The Landscape and Consequences of Structural Variation in the Human Genome

Abstract

Structural variants (SVs), defined as any rearrangement of ≥50 DNA nucleotides, are a major source of human genetic diversity that determines the content, order, and orientation of the six billion nucleotides in every human genome. Despite their outsized impact on genome biology and human phenotypes, surprisingly little is known about SVs compared to better-studied classes of genetic variation, such as single-nucleotide variants. In this dissertation, I examine the patterns and consequences of SVs in the global human population by aggregating and analyzing large genomic datasets. In Chapter 1, I review the foundational properties of SVs that were established at the outset of my dissertation research. In Chapter 2, I present GATK-SV, a scalable computational pipeline for jointly discovering and genotyping SVs in whole-genome sequencing (WGS) of large cohorts, which we subsequently applied 14,891 individuals from five major continental populations to construct a new reference catalog of SVs as part of the Genome Aggregation Database. In Chapter 3, I recap four parallel efforts to probe the roles of SVs in human disease, including a meta-analysis of rare deletions and duplications in nearly one-million individuals across 54 disorders. In Chapter 4, I investigate the predicted consequences of SVs on coding and noncoding functional loci and document how natural selection shapes the distributions of these SVs in human populations. I conclude by proposing how extensions of this dissertation may eventually enable genome-wide maps of evolutionary constraint against changes in DNA copy number—also known as dosage sensitivity—at kilobase resolution, present a prototype computational framework for dosage sensitivity mapping, and describe ongoing genomic data aggregation efforts towards this goal. Taken collectively, this work sheds new light on a variety of topics in contemporary human genomics, which I hope will provide value to the basic, translational, and clinical research communities.