A structural variation reference for medical and population genetics

By Ryan L. Collins, H. Brand, Konrad J. Karczewski, Xuefang Zhao, Jessica Alföldi, L. Francioli, A. Khera, Chelsea Lowther, Laura D. Gauthier, Harold Wang and 173 more. Nature, 2020

876 citations recorded by the source corpus.

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. A large empirical assessment of sequence-resolved structural variants from 14,891 genomes across diverse global populations in the Genome Aggregation Database (gnomAD) provides a reference map for disease-association studies, population genetics, and diagnostic screening.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/a85b86354a118ee2ab05b9b1b66a6b62bdfce121

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Citations in the corpus

High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios (2021, positive): “This prediction is comparable to prior estimates from SVs in short-read WGS from ~15,000 individuals using blood-derived DNA in gnomAD (n=180 genes altered per genome (Collins et al., 2020)).”
Pangenomics enables genotyping known structural variants in 5,202 diverse genomes (2021, methodology): “Of the SV sites genotyped using our pangenome approach, 93% are missing from the 1000 Genomes Project SV catalog ( 32 ), and 67% were missing from the Genome Aggregation Database (gnomAD) – SV catalog ( 33 ) (table S20).”
Haplotype-resolved diverse human genomes and integrated analysis of structural variation (2021, methodology): “5-fold coverage) (18) and discovered SVs by using three analytic pipelines: GATK-SV (5), SVTools (6), and Absinthe.”
A draft human pangenome reference (2022, methodology): “Previous short-read, linear reference studies have discovered 7.5-9.5k SVs per sample (Byrska-Bishop et al., 2021; Collins et al., 2020) while long read-sequencing efforts have routinely discovered ∼25k. Ebert et al. showed that using PanGenie, a pangenomic approach, with 32 samples a subset of…”