Search

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children—a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10(−8) substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

There are more than 55,000 variable number tandem repeats (VNTRs) in the human genome, notable for both their striking polymorphism and mutability. Despite their role in human evolution and genomic variation, they have yet to be studied collectively and in detail, partially owing to their large size, variability, and predominant location in noncoding regions. Here, we examine 467 VNTRs that are human-specific expansions, unique to one location in the genome, and not associated with retrotransposons. We leverage publicly available long-read genomes, including from the Human Genome Structural Variant Consortium, to ascertain the exact nucleotide composition of these VNTRs and compare their composition of alleles. We then confirm repeat unit composition in more than 3000 short-read samples from the 1000 Genomes Project. Our analysis reveals that these VNTRs contain highly structured repeat motif organization, modified by frequent deletion and duplication events. Although overall VNTR compositions tend to remain similar between 1000 Genomes Project superpopulations, we describe a notable exception with substantial differences in repeat composition (in PCBP3), as well as several VNTRs that are significantly different in length between superpopulations (in ART1, PROP1, DYNC2I1, and LOC102723906). We also observe that most of these VNTRs are expanded in archaic human genomes, yet remain stable in length between single generations. Collectively, our findings indicate that repeat motif variability, repeat composition, and repeat length are all informative modalities to consider when characterizing VNTRs and their contribution to genomic variation.

The divergence of chimpanzee and bonobo provides one of the few examples of recent hominid speciation1,2. Here we describe a fully annotated, high-quality bonobo genome assembly, which was constructed without guidance from reference genomes by applying a multiplatform genomics approach. We generate a bonobo genome assembly in which more than 98% of genes are completely annotated and 99% of the gaps are closed, including the resolution of about half of the segmental duplications and almost all of the full-length mobile elements. We compare the bonobo genome to those of other great apes1,3–5 and identify more than 5,569 fixed structural variants that specifically distinguish the bonobo and chimpanzee lineages. We focus on genes that have been lost, changed in structure or expanded in the last few million years of bonobo evolution. We produce a high-resolution map of incomplete lineage sorting and estimate that around 5.1% of the human genome is genetically closer to chimpanzee or bonobo and that more than 36.5% of the genome shows incomplete lineage sorting if we consider a deeper phylogeny including gorilla and orangutan. We also show that 26% of the segments of incomplete lineage sorting between human and chimpanzee or human and bonobo are non-randomly distributed and that genes within these clustered segments show significant excess of amino acid replacement compared to the rest of the genome., A high-quality bonobo genome assembly provides insights into incomplete lineage sorting in hominids and its relevance to gene evolution and the genetic relationship among living hominids.

Despite their importance in disease and evolution, highly identical segmental duplications (SDs) are among the last regions of the human reference genome (GRCh38) to be fully sequenced. Using a complete telomere-to-telomere human genome (T2T-CHM13), we present a comprehensive view of human SD organization. SDs account for nearly one-third of the additional sequence, increasing the genome-wide estimate from 5.4 to 7.0% [218 million base pairs (Mbp)]. An analysis of 268 human genomes shows that 91% of the previously unresolved T2T-CHM13 SD sequence (68.3 Mbp) better represents human copy number variation. Comparing long-read assemblies from human ( n = 12) and nonhuman primate ( n = 5) genomes, we systematically reconstruct the evolution and structural haplotype diversity of biomedically relevant and duplicated genes. This analysis reveals patterns of structural heterozygosity and evolutionary differences in SD organization between humans and other primates.

Tandem repeats are proposed to contribute to human-specific traits, and more than 40 tandem repeat expansions are known to cause neurological disease. Here, we characterize a human-specific 69 bp variable number tandem repeat (VNTR) in the last intron of WDR7, which exhibits striking variability in both copy number and nucleotide composition, as revealed by long-read sequencing. In addition, greater repeat copy number is significantly enriched in three independent cohorts of individuals with sporadic amyotrophic lateral sclerosis (ALS). Each unit of the repeat forms a stem-loop structure with the potential to produce microRNAs, and the repeat RNA can aggregate when expressed in cells. We leveraged its remarkable sequence variability to align the repeat in 288 samples and uncover its mechanism of expansion. We found that the repeat expands in the 3′-5′ direction, in groups of repeat units divisible by two. The expansion patterns we observed were consistent with duplication events, and a replication error called template switching. We also observed that the VNTR is expanded in both Denisovan and Neanderthal genomes but is fixed at one copy or fewer in non-human primates. Evaluating the repeat in 1000 Genomes Project samples reveals that some repeat segments are solely present or absent in certain geographic populations. The large size of the repeat unit in this VNTR, along with our multiplexed sequencing strategy, provides an unprecedented opportunity to study mechanisms of repeat expansion, and a framework for evaluating the roles of VNTRs in human evolution and disease.

