Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in α-satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into α-satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

Three mobile element classes, namely Alu, LINE-1 (L1), and SVA elements, remain actively mobile in human genomes and continue to produce new mobile element insertions (MEIs). Historically, MEIs have been discovered and studied using several methods, including: (1) Southern blots, (2) PCR (including PCR display), and (3) the detection of MEI copies from young subfamilies. We are now entering a new phase of MEI discovery where these methods are being replaced by whole genome sequencing and bioinformatics analysis to discover novel MEIs. We expect that the universe of sequenced human genomes will continue to expand rapidly over the next several years, both with short-read and long-read technologies. These resources will provide unprecedented opportunities to discover MEIs and study their impact on human traits and diseases. They also will allow the MEI community to discover and study the source elements that produce these new MEIs, which will facilitate our ability to study source element regulation in various tissue contexts and disease states. This, in turn, will allow us to better understand MEI mutagenesis in humans and the impact of this mutagenesis on human biology.

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and medical genetic initiatives are reliant upon short-read whole-genome sequencing (srWGS), which presents challenges for the detection of structural variants (SVs) relative to emerging long-read WGS (lrWGS) technologies. Given this ubiquity of srWGS in large-scale genomics initiatives, we sought to establish expectations for routine SV detection from this data type by comparison with lrWGS assembly, as well as to quantify the genomic properties and added value of SVs uniquely accessible to each technology. Analyses from the Human Genome Structural Variation Consortium (HGSVC) of three families captured ~11,000 SVs per genome from srWGS and ~25,000 SVs per genome from lrWGS assembly. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplication (SD) and simple repeat (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of reference sequence, we observed extremely high (93.8%) concordance between technologies for deletions in these datasets. In contrast, lrWGS was superior for detection of insertions across all genomic contexts. Given that non-SD/SR sequences encompass 95.9% of currently annotated disease-associated exons, improved sensitivity from lrWGS to discover novel pathogenic deletions in these currently interpretable genomic regions is likely to be incremental. However, these analyses highlight the considerable added value of assembly-based lrWGS to create new catalogs of insertions and transposable elements, as well as disease-associated repeat expansions in genomic sequences that were previously recalcitrant to routine assessment.

Several large-scale Illumina whole-genome sequencing (WGS) and whole-exome sequencing (WES) projects have emerged recently that have provided exceptional opportunities to discover mobile element insertions (MEIs) and study the impact of these MEIs on human genomes. However, these projects also have presented major challenges with respect to the scalability and computational costs associated with performing MEI discovery on tens or even hundreds of thousands of samples. To meet these challenges, we have developed a more efficient and scalable version of our mobile element locator tool (MELT) called CloudMELT. We then used MELT and CloudMELT to perform MEI discovery in 57,919 human genomes and exomes, leading to the discovery of 104,350 nonredundant MEIs. We leveraged this collection (1) to examine potentially active L1 source elements that drive the mobilization of new Alu, L1, and SVA MEIs in humans; (2) to examine the population distributions and subfamilies of these MEIs; and (3) to examine the mutagenesis of GENCODE genes, ENCODE-annotated features, and disease genes by these MEIs. Our study provides new insights on the L1 source elements that drive MEI mutagenesis and brings forth a better understanding of how this mutagenesis impacts human genomes.

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 minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. Here, we systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections, and pattern growth enables CSV detection without pre-defined models. Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms. Notably, validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%, where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp, respectively. Moreover, the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types, including two novel types of adjacent segment swap and tandem dispersed duplication. Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs. Mako is publicly available at https://github.com/xjtu-omics/Mako.

