Biology subjects

Korbel, J. O.

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

At least 19 recordsLinked to original sources

bioRxiv2026

Escape from replicative crisis and immortalization precedes complex genome evolution

Shortening of telomeres restricts the proliferative capacity of human somatic cells by inducing replicative senescence and crisis. During cancerous transformation, premalignant cells must overcome these barriers and acquire replicative immortality. Single-cell DNA strand-specific genome sequencing of crisis cells revealed extreme genome instability characterized by complex chromosomal abnormalities. Unexpectedly, spontaneously emerging postcrisis clones showed relatively few and simple structural variants. However, with accumulating divisions following crisis escape, the genomes of immortal postcrisis clones evolve and amass genomic alterations, including tetraploidization events with subsequent losses and gains of individual chromosomes. Our data point towards a new model of tumorigenesis in which crisis acts as a strong selective barrier against cells with aberrant karyotypes, and in which high karyotypic complexity is acquired after immortalization and crisis escape.

cell biology↗

bioRxiv2026

HORoSCOPE: Decoding human centromere architecture from short reads using k-mer signatures

Centromeres safeguard genome integrity, yet their roles in human disease remain understudied because of their repetitive sequence. We present HOROSCOPE, a k-mer-based framework that infers centromere architecture and generates centromere length estimates directly from short-read data. Using a reference atlas of 11,836 centromeres from telomere-to-telomere haplotypes, we derive diagnostic k-mer signatures that classify chromosome-specific architectures with 98.2% precision and 99.1% recall. Applied to 4,029 genomes from 80 populations, HOROSCOPE uncovers continental centromeric structure and African-enriched rare architectures. Across 1,359 cancer genomes, HOROSCOPE reveals a dependency of chromosomal rearrangement locations on the kinetochore attachment site position.

genomics↗

bioRxiv2026

Population-scale Y chromosome assemblies reveal recurrent remodeling within constrained architectures

The human Y chromosome is among the most structurally dynamic chromosomes in the human genome, yet much of its diversity remains unresolved because of extensive palindromes, ampliconic gene families, satellite-rich heterochromatin and large segmental duplications. What remained unclear was how these diverse forms of variation fit together across the full chromosome, how often similar structures recur in different lineages, and which aspects of organization remain constrained despite rapid sequence turnover. Here, we generated and analyzed 142 nearly complete human Y chromosome assemblies from 17 major haplogroups spanning approximately 180,000 years of evolution, creating a population-scale resource for studying Y chromosome biology and diversity. These assemblies show that structural change on the Y chromosome is recurrent but constrained, even in its most repetitive regions. In the fertility-associated azoospermia factor c (AZFc) region, recurrent inversions, deletions, and complex rearrangements generate a limited repertoire of structural haplotypes. Multicopy ampliconic gene families follow distinct evolutionary paths: DAZ paralogues differ in structural constraint, RBMY evolves within a modular array, and TSPY copy number varies mainly through local expansion and contraction. The centromere and Yq12 heterochromatin vary greatly in size but retain a stable higher-order organization, including a single hypomethylated centromeric core and conserved Yq12 repeat composition and orientation. Methylation across palindromic and ampliconic regions is likewise structured by repeat class, copy order and local architecture. Together, these results provide a population-scale resource for the human Y chromosome and show that its rapid structural evolution is repeatedly funneled into a limited set of architectural outcomes.

genomics↗

bioRxiv2026

Alternative lengthening of telomeres stratifies complex karyotype sarcomas into distinct genomic and transcriptomic states

