The 1000 Genomes Project has already elucidated the properties and distribution of common and rare variation, provided insights into the processes that shape genetic diversity, and advanced understanding of disease biology^1,2. This resource provides a benchmark for surveys of human genetic variation and constitutes a key component for human genetic studies, by enabling array design^3,4, genotype imputation⁵, cataloguing of variants in regions of interest, and filtering of likely neutral variants^6,7.

In this final phase, individuals were sampled from 26 populations in Africa (AFR), East Asia (EAS), Europe (EUR), South Asia (SAS), and the Americas (AMR) (Fig. 1a; seeSupplementary Table 1 for population descriptions and abbreviations). All individuals were sequenced using both whole-genome sequencing (mean depth = 7.4×) and targeted exome sequencing (mean depth = 65.7×). In addition, individuals and available first-degree relatives (generally, adult offspring) were genotyped using high-density SNP microarrays. This provided a cost-effective means to discover genetic variants and estimate individual genotypes and haplotypes^1,2.

a, Polymorphic variants within sampled populations. The area of each pie is proportional to the number of polymorphisms within a population. Pies are divided into four slices, representing variants private to a population (darker colour unique to population), private to a continental area (lighter colour shared across continental group), shared across continental areas (light grey), and shared across all continents (dark grey). Dashed lines indicate populations sampled outside of their ancestral continental region.b, The number of variant sites per genome.c, The average number of singletons per genome.

PowerPoint slide

Full size image

In contrast to earlier phases of the project, we expanded analysis beyond bi-allelic events to include multi-allelic SNPs, indels, and a diverse set of structural variants (SVs). An overview of the sample collection, data generation, data processing, and analysis is given inExtended Data Fig. 1. Variant discovery used an ensemble of 24 sequence analysis tools (Supplementary Table 2), and machine-learning classifiers to separate high-quality variants from potential false positives, balancing sensitivity and specificity. Construction of haplotypes started with estimation of long-range phased haplotypes using array genotypes for project participants and, where available, their first degree relatives; continued with the addition of high confidence bi-allelic variants that were analysed jointly to improve these haplotypes; and concluded with the placement of multi-allelic and structural variants onto the haplotype scaffold one at a time (Box 1). Overall, we discovered, genotyped, and phased 88 million variant sites (Supplementary Table 3). The project has now contributed or validated 80 million of the 100 million variants in the public dbSNP catalogue (version 141 includes 40 million SNPs and indels newly contributed by this analysis). These novel variants especially enhance our catalogue of genetic variation within South Asian (which account for 24% of novel variants) and African populations (28% of novel variants).

To control the false discovery rate (FDR) of SNPs and indels at <5%, a variant quality score threshold was defined using high depth (>30×) PCR-free sequence data generated for one individual per population. For structural variants, additional orthogonal methods were used for confirmation, including microarrays and long-read sequencing, resulting in FDR < 5% for deletions, duplications, multi-allelic copy-number variants, Alu and L1 insertions, and <20% for inversions, SVA (SINE/VNTR/Alu) composite retrotransposon insertions and NUMTs⁸ (nuclear mitochondrial DNA variants). To evaluate variant discovery power and genotyping accuracy, we also generated deep Complete Genomics data (mean depth = 47×) for 427 individuals (129 mother–father–child trios, 12 parent–child duos, and 16 unrelateds). We estimate the power to detect SNPs and indels to be >95% and >80%, respectively, for variants with sample frequency of at least 0.5%, rising to >99% and >85% for frequencies >1% (Extended Data Fig. 2). At lower frequencies, comparison with >60,000 European haplotypes from the Haplotype Reference Consortium⁹ suggests 75% power to detect SNPs with frequency of 0.1%. Furthermore, we estimate heterozygous genotype accuracy at 99.4% for SNPs and 99.0% for indels (Supplementary Table 4), a threefold reduction in error rates compared to our previous release², resulting from the larger sample size, improvements in sequence data accuracy, and genotype calling and phasing algorithms.

Box 1: Building a haplotype scaffold

To construct high quality haplotypes that integrate multiple variant types, we adopted a staged approach³⁷. (1) A high-quality ‘haplotype scaffold’ was constructed using statistical methods applied to SNP microarray genotypes (black circles) and, where available, genotypes for first degree relatives (available for∼52% of samples;Supplementary Table 11)³⁸. (2a) Variant sites were identified using a combination of bioinformatic tools and pipelines to define a set of high-confidence bi-allelic variants, including both SNPs and indels (white triangles), which were jointly imputed onto the haplotype scaffold. (2b) Multi-allelic SNPs, indels, and complex variants (represented by yellow shapes, or variation in copy number) were placed onto the haplotype scaffold one at a time, exploiting the local linkage disequilibrium information but leaving haplotypes for other variants undisturbed³⁹. (3) The biallelic and multi-allelic haplotypes were merged into a single haplotype representation. This multi-stage approach allows the long-range structure of the haplotype scaffold to be maintained while including more complex types of variation. Comparison to haplotypes constructed from fosmids suggests the average distance between phasing errors is∼1,062 kb, with typical phasing errors stretching∼37 kb (Supplementary Table 12).

We find that a typical genome differs from the reference human genome at 4.1 million to 5.0 million sites (Fig. 1b andTable 1). Although >99.9% of variants consist of SNPs and short indels, structural variants affect more bases: the typical genome contains an estimated 2,100 to 2,500 structural variants (∼1,000 large deletions,∼160 copy-number variants,∼915 Alu insertions,∼128 L1 insertions,∼51 SVA insertions,∼4 NUMTs, and∼10 inversions), affecting∼20 million bases of sequence.

The total number of observed non-reference sites differs greatly among populations (Fig. 1b). Individuals from African ancestry populations harbour the greatest numbers of variant sites, as predicted by the out-of-Africa model of human origins. Individuals from recently admixed populations show great variability in the number of variants, roughly proportional to the degree of recent African ancestry in their genomes.

The majority of variants in the data set are rare:∼64 million autosomal variants have a frequency <0.5%,∼12 million have a frequency between 0.5% and 5%, and only∼8 million have a frequency >5% (Extended Data Fig. 3a). Nevertheless, the majority of variants observed in a single genome are common: just 40,000 to 200,000 of the variants in a typical genome (1–4%) have a frequency <0.5% (Fig. 1c andExtended Data Fig. 3b). As such, we estimate that improved rare variant discovery by deep sequencing our entire sample would at least double the total number of variants in our sample but increase the number of variants in a typical genome by only∼20,000 to 60,000.

When we restricted analyses to the variants most likely to affect gene function, we found a typical genome contained 149–182 sites with protein truncating variants, 10,000 to 12,000 sites with peptide-sequence-altering variants, and 459,000 to 565,000 variant sites overlapping known regulatory regions (untranslated regions (UTRs), promoters, insulators, enhancers, and transcription factor binding sites). African genomes were consistently at the high end of these ranges. The number of alleles associated with a disease or phenotype in each genome did not follow this pattern of increased diversity in Africa (Extended Data Fig. 4): we observed∼2,000 variants per genome associated with complex traits through genome-wide association studies (GWAS) and 24–30 variants per genome implicated in rare disease through ClinVar; with European ancestry genomes at the high-end of these counts. The magnitude of this difference is unlikely to be explained by demography^10,11, but instead reflects the ethnic bias of current genetic studies. We expect that improved characterization of the clinical and phenotypic consequences of non-European alleles will enable better interpretation of genomes from all individuals and populations.

Systematic analysis of the patterns in which genetic variants are shared among individuals and populations provides detailed accounts of population history. Although most common variants are shared across the world, rarer variants are typically restricted to closely related populations (Fig. 1a); 86% of variants were restricted to a single continental group. Using a maximum likelihood approach¹², we estimated the proportion of each genome derived from several putative ‘ancestral populations’ (Fig. 2a andExtended Data Fig. 5). This analysis separates continental groups, highlights their internal substructure, and reveals genetic similarities between related populations. For example, east–west clines are visible in Africa and East Asia, a north–south cline is visible in Europe, and European, African, and Native-American admixture is visible in genomes sampled in the Americas.

a, Population structure inferred using a maximum likelihood approach with 8 clusters.b, Changes to effective population sizes over time, inferred using PSMC. Lines represent the within-population median PSMC estimate, smoothed by fitting a cubic spline passing through bin midpoints.

