This track shows structural variants (SVs) identified by Oxford Nanopore long-read sequencing of 888 individuals from the 1000 Genomes Project, spanning five ancestry groups. Structural variants are genomic rearrangements larger than about 50 bp, such as deletions, insertions, inversions, duplications and breakends (rearrangement junctions); because they alter or move large stretches of DNA at once, they can affect gene dosage and gene regulation more strongly than single-nucleotide changes, yet they are largely missed by the short-read data used in most large studies.
The panel contains more than 107,000 SVs called against GRCh38: about 60,000 insertions, 38,000 deletions, 5,700 inversions, 2,700 breakends and 600 duplications. Each variant carries an overall allele frequency and allele frequencies for each of the five superpopulations (African, Admixed American, East Asian, European, South Asian), Sniffles2 quality metrics, Hardy-Weinberg p-values, and internal (leave-one-out) and UK Biobank imputation accuracy. The authors used this panel to impute SVs into about 500,000 UK Biobank participants and to test them for association with disease-relevant traits and protein levels; where a variant reached genome-wide significance, the associated traits are listed on its details page.
Items are colored by SV type, matching the other subtracks of the container:
| Deletion (DEL) | |
| Insertion (INS) | |
| Duplication (DUP) | |
| Inversion (INV) | |
| Breakend (BND), a single junction of a larger rearrangement |
Insertions and breakends are drawn at a single reference base; the length of inserted sequence is reported for insertions, and the mate locus of the rearrangement junction is reported for breakends. Deletions, inversions and duplications span the affected reference interval. Because the source table does not report an allele count, the allele count and allele number shown here are approximate values derived from the reported allele frequency and the genotype missing rate (allele number = 2 × 888 × (1 − missing rate); allele count = allele frequency × allele number).
The mouseover shows the variant name, SV type, reference and insertion lengths, allele frequency, approximate allele count, and the number of UK Biobank trait associations. Filters are available for SV type, SV length, insertion length, approximate allele count, overall and per-population allele frequency, the number of UK Biobank GWAS hits, and the UK Biobank imputation r².
888 individuals from the 1000 Genomes Project (164 European, 144 Admixed American, 168 East Asian, 171 South Asian and 241 African), out of 906 sequenced, passed quality control. They were sequenced on the Oxford Nanopore PromethION P48 platform with R9.4.1 flow cells and the SQK-LSK110 ligation kit, to a median read length of about 6.2 kb and 15x median coverage. Reads were aligned to GRCh38 with minimap2 v2.24 and structural variants were jointly called across all samples with Sniffles2 v2.0.7 using tandem-repeat annotations. Variants were retained if they were 50 bp to 30 Mb long, present in at least two individuals and had a genotype missing rate below 20%, yielding 107,445 SVs. This SV panel was merged with about 45 million short variants from 1000 Genomes Phase 3 and phased with Beagle to build a multi-ancestry imputation reference panel. Leave-one-out cross-validation with Beagle v5.4 provided per-variant imputation accuracy (r²) and minor-allele concordance. The panel was then used to impute SVs into 488,130 UK Biobank participants, and an SV-wide association study (SV-WAS) with Regenie v3 tested 32 disease-relevant phenotypes and 1,463 protein levels in European-ancestry participants, using a genome-wide significance threshold of p<5×10-8. See Noyvert et al. 2025 for full details.
The per-variant summary table (allele frequencies, quality metrics, imputation accuracy and significant UK Biobank associations for all 107,445 SVs) was provided by the authors. At UCSC it was converted to the shared long-read SV schema (signed lengths made positive, an explicit insertion-length field added, allele count and allele number approximated from allele frequency and missing rate, and colors assigned from the container's shared palette). The step-by-step commands are recorded in the UCSC makeDoc for this track container: doc/hg38/lrSv.txt. The conversion script and autoSql schema live in makeDb/scripts/lrSv, and the track configuration is in trackDb/human/lrSv.ra.
The data can be explored interactively in table format with the Table Browser or the Data Integrator and exported from there to spreadsheet or tab-sep tables. From scripts, the data can be accessed through our API, track=noyvertSv.
The annotation is stored as a bigBed file that can be downloaded from our download server as noyvert.bb. Individual regions or the whole annotation can be obtained with the bigBedToBed utility, available from our utilities page. Example: bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/lrSv/noyvert.bb -chrom=chr21 -start=0 -end=100000000 stdout.
Thanks to Boris Noyvert and colleagues at Boehringer Ingelheim and the wider study team for generating this multi-ancestry long-read SV panel and for sharing the per-variant summary table, and to the 1000 Genomes Project and the UK Biobank participants whose data made the study possible.
Noyvert B, Erzurumluoglu AM, Drichel D, Omland S, Andlauer TFM et al. Imputation of structural variants using a multi-ancestry long-read sequencing panel enables identification of disease associations. eLife. 2025. doi:10.7554/eLife.106115.1