Viral sequence integrations in the human genome have been implicated in various human diseases. Viral integrations remain among the most challenging-to-detect structural changes of the human genome. No studies have systematically analyzed how molecular and bioinformatics factors affect the power (sensitivity) to detect viral integrations using high-throughput sequencing (HTS). We selected a wide-range of molecular and bioinformatics factors covering genome sequence characteristics, HTS features, and viral integration detection. We designed a fast simulation-based framework to model the process of detecting variable viral integration events in the human genome. We then examined the associations of selected factors with viral integration detection power. We identified six factors that significantly affected viral integration detection power ( P

Significance Extrachromosomal circular DNA (eccDNA) plays a role in human diseases such as cancer, but little is known about the impact of eccDNA in healthy human biology. Since eccDNA is a tiny fraction of nuclear DNA, artificial amplification has been employed to increase eccDNA amounts, resulting in the loss of native compositions. We developed an approach to enrich eccDNA populations at the native state (naïve small circular DNA, nscDNA) and investigated their origins in the human genome. We found that, in human sperm, the vast majority of nscDNA came from high-copy genomic regions, including the most variable regions between individuals. Because eccDNA can be incorporated back into chromosomes, eccDNA may promote human genetic variation., Extrachromosomal circular DNA (eccDNA) originates from linear chromosomal DNA in various human tissues under physiological and disease conditions. The genomic origins of eccDNA have largely been investigated using in vitro–amplified DNA. However, in vitro amplification obscures quantitative information by skewing the total population stoichiometry. In addition, the analyses have focused on eccDNA stemming from single-copy genomic regions, leaving eccDNA from multicopy regions unexamined. To address these issues, we isolated eccDNA without in vitro amplification (naïve small circular DNA, nscDNA) and assessed the populations quantitatively by integrated genomic, molecular, and cytogenetic approaches. nscDNA of up to tens of kilobases were successfully enriched by our approach and were predominantly derived from multicopy genomic regions including segmental duplications (SDs). SDs, which account for 5% of the human genome and are hotspots for copy number variations, were significantly overrepresented in sperm nscDNA, with three times more sequencing reads derived from SDs than from the entire single-copy regions. SDs were also overrepresented in mouse sperm nscDNA, which we estimated to comprise 0.2% of nuclear DNA. Considering that eccDNA can be integrated into chromosomes, germline-derived nscDNA may be a mediator of genome diversity.

Short tandem repeats (STRs) and variable number tandem repeats (VNTRs) are important sources of natural and disease-causing variation, yet they have been problematic to resolve in reference genomes and genotype with short-read technology. We created a framework to model the evolution and instability of STRs and VNTRs in apes. We phased and assembled 3 ape genomes (chimpanzee, gorilla, and orangutan) using long-read and 10x Genomics linked-read sequence data for 21,442 human tandem repeats discovered in 6 haplotype-resolved assemblies of Yoruban, Chinese, and Puerto Rican origin. We define a set of 1,584 STRs/VNTRs expanded specifically in humans, including large tandem repeats affecting coding and noncoding portions of genes (e.g., MUC3A , CACNA1C ). We show that short interspersed nuclear element–VNTR– Alu (SVA) retrotransposition is the main mechanism for distributing GC-rich human-specific tandem repeat expansions throughout the genome but with a bias against genes. In contrast, we observe that VNTRs not originating from retrotransposons have a propensity to cluster near genes, especially in the subtelomere. Using tissue-specific expression from human and chimpanzee brains, we identify genes where transcript isoform usage differs significantly, likely caused by cryptic splicing variation within VNTRs. Using single-cell expression from cerebral organoids, we observe a strong effect for genes associated with transcription profiles analogous to intermediate progenitor cells. Finally, we compare the sequence composition of some of the largest human-specific repeat expansions and identify 52 STRs/VNTRs with at least 40 uninterrupted pure tracts as candidates for genetically unstable regions associated with disease.