PowerPoint slide

Full size image

To characterize more recent patterns of shared ancestry, we first focused on variants observed on just two chromosomes (sample frequency of 0.04%), the rarest shared variants within our sample, and known asf₂ variants². As expected, these variants are typically geographically restricted and much more likely to be shared between individuals in the same population or continental group, or between populations with known recent admixture (Extended Data Fig. 6a, b). Analysis of shared haplotype lengths aroundf₂ variants suggests a median common ancestor∼296 generations ago (7,410 to 8,892 years ago;Extended Data Fig. 6c, d), although those confined within a population tend to be younger, with a shared common ancestor∼143 generations ago (3,570 to 4,284 years ago)¹³.

Modelling the distribution of variation within and between genomes can provide insights about the history and demography of our ancestor populations¹⁴. We used the pairwise sequentially Markovian coalescent (PSMC)¹⁴ method to characterize the effective population size (N_e) of the ancestral populations (Fig. 2b andExtended Data Fig. 7). Our results show a shared demographic history for all humans beyond∼150,000 to 200,000 years ago. Further, they show that European, Asian and American populations shared strong and sustained bottlenecks, all withN_e < 1,500, between 15,000 to 20,000 years ago. In contrast, the bottleneck experienced by African populations during the same time period appears less severe, withN_e > 4,250. These bottlenecks were followed by extremely rapid inferred population growth in non-African populations, with notable exceptions including the PEL, MXL and FIN.

Due to the shared ancestry of all humans, only a modest number of variants show large frequency differences among populations. We observed 762,000 variants that are rare (defined as having frequency <0.5%) within the global sample but much more common (>5% frequency) in at least one population (Fig. 3a). Several populations have relatively large numbers of these variants, and these are typically genetically or geographically distinct within their continental group (LWK in Africa, PEL in the Americas, JPT in East Asia, FIN in Europe, and GIH in South Asia; seeSupplementary Table 5). Drifted variants within such populations may reveal phenotypic associations that would be hard to identify in much larger global samples¹⁵.

a, Variants found to be rare (<0.5%) within the global sample, but common (>5%) within a population.b, Genes showing strong differentiation between pairs of closely related populations. The vertical axis gives the maximum obtained value of theF_ST-based population branch statistic (PBS), with selected genes coloured to indicate the population in which the maximum value was achieved.

PowerPoint slide

Full size image

Analysis of the small set of variants with large frequency differences between closely related populations can identify targets of recent, localized adaptation. We used theF_ST-based population branch statistic (PBS)¹⁶ to identify genes with strong differentiation between pairs of populations in the same continental group (Fig. 3b). This approach reveals a number of previously identified selection signals (such asSLC24A5 associated with skin pigmentation¹⁷,HERC2 associated with eye colour¹⁸,LCT associated with lactose tolerance, and theFADS cluster that may be associated with dietary fat sources¹⁹). Several potentially novel selection signals are also highlighted (such asTRBV9, which appears particularly differentiated in South Asia,PRICKLE4, differentiated in African and South Asian populations, and a number of genes in the immunoglobulin cluster, differentiated in East Asian populations;Extended Data Fig. 8), although at least some of these signals may result from somatic rearrangements (for example, via V(D)J recombination) and differences in cell type composition among the sequenced samples. Nonetheless, the relatively small number of genes showing strong differentiation between closely related populations highlights the rarity of strong selective sweeps in recent human evolution²⁰.

The sharing of haplotypes among individuals is widely used for imputation in GWAS, a primary use of 1000 Genomes data. To assess imputation based on the phase 3 data set, we used Complete Genomics data for 9 or 10 individuals from each of 6 populations (CEU, CHS, LWK, PEL, PJL, and YRI). After excluding these individuals from the reference panel, we imputed genotypes across the genome using sites on a typical one million SNP microarray. The squared correlation between imputed and experimental genotypes was >95% for common variants in each population, decreasing gradually with minor allele frequency (Fig. 4a). Compared to phase 1, rare variation imputation improved considerably, particularly for newly sampled populations (for example, PEL and PJL,Extended Data Fig. 9a). Improvements in imputations restricted to overlapping samples suggest approximately equal contributions from greater genotype and sequence quality and from increased sample size (Fig. 4a, inset). Imputation accuracy is now similar for bi-allelic SNPs, bi-allelic indels, multi-allelic SNPs, and sites where indels and SNPs overlap, but slightly reduced for multi-allelic indels, which typically map to regions of low-complexity sequence and are much harder to genotype and phase (Extended Data Fig. 9b). Although imputation of rare variation remains challenging, it appears to be most accurate in African ancestry populations, where greater genetic diversity results in a larger number of haplotypes and improves the chances that a rare variant is tagged by a characteristic haplotype.

a, Imputation accuracy as a function of allele frequency for six populations. The insert compares imputation accuracy between phase 3 and phase 1, using all samples (solid lines) and intersecting samples (dashed lines).b, The average number of tagging variants (r² > 0.8) as a function of physical distance for common (top), low frequency (middle), and rare (bottom) variants.c, The proportion of top eQTL variants that are SNPs and indels, as discovered in 69 samples from each population.d, The percentage of eQTLs in TFBS, having performed discovery in the first population, and fine mapped by including an additional 69 samples from a second population (*P < 0.01, **P < 0.001, ***P < 0.0001, McNemar’s test). The diagonal represents the percentage of eQTLs in TFBS using the original discovery sample.

PowerPoint slide

Full size image

To evaluate the impact of our new reference panel on GWAS, we re-analysed a previous study of age-related macular degeneration (AMD) totalling 2,157 cases and 1,150 controls²¹. We imputed 17.0 million genetic variants with estimatedR² > 0.3, compared to 14.1 million variants using phase 1, and only 2.4 million SNPs using HapMap2. Compared to phase 1, the number of imputed common and intermediate frequency variants increased by 7%, whereas the number of rare variants increased by >50%, and the number of indels increased by 70% (Supplementary Table 6). We permuted case-control labels to estimate a genome-wide significance threshold ofP <∼1.5 × 10⁻⁸, which corresponds to∼3 million independent variants and is more stringent than the traditional threshold of 5 × 10⁻⁸ (Supplementary Table 7). In practice, significance thresholds must balance false positives and false negatives^22,23,24. We recommend that thresholds aiming for strict control of false positives should be determined using permutations. We expect thresholds to become more stringent when larger sample sizes are sequenced, when diverse samples are studied, or when genotyping and imputation is replaced with direct sequencing. After imputation, five independent signals in four previously reported AMD loci^25,26,27,28 reached genome-wide significance (Supplementary Table 8). When we examined each of these to define a set of potentially causal variants using a Bayesian Credible set approach²⁹, lists of potentially functional variants were∼4× larger than in HapMap2-based analysis and 7% larger than in analyses based on phase 1 (Supplementary Table 9). In theARMS2/HTRA1 locus, the most strongly associated variant was now a structural variant (estimated imputationR² = 0.89) that previously could not be imputed, consistent with some functional studies³⁰. Deep catalogues of potentially functional variants will help ensure that downstream functional analyses include the true candidate variants, and will aid analyses that integrate complex disease associations with functional genomic elements³¹.

