Recurrent inversion polymorphisms in humans associate with genetic instability and genomic disorders.

Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1 retrotransposition; 80% of the larger inversions are balanced and affect twice as many nucleotides as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or retrotransposons. Since flanking repeats promote non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7 × 10-4 per locus per generation. Recurrent inversions exhibit a sex-chromosomal bias and co-localize with genomic disorder critical regions. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes specific haplotypes to disease-causing CNVs.

Assembly of 43 human Y chromosomes reveals extensive complexity and variation.

The prevalence of highly repetitive sequences within the human Y chromosome has prevented its complete assembly to date1 and led to its systematic omission from genomic analyses. Here we present de novo assemblies of 43 Y chromosomes spanning 182,900 years of human evolution and report considerable diversity in size and structure. Half of the male-specific euchromatic region is subject to large inversions with a greater than twofold higher recurrence rate compared with all other chromosomes2. Ampliconic sequences associated with these inversions show differing mutation rates that are sequence context dependent, and some ampliconic genes exhibit evidence for concerted evolution with the acquisition and purging of lineage-specific pseudogenes. The largest heterochromatic region in the human genome, Yq12, is composed of alternating repeat arrays that show extensive variation in the number, size and distribution, but retain a 1:1 copy-number ratio. Finally, our data suggest that the boundary between the recombining pseudoautosomal region 1 and the non-recombining portions of the X and Y chromosomes lies 500 kb away from the currently established1 boundary. The availability of fully sequence-resolved Y chromosomes from multiple individuals provides a unique opportunity for identifying new associations of traits with specific Y-chromosomal variants and garnering insights into the evolution and function of complex regions of the human genome.

Criteria for inference of chromothripsis in cancer genomes.

Chromothripsis scars the genome when localized chromosome shattering and repair occurs in a one-off catastrophe. Outcomes of this process are detectable as massive DNA rearrangements affecting one or a few chromosomes. Although recent findings suggest a crucial role of chromothripsis in cancer development, the reproducible inference of this process remains challenging, requiring that cataclysmic one-off rearrangements be distinguished from localized lesions that occur progressively. We describe conceptual criteria for the inference of chromothripsis, based on ruling out the alternative hypothesis that stepwise rearrangements occurred. Robust means of inference may facilitate in-depth studies on the impact of, and the mechanisms underlying, chromothripsis.

Semi-automated assembly of high-quality diploid human reference genomes.

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society1,2. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals3,4. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome5. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

Is stochastic thermodynamics the key to understanding the energy costs of computation?

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.

Gaps and complex structurally variant loci in phased genome assemblies.

There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.

Patterns of somatic structural variation in human cancer genomes.

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1-7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions-as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2-7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and-in liver cancer-frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act.

Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Structural Variation in Cancer: Role, Prevalence, and Mechanisms.

Somatic rearrangements resulting in genomic structural variation drive malignant phenotypes by altering the expression or function of cancer genes. Pan-cancer studies have revealed that structural variants (SVs) are the predominant class of driver mutation in most cancer types, but because they are difficult to discover, they remain understudied when compared with point mutations. This review provides an overview of the current knowledge of somatic SVs, discussing their primary roles, prevalence in different contexts, and mutational mechanisms. SVs arise throughout the life history of cancer, and 55% of driver mutations uncovered by the Pan-Cancer Analysis of Whole Genomes project represent SVs. Leveraging the convergence of cell biology and genomics, we propose a mechanistic classification of somatic SVs, from simple to highly complex DNA rearrangement classes. The actions of DNA repair and DNA replication processes together with mitotic errors result in a rich spectrum of SV formation processes, with cascading effects mediating extensive structural diversity after an initiating DNA lesion has formed. Thanks to new sequencing technologies, including the sequencing of single-cell genomes, open questions about the molecular triggers and the biomolecules involved in SV formation as well as their mutational rates can now be addressed.

Familial long-read sequencing increases yield of de novo mutations.

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.

Somatic structural variant formation is guided by and influences genome architecture.

The occurrence and formation of genomic structural variants (SVs) is known to be influenced by the 3D chromatin architecture, but the extent and magnitude have been challenging to study. Here, we apply Hi-C to study chromatin organization before and after induction of chromothripsis in human cells. We use Hi-C to manually assemble the derivative chromosomes following the occurrence of massive complex rearrangements, which allows us to study the sources of SV formation and their consequences on gene regulation. We observe an action-reaction interplay whereby the 3D chromatin architecture directly impacts the location and formation of SVs. In turn, the SVs reshape the chromatin organization to alter the local topologies, replication timing, and gene regulation in cis We show that SVs have a strong tendency to occur between similar chromatin compartments and replication timing regions. Moreover, we find that SVs frequently occur at 3D loop anchors, that SVs can cause a switch in chromatin compartments and replication timing, and that this is a major source of SV-mediated effects on nearby gene expression changes. Finally, we provide evidence for a general mechanistic bias of the 3D chromatin on SV occurrence using data from more than 2700 patient-derived cancer genomes.