Complex karyotype sarcomas (CKS) are heterogeneous mesenchymal malignancies that typically lack recurrent actionable oncogenic drivers and remain therapeutically challenging. Loss of ATRX is a recurrent feature of CKS and defines a particularly high-risk subgroup. ATRX loss is also associated with activation of the alternative lengthening of telomeres (ALT) pathway, and ALT-positive sarcomas have been linked to poor clinical outcomes. However, the molecular underpinnings underlying ALT-status-dependent differences in CKS, as well as the therapeutic vulnerabilities associated with ALT, remain poorly defined. By integrating C-circle-based ALT detection across 776 sarcoma samples with multi-modal sequencing of five CKS subtypes, we find that ALT activity is associated with enriched hallmarks of genomic instability. ALT-positive transcriptomes are dominated by a coordinated DNA damage response and mitotic program, in contrast to oncogenic signaling pathways that drive TERT activation in ALT-negative tumors. Long-read sequencing reveals telomere repeat clusters and telomere-mediated healing at structural breakpoints in ALT-positive tumors. These events also occur on extrachromosomal DNA (ecDNA), linking ALT activity to ecDNA biology. Together, our findings position ALT status as an important stratifying feature of CKS and identify ALT-associated transcriptional programs as potential therapeutic targets.

cancer biology↗

bioRxiv2026

Selective autophagy of whole micronuclei suppresses chromosomal instability

Chromosomal instability (CIN) arising from mitotic errors generates pervasive structural and numerical chromosome alterations fueling cancer evolution1-3. Entrapment of missegregated chromosomes within micronuclei exacerbates CIN by fostering repeated rounds of aberrant mitotic segregation4-6 and, following micronucleus rupture, promoting catastrophic chromosomal rearrangement processes such as chromothripsis5-9. Whether cellular mechanisms exist to restrain micronucleus-driven CIN has remained unclear. Developing a live-cell chromatin acidification sensor, we tracked micronuclei from genesis through subsequent cell cycles and observed frequent whole-micronucleus capture and acidification via the autophagy pathway. Autophagic targeting is selective for micronuclei with nuclear envelope defects seeded at mitotic exit. Our data indicate that these defects drive progressive loss of chromatin-nuclear envelope tethering, producing a mechanically altered state that is recognised by the autophagic machinery. Autophagy and rupture represent distinct micronuclear fates with opposing genomic consequences. Single-cell sequencing of fate-matched cells demonstrates complete digestion of the chromosomal contents of autophagy-targeted micronuclei, a process we term chromophagy (chromosome-autophagy). By eliminating micronuclei, chromophagy promotes chromosomal loss and arrests the intergenerational transmission of missegregated chromosomal material. This constrains the mutational consequences of micronucleation and suppresses micronucleus-mediated CIN.

cell biology↗

bioRxiv2025

Smart Microscopy: Current Implementations and a Roadmap for Interoperability

Smart microscopy is transforming life sciences by automating experimental imaging workflows and enabling real-time adaptation based on feedback from images and other data streams. This shift increases throughput, improves reproducibility, and expands the functional capabilities of microscopes. However, the current landscape is highly fragmented. Academic researchers often develop custom solutions for specific scientific needs, while industry offerings are typically proprietary and tied to specific hardware. This diversity, while fostering innovation, also creates major challenges in interoperability, reproducibility, and standardization, which slows progress and adaption. This article presents a collaborative effort between academic and industry leaders to survey the current state of smart microscopy, highlight representative implementations, and identify common technical and organizational barriers. We propose a framework for greater interoperability based on shared standards, modular software design, and community-driven development. Our goal is to support collaboration across the field and lay the groundwork for a more connected, reusable, and accessible smart microscopy ecosystem. We conclude with a call to action for researchers, hardware developers, and institutions to join in building an open, interoperable foundation that will unlock the full potential of smart microscopy in life science research.

