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Description
The 18S ribosomal RNA gene is ubiquitous across eukaryotes as it encodes the RNA component of the ribosomal small subunit. It is the most commonly used marker in molecular studies of unicellular eukaryotes (protists) due to its species specificity and high copy number in the protist genome. Recent studies have revealed the widespread occurrence of intragenomic (intra-individual) polymorphism in many protists, an understudied phenomenon which contradicts the assumed homogeneity of the 18S throughout an individual genome. This thesis quantifies and analyzes the level of intragenomic and intraspecific 18S sequence variability in three Trichonympha species (T. campanula, T. collaris, T. postcylindrica) from Zootermopsis termites. Single-cell DNA extractions, PCR, cloning, and sequencing were performed to obtain 18S rRNA sequence reads, which were then analyzed to determine levels of sequence divergence among individuals and among species. Intragenomic variability was encountered in all three species. However, excluding singleton mutations, sequence divergence was less than 1% in 53 of the 56 compared individuals. T. collaris exhibited the most substantial intragenomic variability, with sequence divergence ranging from 0 to 3.4%. Further studies with more clones per cell are needed to elucidate the true extent of intragenomic variability in Trichonympha.
ContributorsBobbett, Bradley (Author) / Gile, Gillian (Thesis director) / Liebig, Juergen (Committee member) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Safe, readily available, and reliable sources of water are an essential component of any municipality’s infrastructure. Phoenix, Arizona, a southwestern city, has among the highest per capita water use in the United States, making it essential to carefully manage its reservoirs. Generally, municipal water bodies are monitored through field sampling. However, this approach is limited spatially and temporally in addition to being costly. In this study, the application of remotely sensed reflectance data from Landsat 7’s Enhanced Thematic Mapper Plus (ETM+) and Landsat 8’s Operational Land Imager (OLI) along with data generated through field-sampling is used to gain a better understanding of the seasonal development of algal communities and levels of suspended particulates in the three main terminal reservoirs supplying water to the Phoenix metro area: Bartlett Lake, Lake Pleasant, and Saguaro Lake. Algal abundances, particularly the abundance of filamentous cyanobacteria, increased with warmer temperatures in all three reservoirs and reached the highest comparative abundance in Bartlett Lake. Prymnesiophytes (the class of algae to which the toxin-producing golden algae belong) tended to peak between June and August, with one notable peak occurring in Saguaro Lake in August 2017 during which time a fish-kill was observed. In the cooler months algal abundance was comparatively lower in all three lakes, with a more even distribution of abundance across algae classes. In-situ data from March 2017 to March 2018 were compared with algal communities sampled approximately ten years ago in each reservoir to understand any possible long-term changes. The findings show that the algal communities in the reservoirs are relatively stable, particularly those of the filamentous cyanobacteria, chlorophytes, and prymnesiophytes with some notable exceptions, such as the abundance of diatoms, which increased in Bartlett Lake and Lake Pleasant. When in-situ data were compared with Landsat-derived reflectance data, two-band combinations were found to be the best-estimators of chlorophyll-a concentration (as a proxy for algal biomass) and total suspended sediment concentration. The ratio of the reflectance value of the red band and the blue band produced reasonable estimates for the in-situ parameters in Bartlett Lake. The ratio of the reflectance value of the green band and the blue band produced reasonable estimates for the in-situ parameters in Saguaro Lake. However, even the best performing two-band algorithm did not produce any significant correlation between reflectance and in-situ data in Lake Pleasant. Overall, remotely-sensed observations can significantly improve our understanding of the water quality as measured by algae abundance and particulate loading in Arizona Reservoirs, especially when applied over long timescales.
ContributorsRussell, Jazmine Barkley (Author) / Neuer, Susanne (Thesis advisor) / Fox, Peter (Committee member) / Myint, Soe (Committee member) / Arizona State University (Publisher)
Created2018