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Integrating common and rare genetic variation in diverse human populations
Open accessAbstract
Despite great progress in identifying genetic variants that influence human disease, most inherited risk remains unexplained. A more complete understanding requires genome-wide studies that fully examine less common alleles in populations with a wide range of ancestry. To inform the design and interpretation of such studies, we genotyped 1.6 million common single nucleotide polymorphisms (SNPs) in 1,184 reference individuals from 11 global populations, and sequenced ten 100-kilobase regions in 692 of these individuals. This integrated data set of common and rare alleles, called 'HapMap 3', includes both SNPs and copy number polymorphisms (CNPs). We characterized population-specific differences among low-frequency variants, measured the improvement in imputation accuracy afforded by the larger reference panel, especially in imputing SNPs with a minor allele frequency of <or=5%, and demonstrated the feasibility of imputing newly discovered CNPs and SNPs. This expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
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“These validated the HLA association but showed no significant linkage to loci outside the MHC.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [26]
Experimental — accuracy not yet measuredIn the citing paper
“High levels of structural variation, including copy-number variation, were previously described for both processes15,22,39.”
From Mapping copy number variation by population-scale genome sequencing (2011) · cites this paper as [39]
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Initial sequencing and analysis of the human genome
International Human Genome Sequencing Consortium, Whitehead Institute for Biomedical Research, C. F. G. R., Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., Devon, K., Dewar, K., et al. (2001) · Nature · doi:10.1038/35057062 · Cited by 24,216
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Self-citationFinding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Self-citationA second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438
Global variation in copy number in the human genome
Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., et al. (2006) · Nature · doi:10.1038/nature05329 · Cited by 4,377
A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms
The International SNP Map Working Group, Laboratories:, C. S. H., Sachidanandam, R., Weissman, D., Schmidt, S. C., Kakol, J. M., Stein, L. D., National Center for Biotechnology Information:, Marth, G., Sherry, S., et al. (2001) · Nature · doi:10.1038/35057149 · Cited by 2,977
Origins and functional impact of copy number variation in the human genome
The Wellcome Trust Case Control Consortium, Conrad, D. F., Pinto, D., Redon, R., Feuk, L., Gokcumen, O., Zhang, Y., Aerts, J., Andrews, T. D., Barnes, C., et al. (2010) · Nature · doi:10.1038/nature08516 · Cited by 1,970
Self-citationPositive Natural Selection in the Human Lineage
Sabeti, P. C., Schaffner, S. F., Fry, B., Lohmueller, J., Varilly, P., Shamovsky, O., Palma, A., Mikkelsen, T. S., Altshuler, D., & Lander, E. S. (2006) · Science · doi:10.1126/science.1124309 · Cited by 1,157
SLC24A5, a putative cation exchanger, affects pigmentation in zebrafish and humans
Lamason, R. L., Mohideen, M.-A. P. K., Mest, J. R., Wong, A. C., Norton, H. L., Aros, M. C., Jurynec, M. J., Mao, X., Humphreville, V. R., Humbert, J. E., et al. (2005) · Science · doi:10.1126/science.1116238 · Cited by 1,043
Research works printed but not linked: 1
- Li, Y. & Abecasis, G. R. Mach 1.0: rapid haplotype reconstruction and missing genotype inference. Am. J. Hum. Genet. S79, 2290 (2006)
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The GTEx Consortium atlas of genetic regulatory effects across human tissues
