High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios
Open accessPublished version of a preprint
Abstract
The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.
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The SV callset that was published in recent studies reported only 27,166 SVs, with 8,093 insertions, 13,506 deletions and 5,567 other types of SV.
“The SV callset that was published in recent studies reported only 27,166 SVs, with 8,093 insertions, 13,506 deletions and 5,567 other types of SV.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
The Results section (“Structural variation across the 3,202 1kGP samples”; page not available) reports 173,366 SV loci, including 49,693 insertions and 90,259 deletions—not the claimed 27,166 total, 8,093 insertions and 13,506 deletions. Its comparison with the earlier phase 3 call set also gives a different total: 68,697 SV sites. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe average SNVs per sample ranged from 3,930,793 (EUR) to 4,771,879 (AFR) and followed expected diversity.
“The average SNVs per sample ranged from 3,930,793 (EUR) to 4,771,879 (AFR) and followed expected diversity60.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
Table 1 in Results, “Small variation across the 3,202 1kGP samples” (page not available), supports the ancestry pattern: AFR has the highest average SNV count and EUR the lowest. But it reports 4,653,521 SNVs per AFR sample and 3,818,951 per EUR sample, not the two figures cited. (LLM, conf=0.90)
Experimental — accuracy not yet measuredAnalysis with DRAGEN showed improved performance of variant calling in terms of novel small variants (SNVs and indels) and SVs.
“Analysis with DRAGEN showed an improved performance of variant callings in terms of novel small variants (that is, SNVs and indels) and SVs60.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
The Results sections comparing calls with the 1kGP phase 3 set report improved discovery of SNVs, indels, and SVs. But STAR★Methods (Method details; page unavailable) says SNVs and indels were called with GATK, while the SV call set used other pipelines; the paper does not attribute these improvements to DRAGEN. (LLM, conf=0.89)
Experimental — accuracy not yet measuredThe low-coverage (7.4×) WGS datasets of 2,504 samples in 1kGP have been expanded to 3,202 high-coverage (35×) datasets.
“Recently, the low-coverage (7.4×) WGS datasets22 of 2,504 samples in 1kGP have been expanded to 3,202 high-coverage (35×) datasets60.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
The Introduction reports that the original 2,504 samples, sequenced at a mean depth of 7.4×, were included in an expanded high-coverage cohort of 3,202 samples. The stated 35× depth does not match our copy: the Introduction gives a target of 30×, and STAR★Methods reports average coverage of 34× per sample (no page numbers provided). (LLM, conf=0.88)
Experimental — accuracy not yet measuredPrevious short-read, linear reference studies have discovered 7,500-9,500 SVs per sample, whereas long-read sequencing efforts have routinely discovered around 25,000.
“Previous short-read, linear reference studies have discovered 7,500–9,500 SVs per sample19,68, whereas long-read sequencing efforts have routinely discovered around 25,000.”
From A draft human pangenome reference. (2023) · cites this paper as [19]
The Results section (“Structural variation across the 3,202 1kGP samples”; page not provided) reports about 9,679 SVs per genome from short-read WGS, supporting the approximate scale of the cited short-read claim. That average is slightly above the stated 7,500–9,500 range, which the paper does not establish. (LLM, conf=0.85)
Experimental — accuracy not yet measured
For the 1kGP cohort dataset, DRAGEN discovered more SNVs, indels (2-50 bp), and large variants (≥50 bp) than the recently published results from the same cohort.
“For the 1kGP cohort dataset, DRAGEN was able to discover more variants, that is, SNVs, indels (2–50 bp) and large variants (≥50 bp) than the recently published60 results from the same cohort.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
For CBS, only 221 variants were reported across 1kGP in a previous study.
“As an example, for CBS, related to cystathionine β-synthase deficiency65, only 221 variants were reported across 1kGP in a previous study60.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
The Results sections on small variation and comparison with the phase 3 call set report cohort-wide counts, but no count for variants in CBS (page numbers unavailable). Searches for “CBS 221 variants,” “cystathionine beta synthase deficiency 221,” and “221” did not locate the claimed gene-specific figure in our copy. (LLM, conf=0.72)
Experimental — accuracy not yet measuredThe previous study only reported 36 SVs in collapsed and 18 SVs in duplicated regions across the entire 1kGP sample.
“By contrast, the previous study only reported 36 SVs in collapsed and 18 SVs in duplicated regions across the entire 1kGP sample.”
