Gene expression is regulated by local genetic sequence, and researchers have identified thousands of common genetic variants in the human population that associate with altered gene expression. These expression quantitative trait loci (eQTLs) often co-localize with genome wide association study (GWAS) loci, suggesting that they may hold the key to understanding genetic effects on human phenotype and cause disease. eQTLs are enriched in cis-regulatory elements, suggesting that many affect gene expression via non-coding mechanisms. However, many of the discovered loci lie in noncoding regions of the genome for which we lack understanding, and determining their mechanisms of action remains a challenge. To complicate matters further, genetic variants may have varied effects in different tissues or under different environmental conditions. The research presented here uses statistical methods to investigate genetic variants’ mechanisms of actions and context specificity.
In Chapter 1, we introduce eQTLs and discuss challenges associated with their discovery and analysis. In Chapter 2, we investigate cross-tissue eQTL and gene expression patterns, including for GWAS genes. We find that eQTL effects show increasing, decreasing, and non-monotonic relationships with gene expression levels across tissues, and we observe higher eQTL effects and eGene expression for GWAS genes in disease-relevant tissues. In Chapter 3, we use the natural variation of transcription factor activity among tissues and between individuals to elucidate mechanisms of action of eQTL regulatory variants and understand context specificity of eQTL effects. We discover thousands of potential transcription factor mechanisms of eQTL effects, and we investigate the transcription factors’ roles with orthogonal datasets and experimental approaches.
Finally, in Chapter 4, we focus on a locus implicated in coronary artery disease risk and unravel the likely causal variants and functional mechanisms of the locus’s effects on gene expression and disease. We confirm the locus’s colocalization with an eQTL for the LIPA gene, and using statistical, functional, and experimental approaches, we highlight two potential causal variants in partial linkage disequilibrium. Taken together, this work develops a framework for understanding eQTL context variability and highlights the complex genetic and environmental contributions to gene regulation. It provides a deeper understanding of gene regulation and of genetic and environmental contributions to complex traits and disease, enabling future research surrounding the context variability of genetic effects on gene expression and disease.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-ysj0-na15 |
| Date | January 2021 |
| Creators | Flynn, Elise Duboscq |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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