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Poplin, R. E., Ruano-Rubio, V., DePristo, M. A., Fennell, T. J., Carneiro, M. O., der Auwera, G. A. V., Kling, D. E., Gauthier, L. D., Levy‐Moonshine, A., Roazen, D., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/201178 · Cited by 1,977
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Elsworth, B., Lyon, M., Alexander, T., Liu, Y., Matthews, P., Hallett, J., Bates, P., Palmer, T., Haberland, V., Smith, G. D., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.10.244293 · Cited by 946
Kukurba, K. R., & Montgomery, S. B. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.top084970 · Cited by 924
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Mardis, E. R. (2011) · Nature · doi:10.1038/nature09796 · Cited by 965
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Green, E. D., & Guyer, M. S. (2011) · Nature · doi:10.1038/nature09764 · Cited by 914
Zheng, J., Erzurumluoglu, A. M., Elsworth, B. L., Kemp, J. P., Howe, L., Haycock, P. C., Hemani, G., Tansey, K., Laurin, C., Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium, et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw613 · Cited by 869
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Reich, D., Patterson, N., Campbell, D., Tandon, A., Mazieres, S., Ray, N., Parra, M. V., Rojas, W., Duque, C., Mesa, N., et al. (2012) · Nature · doi:10.1038/nature11258 · Cited by 696
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Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., Graff, M., Eliasen, A. U., Jiang, Y., Raghavan, S., et al. (2022) · Nature · doi:10.1038/s41586-022-05275-y · Cited by 825
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Gallagher, M. D., & Chen-Plotkin, A. S. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.04.002 · Cited by 822
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Kanai, M., Akiyama, M., Takahashi, A., Matoba, N., Momozawa, Y., Ikeda, M., Iwata, N., Ikegawa, S., Hirata, M., Matsuda, K., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0047-6 · Cited by 801
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Schlötterer, C., Tobler, R., Kofler, R., & Nolte, V. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3803 · Cited by 803
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Vujkovic, M., Keaton, J. M., Lynch, J. A., Miller, D. R., Zhou, J., Tcheandjieu, C., Huffman, J. E., Assimes, T. L., Lorenz, K., Zhu, X., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0637-y · Cited by 741
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Denisova Admixture and the First Modern Human Dispersals into Southeast Asia and Oceania
Reich, D., Patterson, N., Kircher, M., Delfin, F., Nandineni, M. R., Pugach, I., Ko, A. M.-S., Ko, Y.-C., Jinam, T. A., Phipps, M. E., et al. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.09.005 · Cited by 656
Haplotype phasing: existing methods and new developments
Browning, S. R., & Browning, B. L. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3054 · Cited by 681
Francioli, L. C., Menelaou, A., Pulit, S. L., Elbers, C. C., Kloosterman, W. P., van Setten, J., Nijman, I. J., Renkens, I., de Bakker, P. I. W., van Dijk, F., et al. (2014) · Nature Genetics · doi:10.1038/ng.3021 · Cited by 651
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Bhatia, G., Patterson, N., Sankararaman, S., & Price, A. L. (2013) · Genome Research · doi:10.1101/gr.154831.113 · Cited by 612
Fumagalli, M., Sironi, M., Pozzoli, U., Ferrer-Admettla, A., Pattini, L., & Nielsen, R. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002355 · Cited by 600
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Keinan, A., & Clark, A. G. (2012) · Science · doi:10.1126/science.1217283 · Cited by 548
Self-citationGenomic evidence for the Pleistocene and recent population history of Native Americans
