Structural Variation and Medical Genomics

The decade since the assembly of the human genome has witnessed dramatic advances in understanding the genetic differences that distinguish individual humans and that are responsible for specific traits. Genomewide association studies (GWAS) in humans have identified common germline, or inherited, DNA variants that are associated with various common human diseases, including diabetes, heart disease, etc. At the same time, cancer genome sequencing studies have cataloged numerous somatic mutations that arise during the lifetime of an individual and that drive cancer progression. These successes are ushering in the era of personalized medicine, where treatment for a disease is tailored to the genetic characteristics of the individual. Despite this progress, significant hurdles remain in achieving a comprehensive understanding of the genetic basis of human traits and disease. The germline variants discovered by GWAS thus far explain only a small fraction of the heritability of many traits, and this “missing heritability” gap [20] is a major bottleneck for future GWAS. The somatic mutations measured in cancer genomes are very heterogeneous, with relatively few mutations that are shared by large numbers of cancer patients, even those with the same (sub)type of cancer. This mutational heterogeneity complicates efforts to distinguish functional mutations that drive cancer development from random passenger mutations. Comprehensive studies of the genetic basis of disease require the measurement of all variants that distinguish individual genomes. Most GWAS thus far focused on the measurement of single nucleotide polymorphisms (SNPs), single nucleotide differences between individual genomes. In the past few years, it has become clear that germline variants occupy a continuum of scales ranging from single nucleotide polymorphisms (SNPs) to larger structural variants (SVs) – duplications, deletions, inversions, and translocations of large (> 100 nucleotides) blocks of DNA sequence. Similarly, current GWAS focused attention on common SNPs, those whose frequency in the population was at least 5%. This restriction was part of the “common disease, common variant” hypothesis which posits that some fraction of susceptibility to common diseases results from germline variants that are common in the population. However, this restriction was also dictated by technological limitations, as it was not cost effective to measure all variants in the large number of individual genomes that are necessary to perform a GWAS. Beginning the mid-2000’s, next-generation DNA sequencing technologies became commercially available from companies such as 454 Life Sciences, Illumina, and Applied Biosystems (now Life Technologies). These and other technologies continue to advance at a breathtaking pace with the result that the cost of DNA sequencing has declined by several orders of magnitude in the past decade. These technologies provide an unprecedented opportunity to measure all variants; germline and somatic; SNPs and SVs, in both normal and cancer genomes. In this chapter, we discuss the application of these sequencing technologies in medical genomics, and specifically on the characterization of structural variation that was largely absent from earlier GWAS. In this