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and emerging clinical diagnostic approaches utilize short-reads (srWGS), which present constraints for genome-wide discovery of structural variants (SVs). Alternative long-read single molecule technologies (lrWGS) offer significant advantages for genome assembly and SV detection, while these technologies are currently cost prohibitive for large-scale disease studies and clinical diagnostics (∼5-12X higher cost than comparable coverage srWGS). Moreover, only dozens of such genomes are currently publicly accessible by comparison to millions of srWGS genomes that have been commissioned for international initiatives. Given this ubiquitous reliance on srWGS in human genetics and genomics, we sought to characterize and quantify the properties of SVs accessible to both srWGS and lrWGS to establish benchmarks and expectations in ongoing medical and population genetic studies, and to project the added value of SVs uniquely accessible to each technology. In analyses of three trios with matched srWGS and lrWGS from the Human Genome Structural Variation Consortium (HGSVC), srWGS captured ∼11,000 SVs per genome using reference-based algorithms, while haplotype-resolved assembly from lrWGS identified ∼25,000 SVs per genome. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplications (SD) and simple repeats (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of the human reference, we observed extremely high concordance (93.8%) for deletions discovered by srWGS and lrWGS after error correction using the raw lrWGS reads. Conversely, lrWGS was superior for detection of insertions across all genomic contexts. Given that the non-SD/SR sequences span 90.3% of the GRCh38 reference, and encompass 95.9% of coding exons in currently annotated disease associated genes, improved sensitivity from lrWGS to discover novel and interpretable pathogenic deletions not already accessible to srWGS is likely to be incremental. However, these analyses highlight the added value of assembly-based lrWGS to create new catalogues of functional insertions and transposable elements, as well as disease associated repeat expansions in genomic regions previously recalcitrant to routine assessment.

Retrotransposable elements (RTEs) have actively multiplied over the past 80 million years of primate evolution, and as a consequence, such elements collectively occupy ∼ 40% of the human genome. As RTE activity can have detrimental effects on the human genome and transcriptome, silencing mechanisms have evolved to restrict retrotransposition. The brain is the only known somatic tissue where RTEs are de-repressed throughout the life of a healthy human and each neuron in specific brain regions accumulates up to ∼13.7 new somatic L1 insertions (and perhaps more). However, even higher levels of somatic RTE expression and retrotransposition have been found in a number of human neurological disorders. This review is focused on how RTE expression and retrotransposition in neuronal tissues might contribute to the initiation and progression of these disorders. These disorders are discussed in three broad and sometimes overlapping categories: 1) disorders such as Rett syndrome, Aicardi-Goutières syndrome, and ataxia–telangiectasia, where expression/retrotransposition is increased due to mutations in genes that play a role in regulating RTEs in healthy cells, 2) disorders such as autism spectrum disorder, schizophrenia, and substance abuse disorders, which are thought to be caused by a combination of genetic and environmental stress factors, and 3) disorders associated with age, such as frontotemporal lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS), and normal aging, where there is a time-dependent accumulation of neurological degeneration, RTE copy number, and phenotypes. Research has revealed increased levels of RTE activity in many neurological disorders, but in most cases, a clear causal link between RTE activity and these disorders has not been well established. At the same time, even if increased RTE activity is a passenger and not a driver of disease, a detrimental effect is more likely than a beneficial one. Thus, a better understanding of the role of RTEs in neuronal tissues likely is an important part of understanding, preventing, and treating these disorders.

Somatic LINE-1 (L1) retrotransposition has been detected in early embryos, adult brains, and the gastrointestinal (GI) tract, and many cancers, including epithelial GI tumors. We previously found numerous somatic L1 insertions in paired normal and GI cancerous tissues. Here, using a modified method of single-cell analysis for somatic L1 insertions, we studied adenocarcinomas of colon, pancreas, and stomach, and found a variable number of somatic L1 insertions in tumors of the same type from patient to patient. We detected no somatic L1 insertions in single cells of 5 of 10 tumors studied. In three tumors, aneuploid cells were detected by FACS. In one pancreatic tumor, there were many more L1 insertions in aneuploid than in euploid tumor cells. In one gastric cancer, both aneuploid and euploid cells contained large numbers of likely clonal insertions. However, in a second gastric cancer with aneuploid cells, no somatic L1 insertions were found. We suggest that when the cellular environment is favorable to retrotransposition, aneuploidy predisposes tumor cells to L1 insertions, and retrotransposition may occur at the transition from euploidy to aneuploidy. Seventeen percent of insertions were also present in normal cells, similar to findings in genomic DNA from normal tissues of GI tumor patients. We provide evidence that: 1) The number of L1 insertions in tumors of the same type is highly variable, 2) most somatic L1 insertions in GI cancer tissues are absent from normal tissues, and 3) under certain conditions, somatic L1 retrotransposition exhibits a propensity for occurring in aneuploid cells.