Raghavan, M., Steinrücken, M., Harris, K., Schiffels, S., Rasmussen, S., DeGiorgio, M., Albrechtsen, A., Valdiosera, C., Ávila-Arcos, M. C., Malaspinas, A.-S., et al. (2015) · Science · doi:10.1126/science.aab3884 · Cited by 540
Natural selection and infectious disease in human populations
Karlsson, E. K., Kwiatkowski, D. P., & Sabeti, P. C. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3734 · Cited by 546
Evidence for archaic adaptive introgression in humans
Racimo, F., Sankararaman, S., Nielsen, R., & Huerta-Sánchez, E. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3936 · Cited by 521
iPSYCH-Broad Autism Group, Weiner, D. J., Psychiatric Genomics Consortium Autism Group, Wigdor, E. M., Ripke, S., Walters, R. K., Kosmicki, J. A., Grove, J., Samocha, K. E., Goldstein, J. I., et al. (2017) · Nature Genetics · doi:10.1038/ng.3863 · Cited by 516
Greenlandic Inuit show genetic signatures of diet and climate adaptation
Fumagalli, M., Moltke, I., Grarup, N., Racimo, F., Bjerregaard, P., Jørgensen, M. E., Korneliussen, T. S., Gerbault, P., Skotte, L., Linneberg, A. R., et al. (2015) · Science · doi:10.1126/science.aab2319 · Cited by 519
Ishigaki, K., Akiyama, M., Kanai, M., Takahashi, A., Kawakami, E., Sugishita, H., Sakaue, S., Matoba, N., Low, S.-K., Okada, Y., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0640-3 · Cited by 508
Wainschtein, P., Jain, D., Zheng, Z., TOPMed Anthropometry Working Group, Aslibekyan, S. W., Becker, D. M., Bi, W., Brody, J. A., Carlson, J. C., Correa, A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00997-7 · Cited by 519
Quality control and conduct of genome-wide association meta-analyses
Winkler, T. W., Day, F. R., Croteau‐Chonka, D. C., Wood, A. R., Locke, A. E., Mägi, R., Ferreira, T., Fall, T., Graff, M., Justice, A. E., et al. (2014) · Nature Protocols · doi:10.1038/nprot.2014.071 · Cited by 517
Separating endogenous ancient DNA from modern day contamination in a Siberian Neandertal
Skoglund, P., Northoff, B. H., Shunkov, M. V., Derevianko, A. P., Pääbo, S., Krause, J., & Jakobsson, M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1318934111 · Cited by 499
Pasman, J. A., Verweij, K. J. H., Gerring, Z. F., Stringer, S., Sanchez‐Roige, S., Treur, J. L., Abdellaoui, A., Nivard, M. G., Baselmans, B. M. L., Ong, J., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0206-1 · Cited by 505
Genome-wide associations for birth weight and correlations with adult disease
Horikoshi, M., Beaumont, R. N., Day, F. R., Warrington, N. M., Kooijman, M. N., Fernandez-Tajes, J. J., Feenstra, B., van Zuydam, N. R., Gaulton, K. J., Grarup, N., et al. (2016) · Nature · doi:10.1038/nature19806 · Cited by 504
Graur, D., Zheng, Y., Price, N. C., Azevedo, R. B. R., Zufall, R. A., & Elhaik, E. (2013) · Genome Biology and Evolution · doi:10.1093/gbe/evt028 · Cited by 506
The genetics of Mexico recapitulates Native American substructure and affects biomedical traits
Moreno-Estrada, A., Gignoux, C. R., Fernández-López, J. C., Zakharia, F., Sikora, M., Contreras, A. V., Acuña-Alonzo, V., Sandoval, K., Eng, C., Romero-Hidalgo, S., et al. (2014) · Science · doi:10.1126/science.1251688 · Cited by 478
Molecular Diagnosis of Infantile Mitochondrial Disease with Targeted Next-Generation Sequencing
Calvo, S. E., Compton, A. G., Hershman, S. G., Lim, S. C., Lieber, D. S., Tucker, E. J., Laskowski, A., Garone, C., Liu, S., Jaffe, D. B., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003310 · Cited by 476
Genetic adaptation and Neandertal admixture shaped the immune system of human populations
Quach, H., Rotival, M., Pothlichet, J., Loh, Y.-H. E., Dannemann, M., Zidane, N., Laval, G., Patin, E., Harmant, C., Lopez, M., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.024 · Cited by 475
Traylor, M., Farrall, M., Holliday, E. G., Sudlow, C. L. M., Hopewell, J. C., Cheng, Y., Fornage, M., Ikram, M. A., Malik, R., Bevan, S., et al. (2012) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70234-x · Cited by 484