Oncoviral infection is responsible for 12%–15% of cancer in humans. Convergent evidence from epidemiology, pathology, and oncology suggests that new viral etiologies for cancers remain to be discovered. Oncoviral profiles can be obtained from cancer genome sequencing data; however, widespread viral sequence contamination and noncausal viruses complicate the process of identifying genuine oncoviruses. Here, we propose a novel strategy to address these challenges by performing virome-wide screening of early-stage clonal viral integrations. To implement this strategy, we developed VIcaller, a novel platform for identifying viral integrations that are derived from any characterized viruses and shared by a large proportion of tumor cells using whole-genome sequencing (WGS) data. The sensitivity and precision were confirmed with simulated and benchmark cancer data sets. By applying this platform to cancer WGS data sets with proven or speculated viral etiology, we newly identified or confirmed clonal integrations of hepatitis B virus (HBV), human papillomavirus (HPV), Epstein-Barr virus (EBV), and BK Virus (BKV), suggesting the involvement of these viruses in early stages of tumorigenesis in affected tumors, such as HBV in TERT and KMT2B (also known as MLL4) gene loci in liver cancer, HPV and BKV in bladder cancer, and EBV in non-Hodgkin's lymphoma. We also showed the capacity of VIcaller to identify integrations from some uncharacterized viruses. This is the first study to systematically investigate the strategy and method of virome-wide screening of clonal integrations to identify oncoviruses. Searching clonal viral integrations with our platform has the capacity to identify virus-caused cancers and discover cancer viral etiologies.

Despite their importance in disease and evolution, highly identical segmental duplications (SDs) have been among the last regions of the human reference genome (GRCh38) to be finished. Based on a complete telomere-to-telomere human genome (T2T-CHM13), we present the first comprehensive view of human SD organization. SDs account for nearly one-third of the additional sequence increasing the genome-wide estimate from 5.4% to 7.0% (218 Mbp). An analysis of 266 human genomes shows that 91% of the new T2T-CHM13 SD sequence (68.3 Mbp) better represents human copy number. We find that SDs show increased single-nucleotide variation diversity when compared to unique regions; we characterize methylation signatures that correlate with duplicate gene transcription and predict 182 novel protein-coding gene candidates. We find that 63% (35.11/55.7 Mbp) of acrocentric chromosomes consist of SDs distinct from rDNA and satellite sequences. Acrocentric SDs are 1.75-fold longer (p=0.00034) than other SDs, are frequently shared with autosomal pericentromeric regions, and are heteromorphic among human chromosomes. Comparing long-read assemblies from other human (n=12) and nonhuman primate (n=5) genomes, we use the T2T-CHM13 genome to systematically reconstruct the evolution and structural haplotype diversity of biomedically relevant (LPA, SMN) and duplicated genes (TBC1D3, SRGAP2C, ARHGAP11B) important in the expansion of the human frontal cortex. The analysis reveals unprecedented patterns of structural heterozygosity and massive evolutionary differences in SD organization between humans and their closest living relatives.

Despite widespread clinical genetic testing, many individuals with suspected genetic conditions lack a precise diagnosis, limiting their opportunity to take advantage of state-of-the-art treatments. In some cases, testing reveals difficult-to-evaluate structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. We performed targeted long-read sequencing (T-LRS) using adaptive sampling on the Oxford Nanopore platform on 40 individuals, 10 of whom lacked a complete molecular diagnosis. We computationally targeted up to 151 Mbp of sequence per individual and searched for pathogenic substitutions, structural variants, and methylation differences using a single data source. We detected all genomic aberrations-including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences-identified by prior clinical testing. In 8/8 individuals with complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, leading to changes in clinical management in one case. In ten individuals with suspected Mendelian conditions lacking a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in six and variants of uncertain significance in two others. T-LRS accurately identifies pathogenic structural variants, resolves complex rearrangements, and identifies Mendelian variants not detected by other technologies. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority genes and regions or complex clinical testing results.

