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- All Subjects: Evolution
- Creators: School of Molecular Sciences
- Creators: Wilson Sayres, Melissa
- Member of: Theses and Dissertations
My research is focused on the people of Turkana, a human pastoral population inhabiting Northwest Kenya. The people of Turkana are Nilotic people that are native to the Turkana district. There are currently no conclusive studies done on evidence for genetic lactase persistence in Turkana. Therefore, my research will be on the evolution of lactase persistence in the people of Turkana. The goal of this project is to investigate the evolutionary history of two genes with known involvement in lactase persistence, LCT and MCM6, in the Turkana. Variants in these genes have previously been identified to result in the ability to digest lactose post-weaning age. Furthermore, an additional study found that a closely related population to the Turkana, the Massai, showed stronger signals of recent selection for lactase persistence than Europeans in these genes. My goal is to characterize known variants associated with lactase persistence by calculating their allele frequencies in the Turkana and conduct selection scans to determine if LCT/MCM6 show signatures of positive selection. In doing this, we conducted a pilot study consisting of 10 female Turkana individuals and 10 females from four different populations from the 1000 genomes project namely: the Yoruba in Ibadan, Nigeria (YRI); Luhya in Webuye, Kenya; Utah Residents with Northern and Western European Ancestry (CEU); and the Southern Han Chinese. The allele frequency calculation suggested that the CEU (Utah Residents with Northern and Western European Ancestry) population had a higher lactase persistence associated allele frequency than all the other populations analyzed here, including the Turkana population. Our Tajima’s D calculations and analysis suggested that both the Turkana population and the four haplotype map populations shows signatures of positive selection in the same region. The iHS selection scans we conducted to detect signatures of positive selection on all five populations showed that the Southern Han Chinese (CHS), the LWK (Luhya in Webuye, Kenya) and the YRI (Yoruba in Ibadan, Nigeria) populations had stronger signatures of positive selection than the Turkana population. The LWK (Luhya in Webuye, Kenya) and the YRI (Yoruba in Ibadan, Nigeria) populations showed the strongest signatures of positive selection in this region. This project serves as a first step in the investigation of lactase persistence in the Turkana population and its evolution over time.
One of the largest problems facing modern medicine is drug resistance. Many classes of drugs can be rendered ineffective if their target is able to acquire beneficial mutations. While this is an excellent showcase of the power of evolution, it necessitates the development of increasingly stronger drugs to combat resistant pathogens. Not only is this strategy costly and time consuming, it is also unsustainable. To contend with this problem, many multi-drug treatment strategies are being explored. Previous studies have shown that resistance to some drug combinations is not possible, for example, resistance to a common antifungal drug, fluconazole, seems impossible in the presence of radicicol. We believe that in order to understand the viability of multi-drug strategies in combating drug resistance, we must understand the full spectrum of resistance mutations that an organism can develop, not just the most common ones. It is possible that rare mutations exist that are resistant to both drugs. Knowing the frequency of such mutations is important for making predictions about how problematic they will be when multi-drug strategies are used to treat human disease. This experiment aims to expand on previous research on the evolution of drug resistance in S. cerevisiae by using molecular barcodes to track ~100,000 evolving lineages simultaneously. The barcoded cells were evolved with serial transfers for seven weeks (200 generations) in three concentrations of the antifungal Fluconazole, three concentrations of the Hsp90 inhibitor Radicicol, and in four combinations of Fluconazole and Radicicol. Sequencing data was used to track barcode frequencies over the course of the evolution, allowing us to observe resistant lineages as they rise and quantify differences in resistance evolution across the different conditions. We were able to successfully observe over 100,000 replicates simultaneously, revealing many adaptive lineages in all conditions. Our results also show clear differences across drug concentrations and combinations, with the highest drug concentrations exhibiting distinct behaviors.
Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.