cell biology↗

bioRxiv2025

The JEDI marker as a universal measure of planetary biodiversity

Despite its critical importance in the formation and maintenance of ecosystems and homeostasis on Earth, biodiversity remains a complex and non-unified concept. Consequently, standards for measuring global biodiversity are lacking, hindering our capacity to document Earths biota and track its change. Here, we propose the Joint, cellular life-Encompassing DIversity (JEDI) marker as a simple, effective and quantitative measure to assess and monitor biodiversity. The JEDI marker is a ribosomal RNA gene fragment that can be amplified from all domains of life using a single pair of PCR primers. We demonstrate the applicability and effectiveness of this approach for assessing biodiversity across ecological and biological scales, from holobionts to diverse ecosystems. In addition, we provide an automated bioinformatic workflow to support the standardised and reproducible analysis of the JEDI marker in future studies. While this approach is not free from trade-offs, we argue that its advantages outweigh its limitations by providing a unique, operational and scalable solution that builds on established infrastructure to integrate the microbial majority into biodiversity assessments and provide fundamental insights into organismal dynamics and associations across domains of life. Thus, the JEDI marker approach addresses the urgent need for a universal and standardised framework to effectively measure and monitor biodiversity at planetary scales in an era of profound global change.

ecology↗

bioRxiv2025

Integrative spatial and multi-omic profiling in bladder cancer links L1 retrotransposition to extrachromosomal DNA, genomic instability, and viral mimicry response

Bladder cancer is one of the most frequent cancers and shows high recurrence rates. Despite recent advances, key knowledge gaps remain in understanding the molecular mechanisms of disease progression, which would support the development of early detection methods and effective personalized treatments. We apply integrated multi-omics and spatial analyses in a cohort of 49 bladder cancer patients to comprehensively profile genetic, epigenetic, transcriptomic, and spatial features of bladder cancer, alongside cell-free DNA blood analysis. Combining low-pass whole-genome cell-free DNA sequencing, Oxford Nanopore long-read tumor DNA sequencing, RNA-sequencing, and spatial transcriptomics, we provide insights into molecular alterations driving bladder cancer. We show frequent somatic LINE-1 (L1) insertions, with up to more than 500 insertions per tumor. We find that L1 insertions are active and occur early in bladder cancer development. We link aberrant somatic L1 insertion in bladder cancer with downstream genomic rearrangements and chromosomal instability, with an excess of structural variants and extrachromosomal DNA (ecDNA) in patients with particularly high L1 counts. By detecting ecDNA within tissue architecture using spatial transcriptomics, we identify the localization of ecDNA to distinct spatial clusters with differential expression of APOBEC3B and immune response pathways. These results, combined with replication timing analysis and gene set enrichment analysis (GSEA), offer evidence for the previously hypothesized viral mimicry response to L1 retrotransposition, mediated via APOBEC3B-editing, the cGAS-STING pathway, and RIG-I and MDA5 responses.

cancer biology↗

bioRxiv2025

Population differences of chromosome 22q11.2 duplication structure predisposes differentially to microdeletion and inversion.

The most common genomic disorder, chromosome 22q11.2 microdeletion syndrome (22q11.2DS), is mediated by highly identical and polymorphic segmental duplications (SDs) known as low copy repeats (LCRs; regions A-D) that have been challenging to sequence and characterize. Here, we report the sequence-resolved genomic architecture of 135 chromosome 22q11.2 haplotypes from diverse 1000 Genomes Project samples. We find that more than 90% of the copy number variation is polarized to the most proximal LCR region A (LCRA) where 50 distinct structural configurations are observed ([~]189 kbp to [~]2.15 Mbp or 11-fold length variation). A higher-order SD cassette structure of 105 kbp in length, flanked by 25 kbp long inverted repeats, drives this variation and emerged in the human-chimpanzee ancestral lineage later expanding in humans [~]1.0 [0.8-1.2] million years ago. African LCRA haplotypes are significantly longer (p=0.0047) when compared to non-Africans yet are predicted to be more protected against recurrent microdeletions (p=0.00053) due to a preponderance of flanking SDs in an inverted orientation. Conversely, we identified nine distinct inversion polymorphisms, including five recurrent [~]2.28 Mbp inversions extending across the critical region (LCRA-D) and four smaller inversions (two LCRA-B, one LCRC-D, and one LCRB-D); 7/9 of these events were identified in haplotypes of African and admixed American ancestry. Finally, we sequence and assemble four families and show that LCRA-D deletion breakpoints map to the 105 kbp repeat unit while inversion breakpoints associate with the 25 kbp repeats adjacent to palindromic AT-rich regions. In one family, we observe evidence of more complex unequal crossover events associated with gene conversion and multiple breakpoints. Our findings suggest that specific haplotype configurations are protective and susceptible to chromosome 22q11.2DS while recurrent large-scale inversions help to explain why this syndrome is less prevalent among individuals of African descent.

