Biology subjects

Korbel, J. O.

Publications and source records attributed to Korbel, J. O..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Impact and characterization of serial structural variations across humans and great apes

Modern sequencing technology enables the detection of complex structural variation (SV) across genomes. However, extensive DNA rearrangements arising through series of mutations, a phenomenon we term serial SV (sSV), remain understudied since their complexity poses a challenge for SV discovery. Here, we present NAHRwhals (https://github.com/WHops/NAHRwhals), a method to infer repeat-mediated series of SVs in long-read genomic assemblies. Applying NAHRwhals to 58 haplotype-resolved human genomes reveals 37 sSV loci of various length and complexity. These sSVs explain otherwise cryptic variation in medically relevant regions such as the TPSAB1 gene, 8p23.1 and the DiGeorge and Sotos syndrome regions. Comparisons with great ape assemblies indicate that most human sSVs formed recently and involved non-repeat-mediated processes. NAHRwhals reliably discovers and characterizes sSVs at scale and independent of species, uncovering their genomic abundance and revealing broader implications for disease than prior studies suggested.

bioinformatics↗

bioRxiv2022

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

The prevalence of highly repetitive sequences within the human Y chromosome has led to its incomplete assembly and systematic omission from genomic analyses. Here, we present long-read de novo assemblies of 43 diverse Y chromosomes spanning 180,000 years of human evolution, including two from deep-rooted African Y lineages, and report remarkable complexity and diversity in chromosome size and structure, in contrast with its low level of base substitution variation. The size of the Y chromosome assemblies varies extensively from 45.2 to 84.9 Mbp and include, on average, 81 kbp of novel sequence per Y chromosome. Half of the male-specific euchromatic region is subject to large inversions with a >2-fold higher recurrence rate compared to inversions in the rest of the human genome. Ampliconic sequences associated with these inversions further show differing mutation rates that are sequence context-dependent and some ampliconic genes show evidence for concerted evolution with the acquisition and purging of lineage-specific pseudogenes. The largest heterochromatic region in the human genome, the Yq12, is composed of alternating arrays of DYZ1 and DYZ2 repeat units that show extensive variation in the number, size and distribution of these arrays, but retain a 1:1 copy number ratio of the monomer repeats, consistent with the notion that functional or evolutionary forces are acting on this chromosomal region. Finally, our data suggests that the boundary between the recombining pseudoautosomal region 1 and the non-recombining portions of the X and Y chromosomes lies 500 kbp distal to the currently established boundary. The availability of sequence-resolved Y chromosomes from multiple individuals provides a unique opportunity for identifying new associations of specific traits with Y-chromosomal variants and garnering novel insights into the evolution and function of complex regions of the human genome.

genomics↗

bioRxiv2022

Inversion polymorphism in a complete human genome assembly

The completion of the human genome significantly improved our ability to discover and interpret genome copy number variation. In order to understand its impact on the characterization of inversion polymorphisms, we remapped data from 41 human genomes and 10 new samples against the telomere-to-telomere (T2T) reference genome as compared to the standard GRCh38 reference. Our analysis shows a ~21% increase in sensitivity identifying and improving mapping of 63 inversions. We further identify 26 misorientations within GRCh38, and show that the T2T reference is three times more likely to represent the correct orientation of the major human allele. As a result, we report a significant bias for inversions accumulating within the pericentromeric regions of specific chromosomes and show that functional annotations around inverted regions, such as topological-associated domains, can be better interpreted.

genomics↗

bioRxiv2022

Gaps and complex structurally variant loci in phased genome assemblies

There has been tremendous progress in the production of phased genome assemblies by combining long-read data with parental information or linking 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 77 phased and assembled human genomes (154 unique haplotypes). We find that trio-based approaches using HiFi are the current gold standard although chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. We find two-thirds of defined contig ends cluster near the largest and most identical repeats [including segmental duplications (35.4%) or satellite DNA (22.3%) or to regions enriched in GA/AT rich DNA (27.4%)]. As a result, 1513 protein-coding genes overlap assembly gaps in at least one haplotype and 231 are recurrently disrupted or missing from five or more haplotypes. In addition, we estimate that 6-7 Mbp of DNA are incorrectly orientated per haplotype irrespective of whether trio-free or trio-based approaches are employed. 81% of such misorientations correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large identical segmental duplications. In addition, we also identify large-scale alignment discontinuities consistent with an 11.9 Mbp deletion and 161.4 Mbp of insertion per human haploid genome. While 99% of this variation corresponds to satellite DNA, we identify 230 regions of the euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Although not completely resolved, these regions include copy number polymorphic and biomedically relevant genic regions where complete resolution and a pangenome representation will be most useful, yet most challenging, to realize.

