Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Individually rare, large copy number variants (CNVs) contribute to genetic vulnerability for schizophrenia. Unresolved questions remain, however, regarding the anticipated yield of clinical microarray testing in schizophrenia. Using high-resolution genome-wide microarrays and rigorous methods, we investigated rare CNVs in a prospectively recruited community-based cohort of 459 unrelated adults with schizophrenia and estimated the minimum prevalence of clinically significant CNVs that would be detectable on a clinical microarray. A blinded review by two independent clinical cytogenetic laboratory directors of all large (>500 kb) rare CNVs in cases and well-matched controls showed that those deemed to be clinically significant were highly enriched in schizophrenia (16.4-fold increase, P < 0.0001). In a single community catchment area, the prevalence of individuals with these CNVs was 8.1%. Rare 1.7 Mb CNVs at 2q13 were found to be significantly associated with schizophrenia for the first time, compared with the prevalence in 23 838 population-based controls (42.9-fold increase, P = 0.0002). Additional novel findings that will facilitate the future clinical interpretation of smaller CNVs in schizophrenia include: (i) a greater proportion of individuals with two or more rare exonic CNVs >10 kb in size (1.5-fold increase, P = 0.0109) in schizophrenia; (ii) the systematic discovery of new candidate genes for schizophrenia; and, (iii) functional gene enrichment mapping highlighting a differential impact in schizophrenia of rare exonic deletions involving diverse functions, including neurodevelopmental and synaptic processes (4.7-fold increase, P = 0.0060). These findings suggest consideration of a potential role for clinical microarray testing in schizophrenia, as is now the suggested standard of care for related developmental disorders like autism.

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