Mapping copy number variation by population-scale genome sequencing

Genomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies. Fine-scale mapping of genetic variation Copy number variations (or CNVs) are large-scale deletions, duplications and insertions that contribute significantly to genetic variation in the human genome, and many CNVs are linked to susceptibility to disease. A high-resolution map of CNVs has now been produced by harnessing information from whole-genome sequencing in 185 individuals. Nucleotide resolution of the map facilitates analysis of structural variant distribution and identification of the mechanisms of their origin. The study provides a resource for sequence-based association studies. Harnessing information from whole genome sequencing in 185 individuals, this study generates a high-resolution map of copy number variants. Nucleotide resolution of the map facilitates analysis of structural variant distribution and identification of the mechanisms of their origin. The study provides a resource for sequence-based association studies.