in the field, and the progeny generation was maladapted. However, maladaptation was buffered by the environment at the home and westernmost site, as the fitness of these populations was above replacement. This work suggests C. fasciculata possesses significant genetic variance to adapt in situ to wetter environments, but a change in the selective environment between generations may cause maladaptation. In chapter 3 we used the experimental design of chapter 2 and asked how climate change alters plasticity of, selection on, and heritability of two key traits, SLA and corolla width, to investigate if changes in plasticity or selection on these traits affects the capacity of C. fasciculata to adapt to future climates. We found significant differences in selection on traits between sites, as well as significant selection for thicker leaves and larger flowers across sites. The plastic response was generally maladaptive (thinner leaves and smaller flowers). We did not find traits to be heritable, which may be a consequence of limited power. Mean fitness in the western most site was above replacement which implies adaptive phenotypic plasticity and adaptive evolution of SLA and corolla width may not be necessary for this population to increase in mean fitness. We detected abundant and significant additive genetic variance for mean lifetime fitness which suggests the populations of C. fasciculata used in this research possess the capacity to adapt to wetter environments. However, temporal environmental variation caused alleles selected by the environment in the parental generation to change frequency in a maladaptive direction, according to the environment in the progeny generation. While the progeny generation was maladapted, mean fitness remained above replacement which is a consequence of plasticity, not adaptive evolution. Mean fitness above replacement at the western most site suggests that this population of C. fasciculata may be able to persist in future climates without seed from other sites. However, the ability of plasticity to buffer populations from environmental change in the long term, as well as the long-term effects of fluctuating selection for demography and evolution, remain unclear and are future research directions. More studies employing the Fundamental Theorem of Natural Selection (FTNS) are needed so we can increase our predictive power of the adaptive capacity of populations in hopes of conserving populations at risk of extinction from climate change.Item Human Impacts on Minnesota Prairie Genetics: Salted Environments, Echinacea Hybrids, and Local Seed Sourcing(2018-12) Goldsmith, NicholasHumans are modifying various aspects of the environment, from building roadways, to moving species beyond their range, to purposefully reconstructing plant communities. These actions affect both the current distribution of populations and the potential for populations to persist. In this dissertation, I examine two human-caused impacts to plant populations and one aspect of efforts to support native plant communities. In chapter one, I focus on the impact of sodium chloride, a road de-icing agent. Such agents can damage plants and change dominant species along roadsides. I carried out two experiments, planting a pedigreed population of the native prairie legume Chamaecrista fasciculata into a roadside environment and into four greenhouse salinity treatments. I tracked their survival and reproduction. Using Aster models, I detected potential to adapt both to roadside salinity and to low salinity in the greenhouse. I also detected gene-by-environment interactions in both experiments. These results indicate a potential to adapt, but a potential which may be slowed by gene-by-environment interactions. In chapter two, I focus on the interaction of Echinacea pallida, introduced outside of its range, on local populations of E. angustifolia. I used controlled crosses and monitored their seed set and the survival of the progeny over five years. Crossing of the two species produces offspring capable of surviving multiple years. Comparing conspecific and heterospecific crosses, I found that conspecific crosses of E. angustifolia resulted in lower pollen compatibility and survival to year four than did conspecific crosses with E. pallida or heterospecific crosses. These results demonstrate a risk to E. angustifolia populations by E. pallida populations planted nearby. In chapter three, I focus on efforts to remediate human impacts through restoration of Minnesota prairie plant communities, which depends on the production and use of source-identified seeds. Restoration practice often emphasizes use of seeds sourced from populations near the restoration site, but demand frequently outstrips supply. I conducted focus group interviews with groups of producers and users of locally-sourced seeds to identify strengths and weaknesses with current practices. Participants discussed continued increases in production and use of these plant materials but also identified aspects where improvement is needed.