Cell Biology & Molecular Genetics Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2750
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Item ANALYSIS OF CONSENSUS GENOME-WIDE EXPRESSION-QTLS AND THEIR RELATIONSHIPS TO HUMAN COMPLEX TRAIT DISEASES(2014) YU, CHEN-HSIN; Moult, John; Molecular and Cell Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Genome-wide association studies of human complex disease have identified a large number of disease associated genetic loci. However, most of these risk loci do not provide direct information on the biological basis of a disease or on the underlying mechanisms. Recent genome-wide expression quantitative trait loci (eQTLs) association studies have provided information on genetic factors, especially SNPs, associated with gene expression variation. These eQTLs might contribute to phenotype diversity and disease susceptibility, but interpretation is handicapped by low reproducibility of the expression results. Our first major goal was to establish a list of consensus eQTLs by integrating publicly available data for specific human populations and cell types. We used linkage disequilibrium data from Hapmap and the 1000 Genomes Project to integrate the results of eQTL studies. Overall, we find over 4000 genes that are involved in high confidence eQTL relationships. We also assessed the possible underlying mechanisms of tissue dependent eQTLs by mapping these to known genome sites of functional elements. Results of comparison of eQTLs across studies on the same cell type versus those on different cell types suggest that tissue specific eQTLs are less common than pan-tissue eQTLs. Our second major goal was to use these results to elucidate the role eQTLs play in human common diseases. For this purpose, we matched the high confidence eQTLs to a set of 335 disease risk loci identified from the Wellcome Trust Case Control Consortium (WTCCC1) genome-wide association study and follow-up studies for seven human common diseases. Our results show that the data are consistent with approximately 50% of these disease loci arising from an underlying expression change mechanism. In many cases, the results provide a proposed expression mechanism for genes previously suggested as disease relevant, in others, new disease relevant genes are identified. A web-based database, ExSNP, was designed to provide comprehensive access to the eQTL data and results from our analysis, including original eQTLs, high-confidence eQTLs, cell type dependent eQTLs, population dependent eQTLs, disease associated eQTLs, and functionally annotated eQTLs. The website also incorporates a genome browser that allows visualization of the relative positions of eQTL SNPs to their associated genes and other neighboring genes, as well as the relationship to functional elements and disease associations.Item IDENTIFICATION OF GENES INVOLVED IN THE ANTIVIRAL RESPONSE THROUGH GENETIC SCREENS IN DROSOPHILA(2014) Tang, Jessica (Juanjie); Wu, Louisa; Molecular and Cell Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Innate immunity is essential for the host to defend against invading pathogens, such as viruses and bacteria. To identify novel genes or molecules that are involved in innate immunity, we carried out two genetic screens in Drosophila. From a forward screen of flies mutagenized with Ethyl methane sulfonate (EMS), four mutants with increased susceptibility to Drosophila X virus (DXV) were found. In this study, we focused on the rogue mutant and identified a novel antiviral gene rogue. The rogue mutant is highly susceptible to DXV infection and is unable to control viral replication during infection. The expression of rogue in either the hemocytes or the fat body is required for flies to control viral accumulation and to survive a viral infection. At an early stage of infection, rogue is induced and the amount of Rogue protein that locates to the nucleus increases. In addition, we confirm that the Rogue protein interacts with the polyA binding protein (PABP), and we propose that rogue restricts viral replication via translation regulation in Drosophila. The rogue mutant also has a phagosome maturation defect, which may contribute to its susceptibility to Staphylococcus aureus infection. RNAi knockdown of rogue in the fat body or the hemocytes in wild type flies results in high bacterial susceptibility. Introducing the rogue transgene in the hemocytes of the rogue mutant can rescue the mutant survival to both DXV and S. aureus. Together, our results demonstrate that rogue plays a critical role in defending against DXV and S. aureus infections. We performed another genetic screen on wild derived inbred flies from the Drosophila Genetic Reference Panel (DGRP). From a genome wide association study (GWAS) in these flies, we found four single nucleotide polymorphisms (SNPs) associated with susceptibility of flies to DXV. One allele contributed most to the susceptibility is located in the intron of Socs36E, a negative regulator of the JAK-STAT pathway, implicating that the JAK-STAT pathway plays a role in the immune responses against DXV. Our study also shows that natural genetic variation can be used as a tool for identifying novel genes or pathways involved in antiviral immunity.Item COMPUTATIONAL METHODS IN PROTEIN STRUCTURE, EVOLUTION AND NETWORKS.(2013) Cao, Chen; Moult, John; Molecular and Cell Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The advent of new sequencing technology has resulted in the accumulation of a large amount of information on human DNA variation. In order to make sense of these data in the context of biology and medicine, new methods are needed both for analysis and for integration with other resources. In this work: 1) I studied the distribution pattern of human DNA variants across populations using data from the 1000 genomes project and investigated several evolutionary biology questions from the perspective of population genomics. I found population level support for trends previously observed between species, including selection against deleterious variants, and lower frequency of variants in highly expressed genes and highly connected genes. I was also able to show that the correlation between synonymous and non-synonymous variant levels is a consequence of both mutation prevalence variation across the genome and shared selection pressure. 2) I performed a systematic evaluation of the effectiveness of GWAS (Genome Wide Association Studies) for finding potential drug targets and discovered the method is very ineffective for this purpose. I proposed two reasons to explain this finding, selection against variants in drug targets and the relatively short length of drug target genes. I discovered that GWAS genes and drug targets are closely associated in the biological network, and on that basis, developed a machine learning algorithm to leverage the GWAS results for the identification of potential drug targets, making use of biological network information. As a result, I identified some potential drug repurposing opportunities. 3) I developed a method to increase the number of protein structure models available for interpreting the impact of human non-synonymous variants, important for not only the understanding the mechanisms of genetic disease but also in the study of human protein evolution. The method enables the impact of approximately 40% more missense variants to be reliably modeled. In summary, these three projects demonstrate that value of computational methods in addressing a wide range of problems in protein structure, evolution, and networks.