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 across even complex loci such as the major histocompatibility complex. We focus on 107,590 structural variants (SVs), of which 68% are inaccessible by short-read sequencing. We identify new SV hotspots (spanning megabases of gene-rich sequence), characterize 130 of the most active mobile element source elements, and find that 63% of all SVs arise by homology-mediated mechanisms—a twofold increase from previous studies. Our resource now enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1,525 expression quantitative trait loci (SV-eQTLs) as well as SV candidates for adaptive selection within the human population.

Human genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

The prevailing genome assembly paradigm is to produce consensus sequences that “collapse” parental haplotypes into a consensus sequence. Here, we leverage the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing (Strand-seq)1,2 and combine them with high-fidelity (HiFi) long sequencing reads3, in a novel reference-free workflow for diploid de novo genome assembly. Employing this strategy, we produce completely phased de novo genome assemblies separately for each haplotype of a single individual of Puerto Rican origin (HG00733) in the absence of parental data. The assemblies are accurate (QV > 40), highly contiguous (contig N50 > 25 Mbp) with low switch error rates (0.4%) providing fully phased single-nucleotide variants (SNVs), indels, and structural variants (SVs). A comparison of Oxford Nanopore and PacBio phased assemblies identifies 150 regions that are preferential sites of contig breaks irrespective of sequencing technology or phasing algorithms.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Glioma is a unique neoplastic disease that develops exclusively in the central nervous system (CNS) and rarely metastasizes to other tissues. This feature strongly implicates the tumor-host CNS microenvironment in gliomagenesis and tumor progression. We investigated the differences and similarities in glioma biology as conveyed by transcriptomic patterns across four mammalian hosts: rats, mice, dogs, and humans. Given the inherent intra-tumoral molecular heterogeneity of human glioma, we focused this study on tumors with upregulation of the platelet-derived growth factor signaling axis, a common and early alteration in human gliomagenesis. The results reveal core neoplastic alterations in mammalian glioma, as well as unique contributions of the tumor host to neoplastic processes. Notable differences were observed in gene expression patterns as well as related biological pathways and cell populations known to mediate key elements of glioma biology, including angiogenesis, immune evasion, and brain invasion. These data provide new insights regarding mammalian models of human glioma, and how these insights and models relate to our current understanding of the human disease.

The human LINE-1 (or L1) element is a non-LTR retrotransposon that is mobilized through an RNA intermediate by an L1-encoded reverse transcriptase and other L1-encoded proteins. L1 elements remain actively mobile today and continue to mutagenize human genomes. Importantly, when new insertions disrupt gene function, they can cause diseases. Historically, L1s were thought to be active in the germline but silenced in adult somatic tissues. However, recent studies now show that L1 is active in at least some somatic tissues, including epithelial cancers. In this review, we provide an overview of these recent developments, and examine evidence that somatic L1 retrotransposition can initiate and drive tumorigenesis in humans. Recent studies have: (i) cataloged somatic L1 activity in many epithelial tumor types; (ii) identified specific full-length L1 source elements that give rise to somatic L1 insertions; and (iii) determined that L1 promoter hypomethylation likely plays an early role in the derepression of L1s in somatic tissues. A central challenge moving forward is to determine the extent to which L1 driver mutations can promote tumor initiation, evolution, and metastasis in humans.

Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projects involving population genetics, human diseases, and clinical genomics. Here, we describe the Mobile Element Locator Tool (MELT), which was developed as part of the 1000 Genomes Project to perform MEI discovery on a population scale. Using both Illumina WGS data and simulations, we demonstrate that MELT outperforms existing MEI discovery tools in terms of speed, scalability, specificity, and sensitivity, while also detecting a broader spectrum of MEI-associated features. Several run modes were developed to perform MEI discovery on local and cloud systems. In addition to using MELT to discover MEIs in modern humans as part of the 1000 Genomes Project, we also used it to discover MEIs in chimpanzees and ancient (Neanderthal and Denisovan) hominids. We detected diverse patterns of MEI stratification across these populations that likely were caused by (1) diverse rates of MEI production from source elements, (2) diverse patterns of MEI inheritance, and (3) the introgression of ancient MEIs into modern human genomes. Overall, our study provides the most comprehensive map of MEIs to date spanning chimpanzees, ancient hominids, and modern humans and reveals new aspects of MEI biology in these lineages. We also demonstrate that MELT is a robust platform for MEI discovery and analysis in a variety of experimental settings.

Although human LINE-1 (L1) elements are actively mobilized in many cancers, a role for somatic L1 retrotransposition in tumor initiation has not been conclusively demonstrated. Here, we identify a novel somatic L1 insertion in the APC tumor suppressor gene that provided us with a unique opportunity to determine whether such insertions can actually initiate colorectal cancer (CRC), and if so, how this might occur. Our data support a model whereby a hot L1 source element on Chromosome 17 of the patient's genome evaded somatic repression in normal colon tissues and thereby initiated CRC by mutating the APC gene. This insertion worked together with a point mutation in the second APC allele to initiate tumorigenesis through the classic two-hit CRC pathway. We also show that L1 source profiles vary considerably depending on the ancestry of an individual, and that population-specific hot L1 elements represent a novel form of cancer risk.

Nat. Neurosci. 18, 690–697 (2015); published online 30 March 2015; corrected after print 8 February 2017 In the version of this article initially published, the Whole Genome Bisulfite Sequencing (WGBS) analysis was based on a data set in which one of the female .bam alignment files (FV2) was mistakenly truncated.

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

RATIONALEThe clinical features of patients infected with pulmonary nontuberculous mycobacteria (PNTM) are well described, but the genetic components of infection susceptibility are not.OBJECTIVESTo examine genetic variants in patients with PNTM, their unaffected family members, and a control group.METHODSWhole-exome sequencing was done on 69 white patients with PNTM and 18 of their white unaffected family members. We performed a candidate gene analysis using immune, cystic fibrosis transmembrance conductance regulator (CFTR), cilia, and connective tissue gene sets. The numbers of patients, family members, and control subjects with variants in each category were compared, as was the average number of variants per person.MEASUREMENTS AND MAIN RESULTSA significantly higher number of patients with PNTM than the other subjects had low-frequency, protein-affecting variants in immune, CFTR, cilia, and connective tissue categories (35, 26, 90, and 90%, respectively). Patients with PNTM also had significantly more cilia and connective tissue variants per person than did control subjects (2.47 and 2.55 compared with 1.38 and 1.40, respectively; P = 1.4 × 10(-6) and P = 2.7 × 10(-8), respectively). Patients with PNTM had an average of 5.26 variants across all categories (1.98 in control subjects; P = 2.8 × 10(-17)), and they were more likely than control subjects to have variants in multiple categories. We observed similar results for family members without PNTM infection, with the exception of the immune category.CONCLUSIONSPatients with PNTM have more low-frequency, protein-affecting variants in immune, CFTR, cilia, and connective tissue genes than their unaffected family members and control subjects. We propose that PNTM infection is a multigenic disease in which combinations of variants across gene categories, plus environmental exposures, increase susceptibility to the infection.