There are over 55,000 variable number tandem repeats (VNTRs) in the human genome, notable for both their striking polymorphism and mutability. Despite their role in human evolution and genomic variation, they have yet to be studied collectively and in detail, partially due to their large size, variability, and predominant location in non-coding regions. Here, we examine 467 VNTRs that are human-specific expansions, unique to one location in the genome, and not associated with retrotransposons. We leverage publicly available long-read genomes – including from the Human Genome Structural Variant Consortium – to ascertain the exact nucleotide composition of these VNTRs, and compare their composition of alleles. We then confirm repeat unit composition in over 3000 short-read samples from the 1000 Genomes Project. Our analysis reveals that these VNTRs contain remarkably structured repeat motif organization, modified by frequent deletion and duplication events. While overall VNTR compositions tend to remain similar between 1000 Genomes Project super-populations, we describe a notable exception with substantial differences in repeat composition (in PCBP3), as well as several VNTRs that are significantly different in length between super-populations (in ART1, PROP1, WDR60, and LOC102723906). We also observe that most of these VNTRs are expanded in archaic human genomes, yet remain stable in length between single generations. Collectively, our findings indicate that repeat motif variability, repeat composition, and repeat length are all informative modalities to consider when characterizing VNTRs and their contribution to genomic variation.

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., Assembly of haplotype-resolved human genomes is achieved by combining short and long reads.

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.

Resolving genomic structural variationMany human genomes have been reported using short-read technology, but it is difficult to resolve structural variants (SVs) using these data. These genomes thus lack comprehensive comparisons among individuals and populations. Ebertet al.used long-read structural variation calling across 64 human genomes representing diverse populations and developed new methods for variant discovery. This approach allowed the authors to increase the number of confirmed SVs and to describe the patterns of variation across populations. From this dataset, they identified quantitative trait loci affected by these SVs and determined how they may affect gene expression and potentially explain genome-wide association study hits. This information provides insights into patterns of normal human genetic variation and generates reference genomes that better represent the diversity of our species.Science, this issue p.eabf7117

BACKGROUNDDespite widespread availability of clinical genetic testing, many individuals with suspected genetic conditions do not have a precise diagnosis. This limits their opportunity to take advantage of state-of-the-art treatments. In such instances, testing sometimes reveals difficult-to-evaluate complex structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in specific genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted.METHODSTargeted long-read sequencing (T-LRS) was performed on 33 individuals using Read Until on the Oxford Nanopore platform. This method allowed us to computationally target up to 100 Mbp of sequence per experiment, resulting in an average of 20x coverage of target regions, a 500% increase over background. We analyzed patient DNA for pathogenic substitutions, structural variants, and methylation differences using a single data source.RESULTSThe effectiveness of T-LRS was validated by detecting all genomic aberrations, including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences, previously identified by prior clinical testing. In 6/7 individuals who had complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, which led, in one case, to a change in clinical management. In nine individuals with suspected Mendelian conditions who lacked a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in five and variants of uncertain significance in two others.CONCLUSIONST-LRS can accurately predict pathogenic copy number variants and triplet repeat expansions, resolve complex rearrangements, and identify single-nucleotide variants not detected by other technologies, including short-read sequencing. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority candidate genes and regions or to further evaluate complex clinical testing results. The application of T-LRS will likely increase the diagnostic rate of rare disorders.

Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p 1.25E-06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p 3.64E-07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype-genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort.