genomics↗

bioRxiv2022

Mutation-Attention (MuAt): deep representation learning of somatic mutations for tumour typing and subtyping

Cancer genome sequencing enables accurate classification of tumours and tumour sub-types. However, prediction performance is still limited using exome-only sequencing and for tumor types with low somatic mutation burden such as many pediatric tumours. Moreover, the ability to leverage deep representation learning in discovery of tumour entities remains unknown. We introduce here Mutation-Attention (MuAt), a deep neural network to learn representations of simple and complex somatic alterations for prediction of tumour types and subtypes. MuAt achieved prediction accuracy of 89% for whole genomes (24 tumour types) and 64% for whole exomes (20 types), and a top-5 accuracy of 97% and 90%, respectively. Tumour representations learnt by MuAt included tumour entities such as acral melanoma, SHH-activated medulloblastoma, SPOP-associated prostate cancer, microsatellite instability, and MUTYH-associated pancreatic endocrine tumours although these tumour subtypes and subgroups were not used as training labels. Integrated representations of somatic alterations hold significant potential to drive discovery of novel tumour entities and clinical application.

genomics↗

bioRxiv2022

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 greatly benefited society1, 2. However, it still has many gaps and errors, and does not represent a biological human genome since it is a blend of multiple individuals3, 4. Recently, a high-quality telomere-to-telomere reference genome, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a duplicate genome, and is thus nearly homozygous5. To address these limitations, the Human Pangenome Reference Consortium (HPRC) recently formed with the goal of creating a collection of 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 automated assembly approaches yields the most complete, accurate, and cost-effective diploid genome assemblies with minimal manual curation. Approaches that used highly accurate long reads and parent-child data to sort haplotypes during assembly outperformed those that did not. Developing a combination of all the top performing methods, we generated our first high- quality diploid reference assembly, containing only [~]4 gaps (range 0-12) per chromosome, most within + 1% of CHM13s length. Nearly 1/4th of protein coding genes have synonymous amino acid changes between haplotypes, and centromeric regions showed the highest density of variation. Our findings serve as a foundation for assembling near-complete diploid human genomes at the scale required for constructing a human pangenome reference that captures all genetic variation from single nucleotides to large structural rearrangements.

genomics↗

bioRxiv2022

Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed templated insertion thread, characterized by short (mostly <1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY I) We investigate a single patient with chromothriptic sonic hedgehog medulloblastoma (Li-Fraumeni syndrome), with tissue samples taken from blood, the primary tumor at diagnosis, and a post-treatment (relapse) tumor. II) Data on the three samples has been collected from four sources, 1) Illumina whole-genome, 2) Illumina transcriptome sequencing, 3) Illumina Infinium HumanMethylation450k, as well as 4) long-read whole-genome sequencing using Oxford Nanopore Technologies (ONT) sequencing. III) An integrative analysis combines genomic, epigenomic as well as transcriptomic data to provide a comprehensive analysis of this heavily rearranged tumor sample. Long and short read sequencing data is used to inform the analysis of complex structural genomic variants and methylation called from haplotyped ONT reads and validated through the methylation array data allows for a haplotype-resolved study of genomic and epigenomic variation, which can then be examined for transcriptional effect. IV) This integrative analysis allows us to identify a large number of inter- and intra-chromosomal genomic rearrangements (A) including a complex rearrangement pattern we term templated insertion threads (B), as well as sample-specific and haplotype specific methylation patterns of known cancer genes (C). C_FIG_DISPLAY

cancer biology↗

bioRxiv2021

Haplotype-resolved inversion landscape reveals hotspots of mutational recurrence associated with 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 base pairs as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or mobile elements. Since this suggests recurrence due to 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 2.7x10-4 per locus and generation. Recurrent inversions exhibit a sex- chromosomal bias, and significantly co-localize to the critical regions of genomic disorders. 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 to disease- causing CNVs.