The performance of imputation and GWAS studies depends on the local distribution of linkage disequilibrium (LD) between nearby variants. Controlling for sample size, the decay of LD as a function of physical distance is fastest in African populations and slowest in East Asian populations (Extended Data Fig. 10). To evaluate how these differences influence the resolution of genetic association studies and, in particular, their ability to identify a narrow set of candidate functional variants, we evaluated the number of tagging variants (r² > 0.8) for a typical variant in each population. We find that each common variant typically has over 15–20 tagging variants in non-African populations, but only about 8 in African populations (Fig. 4b). At lower frequencies, we find 3–6 tagging variants with 100 kb of variants with frequency <0.5%, and differences in the number of tagging variants between continental groups are less marked.

Among variants in the GWAS catalogue (which have an average frequency of 26.6% in project haplotypes), the number of proxies averages 14.4 in African populations and 30.3–44.4 in other continental groupings (Supplementary Table 10). The potential value of multi-population fine-mapping is illustrated by the observation that the number of proxies shared across all populations is only 8.2 and, furthermore, that 34.9% of GWAS catalogue variants have no proxy shared across all continental groupings.

To further assess prospects for fine-mapping genetic association signals, we performed expression quantitative trait loci (eQTL) discovery at 17,667 genes in 69 samples from each of 6 populations (CEU, CHB, GIH, JPT, LWK, and YRI)³². We identified eQTLs for 3,285 genes at 5% FDR (average 1,265 genes per population). Overall, a typical eQTL signal comprised 67 associated variants, including an indel as one of the top associated variants 26–40% of the time (Fig. 4c). Within each discovery population, 17.5–19.5% of top eQTL variants overlapped annotated transcription factor binding sites (TFBSs), consistent with the idea that a substantial fraction of eQTL polymorphisms are TFBS polymorphisms. Using a meta-analysis approach to combine pairs of populations, the proportion of top eQTL variants overlapping TFBSs increased to 19.2–21.6% (Fig. 4d), consistent with improved localization. Including an African population provided the greatest reduction in the count of associated variants and the greatest increase in overlap between top variants and TFBSs.

Over the course of the 1000 Genomes Project there have been substantial advances in sequence data generation, archiving and analysis. Primary sequence data production improved with increased read length and depth, reduced per-base errors, and the introduction of paired-end sequencing. Sequence analysis methods improved with the development of strategies for identifying and filtering poor-quality data, for more accurate mapping of sequence reads (particularly in repetitive regions), for exchanging data between analysis tools and enabling ensemble analyses, and for capturing more diverse types of variants. Importantly, each release has examined larger numbers of individuals, aiding population-based analyses that identify and leverage shared haplotypes during genotyping. Whereas our first analyses produced high-confidence short-variant calls for 80–85% of the reference genome¹, our newest analyses reach∼96% of the genome using the same metrics, although our ability to accurately capture structural variation remains more limited³³. In addition, the evolution of sequencing, analysis and filtering strategies means that our results are not a simple superset of previous analysis. Although the number of characterized variants has more than doubled relative to phase 1,∼2.3 million previously described variants are not included in the current analysis; most missing variants were rare or marked as low quality: 1.6 million had frequency <0.5% and may be missing from our current read set, while the remainder were removed by our filtering processes.

These same technical advances are enabling the application of whole genome sequencing to a variety of medically important samples. Some of these studies already exceed the 1000 Genomes Project in size^34,35,36, but the results described here remain a prime resource for studies of genetic variation for several reasons. First, the 1000 Genomes Project samples provide a broad representation of human genetic variation—in contrast to the bulk of complex disease studies in humans, which primarily study European ancestry samples and which, as we show, fail to capture functionally important variation in other populations. Second, the project analyses incorporate multiple analysis strategies, callsets and variant types. Although such ensemble analyses are cumbersome, they provide a benchmark for what can be achieved and a yardstick against which more practical analysis strategies can be evaluated. Third, project samples and data resulting from them can be shared broadly, enabling sequencing strategies and analysis methods to be compared easily on a benchmark set of samples. Because of the wide availability of the data and samples, these samples have been and will continue to be used for studying many molecular phenotypes. Thus, we predict that the samples will accumulate many types of data that will allow connections to be drawn between variants and both molecular and disease phenotypes.

We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Dökel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche du Québec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute.

1. Leena Peltonen: Deceased

Authors and Affiliations

1. Department of Genetics, Albert Einstein College of Medicine, Bronx, 10461, New York, USA

   Adam Auton, Adam Auton (Principal Investigator), Christopher L. Campbell, Yu Kong, Anthony Marcketta, Adam Auton (Principal Investigator), Anthony Marcketta & Adam Auton

2. Center for Statistical Genetics, Biostatistics, University of Michigan, Ann Arbor, 48109, Michigan, USA

   Gonçalo R. Abecasis, Gonçalo R. Abecasis, Gonçalo R. Abecasis (Principal Investigator) (Co-Chair), Hyun Min Kang (Project Leader), Tom Blackwell, Sean Caron, Lars Fritsche, Christian Fuchsberger, Goo Jun, Chris Scheller, Carlo Sidore, Daniel Taliun, Adrian Tan, Ryan Welch, Mary Kate Wing, Gonçalo R. Abecasis (Principal Investigator), Goo Jun, Gonçalo R. Abecasis (Principal Investigator), Hyun Min Kang, Gonçalo R. Abecasis (Principal Investigator), Gonçalo R. Abecasis (Principal Investigator), Gonçalo R. Abecasis, Hyun Min Kang & Gonçalo R. Abecasis

3. Vertex Pharmaceuticals, Boston, 02210, Massachusetts, USA

   David M. Altshuler (Co-Chair), David M. Altshuler, David M. Altshuler, David M. Altshuler & David M. Altshuler

4. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK

   Richard M. Durbin (Co-Chair), Matthew E. Hurles, Richard M. Durbin (Principal Investigator), Senduran Balasubramaniam, John Burton, Petr Danecek, Thomas M. Keane, Anja Kolb-Kokocinski, Shane McCarthy, James Stalker, Michael Quail, Erik P. Garrison (Project Lead), Richard M. Durbin (Principal Investigator), Matthew E. Hurles (Principal Investigator), Chris Tyler-Smith (Principal Investigator), Qasim Ayub, Senduran Balasubramaniam, Yuan Chen, Vincenza Colonna, Petr Danecek, Thomas M. Keane, Shane McCarthy, Klaudia Walter, Yali Xue, Erik P. Garrison, Matthew E. Hurles (Principal Investigator), Ben Blackburne, Sarah J. Lindsay, Zemin Ning, Klaudia Walter, Yujun Zhang, Erik P. Garrison, Chris Tyler-Smith (Principal Investigator) (Co-Chair), Yuan Chen, Vincenza Colonna, Yali Xue, Erik P. Garrison, Chris Tyler-Smith (Principal Investigator) (Co-Chair), Qasim Ayub, Ruby Banerjee, Maria Cerezo, Yuan Chen, Thomas W. Fitzgerald, Sandra Louzada, Andrea Massaia, Shane McCarthy, Graham R. Ritchie, Yali Xue, Fengtang Yang, Richard M. Durbin (Principal Investigator), Senduran Balasubramaniam, Thomas M. Keane, Shane McCarthy, James Stalker, Richard M. Durbin, Chris Tyler-Smith, Richard M. Durbin, Erik P. Garrison & Shane McCarthy

5. Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, CB10 1XL, Essex, UK

   David R. Bentley, David R. Bentley (Principal Investigator), Russell Grocock, Sean Humphray, Terena James, Zoya Kingsbury, David R. Bentley (Principal Investigator), Markus Bauer, R. Keira Cheetham, Anthony Cox, Michael Eberle, Sean Humphray, Lisa Murray, John Peden, Richard Shaw, David R. Bentley (Principal Investigator), R. Keira Cheetham, Michael Eberle, Sean Humphray, Lisa Murray, Richard Shaw, David R. Bentley (Principal Investigator), Anthony Cox & Sean Humphray

6. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21205, Maryland, USA

   Aravinda Chakravarti & Aravinda Chakravarti (Co-Chair)