From Comprehensive genome analysis and variant detection at scale using DRAGEN (2025) · cites this paper as [60]
The Results section, “Structural variation across the 3,202 1kGP samples” (page unavailable), reports an overall SV call set but gives no counts for collapsed or duplicated regions. Searches for “collapsed regions,” “duplicated regions,” and “36 SVs 18 SVs” found no passage establishing the claimed regional counts. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Hara, K., Fujita, H., Johnson, T. A., Yamauchi, T., Yasuda, K., Horikoshi, M., Chen, P., Hu, C., Ronald, C. W., Imamura, M., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt399 · Cited by 169 · see citing works
STRetch: detecting and discovering pathogenic short tandem repeat expansions
Dashnow, H., Lek, M., Phipson, B., Halman, A., Sadedin, S., Lonsdale, A., Davis, M. R., Lamont, P. J., Clayton, J. S., Laing, N. G., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1505-2 · Cited by 155 · see citing works
Wham: Identifying Structural Variants of Biological Consequence
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Zhao, X., Collins, R. L., Lee, W.-P., Weber, A. M., Jun, Y., Zhu, Q., Weisburd, B., Huang, Y., Audano, P. A., Wang, H., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.03.014 · Cited by 132 · see citing works
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svtools: population-scale analysis of structural variation
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Self-citationBenchmarking challenging small variants with linked and long readsPreprint
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Applications of the 1000 Genomes Project resources
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Self-citationFine mapping of the celiac disease-associated LPP locus reveals a potential functional variant
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Zhao, X., Weber, A. M., & Mills, R. E. (2017) · GigaScience · doi:10.1093/gigascience/gix061 · Cited by 32 · see citing works
Self-citationde novo variant calling identifies cancer mutation signatures in the 1000 Genomes Project
Ng, J. K., Vats, P., Fritz‐Waters, E., Sarkar, S., Sams, E. I., Padhi, E. M., Payne, Z. L., Leonard, S., West, M. A., Prince, C., et al. (2022) · Human Mutation · doi:10.1002/humu.24455 · Cited by 18 · see citing works
eQTL mapping identifies insertion- and deletion-specific eQTLs in multiple tissues
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de novo variant calling identifies cancer mutation profiles in the 1000 Genomes ProjectPreprint
Ng, J. K., Vats, P., Fritz‐Waters, E., Sarkar, S., Sams, E. I., Padhi, E. M., Payne, Z. L., Leonard, S., West, M. A., Prince, C., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.27.445979 · Cited by 8 · see citing works
Flagged first, then by citations
Cited by
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The complete sequence of a human genome
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Self-citationA draft human pangenome reference.
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Self-citationHaplotype-resolved diverse human genomes and integrated analysis of structural variation
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Self-citationNucleotide Transformer: building and evaluating robust foundation models for human genomics
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Complete genomic and epigenetic maps of human centromeres
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Self-citationA complete reference genome improves analysis of human genetic variation
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Self-citationPangenomics enables genotyping of known structural variants in 5202 diverse genomes
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Ebler, J., Ebert, P., Clarke, W. E., Rausch, T., Audano, P. A., Houwaart, T., Mao, Y., Korbel, J. O., Eichler, E. E., Zody, M. C., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01043-w · Cited by 277 · see citing works
Self-citationLong-Read DNA Sequencing: Recent Advances and Remaining Challenges
Warburton, P. E., & Sebra, R. P. (2023) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-101722-103045 · Cited by 163 · see citing works
Zhao, X., Collins, R. L., Lee, W.-P., Weber, A. M., Jun, Y., Zhu, Q., Weisburd, B., Huang, Y., Audano, P. A., Wang, H., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.03.014 · Cited by 132 · see citing works