Background The complex interspersed pattern of segmental duplications in humans is responsible for rearrangements associated with neurodevelopmental disease, including the emergence of novel genes important in human brain evolution. We investigate the evolution of LCR16a, a putative driver of this phenomenon that encodes one of the most rapidly evolving human–ape gene families, nuclear pore interacting protein (NPIP). Results Comparative analysis shows that LCR16a has independently expanded in five primate lineages over the last 35 million years of primate evolution. The expansions are associated with independent lineage-specific segmental duplications flanking LCR16a leading to the emergence of large interspersed duplication blocks at non-orthologous chromosomal locations in each primate lineage. The intron-exon structure of the NPIP gene family has changed dramatically throughout primate evolution with different branches showing characteristic gene models yet maintaining an open reading frame. In the African ape lineage, we detect signatures of positive selection that occurred after a transition to more ubiquitous expression among great ape tissues when compared to Old World and New World monkeys. Mouse transgenic experiments from baboon and human genomic loci confirm these expression differences and suggest that the broader ape expression pattern arose due to mutational changes that emerged in cis. Conclusions LCR16a promotes serial interspersed duplications and creates hotspots of genomic instability that appear to be an ancient property of primate genomes. Dramatic changes to NPIP gene structure and altered tissue expression preceded major bouts of positive selection in the African ape lineage, suggestive of a gene undergoing strong adaptive evolution.

Autism is a highly heritable complex disorder in which de novo mutation (DNM) variation contributes significantly to risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare variants. We report and replicate a transmission disequilibrium of private, likely gene-disruptive (LGD) variants in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin–protein ligase complex, intracellular transport and Erb signaling protein networks. We estimate that these variants are approximately 2.5 generations old and significantly younger than other variants of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and appear to act on a distinct set of genes not yet associated with autism. Analysis of whole-genome sequence data from 3,474 families finds an excess of private, likely gene-disrupting variants in individuals with autism. These variants are under purifying selection and suggest candidate genes not previously associated with autism.

Autism is a highly heritable, complex disorder where de novo mutation (DNM) variation contributes significantly to disease risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare mutations. We report and replicate a transmission disequilibrium of private likely-gene disruptive (LGD) mutations in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin-protein ligase complex, intracellular transport, and Erb signaling protein networks. We estimate these mutations are ~2.5 generations old and significantly younger than other mutations of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and act on a distinct set of genes not yet associated with autism.One sentence summaryUltra-rare autism variants preferentially transmitted to probands are younger and identify distinct gene candidates and functional networks.

Rhesus macaque is an Old World monkey that shared a common ancestor with human ∼25 Myr ago and is an important animal model for human disease studies. A deep understanding of its genetics is therefore required for both biomedical and evolutionary studies. Among structural variants, inversions represent a driving force in speciation and play an important role in disease predisposition. Here we generated a genome-wide map of inversions between human and macaque, combining single-cell strand sequencing with cytogenetics. We identified 375 total inversions between 859 bp and 92 Mbp, increasing by eightfold the number of previously reported inversions. Among these, 19 inversions flanked by segmental duplications overlap with recurrent copy number variants associated with neurocognitive disorders. Evolutionary analyses show that in 17 out of 19 cases, the Hominidae orientation of these disease-associated regions is always derived. This suggests that duplicated sequences likely played a fundamental role in generating inversions in humans and great apes, creating architectures that nowadays predispose these regions to disease-associated genetic instability. Finally, we identified 861 genes mapping at 156 inversions breakpoints, with some showing evidence of differential expression in human and macaque cell lines, thus highlighting candidates that might have contributed to the evolution of species-specific features. This study depicts the most accurate fine-scale map of inversions between human and macaque using a two-pronged integrative approach, such as single-cell strand sequencing and cytogenetics, and represents a valuable resource toward understanding of the biology and evolution of primate species.

Inversions play an important role in disease and evolution but are difficult to characterize because their breakpoints map to large repeats. We increased by sixfold the number (n = 1,069) of previously reported great ape inversions by using single-cell DNA template strand and long-read sequencing. We find that the X chromosome is most enriched (2.5-fold) for inversions, on the basis of its size and duplication content. There is an excess of differentially expressed primate genes near the breakpoints of large (>100 kilobases (kb)) inversions but not smaller events. We show that when great ape lineage-specific duplications emerge, they preferentially (approximately 75%) occur in an inverted orientation compared to that at their ancestral locus. We construct megabase-pair scale haplotypes for individual chromosomes and identify 23 genomic regions that have recurrently toggled between a direct and an inverted state over 15 million years. The direct orientation is most frequently the derived state for human polymorphisms that predispose to recurrent copy number variants associated with neurodevelopmental disease.

