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The ability to link a particular phenotype to its causative genotype is one of the most challenging objectives for biological research. Although the genetic code provides an explicit formula for determining the sequence of amino acid phenotypes produced by a given nucleotide sequence, identifying specific residues that are functionally important remains problematic. Many computational approaches have been developed that use patterns observed in DNA sequences to identify these critical sites. However, very few research studies have used empirical data to test whether these approaches are truly able to identify sites of interest.In most empirical studies, the actual protein function and selective pressures are unknown; thus it is difficult to assess whether computational approaches are correctly identifying critical sites. Here I present two studies that utilize well-characterized empirical systems to evaluate and compare the performance of several computational approaches. In both cases, the proteins under study have specific amino acid substitutions that are confirmed to alter protein function and expected to be constrained by natural selection. In chapter 2, I examine functional variants in angiopoietin-like protein 4 (ANGPTL4), a protein involved in regulating plasma triglyceride levels; loss-of-function variants in this gene are believed to decrease the risk of cardiovascular disease. I apply several computational approaches to identify functional variants, including phylogenetic approaches for detecting positive selection. In chapter 3, I investigate the emergence of drug-resistance in HIV-1 during the course of antiretroviral drug therapy. I compare the performance of eight selection detection methods in identifying drug-resistant mutations in 109 intrapatient datasets with HIV-1 sequences isolated at multiple timepoints throughout drug treatment.It is critical that we develop methods to detect positively selected sites. The ability to detect these sites in silico, without the need for expensive and time consuming assays, would be invaluable to researchers in evolutionary biology, human genetics, and medicine. Through the research presented in this thesis, I hope to provide insight into the strengths and weaknesses of current approaches, thereby facilitating future research towards the development and improvement of evolutionary models.

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Background: HIV drug resistance limits the effectiveness of antiretroviral therapy. Adequate surveillance of HIV drug resistance prevalence is challenged by heterogenous and inadequate data reporting. In this study, we sought to identify a list of reporting items for studies of HIV drug resistance prevalence and an understanding of why these items are important to report. Methods: We used a mixed-methods sequential explanatory design involving authors and users of studies of HIV drug resistance prevalence. In the quantitative phase we conducted a cross-sectional electronic survey (n=51). Survey participants rated various reporting items on whether they are essential to report, producing validity ratios which were used to produce a draft reporting item checklist. In the qualitative phase, two focus group discussions (n=9 in total) discussed this draft item checklist and which of the items should be reported and why. We also conducted a thematic analysis of the group discussions to identify emergent themes regarding items to be considered for the reporting guideline. Results: We identified 38 potential reporting items including participant characteristics, sampling methods, and resistance testing methods. The strongest themes that emerged from the discussions were agreement over the importance of reporting certain items, concerns over the availability and ethics of reporting certain participant data, the importance of interpretability and comparability, and the necessity for reporting guidelines to appreciate context-specific prevalence research. Conclusions: We have identified a list of reporting items for studies of the prevalence of HIV drug resistance along with an explanation of why researchers believe these items are important. The next steps involve further elaborating upon these findings in the reporting guidelines. / Thesis / Master of Science (MSc) / Drug resistant HIV is very challenging to treat and is an important global health problem. It is difficult to know how common HIV drug resistance is around the world because the studies on HIV drug resistance are not reported similarly. This is because there are no standard guidelines for these studies. In this study, we asked HIV drug resistance researchers to complete a survey on what they thought should be reported is studies measuring HIV drug resistance. Then, we had group conversations where we asked them to explain why they believed the items were important. We identified 38 potential reporting items, most of which would require authors of HIV drug resistance studies to clarify the settings, participants and methods used in their research. These items will make up a reporting checklist for authors of HIV drug resistance studies and make research in this area more comparable

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