genomics↗

bioRxiv2021

Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation

Somatic structural variants (SVs) are widespread in cancer genomes, however, their impact on tumorigenesis and intra-tumour heterogeneity is incompletely understood, since methods to functionally characterize the broad spectrum of SVs arising in cancerous single-cells are lacking. We present a computational method, scNOVA, that couples SV discovery with nucleosome occupancy analysis by haplotype-resolved single-cell sequencing, to systematically uncover SV effects on cis-regulatory elements and gene activity. Application to leukemias and cell lines uncovered SV outcomes at several loci, including dysregulated cancer-related pathways and mono-allelic oncogene expression near SV breakpoints. At the intra-patient level, we identified different yet overlapping subclonal SVs that converge on aberrant Wnt signaling. We also deconvoluted the effects of catastrophic chromosomal rearrangements resulting in oncogenic transcription factor dysregulation. scNOVA directly links SVs to their functional consequences, opening the door for single-cell multiomics of SVs in heterogeneous cell populations.

genomics↗

bioRxiv2021

AlphaDesign: A de novo protein design framework based on AlphaFold

De novo protein design is a longstanding fundamental goal of synthetic biology, but has been hindered by the difficulty in reliable prediction of accurate high-resolution protein structures from sequence. Recent advances in the accuracy of protein structure prediction methods, such as AlphaFold (AF), have facilitated proteome scale structural predictions of monomeric proteins. Here we develop AlphaDesign, a computational framework for de novo protein design that embeds AF as an oracle within an optimisable design process. Our framework enables rapid prediction of completely novel protein monomers starting from random sequences. These are shown to adopt a diverse array of folds within the known protein space. A recent and unexpected utility of AF to predict the structure of protein complexes, further allows our framework to design higher-order complexes. Subsequently a range of predictions are made for monomers, homodimers, heterodimers as well as higher-order homo-oligomers - trimers to hexamers. Our analyses also show potential for designing proteins that bind to a pre-specified target protein. Structural integrity of predicted structures is validated and confirmed by standard ab initio folding and structural analysis methods as well as more extensively by performing rigorous all-atom molecular dynamics simulations and analysing the corresponding structural flexibility, intramonomer and interfacial amino-acid contacts. These analyses demonstrate widespread maintenance of structural integrity and suggests that our framework allows for fairly accurate protein design. Strikingly, our approach also reveals the capacity of AF to predict proteins that switch conformation upon complex formation, such as involving switches from -helices to {beta}-sheets during amyloid filament formation. Correspondingly, when integrated into our design framework, our approach reveals de novo design of a subset of proteins that switch conformation between monomeric and oligomeric state.

bioinformatics↗

bioRxiv2021

Somatic structural variant formation is guided by and influences genome architecture

The occurrence and formation of genomic structural variants (SV) is known to be influenced by the 3D chromatin architecture, but the extent and magnitude has 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 massive complex rearrangements, which allowed 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 on 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 genomic compartments and replication timing are important determinants for juxtaposing distant loci to form SVs across 30 different cancer types with a pronounced abundance of SVs between early replicating regions in uterine cancer. We find that SVs frequently occur at 3D loop-anchors, cause compartment switching and changes in replication timing, and that this is a major source of SV-mediated effects on nearby gene expression changes.

genomics↗

bioRxiv2021

Systems approaches identify the consequences ofmonosomy in somatic human cells

Chromosome loss that results in monosomy is detrimental to viability, yet, it is frequently observed in cancers. How cancers survive with monosomy is unknown. Using p53 deficient monosomic cell lines, we found that chromosome loss impairs proliferation and genomic stability. Transcriptome and proteome analysis revealed a partial compensation of the gene dosage changes that mitigates the effects of chromosome loss. Monosomy triggers global gene expression changes that differ from the effects of trisomy. We show that ribosome biogenesis and translation were commonly downregulated in monosomic cells, likely due to haploinsufficiency of ribosomal genes. The ensuing ribosome biogenesis stress triggers the p53 pathway and G1 arrest when TP53 is reintroduced into monosomic cells. Accordingly, impaired ribosome biogenesis and p53 inactivation are associated with monosomy in cancer. Our first systematic study of monosomy in human cells explains why monosomy is so detrimental and how loss of p53 enables its incidence in cancer.

systems biology↗

bioRxiv2020

Expectations and blind spots for structural variation detection from short-read alignment and long-read assembly

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.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2020

Versatile workflow for cell type resolved transcriptional and epigenetic profiles from cryopreserved human lung.

