ArticleNature genetics2026
Genome-wide associations of structural variants with human traits through imputation from long-read assemblies.
Article in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Pangenomic analyses in the cultivated grapevine confirm high genomic collinearity and extensive dispensable gene content likely involved in adaptation.G3 (Bethesda, Md.) · 2026Article
- Comprehensive evaluation of structural variation detection for germline and somatic analysis with long-read sequencing data.Briefings in bioinformatics · 2026Article
- Structural variants contribute substantially to complex trait heritability.Research square · 2026Article
- Computational strategies for copy number variation detection, disease association, and beyond.Genome biology · 2026Review
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Structural variants (SVs) are a major type of genetic variation, yet their role in human traits remains largely uncharacterized, primarily due to challenges in genotyping them on a genome-wide scale in large cohorts. Here we identified 171,233 high-quality, genome-wide SVs from 482 haplotype-resolved genome assemblies derived from PacBio HiFi long-read sequencing of 241 individuals. We developed a reference panel and a web application (ImputeSV) to impute these SVs from single-nucleotide polymorphism (SNP) data and demonstrated high imputation accuracy at both the individual and cohort levels. Using this tool, we imputed 54,578 common SVs (minor allele frequencies (MAFs) ≥1%) in 456,643 UK Biobank (UKB) participants of European ancestry. Through analysis of UKB data and simulations, we estimated that SVs contributed to at least 4.7% of the common genetic variation for complex traits. Genome-wide association analyses of SVs for 2,624 UKB traits identified 17,335 SV-trait associations, including 958 unlikely to be driven by small genetic variants. Our study demonstrates the power of using long-read assemblies for imputing SVs from SNPs, unveils the role of SVs in complex trait variation and provides a catalog of SV associations in the UKB.
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