7. Center for Comparative and Population Genomics, Cornell University, Ithaca, 14850, New York, USA

   Andrew G. Clark, Andrew G. Clark (Principal Investigator), Alon Keinan, Jeremiah Degenhardt, Andrew G. Clark (Principal Investigator) & Alon Keinan

8. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK

   Peter Donnelly, Gil A. McVean, Gil A. McVean (Principal Investigator), Gerton Lunter (Principal Investigator), Gil A. McVean (Principal Investigator) (Co-Chair), Jonathan L. Marchini (Principal Investigator), Simon Myers (Principal Investigator), Anjali Gupta-Hinch, Warren Kretzschmar, Zamin Iqbal, Iain Mathieson, Dionysia K. Xifara, Luke Jostins, Gerton Lunter (Principal Investigator), Gil A. McVean (Principal Investigator), Gil A. McVean (Principal Investigator), Gil A. McVean (Principal Investigator), Gil A. McVean, Muminatou Jallow, Fatoumatta Sisay Joof, Tumani Corrah, Kirk Rockett, Dominic Kwiatkowski, Jonathan L. Marchini & Gil A. McVean

9. Department of Statistics, University of Oxford, Oxford, OX1 3TG, UK

   Peter Donnelly, Gil A. McVean, Gil A. McVean (Principal Investigator), Gil A. McVean (Principal Investigator) (Co-Chair), Jonathan L. Marchini (Principal Investigator), Simon Myers (Principal Investigator), Claire Churchhouse, Olivier Delaneau, Androniki Menelaou, Dionysia K. Xifara, Gil A. McVean (Principal Investigator), Gil A. McVean (Principal Investigator), Gil A. McVean (Principal Investigator), Gil A. McVean, Jonathan L. Marchini & Gil A. McVean

10. Department of Genome Sciences, University of Washington School of Medicine, Seattle, 98195, Washington, USA

    Evan E. Eichler, Deborah A. Nickerson, Evan E. Eichler (Principal Investigator), Fereydoun Hormozdiari, Peter H. Sudmant, Evan E. Eichler (Principal Investigator) (Co-Chair), Mark J. Chaisson, Fereydoun Hormozdiari, John Huddleston, Maika Malig, Bradley J. Nelson & Peter H. Sudmant

11. Howard Hughes Medical Institute, University of Washington, Seattle, 98195, Washington, USA

    Evan E. Eichler, Evan E. Eichler (Principal Investigator), Evan E. Eichler (Principal Investigator) (Co-Chair) & John Huddleston

12. European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK

    Paul Flicek, Jan O. Korbel, Paul Flicek (Principal Investigator), Jonathan Barker, Laura Clarke, Laurent Gil, Sarah E. Hunt, Gavin Kelman, Eugene Kulesha, Rasko Leinonen, William M. McLaren, Rajesh Radhakrishnan, Asier Roa, Dmitriy Smirnov, Richard E. Smith, Ian Streeter, Anja Thormann, Iliana Toneva, Brendan Vaughan, Xiangqun Zheng-Bradley, Jan O. Korbel (Principal Investigator), Paul Flicek (Principal Investigator), Kathryn Beal, Laura Clarke, Avik Datta, William M. McLaren, Graham R. S. Ritchie, Richard E. Smith, Daniel Zerbino, Xiangqun Zheng-Bradley, Jan O. Korbel (Principal Investigator) (Co-Chair), Paul Flicek (Principal Investigator), Francesco Paolo Casale, Laura Clarke, Richard E. Smith, Oliver Stegle, Xiangqun Zheng-Bradley, Paul Flicek (Principal Investigator), Laura Clarke, Richard E. Smith, Xiangqun Zheng-Bradley, Paul Flicek (Principal Investigator), Laura Clarke, Fiona Cunningham, Ian Dunham, Daniel Zerbino, Xiangqun Zheng-Bradley, Paul Flicek (Principal Investigator), Laura Clarke, Xiangqun Zheng-Bradley, Paul Flicek (Principal Investigator) (Co-Chair), Laura Clarke (Project Lead), Xiangqun Zheng-Bradley & Jan O. Korbel

13. The Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, 02142, Massachusetts, USA

    Stacey B. Gabriel, Eric S. Lander, Eric S. Lander (Principal Investigator), Stacey B. Gabriel (Co-Chair), Namrata Gupta, Mark J. Daly (Principal Investigator), Robert E. Handsaker (Project Leader), Eric Banks, Gaurav Bhatia, Guillermo del Angel, Stacey B. Gabriel, Giulio Genovese, Namrata Gupta, Heng Li, Seva Kashin, Eric S. Lander, Steven A. McCarroll, James C. Nemesh, Ryan E. Poplin, Pardis C. Sabeti (Principal Investigator), Ilya Shlyakhter, Stephen F. Schaffner, Joseph Vitti, Melissa Gymrek, Xinmeng Jasmine Mu, Steven A. McCarroll (Principal Investigator), Robert E. Handsaker (Project Leader), Eric Banks, Guillermo del Angel, Giulio Genovese, Chris Hartl, Heng Li, Seva Kashin, James C. Nemesh, Khalid Shakir, Xinmeng Jasmine Mu, Guillermo del Angel, Stacey B. Gabriel, Namrata Gupta, Chris Hartl, Ryan E. Poplin, Kasper Lage (Principal Investigator), Jakob Berg Jespersen, Heiko Horn, Robert E. Handsaker, Seva Kashin, Steven A. McCarroll, Melissa Gymrek, Pardis C. Sabeti, Pardis C. Sabeti, Matt Stremlau, Ridhi Tariyal & Pardis C. Sabeti

14. Baylor College of Medicine, Human Genome Sequencing Center, Houston, 77030, Texas, USA

    Richard A. Gibbs, Richard A. Gibbs (Principal Investigator), Eric Boerwinkle, Harsha Doddapaneni, Yi Han, Viktoriya Korchina, Christie Kovar, Sandra Lee, Donna Muzny, Jeffrey G. Reid, Yiming Zhu, Richard A. Gibbs (Principal Investigator), Fuli Yu (Project Leader), Lilian Antunes, Matthew Bainbridge, Donna Muzny, Aniko Sabo, Zhuoyi Huang, Richard A. Gibbs (Principal Investigator) (Co-Chair), Fuli Yu (Project Leader), Matthew Bainbridge, Danny Challis, Uday S. Evani, Christie Kovar, James Lu, Donna Muzny, Uma Nagaswamy, Jeffrey G. Reid, Aniko Sabo, Jin Yu, Richard A. Gibbs (Principal Investigator), Christie Kovar, Divya Kalra, Walker Hale, Donna Muzny, Jeffrey G. Reid & Richard A. Gibbs

15. US National Institutes of Health, National Human Genome Research Institute, 31 Center Drive, Bethesda, 20892, Maryland, USA

    Eric D. Green & Eric D. Green

16. Centre of Genomics and Policy, McGill University, Montreal, H3A 1A4, Quebec, Canada

    Bartha M. Knoppers & Bartha M. Knoppers (Co-Chair)

17. European Molecular Biology Laboratory, Genome Biology Research Unit, Meyerhofstr. 1, Heidelberg, Germany

    Jan O. Korbel, Jan O. Korbel (Principal Investigator), Tobias Rausch (Project Leader), Adrian M. Stütz, Jan O. Korbel (Principal Investigator) (Co-Chair), Sascha Meiers, Benjamin Raeder, Tobias Rausch, Adrian M. Stütz & Jan O. Korbel

18. The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, 06032, Connecticut, USA

    Charles Lee, Charles Lee (Principal Investigator), Eliza Cerveira, Jaeho Hwang, Ankit Malhotra (Co-Project Lead), Dariusz Plewczynski, Kamen Radew, Mallory Romanovitch, Chengsheng Zhang (Co-Project Lead), Charles Lee (Principal Investigator) (Co-Chair), Eliza Cerveira, Ankit Malhotra, Jaeho Hwang, Dariusz Plewczynski, Kamen Radew, Mallory Romanovitch, Chengsheng Zhang, Charles Lee, Eliza Cerveira, Ankit Malhotra, Mallory Romanovitch & Chengsheng Zhang

