Abstract

Structural variants (SVs) are an important source of human genetic diversity but their contribution to traits, disease, and gene regulation remains unclear. In conjunction with technical challenges associated with SV discovery, a dearth of available software to analyze SVs in large cohorts sets has hindered the characterization of SVs in a number of functional aspects, including their effects on gene expression. Here, we present computational tools for rapid, accurate, and scalable detection of SVs, and we apply these methods to examine the effects of SVs on human gene expression in the Genotype-Tissue Expression (GTEx) project. We mapped cis expression quantitative trait loci (eQTLs) in 13 tissues from deep whole genome sequencing (WGS). We estimate that SVs are causal at 3.5-6.8% of eQTLs – a substantially higher fraction than prior estimates – and that expression-altering SVs have larger effect sizes than SNVs and indels. We observe a notable abundance of rare, high impact SVs associated with aberrant expression of nearby genes. These results suggest that comprehensive WGS-based SV analyses, using novel tools described herein, will increase the power of common and rare variant association studies.

Committee Chair

Ira M. Hall

Committee Members

Donald F. Conrad, Todd E. Druley, Christina A. Gurnett, Nathan O. Stitziel,

Comments

Permanent URL: https://doi.org/10.7936/tweq-0j24

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Molecular Genetics & Genomics)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

Spring 5-15-2019

Language

English (en)

Author's ORCID

http://orcid.org/0000-0002-4113-6065

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Available for download on Monday, May 15, 2119

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Biology Commons

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