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 sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective stand-alone technology for de novo assembly of human genomes.

We combined de novo mutation (DNM) data from 10,927 individuals with developmental delay and autism to identify 253 candidate neurodevelopmental disease genes with an excess of missense and/or likely gene-disruptive (LGD) mutations. Of these genes, 124 reach exome-wide significance (P

Genetic variants with extreme allele frequency differences (EAFD) may underlie some human health disparities across populations. To identify EAFD loci, we systematically analyzed and characterized 81 million genomic variants from 2504 unrelated individuals of 26 world populations (phase III of the 1000 Genomes Project). Our analyses revealed a total of 434 genes, 15 pathways, and 18 diseases and traits influenced by EAFD variants from five continental populations. They included known EAFD genes, such as LCT (lactose tolerance), SLC24A5 (skin pigmentation), and EDAR (hair morphology). We found many novel EAFD genes, including TBC1D2B (autophagy mediator), TRIM40 (gastrointestinal inflammatory regulator), KRT71, KRT75, KRT83, and KRTAP10-1 (hair and epithelial keratin synthesis), PIK3R3 (insulin receptor interaction), DARS (neurological disorders), and NACA2 (skin inflammatory response). Our results also showed four complex diseases significantly associated with EAFD loci, including asthma (adjusted enrichment P = 4 × 10−8), type I diabetes (P = 6 × 10−9), alcohol consumption (P = 0.0002), and attention deficit/hyperactivity disorder (P = 0.003). This study provides a comprehensive atlas of genes, pathways, and human diseases significantly influenced by EAFD variants.

Next-generation sequencing (NGS) is now more accessible to clinicians and researchers. As a result, our understanding of the genetics of neurodevelopmental disorders (NDDs) has rapidly advanced over the past few years. NGS has led to the discovery of new NDD genes with an excess of recurrent de novo mutations (DNMs) when compared to controls. Development of large-scale databases of normal and disease variation has given rise to metrics exploring the relative tolerance of individual genes to human mutation. Genetic etiology and diagnosis rates have improved, which have led to the discovery of new pathways and tissue types relevant to NDDs. In this review, we highlight several key findings based on the discovery of recurrent DNMs ranging from copy number variants to point mutations. We explore biases and patterns of DNM enrichment and the role of mosaicism and secondary mutations in variable expressivity. We discuss the benefit of whole-genome sequencing (WGS) over whole-exome sequencing (WES) to understand more complex, multifactorial cases of NDD and explain how this improved understanding aids diagnosis and management of these disorders. Comprehensive assessment of the DNM landscape across the genome using WGS and other technologies will lead to the development of novel functional and bioinformatics approaches to interpret DNMs and drive new insights into NDD biology.

We combinedde novomutation (DNM) data from 10,927 cases of developmental delay and autism to identify 301 candidate neurodevelopmental disease genes showing an excess of missense and/or likely gene-disruptive (LGD) mutations. 164 genes were predicted by two different DNM models, including 116 genes with an excess of LGD mutations. Among the 301 genes, 76% show DNM in both autism and intellectual disability/developmental delay cohorts where they occur in 10.3% and 28.4% of the cases, respectively. Intersecting these results with copy number variation (CNV) morbidity data identifies a significant enrichment for the intersection of our gene set and genomic disorder regions (36/301, LR+ 2.53, p=0.0005). This analysis confirms many recurrent LGD genes and CNV deletion syndromes (e.g.,KANSL1, PAFAH1B1, RA1,etc.), consistent with a model of haploinsufficiency. We also identify genes with an excess of missense DNMs overlapping deletion syndromes (e.g.,KIF1Aand the 2q37 deletion) as well as duplication syndromes, such as recurrentMAPK3missense mutations within the chromosome 16p11.2 duplication, recurrentCHD4missense DNMs in the 12p13 duplication region, and recurrentWDFY4missense DNMs in the 10q11.23 duplication region. Finally, we also identify pathogenic CNVs overlapping more than one recurrently mutated gene (e.g., Sotos and Kleefstra syndromes) raising the possibility that multiple gene-dosage imbalances may contribute to phenotypic complexity of these disorders. Network analyses of genes showing an excess of DNMs confirm previous well-known enrichments but also highlight new functional networks, including cell-specific enrichments in the D1+ and D2+ spiny neurons of the striatum for both recurrently mutated genes and genes where missense mutations cluster.