19. Department of Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, Seoul, South Korea, 120-750

    Charles Lee, Charles Lee (Principal Investigator), Charles Lee (Principal Investigator) (Co-Chair) & Charles Lee

20. Max Planck Institute for Molecular Genetics, D-14195 Berlin-Dahlem, Germany

    Hans Lehrach, Hans Lehrach (Principal Investigator), Vyacheslav S. Amstislavskiy, Matthias Lienhard, Florian Mertes, Marc Sultan, Bernd Timmermann, Marie-Laure Yaspo, Vyacheslav S. Amstislavskiy, Ralf Herwig & Matthias Lienhard

21. Dahlem Centre for Genome Research and Medical Systems Biology, D-14195 Berlin-Dahlem, Germany

    Hans Lehrach & Hans Lehrach (Principal Investigator)

22. McDonnell Genome Institute at Washington University, Washington University School of Medicine, St Louis, 63108, Missouri, USA

    Elaine R. Mardis, Richard K. Wilson, Elaine R. Mardis (Co-Principal Investigator) (Co-Chair), Richard K. Wilson (Co-Principal Investigator), Lucinda Fulton, Robert Fulton, Elaine R. Mardis (Co-Principal Investigator), Li Ding, Daniel C. Koboldt, David Larson, Kai Ye, Li Ding (Principal Investigator), Ira Hall, Kai Ye, Elaine R. Mardis (Principal Investigator), Robert Fulton, Daniel C. Koboldt & David Larson

23. USTAR Center for Genetic Discovery & Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, 84112, Utah, USA

    Gabor T. Marth, Gabor T. Marth (Principal Investigator), Alistair N. Ward, Gabor T. Marth (Principal Investigator), Alistair N. Ward, Jiantao Wu, Mengyao Zhang, Gabor T. Marth (Principal Investigator) (Co-Chair), Wen Fung Leong & Alistair N. Ward

24. Affymetrix, Santa Clara, California, 95051, USA

    Jeanette P. Schmidt, Jeanette P. Schmidt (Principal Investigator), Christopher J. Davies, Jeremy Gollub, Teresa Webster, Brant Wong & Yiping Zhan

25. US National Institutes of Health, National Center for Biotechnology Information, 45 Center Drive, Bethesda, 20892, Maryland, USA

    Stephen T. Sherry, Stephen T. Sherry (Principal Investigator), Victor Ananiev, Zinaida Belaia, Dimitriy Beloslyudtsev, Nathan Bouk, Chao Chen, Robert Cohen, Charles Cook, John Garner, Timothy Hefferon, Mikhail Kimelman, Chunlei Liu, John Lopez, Peter Meric, Yuri Ostapchuk, Lon Phan, Sergiy Ponomarov, Valerie Schneider, Eugene Shekhtman, Karl Sirotkin, Douglas Slotta, Hua Zhang, Stephen T. Sherry (Principal Investigator), Chunlin Xiao, Chunlin Xiao, Stephen T. Sherry (Principal Investigator), Chunlin Xiao, Stephen T. Sherry (Principal Investigator) (Co-Chair) & Chunlin Xiao

26. BGI-Shenzhen, Shenzhen 518083, China

    Jun Wang, Jun Wang (Principal Investigator), Yuqi Chang, Qiang Feng, Xiaodong Fang, Xiaosen Guo, Min Jian, Hui Jiang, Xin Jin, Tianming Lan, Guoqing Li, Jingxiang Li, Yingrui Li, Shengmao Liu, Xiao Liu, Yao Lu, Xuedi Ma, Meifang Tang, Bo Wang, Guangbiao Wang, Honglong Wu, Renhua Wu, Xun Xu, Ye Yin, Dandan Zhang, Wenwei Zhang, Jiao Zhao, Meiru Zhao, Xiaole Zheng, Jun Wang (Principal Investigator), Lachlan J. M. Coin, Lin Fang, Xiaosen Guo, Xin Jin, Guoqing Li, Qibin Li, Yingrui Li, Zhenyu Li, Haoxiang Lin, Binghang Liu, Ruibang Luo, Haojing Shao, Yinlong Xie, Chen Ye, Chang Yu, Fan Zhang, Hancheng Zheng, Hongmei Zhu, Yingrui Li, Ruibang Luo, Hongmei Zhu, Xiaosen Guo, Wangshen Li, Yingrui Li, Renhua Wu, Jun Wang (Principal Investigator), Xu Dan, Xiaosen Guo, Guoqing Li, Yingrui Li, Chen Ye, Xiaole Zheng, Hongyu Cai, Hongzhi Cao, Yingrui Li, Yeyang Su, Zhongming Tian, Yuhong Wang, Huanming Yang, Ling Yang, Jiayong Zhu, Zhiming Cai, Jiayong Zhu, Jun Wang & Huanming Yang

27. Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen, 2200, Denmark

    Jun Wang, Jun Wang (Principal Investigator), Qiang Feng, Xiaodong Fang, Xiaosen Guo, Min Jian, Hui Jiang, Xiao Liu, Jun Wang (Principal Investigator), Lin Fang, Xiaosen Guo, Jun Wang (Principal Investigator), Xiaosen Guo, Hongzhi Cao & Jun Wang

28. Princess Al Jawhara Albrahim Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah, 80205, Saudi Arabia

    Jun Wang, Jun Wang (Principal Investigator), Jun Wang (Principal Investigator), Jun Wang (Principal Investigator) & Jun Wang

29. Macau University of Science and Technology, Avenida Wai long, Taipa, 999078, Macau, China

    Jun Wang, Jun Wang (Principal Investigator), Jun Wang (Principal Investigator), Jun Wang (Principal Investigator) & Jun Wang

30. Department of Medicine and State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, 21 Sassoon Road, Hong Kong

    Jun Wang, Jun Wang (Principal Investigator), Jun Wang (Principal Investigator), Jun Wang (Principal Investigator) & Jun Wang

31. Coriell Institute for Medical Research, Camden, 08103, New Jersey, USA

    Neda Gharani, Lorraine H. Toji, Norman P. Gerry, Alissa M. Resch, Christine Beiswanger, Norman P. Gerry, Neda Gharani, Alissa M. Resch & Lorraine H. Toji

32. European Centre for Public Heath Genomics, UNU-MERIT, Maastricht University, PO Box 616, Maastricht, 6200, MD, The Netherlands

    Ralf Sudbrak (Project Leader), Ralf Sudbrak (Project Leader), Ralf Sudbrak (Project Lead) & Ralf Sudbrak

33. Alacris Theranostics, D-14195 Berlin-Dahlem, Germany

    Marcus W. Albrecht, Tatiana A. Borodina & Marcus W. Albrecht

34. Personalis, Menlo Park, California, 94025, USA

    Deanna Church & Deanna Church

35. US National Institutes of Health, National Human Genome Research Institute, 50 South Drive, Bethesda, 20892, Maryland, USA

    Chris O’Sullivan

36. Department of Computer Engineering, Bilkent University, Bilkent, TR-06800, Ankara, Turkey

    Can Alkan, Elif Dal, Fatma Kahveci, Can Alkan, Elif Dal & Fatma Kahveci

37. Seven Bridges Genomics, 1 Broadway, 14th floor, Cambridge, 02142, Massachusetts, USA

    Deniz Kural, Wan-Ping Lee, Deniz Kural & Wan-Ping Lee

38. Department of Agronomy, Kansas State University, Manhattan, 66506, Kansas, USA

    Wen Fung Leong

39. Illumina, San Diego, 92122, California, USA

    Michael Stromberg, Jiantao Wu, Bret Barnes, Scott Kahn, Bret Barnes, Scott Kahn & Scott Kahn