Human Genome Sequencing in Health and Disease
Gonzaga-Jauregui, C. G., Lupski, J. R., & Gibbs, R. A. (2011) · Annual Review of Medicine · doi:10.1146/annurev-med-051010-162644 · Cited by 491
Kranzler, H. R., Zhou, H., Kember, R. L., Vickers‐Smith, R., Justice, A. C., Damrauer, S. M., Tsao, P. S., Klarin, D. M., Baras, A., Reid, J. G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09480-8 · Cited by 482
Genetic diversity fuels gene discovery for tobacco and alcohol use
Saunders, G., Wang, X., Chen, F., Jang, S.-K., Liu, M., Wang, C., Gao, S., Jiang, Y., Khunsriraksakul, C., Otto, J. M., et al. (2022) · Nature · doi:10.1038/s41586-022-05477-4 · Cited by 481
Inferring admixture histories of human populations using linkage disequilibrium
Loh, P.-R., Lipson, M., Patterson, N., Moorjani, P., Pickrell, J. K., Reich, D., & Berger, B. (2013) · Genetics · doi:10.1534/genetics.112.147330 · Cited by 466
Voight, B. F., Kang, H. M., Ding, J., Palmer, C. D., Sidore, C., Chines, P. S., Burtt, N. P., Fuchsberger, C., Li, Y., Erdmann, J., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002793 · Cited by 475
LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms
Money, D., Gardner, K. M., Migicovsky, Z., Schwaninger, H. R., Zhong, G., & Myles, S. (2015) · G3 Genes Genomes Genetics · doi:10.1534/g3.115.021667 · Cited by 483
Assuring the quality of next-generation sequencing in clinical laboratory practice
Gargis, A. S., Kalman, L. V., Berry, M. W., Bick, D. P., Dimmock, D., Hambuch, T. M., Lu, F., Lyon, E., Voelkerding, K. V., Zehnbauer, B. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2403 · Cited by 460
Genomic Variation in Seven Khoe-San Groups Reveals Adaptation and Complex African History
Schlebusch, C. M., Skoglund, P., Sjödin, P., Gattepaille, L. M., Hernandez, D. G., Jay, F., Li, S., de Jongh, M., Singleton, A., Blum, M. G. B., et al. (2012) · Science · doi:10.1126/science.1227721 · Cited by 463
W hats H ap : Weighted Haplotype Assembly for Future-Generation Sequencing Reads
Patterson, M., Marschall, T., Pisanti, N., van Iersel, L., Stougie, L., Klau, G. W., & Schönhuth, A. (2015) · Journal of Computational Biology · doi:10.1089/cmb.2014.0157 · Cited by 453
Mersha, T. B., & Abebe, T. (2015) · Human Genomics · doi:10.1186/s40246-014-0023-x · Cited by 450
Bias correction for inverse variance weighting Mendelian randomization
Mounier, N., & Kutalik, Z. (2023) · Genetic Epidemiology · doi:10.1002/gepi.22522 · Cited by 465
Metadata
- Authors
- The International HapMap 3 Consortium
- Venue
- Nature
- Published
- 2010-09
- Volume
- 467
- Issue
- 7311
- Pages
- 52-58
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3173859
- OpenAlex
- W2107916366
- Cited by
- 3,026
- References
- 26
- Citations by year
- 2026: 101 · 2025: 183 · 2024: 130 · 2023: 129 · 2022: 137 · 2021: 155 · 2020: 156 · 2019: 132 · 2018: 143 · 2017: 172 · 2016: 250 · 2015: 274 · 2014: 309 · 2013: 257 · 2012: 285
- FWCI
- 133.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Archive ouverte UNIGE (University of Geneva) (acceptedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- ANU Open Research (Australian National University) (submittedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (068545/Z/02), 077011, 089062, 082371, 077014, 068545, 091746, 089061, 076113)
- National Human Genome Research Institute (U54HG003273)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK043351)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Keywords
- single nucleotide polymorphisms, copy number variation, imputation accuracy, reference panel, low-frequency variants, human genetic variation
- MeSH terms
- Humans, Genome, Human, Human Genome Project, Polymorphism, Single Nucleotide, Population Groups, DNA Copy Number Variations
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