Dysregulated oxidative metabolism is a well-recognized aspect of cancer biology, and many therapeutic strategies are based on targeting cancers by altering cellular redox pathways. The NADPH oxidases (NOXes) present an important enzymatic source of biological oxidants, and the expression and activation of several NOX isoforms are frequently dysregulated in many cancers. Cell-based studies have demonstrated a role for several NOX isozymes in controlling cell proliferation and/or cell migration, further supporting a potential contributing role for NOX in promoting cancer. While various NOX isoforms are often upregulated in cancers, paradoxical recent findings indicate that dual oxidases (DUOXes), normally prominently expressed in epithelial lineages, are frequently suppressed in epithelial-derived cancers by epigenetic mechanisms, although the functional relevance of such DUOX silencing has remained unclear. This review will briefly summarize our current understanding regarding the importance of reactive oxygen species (ROS) and NOXes in cancer biology, and focus on recent observations indicating the unique and seemingly opposing roles of DUOX enzymes in cancer biology. We will discuss current knowledge regarding the functional properties of DUOX, and recent studies highlighting mechanistic consequences of DUOX1 loss in lung cancer, and its consequences for tumor invasiveness and current anticancer therapy. Finally, we will also discuss potentially unique roles for the DUOX maturation factors. Overall, a better understanding of mechanisms that regulate DUOX and the functional consequences of DUOX silencing in cancer may offer valuable new diagnostic insights and novel therapeutic opportunities.

Genetic association studies and meta-analyses of alcohol dependence (AD) have reported AD-associated single nucleotide polymorphisms (SNPs). These SNPs collectively account for a small portion of estimated heritability in AD. Recent genome-wide copy number variation (CNV) studies have identified CNVs associated with AD and substance dependence, suggesting that a portion of the missing heritability is explained by CNV. We applied PennCNV and QuantiSNP CNV calling algorithms to identify consensus CNVs in five AD cohorts of European and African origins. After rigorous quality control, genome-wide meta-analyses of CNVs were carried out in 3243 well-diagnosed AD cases and 2802 controls. We identified nine CNV regions, including a deletion in chromosome 5q21.3 with a suggestive association with AD (OR=2.15 (1.41-3.29) and P=3.8 × 10-4) and eight nominally significant CNV regions. All regions were replicated with consistent effect sizes across studies and populations. Pathway and gene-drug interaction enrichment analyses based on the resulting genes indicated the mitogen-activated protein kinase signaling pathway and the recombinant insulin and hyaluronidase drugs, which were relevant to AD biology or treatment. To our knowledge, this is the first genome-wide meta-analysis of CNVs with addiction. Further investigation of the AD-associated CNV regions will provide better understanding of the AD genetic mechanism.

In order to provide a comprehensive resource for human structural variants (SVs), we generated long-read sequence data and analyzed SVs for fifteen human genomes. We sequence resolved 99,604 insertions, deletions, and inversions including 2,238 (1.6 Mbp) that are shared among all discovery genomes with an additional 13,053 (6.9 Mbp) present in the majority, indicating minor alleles or errors in the reference. Genotyping in 440 additional genomes confirms the most common SVs in unique euchromatin are now sequence resolved. We report a ninefold SV bias toward the last 5 Mbp of human chromosomes with nearly 55% of all VNTRs (variable number of tandem repeats) mapping to this portion of the genome. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity.

Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter in mammalian brain. GABA receptor are involved in a number of complex disorders, including substance abuse. No variants of the commonly studied GABA receptor genes that have been associated with substance dependence have been determined to be functional or pathogenic. To reconcile the conflicting associations with substance dependence traits, we performed a meta-analysis of variants in the GABAA receptor genes (GABRB2, GABRA6, GABRA1, and GABRG2 on chromosome 5q and GABRA2 on chromosome 4p12) using genotype data from 4739 cases of alcohol, opioid, or methamphetamine dependence and 4924 controls. Then, we combined the data from candidate gene association studies in the literature with two alcohol dependence (AD) samples, including 1691 cases and 1712 controls from the Study of Addiction: Genetics and Environment (SAGE), and 2644 cases and 494 controls from our own study. Using a Bonferroni-corrected threshold of 0.007, we found strong associations between GABRA2 and AD (P=9 × 10(-6) and odds ratio (OR) 95% confidence interval (CI)=1.27 (1.15, 1.4) for rs567926, P=4 × 10(-5) and OR=1.21 (1.1, 1.32) for rs279858), and between GABRG2 and both dependence on alcohol and dependence on heroin (P=0.0005 and OR=1.22 (1.09, 1.37) for rs211014). Significant association was also observed between GABRA6 rs3219151 and AD. The GABRA2 rs279858 association was observed in the SAGE data sets with a combined P of 9 × 10(-6) (OR=1.17 (1.09, 1.26)). When all of these data sets, including our samples, were meta-analyzed, associations of both GABRA2 single-nucleotide polymorphisms remained (for rs567926, P=7 × 10(-5) (OR=1.18 (1.09, 1.29)) in all the studies, and P=8 × 10(-6) (OR=1.25 (1.13, 1.38)) in subjects of European ancestry and for rs279858, P=5 × 10(-6) (OR=1.18 (1.1, 1.26)) in subjects of European ancestry. Findings from this extensive meta-analysis of five GABAA receptor genes and substance abuse support their involvement (with the best evidence for GABRA2) in the pathogenesis of AD. Further replications with larger samples are warranted.

In archival samples of European-ancestry subjects, light-eyed individuals have been found to consume more alcohol than dark-eyed individuals. No published population-based studies have directly tested the association between alcohol dependence (AD) and eye color. We hypothesized that light-eyed individuals have a higher prevalence of AD than dark-eyed individuals. A mixture model was used to select a homogeneous sample of 1,263 European-Americans and control for population stratification. After quality control, we conducted an association study using logistic regression, adjusting for confounders (age, sex, and genetic ancestry). We found evidence of association between AD and blue eye color (P = 0.0005 and odds ratio = 1.83 (1.31-2.57)), supporting light eye color as a risk factor relative to brown eye color. Network-based analyses revealed a statistically significant (P = 0.02) number of genetic interactions between eye color genes and AD-associated genes. We found evidence of linkage disequilibrium between an AD-associated GABA receptor gene cluster, GABRB3/GABRG3, and eye color genes, OCA2/HERC2, as well as between AD-associated GRM5 and pigmentation-associated TYR. Our population-phenotype, network, and linkage disequilibrium analyses support association between blue eye color and AD. Although we controlled for stratification we cannot exclude underlying occult stratification as a contributor to this observation. Although replication is needed, our findings suggest that eye pigmentation information may be useful in research on AD. Further characterization of this association may unravel new AD etiological factors. © 2015 Wiley Periodicals, Inc. Language: en

The fast measurement of millions of sequence variations across the genome is possible with the current technology. As a result, a difficult challenge arise in bioinformatics: the identification of combinations of interacting DNA sequence variations predictive of common disease [1]. The Multifactor Dimensionality Reduction (MDR) method is capable of analysing such interactions but an exhaustive MDR search would require exponential time. Thus, we use the Ant Colony Optimization (ACO) as a stochastic wrapper. It has been shown by Greene et al. that this approach, if expert knowledge is incorporated, is effective for analysing large amounts of genetic variation[2]. In the ACO method integrated in the MDR package, a linear and an exponential probability distribution function can be used to weigh the expert knowledge. We generate our biological expert knowledge from a network of gene-gene interactions produced by a literature mining platform, Pathway Studio. We show that the linear distribution function of expert knowledge is the most appropriate to weigh our scores when expert knowledge from literature mining is used. We find that ACO parameters significantly affect the power of the method and we suggest values for these parameters that can be used to optimize MDR in Genome Wide Association Studies that use biological expert knowledge.

Background Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. Results In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. Conclusion GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep-sequencing, particularly for data from the dbGaP and other public databases. GACT software http://www.uvm.edu/genomics/software/gact