40. Department of Genetics, Harvard Medical School, Cambridge, 02142, Massachusetts, USA

    Mengyao Zhang, Robert E. Handsaker (Project Leader), Seva Kashin, Steven A. McCarroll, Steven A. McCarroll (Principal Investigator), Robert E. Handsaker (Project Leader), Seva Kashin, Robert E. Handsaker, Seva Kashin & Steven A. McCarroll

41. SynapDx, Four Hartwell Place, Lexington, 02421, Massachusetts, USA

    Mark A. DePristo (Project Leader) & Mark A. DePristo

42. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, 11724, USA

    Seungtai C. Yoon (Principal Investigator), Jayon Lihm, Seungtai C. Yoon (Principal Investigator) & Jayon Lihm

43. Seaver Autism Center and Department of Psychiatry, Mount Sinai School of Medicine, New York, 10029, New York, USA

    Vladimir Makarov & Vladimir Makarov

44. Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, 14853, New York, USA

    Srikanth Gottipati, Haiyuan Yu (Principal Investigator) & Danielle Jones

45. Department of Genetic Medicine, Weill Cornell Medical College, New York, 10044, New York, USA

    Juan L. Rodriguez-Flores, Juan L. Rodriguez-Flores & Juan L. Rodriguez-Flores

46. European Molecular Biology Laboratory, Genomics Core Facility, Meyerhofstrasse 1, Heidelberg, 69117, Germany

    Tobias Rausch (Project Leader), Markus H. Fritz, Markus H. Fritz & Tobias Rausch

47. Bill Lyons Informatics Centre, UCL Cancer Institute, University College London, London, WC1E 6DD, UK

    Javier Herrero

48. Center for Systems Biology and Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, 02138, Massachusetts, USA

    Pardis C. Sabeti (Principal Investigator), Ilya Shlyakhter, Stephen F. Schaffner, Pardis C. Sabeti, Pardis C. Sabeti, Matt Stremlau, Ridhi Tariyal & Pardis C. Sabeti

49. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, 02138, Massachusetts, USA

    Joseph Vitti

50. Institute of Medical Genetics, School of Medicine, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK

    David N. Cooper (Principal Investigator), Edward V. Ball & Peter D. Stenson

51. Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, 10029-6574, New York, USA

    Eimear E. Kenny (Principal Investigator)

52. Department of Biological Sciences, Louisiana State University, Baton Rouge, 70803, Louisiana, USA

    Mark A. Batzer (Principal Investigator), Miriam K. Konkel, Jerilyn A. Walker, Mark A. Batzer (Principal Investigator), Miriam K. Konkel & Jerilyn A. Walker

53. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

    Daniel G. MacArthur (Principal Investigator), Monkol Lek & Daniel G. MacArthur (Principal Investigator)

54. McGill University and Genome Quebec Innovation Centre, 740, Avenue du Dr. Penfield, Montreal, H3A 0G1, Quebec, Canada

    Simon Gravel, Simon Gravel & Simon Gravel

55. National Eye Institute, National Institutes of Health, Bethesda, 20892, Maryland, USA

    Anand Swaroop & Emily Chew

56. New York Genome Center, 101 Avenue of the Americas, 7th floor, New York, 10013, New York, USA

    Tuuli Lappalainen (Principal Investigator), Yaniv Erlich (Principal Investigator), Melissa Gymrek, Yaniv Erlich & Melissa Gymrek

57. Department of Systems Biology, Columbia University, New York, 10032, NY, USA

    Tuuli Lappalainen (Principal Investigator)

58. Department of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, New York, USA

    Yaniv Erlich (Principal Investigator) & Yaniv Erlich

59. Harvard–MIT Division of Health Sciences and Technology, Cambridge, 02139, Massachusetts, USA

    Melissa Gymrek & Melissa Gymrek

60. General Hospital and Harvard Medical School, Boston, 02114, Massachusetts, USA

    Melissa Gymrek & Melissa Gymrek

61. Whitehead Institute for Biomedical Research, Nine Cambridge Center, Cambridge, 02142, Massachusetts, USA

    Thomas Frederick Willems & Thomas Frederick Willems

62. Ontario Institute for Cancer Research, MaRS Centre, 661 University Avenue, Suite 510, Toronto, M5G 0A3, Ontario, Canada

    Jared T. Simpson & Philip Awadalla (Principal Investigator)

63. Department of Anthropology, Penn State University, University Park, Pennsylvania, 16802, USA

    Mark D. Shriver (Principal Investigator)

64. Rutgers Cancer Institute of New Jersey, New Brunswick, 08903, New Jersey, USA

    Jeffrey A. Rosenfeld (Principal Investigator) & Carlos D. Bustamante (Principal Investigator)

65. Department of Genetics, Stanford University, Stanford, 94305, California, USA

    Francisco M. De La Vega (Principal Investigator), Phil Lacroute, Brian K. Maples, Alicia R. Martin, Andres Moreno-Estrada, Suyash S. Shringarpure, Fouad Zakharia, Phil Lacroute, Carlos D. Bustamante (Principal Investigator), Carlos D. Bustamante (Principal Investigator) (Co-Chair), Fernando L. Mendez, Peter A. Underhill, Carlos D. Bustamante, Andres Moreno-Estrada & Karla Sandoval

66. Departments of Genetics and Pathology, Stanford University, Stanford, 94305-5324, California, USA

    Stephen B. Montgomery (Principal Investigator), Marianne K. DeGorter, Stephen B. Montgomery (Principal Investigator) & Marianne K. DeGorter

67. Ancestry.com, San Francisco, 94107, California, USA

    Jake K. Byrnes

68. DNAnexus, 1975 West El Camino Real STE 101, Mountain View California, 94040, USA

    Andrew W. Carroll

69. Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV, Irapuato, 36821, Guanajuato, Mexico

    Andres Moreno-Estrada & Andres Moreno-Estrada

70. Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, 69978, Israel

    Eran Halperin (Principal Investigator) & Yael Baran

71. Department of Microbiology, Tel-Aviv University, Tel-Aviv, 69978, Israel

    Eran Halperin (Principal Investigator)

72. International Computer Science Institute, Berkeley, 94704, California, USA

    Eran Halperin (Principal Investigator)

73. Thermo Fisher Scientific, 200 Oyster Point Boulevard, South San Francisco, 94080, California, USA

    Fiona C. L. Hyland

74. The Translational Genomics Research Institute, Phoenix, 85004, Arizona, USA

    David W. Craig (Principal Investigator), Alexis Christoforides, Tyler Izatt, Ahmet A. Kurdoglu, Shripad A. Sinari, David W. Craig (Principal Investigator), David W. Craig (Principal Investigator), Alexis Christoforides, Tyler Izatt, David W. Craig (Principal Investigator), Tyler Izatt & Ahmet A. Kurdoglu

75. Life Technologies, Beverly, 01915, Massachusetts, USA

    Nils Homer, Nils Homer & Nils Homer

76. Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, 90024, California, USA

    Kevin Squire

77. Department of Psychiatry, University of California, San Diego, La Jolla, 92093, California, USA

    Jonathan Sebat (Principal Investigator), Danny Antaki, Madhusudan Gujral, Amina Noor, Jonathan Sebat (Principal Investigator) & Danny Antaki

78. Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, 92093, California, USA

    Jonathan Sebat (Principal Investigator)

79. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, 10461, New York, USA

    Kenny Ye & Kenny Ye

80. Departments of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, 94158, San Francisco, USA

    Esteban G. Burchard (Principal Investigator), Ryan D. Hernandez (Principal Investigator), Christopher R. Gignoux, Esteban G. Burchard & Christopher R. Gignoux

81. Institute for Quantitative Biosciences (QB3), University of California, San Francisco, 1700 4th Street, San Francisco, 94158, California, USA

    Ryan D. Hernandez (Principal Investigator)

82. Institute for Human Genetics, University of California, San Francisco, 1700 4th Street, San Francisco, 94158, California, USA

    Ryan D. Hernandez (Principal Investigator)

83. Center for Biomolecular Science and Engineering, University of California, Santa Cruz, Santa Cruz, 95064, California, USA