A high-resolution map of small-scale inversions in the gibbon genome.

Gibbons are the most speciose family of living apes, characterized by a diverse chromosome number and rapid rate of large-scale rearrangements. Here we performed single-cell template strand sequencing (Strand-seq), molecular cytogenetics, and deep in silico analysis of a southern white-cheeked gibbon genome, providing the first comprehensive map of 238 previously hidden small-scale inversions. We determined that more than half are gibbon specific, at least fivefold higher than shown for other primate lineage-specific inversions, with a significantly high number of small heterozygous inversions, suggesting that accelerated evolution of inversions may have played a role in the high sympatric diversity of gibbons. Although the precise mechanisms underlying these inversions are not yet understood, it is clear that segmental duplication-mediated NAHR only accounts for a small fraction of events. Several genomic features, including gene density and repeat (e.g., LINE-1) content, might render these regions more break-prone and susceptible to inversion formation. In the attempt to characterize interspecific variation between southern and northern white-cheeked gibbons, we identify several large assembly errors in the current GGSC Nleu3.0/nomLeu3 reference genome comprising more than 49 megabases of DNA. Finally, we provide a list of 182 candidate genes potentially involved in gibbon diversification and speciation.

Leveraging European infrastructures to access 1 million human genomes by 2022.

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

Author Correction: Leveraging European infrastructures to access 1 million human genomes by 2022.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Empirical social triad statistics can be explained with dyadic homophylic interactions.

The remarkable robustness of many social systems has been associated with a peculiar triangular structure in the underlying social networks. Triples of people that have three positive relations (e.g., friendship) between each other are strongly overrepresented. Triples with two negative relations (e.g., enmity) and one positive relation are also overrepresented, and triples with one or three negative relations are drastically suppressed. For almost a century, the mechanism behind these very specific ("balanced") triad statistics remained elusive. Here, we propose a simple realistic adaptive network model, where agents tend to minimize social tension that arises from dyadic interactions. Both opinions of agents and their signed links (positive or negative relations) are updated in the dynamics. The key aspect of the model resides in the fact that agents only need information about their local neighbors in the network and do not require (often unrealistic) higher-order network information for their relation and opinion updates. We demonstrate the quality of the model on detailed temporal relation data of a society of thousands of players of a massive multiplayer online game where we can observe triangle formation directly. It not only successfully predicts the distribution of triangle types but also explains empirical group size distributions, which are essential for social cohesion. We discuss the details of the phase diagrams behind the model and their parameter dependence, and we comment on to what extent the results might apply universally in societies.

Expectations and blind spots for structural variation detection from long-read assemblies and short-read genome sequencing technologies.

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.

MosaiCatcher v2: a single-cell structural variations detection and analysis reference framework based on Strand-seq.

SUMMARY: Single-cell DNA template strand sequencing (Strand-seq) allows a range of various genomic analysis including chromosome length haplotype phasing and structural variation (SV) calling in individual cells. Here, we present MosaiCatcher v2, a standardized workflow and reference framework for single-cell SV detection using Strand-seq. This framework introduces a range of functionalities, including: an automated upstream Quality Control (QC) and assembly sub-workflow that relies on multiple genome assemblies and incorporates a multistep normalization module, integration of the single-cell nucleosome occupancy and genetic variation analysis SV functional characterization and of the ArbiGent SV genotyping modules, platform portability, as well as a user-friendly and shareable web report. These new features of MosaiCatcher v2 enable reproducible computational processing of Strand-seq data, which are increasingly used in human genetics and single-cell genomics, toward production environments. MosaiCatcher v2 is compatible with both container and conda environments, ensuring reproducibility and robustness and positioning the framework as a cornerstone in computational processing of Strand-seq data. AVAILABILITY AND IMPLEMENTATION: MosaiCatcher v2 is a standardized workflow, implemented using the Snakemake workflow management system. The pipeline is available on GitHub: https://github.com/friendsofstrandseq/mosaicatcher-pipeline/ and on the snakemake-workflow-catalog: https://snakemake.github.io/snakemake-workflow-catalog/?usage=friendsofstrandseq/mosaicatcher-pipeline. Strand-seq example input data used in the publication can be found in the Data availability statement. Additionally, a lightweight dataset for test purposes can be found on the GitHub repository.

Single-cell strand sequencing of a macaque genome reveals multiple nested inversions and breakpoint reuse during primate evolution.

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.