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The Genetic Basis of Hypoxia Tolerance

Abstract

Research into hypoxia (or low oxygen levels) has been a hot topic for a number of decades, because many harmful diseases, such as heart attacks and cancer, create much of their damage by inducing hypoxia. It has been suspected for years that the ability of a cell (or an organism) to cope with a hypoxic environment is, at least in part, influenced by genetic factors. However, for financial reasons, virtually all studies that have attempted to find these factors have been constrained to a subset of variant sites (targeted genes, exons, or genotyping arrays). As the costs of sequencing drop, though, whole-genome sequencing will become increasingly used. The primary goal of this dissertation is to build computational tools that use the power of whole-genome sequencing to identify genetic variants that can confer tolerance to hypoxia. Even though the basic computational problem is one of correlation, the experimental design plays a huge role in determining the best way to measure this correlation. First, we discuss ways to identify correlated sites in a typical association study. While the single-locus case is trivial to solve, extending this to multiple loci is intractable using a naive approach. We discuss existing randomized algorithms that solve this problem quickly, and extend these algorithms to handle quantitative phenotypes. We then apply one of these approaches to identify interacting sites correlating with survival rate under acute hypoxia. We then focus on a different problem --- detecting natural selection. As the signatures of natural selection are dependent on several parameters, such as selection pressure and time under selection, which are largely unknown, we compare the performance of a number of tests over a wide range of parameters and identify optimal regimes for each of them. We then select a statistic appropriate for strong, laboratory selection and use it to identify elements of the Notch repression mechanism in flies that have adapted to extreme hypoxia (4% O₂). Finally, we apply a number of these statistics to two different populations of humans adapting to mild hypoxia, identifying novel and distinct mechanisms in both cases

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