Self-citationComprehensive genome analysis and variant detection at scale using DRAGEN
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Gaps and complex structurally variant loci in phased genome assemblies
Porubsky, D., Vollger, M. R., Harvey, W. T., Rozanski, A. N., Ebert, P., Hickey, G., Hasenfeld, P., Sanders, A. D., Stober, C., Human Pangenome Reference Consortium, et al. (2023) · Genome Research · doi:10.1101/gr.277334.122 · Cited by 58 · see citing works
Self-citationHaplotype-based inference of recent effective population size in modern and ancient DNA samples
Fournier, R., Tsangalidou, Z., Reich, D., & Palamara, P. F. (2023) · Nature Communications · doi:10.1038/s41467-023-43522-6 · Cited by 49 · see citing works
Liang, S.-A., Ren, T., Zhang, J., He, J., Wang, X., Jiang, X., He, Y., McCoy, R. C., Fu, Q., Akey, J. M., et al. (2025) · Genome Biology · doi:10.1186/s13059-025-03502-z · Cited by 8 · see citing works
High false sign rates in transcriptome-wide association studies
Gerlach, P. A., Milind, N., Spence, J. P., & Pritchard, J. K. (2026) · Nature Genetics · doi:10.1038/s41588-026-02796-4 · Cited by 1 · see citing works
Message in a bottleneck: Nested founder effects from French Polynesia to Rapa Nui and Hawaiʻi
Shanks, C., Huang, E. C., Thomassin, C., Emde, A.-K., Rodière, V., Moraga, M., Sandoval, K., Merriman, T., Pascart, T., Moreno-Estrada, A., et al. (2026) · Science · doi:10.1126/science.aec7662
A phenome-wide structural variant map from 467,152 UK Biobank genomes
Atanur, S. S., Hu, F., Lou, H., Li, X., Zou, X. Z., O’Dell, S., Deevi, S. V. V., Sawczuk, P., Megy, K., Fairhurst-Hunter, Z., et al. (2026) · Cell · doi:10.1016/j.cell.2026.09.035
- Authors
- Byrska-Bishop, M., Evani, U. S., Zhao, X., Basile, A. O., Abel, H. J., Regier, A. A., Corvelo, A., Clarke, W. E., Musunuri, R., Nagulapalli, K., Fairley, S., Runnels, A., Winterkorn, L., Lowy, E., Eichler, E. E., Korbel, J. O., Lee, C., Marschall, T., Devine, S. E., Harvey, W. T., Zhou, W., Mills, R. E., Rausch, T., Kumar, S., Alkan, C., Hormozdiari, F., Chong, Z., Chen, Y., Yang, X., Lin, J., Gerstein, M. B., Kai, Y., Zhu, Q., Yilmaz, F., Xiao, C., Flicek, P., Germer, S., Brand, H., Hall, I. M., Talkowski, M. E., Narzisi, G., & Zody, M. C.
- Affiliations
- New York Genome Center (US)
- Broad Institute (US)
- Washington University in St. Louis (US)
- European Bioinformatics Institute (GB)
- Corresponding author
- Zody, Michael C.
- ORCID
- Evani, Uday S.
- Zhao, Xuefang
- Basile, Anna O.
- Abel, Haley J.
- Regier, Allison A.
- Corvelo, André
- Clarke, Wayne E.
- Musunuri, Rajeeva
- Fairley, Susan
- Runnels, Alexi
- Winterkorn, Lara
- Lowy, Ernesto
- Eichler, Evan E.
- Korbel, Jan O.
- Lee, Charles
- Marschall, Tobias
- Devine, Scott E.
- Harvey, William T.
- Zhou, Weichen
- Mills, Ryan E.
- Rausch, Tobias
- Kumar, Sushant
- Alkan, Can
- Hormozdiari, Fereydoun
- Chong, Zechen
- Chen, Yu
- Yang, Xiaofei
- Lin, Jiadong
- Gerstein, Mark B.
- Zhu, Qihui
- Yilmaz, Feyza
- Xiao, Chunlin
- Paul Flicek
- Brand, Harrison
- Hall, Ira M.
- Talkowski, Michael E.
- Narzisi, Giuseppe
- Zody, Michael C.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 185
- Issue
- 18
- Pages
- 3426-3440.e19
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC9439720
- OpenAlex
- W4294012180
- Cited by
- 1,094
- References
- 81
- Citations by year
- 2026: 234 · 2025: 301 · 2024: 246 · 2023: 168 · 2022: 104 · 2021: 36 · 2020: 1 · 2019: 1 · 2017: 1 · 2014: 1
- FWCI
- 126.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- SSRN Electronic Journal (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (U24HG007497)
- Wellcome Trust (WT104947/Z/14/Z)
- National Human Genome Research Institute (UM1HG008853, UM1HG008901)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD081256, UM1HG008895)
- National Institute of Mental Health (MH115957)
- U.S. National Library of Medicine
- European Molecular Biology Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- 1000 Genomes Project, trios, single nucleotide variants, structural variants, rare variants, human genetic variation
- MeSH terms
- Whole Genome Sequencing, Female, Humans, Male, Genome, Human, Polymorphism, Single Nucleotide, INDEL Mutation, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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