The complexity of the lung microenvironment together with changes in cellular composition during disease progression make it exceptionally hard to understand the molecular mechanisms leading to the development of chronic lung diseases. Although recent advances in cell type resolved and single-cell sequencing approaches hold great promise for studying complex diseases, their implementation greatly relies on local access to fresh tissue, as traditional methods to process and store tissue do not allow viable cell isolation. To overcome these hurdles, we developed a novel, versatile workflow that allows long-term storage of human lung tissue with high cell viability, permits thorough sample quality check before cell isolation, and is compatible with next generation sequencing-based profiling, including single-cell approaches. We demonstrate that cryopreservation is suitable for isolation of multiple cell types from different lung locations and is applicable to both healthy and diseased tissue, including COPD and tumor samples. Basal cells isolated from cryopreserved airways retain the ability to differentiate, indicating that cellular identity is not altered by cryopreservation. Importantly, using RNA sequencing (RNA-seq) and Illumina EPIC Array, we show that genome-wide gene expression and DNA methylation signatures are preserved upon cryopreservation, emphasizing the suitability of our workflow for -omics profiling of human lung cells. In addition, we obtained high-quality single-cell RNA sequencing data of cells isolated from cryopreserved human lung, demonstrating that cryopreservation empowers single-cell approaches. Overall, thanks to its simplicity, our cryopreservation workflow is well-suited for prospective tissue collection by academic collaborators and biobanks, opening worldwide access to human tissue.

cell biology↗

bioRxiv2019

A fully phased accurate assembly of an individual human genome

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.

bioinformatics↗

bioRxiv2019

Single cell tri-channel-processing reveals structural variation landscapes and complex rearrangement processes

Structural variation (SV), where rearrangements delete, duplicate, invert or translocate DNA segments, is a major source of somatic cell variation. It can arise in rapid bursts, mediate genetic heterogenity, and dysregulate cancer-related pathways. The challenge to systematically discover SVs in single cells remains unsolved, with copy-neutral and complex variants typically escaping detection. We developed single cell tri-channel-processing (scTRIP), a computational framework that jointly integrates read depth, template strand and haplotype phase to comprehensively discover SVs in single cells. We surveyed SV landscapes of 565 single cell genomes, including transformed epithelial cells and patient-derived leukemic samples, and discovered abundant SV classes including inversions, translocations and large-scale genomic rearrangements mediating oncogenic dysregulation. We dissected the molecular karyotype of the leukemic samples and examined their clonal structure. Different from prior methods, scTRIP also enabled direct detection and discrimination of SV mutational processes in individual cells, including breakage-fusion-bridge cycles. scTRIP will facilitate studies of clonal evolution, genetic mosaicism and somatic SV formation, and could improve disease classification for precision medicine.

genomics↗

bioRxiv2017

The whole-genome panorama of cancer drivers

The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.

cancer biology↗

bioRxiv2017

Enabling rapid cloud-based analysis of thousands of human genomes via Butler

We present Butler, a computational framework developed in the context of the international Pan-cancer Analysis of Whole Genomes (PCAWG)1 project to overcome the challenges of orchestrating analyses of thousands of human genomes on the cloud. Butler operates equally well on public and academic clouds. This highly flexible framework facilitates management of virtual cloud infrastructure, software configuration, genomics workflow development, and provides unique capabilities in workflow execution management. By comprehensively collecting and analysing metrics and logs, performing anomaly detection as well as notification and cluster self-healing, Butler enables large-scale analytical processing of human genomes with 43% increased throughput compared to prior setups. Butler was key for delivering the germline genetic variant call-sets in 2,834 cancer genomes analysed by PCAWG1.

bioinformatics↗