    David Haussler (Principal Investigator), Sol J. Katzman, W. James Kent & David Haussler (Principal Investigator)

84. Howard Hughes Medical Institute, Santa Cruz, 95064, California, USA

    David Haussler (Principal Investigator) & David Haussler (Principal Investigator)

85. Department of Human Genetics, University of Chicago, Chicago, 60637, Illinois, USA

    Bryan Howie

86. Department of Genetics, Evolution and Environment, University College London, London, WC1E 6BT, UK

    Andres Ruiz-Linares (Principal Investigator) & Andres Ruiz-Linares

87. Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland

    Emmanouil T. Dermitzakis (Principal Investigator), Olivier Delaneau, Andy Rimmer & Emmanouil T. Dermitzakis (Principal Investigator)

88. Institute for Genetics and Genomics in Geneva, University of Geneva, 1211 Geneva, Switzerland

    Emmanouil T. Dermitzakis (Principal Investigator) & Emmanouil T. Dermitzakis (Principal Investigator)

89. Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland

    Emmanouil T. Dermitzakis (Principal Investigator) & Emmanouil T. Dermitzakis (Principal Investigator)

90. Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, 21201, Maryland, USA

    Scott E. Devine (Principal Investigator), Scott E. Devine (Principal Investigator) & Eugene J. Gardner (Project Leader)

91. Department of Computational Medicine and Bioinfomatics, University of Michigan, Ann Arbor, 48109, Michigan, USA

    Jeffrey M. Kidd (Principal Investigator), Shiya Song, Jeffrey M. Kidd (Principal Investigator), Ryan E. Mills (Principal Investigator) & Gargi Dayama

92. Department of Human Genetics, University of Michigan Medical School, Ann Arbor, 48109, Michigan, USA

    Jeffrey M. Kidd (Principal Investigator), Sarah Emery, Elzbieta Sliwerska, Jeffrey M. Kidd (Principal Investigator), Ryan E. Mills (Principal Investigator), Gargi Dayama & Sarah Emery

93. Department of Pediatrics, University of Pittsburgh, Pittsburgh, 15224, Pennsylvania, USA

    Wei Chen

94. The University of Texas Health Science Center at Houston, Houston, 77030, Texas, USA

    Goo Jun, Yunxin Fu (Principal Investigator), Xiaoming Liu, Momiao Xiong & Goo Jun

95. Vanderbilt University School of Medicine, Nashville, 37232, Tennessee, USA

    Bingshan Li & Nicholas F. Parrish

96. University of Michigan Sequencing Core, University of Michigan, Ann Arbor, 48109, Michigan, USA

    Robert Lyons

97. Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, 09042, Cagliari, Italy

    Carlo Sidore

98. Dipartimento di Scienze Biomediche, Università delgi Studi di Sassari, Sassari, 07100, Italy

    Carlo Sidore

99. University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, 75390, Texas, USA

    Xiaowei Zhan

100. Department of Pediatrics, University of Montreal, Ste. Justine Hospital Research Centre, Montreal, H3T 1C5, Quebec, Canada

     Philip Awadalla (Principal Investigator) & Alan Hodgkinson

101. Department of Genetics, Department of Biostatistics, Department of Computer Science, University of Chapel Hill, North Carolina, 27599, USA

     Yun Li

102. Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, 28223, North Carolina, USA

     Xinghua Shi (Principal Investigator), Andrew Quitadamo, Xinghua Shi (Principal Investigator) & Andrew Quitadamo

103. Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands

     Androniki Menelaou

104. Department of Biology, University of Puerto Rico at Mayagüez, Mayagüez, 00680, Puerto Rico, USA

     Taras K. Oleksyk (Principal Investigator), Juan C. Martinez-Cruzado & Taras K. Oleksyk

105. Eccles Institute of Human Genetics, University of Utah School of Medicine, Salt Lake City, 84112, Utah, USA

     Lynn Jorde (Principal Investigator), David Witherspoon, David Witherspoon & Lynn Jorde

106. Department of Genetics, Rutgers University, Piscataway, New Jersey, 08854, USA

     Jinchuan Xing & Jinchuan Xing

107. Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, 98195, Washington, USA

     Brian L. Browning (Principal Investigator)

108. Department of Biostatistics, University of Washington, Seattle, 98195, Washington, USA

     Sharon R. Browning (Principal Investigator)

109. Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA,

     Ekta Khurana (Principal Investigator), Ekta Khurana (Principal Investigator) & Ekta Khurana (Principal Investigator)

110. Department of Human Genetics, Radboud Institute for Molecular Life Sciences and Donders Centre for Neuroscience, Radboud University Medical Center, Geert Grooteplein 10, GA Nijmegen, 6525, The Netherlands

     Cornelis A. Albers

111. Department of Molecular Developmental Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences (RIMLS), Radboud University, Nijmegen, 6500, HB, The Netherlands

     Cornelis A. Albers

112. Institute of Genetics and Biophysics, National Research Council (CNR), Naples, 80125, Italy

     Vincenza Colonna & Vincenza Colonna

113. Program in Computational Biology and Bioinformatics, Yale University, New Haven, 06520, Connecticut, USA

     Mark B. Gerstein (Principal Investigator), Jieming Chen, Yao Fu, Arif O. Harmanci, Donghoon Lee, Xinmeng Jasmine Mu, Jing Zhang, Yan Zhang, Mark B. Gerstein (Principal Investigator), Jieming Chen, Xinmeng Jasmine Mu, Cristina Sisu, Jing Zhang, Yan Zhang, Mark B. Gerstein (Principal Investigator), Lukas Habegger, Mark B. Gerstein (Principal Investigator) (Co-Chair) & Yao Fu

114. Department of Computer Science, Yale University, New Haven, 06520, Connecticut, USA

     Mark B. Gerstein (Principal Investigator), Mark B. Gerstein (Principal Investigator), Mark B. Gerstein (Principal Investigator) & Mark B. Gerstein (Principal Investigator) (Co-Chair)

115. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, 06520, Connecticut, USA

     Mark B. Gerstein (Principal Investigator), Suganthi Balasubramanian, Mike Jin, Jeremy Liu, Jing Zhang, Yan Zhang, Mark B. Gerstein (Principal Investigator), Jing Zhang, Yan Zhang, Mark B. Gerstein (Principal Investigator), Suganthi Balasubramanian, Mark B. Gerstein (Principal Investigator) (Co-Chair), Suganthi Balasubramanian & Donghoon Kim

116. Department of Health Sciences Research, Mayo Clinic, Rochester, 55905, Minnesota, USA

     Alexej Abyzov & Alexej Abyzov

117. Department of Chemistry, Yale University, New Haven, 06520, Connecticut, USA

     Declan Clarke & Declan Clarke

118. Department of Medical Statistics and Bioinformatics, Molecular Epidemiology Section, Leiden University Medical Center, 2333, ZA, The Netherlands

     Eric-Wubbo Lameijer

119. Department of Computer Science, University of California, San Diego, La Jolla, 92093, California, USA

     Vineet Bafna

120. Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, 92093, California, USA

     Jacob Michaelson

121. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, 77230, Texas, USA

     Ken Chen (Principle Investigator), Xian Fan, Zechen Chong & Tenghui Chen

122. Bina Technologies, Roche Sequencing, Redwood City, 94065, California, USA

     Hugo Lam

123. Department of Surgery, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

     Kasper Lage (Principal Investigator), Jakob Berg Jespersen & Heiko Horn

124. Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, Kemitorvet Building 208, Lyngby, 2800, Denmark

