Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent–child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average contig N50: 26 Mbp) integrate all forms of genetic variation even across complex loci. We identify 107,590 structural variants (SVs), of which 68% are not discovered by short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterize 130 of the most active mobile element source elements and find that 63% of all SVs arise by homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1,526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

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The 1000 Genomes Project (1kGP), launched in 2008, is the largest fully open resource of whole genome sequencing (WGS) data consented for public distribution of raw sequence data without access or use restrictions. The final (phase 3) 2015 release of 1kGP included 2,504 unrelated samples from 26 populations, representing five continental regions of the world and was based on a combination of technologies including low coverage WGS (mean depth 7.4X), high coverage whole exome sequencing (mean depth 65.7X), and microarray genotyping. Here, we present a new, high coverage WGS resource encompassing the original 2,504 1kGP samples, as well as an additional 698 related samples that result in 602 complete trios in the 1kGP cohort. We sequenced this expanded 1kGP cohort of 3,202 samples to a targeted depth of 30X using Illumina NovaSeq 6000 instruments. We performed SNV/INDEL calling against the GRCh38 reference using GATK HaplotypeCaller, and generated a comprehensive set of SVs by integrating multiple analytic methods through a sophisticated machine learning model, upgrading the 1kGP dataset to current state-of-the-art standards. Using this strategy, we defined over 111 million SNVs, 14 million INDELs, and ~170 thousand SVs across the entire cohort of 3,202 samples with estimated false discovery rate (FDR) of 0.3%, 1.0%, and 1.8%, respectively. By comparison to the low-coverage phase 3 callset, we observed substantial improvements in variant discovery and estimated FDR that were facilitated by high coverage re-sequencing and expansion of the cohort. Specifically, we called 7% more SNVs, 59% more INDELs, and 170% more SVs per genome than the phase 3 callset. Moreover, we leveraged the presence of families in the cohort to achieve superior haplotype phasing accuracy and we demonstrate improvements that the high coverage panel brings especially for INDEL imputation. We make all the data generated as part of this project publicly available and we envision this updated version of the 1kGP callset to become the new de facto public resource for the worldwide scientific community working on genomics and genetics.

A key goal of whole genome sequencing (WGS) for human genetics studies is to interrogate all forms of variation, including single nucleotide variants (SNV), small insertion/deletion (indel) variants and structural variants (SV). However, tools and resources for the study of SV have lagged behind those for smaller variants. Here, we used a scalable pipeline 22 to map and characterize SV in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest WGS-based SV resource to date. On average, individuals carry 2.9 rare SVs that alter coding regions, affecting the dosage or structure of 4.2 genes and accounting for 4.0-11.2% of rare high-impact coding alleles. Based on a computational model, we estimate that SVs account for 17.2% of rare alleles genome-wide with predicted deleterious effects equivalent to loss-of-function coding alleles; ~90% of such SVs are non-coding deletions (mean 19.1 per genome). We report 158,991 ultra-rare SVs and show that ~2% of individuals carry ultra-rare megabase-scale SVs, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and non-coding elements, revealing trends related to element class and conservation. This work will help guide SV analysis and interpretation in the era of WGS.