     Jakob Berg Jespersen

125. Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, 10024, New York, USA

     Rob Desalle

126. Department of Invertebrate Zoology, American Museum of Natural History, New York, 10024, New York, USA

     Apurva Narechania

127. School of Life Sciences, Arizona State University, Tempe, 85287-4701, Arizona, USA

     Melissa A. Wilson Sayres

128. Program in Biomedical Informatics, Stanford University, Stanford, 94305, California, USA

     G. David Poznik

129. Institute for Molecular Bioscience, University of Queensland, St Lucia, QLD 4072, Australia

     Lachlan Coin (Principal Investigator) & Haojing Shao

130. Virginia Bioinformatics Institute, 1015 Life Sciences Drive, Blacksburg, 24061, Virginia, USA

     David Mittelman

131. Division of Allergy and Clinical Immunology, School of Medicine, Johns Hopkins University, Baltimore, 21205, Maryland, USA

     Kathleen C. Barnes & Kathleen C. Barnes

132. Department of Ecology and Evolution, Stony Brook University, Stony Brook, 11794, New York, USA

     Brenna Henn

133. Centre for Health, Law and Emerging Technologies, University of Oxford, Oxford, OX3 7LF, UK

     Jane S. Kaye

134. Genetic Alliance, London, N1 3QP, UK

     Alastair Kent

135. Nuffield Department of Population Health, The Ethox Center, University of Oxford, Old Road Campus, OX3 7LF, UK

     Angeliki Kerasidou & Michael Parker

136. Johns Hopkins University School of Medicine, Baltimore, 21205, Maryland, USA

     Rasika Mathias & Rasika A. Mathias

137. Department of Medical History and Bioethics, Morgridge Institute for Research, University of Wisconsin-Madison, Madison, 53706, Wisconsin, USA

     Pilar N. Ossorio

138. University of Wisconsin Law School, Madison, 53706, Wisconsin, USA

     Pilar N. Ossorio

139. US National Institutes of Health, Center for Research on Genomics and Global Health, National Human Genome Research Institute, 12 South Drive, Bethesda, 20892, Maryland, USA

     Charles N. Rotimi

140. Department of African & African American Studies, Duke University, Durham, North, 27708, Carolina, USA

     Charmaine D. Royal

141. Department of Genetics, University of Pennsylvania School of Medicine, Philadelphia, 19104, Pennsylvania, USA

     Sarah Tishkoff

142. Department of Psychiatry and Clinical Psychobiology & Institute for Brain, Cognition and Behavior (IR3C), University of Barcelona, Barcelona, 08035, Spain

     Marc Via

143. Cancer and Immunogenetics Laboratory, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK

     Walter Bodmer

144. Laboratory of Molecular Genetics, Institute of Biology, University of Antioquia, Medellín, Colombia

     Gabriel Bedoya

145. Peking University Shenzhen Hospital, Shenzhen, 518036, China

     Yang Gao

146. Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, 650118, China

     Jiayou Chu

147. Instituto de Biologia Molecular y Celular del Cancer, Centro de Investigacion del Cancer/IBMCC (CSIC-USAL), Institute of Biomedical Research of Salamanca (IBSAL) & National DNA Bank Carlos III, University of Salamanca, Salamanca, 37007, Spain

     Andres Garcia-Montero & Alberto Orfao

148. Ponce Research Institute, Ponce Health Sciences University, Ponce, 00716, Puerto Rico

     Julie Dutil

149. Chronic Disease Research Centre, Tropical Medicine Research Institute, Cave Hill Campus, The University of the West Indies,

     Anselm Hennis

150. Faculty of Medical Sciences, Cave Hill Campus, The University of the West Indies,

     Anselm Hennis & Harold Watson

151. Tropical Metabolism Research Unit, Tropical Medicine Research Institute, Mona Campus, The University of the West Indies,

     Colin McKenzie

152. International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh

     Firdausi Qadri & Regina LaRocque

153. Xishuangbanna Health School, Xishuangbanna, 666100, China

     Xiaoyan Deng

154. Irrua Specialist Teaching Hospital, Edo State, Nigeria

     Danny Asogun

155. Redeemers University, Ogun State, Nigeria

     Onikepe Folarin, Christian Happi & Omonwunmi Omoniwa

156. Harvard T. H. Chan School of Public Health, Boston, 02115, Massachusetts, USA

     Christian Happi & Omonwunmi Omoniwa

157. Medical Research Council Unit, The Gambia, Atlantic Boulevard, Fajara, P.O. Box 273, Banjul, The Gambia

     Muminatou Jallow, Fatoumatta Sisay Joof, Tumani Corrah, Kirk Rockett & Dominic Kwiatkowski

158. NHLI, Imperial College London, Hammersmith Hospital, London, SW7 2AZ, UK

     Jaspal Kooner

159. Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam

     Trâ`n Tịnh Hiê`n, Sarah J. Dunstan & Nguyen Thuy Hang

160. Peter Doherty Institute of Infection and Immunity, The University of Melbourne, 792 Elizabeth Street, Melbourne, 3000, VIC, Australia

     Sarah J. Dunstan

161. Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone

     Richard Fonnie, Lansana Kanneh & Donald S. Grant

162. Tulane University Health Sciences Center, New Orleans, 70112, Louisiana, USA

     Robert Garry, Lina Moses, John Schieffelin & Donald S. Grant

163. Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Peru

     Carla Gallo & Giovanni Poletti

164. Center for Non-Communicable Diseases, Karachi, Pakistan

     Danish Saleheen & Asif Rasheed

165. Department of Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, Pennsylvania, USA

     Danish Saleheen

166. US National Institutes of Health, National Human Genome Research Institute, 5635 Fishers Lane, Bethesda, 20892, Maryland, USA

     Lisa D. Brooks, Adam L. Felsenfeld, Jean E. McEwen, Yekaterina Vaydylevich, Jeffery A. Schloss & Lisa D. Brooks

167. Wellcome Trust, Gibbs Building, 215 Euston Road, London, NW1 2BE, UK

     Audrey Duncanson & Michael Dunn

168. James D. Watson Institute of Genome Sciences, Hangzhou, 310008, China

     Huanming Yang

Consortia

Contributions

Details of author contributions can be found in the author list.

Corresponding authors

Correspondence toAdam Auton,Gonçalo R. Abecasis,Gonçalo R. Abecasis,Gonçalo R. Abecasis,Adam Auton orGonçalo R. Abecasis.

Competing interests

D.M.A. is affiliated with Vertex Pharmaceuticals, E.A. is on the speaker’s bureau for Illumina, P.A. is an advisor to Illumina and Ancestry.com, D.R.B., B.B., M.B., R.K.C., A.C., M.E., S.H., S.K., L.M., J.P. and R.S. are affiliated with Illumina, J.K.B. is affiliated with Ancestry.com, A.C. is on the Science Advisory Board of Biogen Idec. and the scientific advisory board of Affymetrix, A.W.C. is affiliated with DNAnexus, D.C. is affiliated with Personalis, C.J.D., J.G., J.P.S., T.W., B.W., and Y.Z. are affiliated with Affymetrix, E.T.D. is an advisor for DNAnexus, F.M.D.L.V. is employed by Real Time Genomics, M.A.D. is affiliated with SynapDx, P.D. is a co-founder and director of Genomics, and a partner in Peptide Groove, R.D. is a founder of Congenica and a consultant for Dovetail, E.E.E. is on the scientific advisory board of DNAnexus, and is a consultant for Kunming University of Science and Technology as part of the 1000 China Talent Program, P.F. is a member of the scientific advisory board of Omicia, M.G. is an advisor to Bina and DNAnexus, F.C.L.H. is affiliated with ThermoFisher Scientific, N.H. is affiliated with Life Technologies, C.L. is a scientific advisor for BioNano Genomics, H.Y.K.L. is affiliated with Bina Technologies which is part of Roche Sequencing, E.R.M. holds shares in Life Technologies, and G.M. is a co-founder of Genomics and a partner in Peptide Groove.

(Participants are arranged by project role, then by institution alphabetically, and finally alphabetically within institutions except for Principal Investigators and Project Leaders, as indicated.)

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported licence. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons licence, users will need to obtain permission from the licence holder to reproduce the material. To view a copy of this licence, visithttp://creativecommons.org/licenses/by-nc-sa/3.0/.

Reprints and permissions