genomics↗

bioRxiv2025

Efficient protein structure generation with sparse denoising models

Generating designable protein backbones has become an integral part of machine learning-assisted approaches to protein design. Together with sequence design and structure predictor-based filtering, it forms the backbone of the computational protein design pipeline. However, current protein structure generators face important limitations for large proteins and require retraining for protein design tasks unseen during model training. To address the first issue, we introduce salad, a family of sparse all-atom denoising models for protein backbone generation. Our models are notably faster than the state-of-the-art while matching or improving designability and diversity, and generate designable structures for protein lengths up to 1,000 amino acids. To address the second issue, we combine salad with structure-editing, a strategy for expanding the capability of protein denoising models to unseen tasks. We apply our approach to a variety of protein design tasks, from motif-scaffolding to multi-state protein design, demonstrating the flexibility of salad and structure-editing.

bioinformatics↗

bioRxiv2024

Origins of de novo chromosome rearrangements unveiled by coupled imaging and genomics

Chromosomal instability results in widespread structural and numerical chromosomal abnormalities (CAs) during cancer evolution1-3. While CAs have been linked to mitotic errors resulting in the emergence of nuclear atypias4-7, the underlying processes and basal rates of spontaneous CA formation in human cells remain under-explored. Here we introduce machine learning-assisted genomics-and-imaging convergence (MAGIC), an autonomously operated platform that integrates automated live-cell imaging of micronucleated cells, machine learning in real-time, and single-cell genomics to investigate de novo CA formation at scale. Applying MAGIC to near-diploid, non-transformed cell lines, we track CA events over successive cell cycles, highlighting the common role of dicentric chromosomes as an initiating event. We determine the baseline CA rate, which approximately doubles in TP53-deficient cells, and show that chromosome losses arise more rapidly than gains. The targeted induction of DNA double-strand breaks along chromosomes triggers distinct CA processes, revealing stable isochromosomes, amplification and coordinated segregation of isoacentric segments in multiples of two, and complex CA outcomes, depending on the break location. Our data contrast de novo CA spectra from somatic mutational landscapes after selection occurred. The large-scale experimentation enabled by MAGIC provides insights into de novo CA formation, paving the way to unravel fundamental determinants of chromosome instability.

genomics↗

bioRxiv2024

Role of Stem-Like Cells in Chemotherapy Resistance and Relapse in pediatric T Cell Acute Lymphoblastic Leukemia

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive leukemia predominantly affecting adolescents and young adults. T-ALL relapses are characterized by chemotherapy resistance, cellular heterogeneity and dismal outcome. To gain a deeper understanding of the cellular heterogeneity and mechanisms driving relapse, we conducted single-cell full-length RNA sequencing of 13 matched pediatric T-ALL patient-derived xenografts (PDX) samples obtained at initial diagnosis and relapse, generating the to date most comprehensive longitudinal single cell study in paired T-ALL samples, along with 5 non-relapsing PDX samples collected at initial diagnosis. This dataset identifies considerable transcriptomic diversity among individual T-ALL cell populations. Notably however, 11 of the 18 patients exhibit a small T-ALL cell subpopulation with a shared set of gene regulatory networks characterized by a common set of active regulons, expression patterns and splice isoforms. This profile involves the upregulation of a stem-like cell signature with enrichment of cell adhesion, and inhibition of the cell cycle and metabolic activity. Comprehensive investigations of these networks identify transcripts enforcing drug resistance through NF-{kappa}B expression and TGF-{beta} signaling and of anti-apoptotic T cell signaling. Longitudinal monitoring of these stem-like cells demonstrates this subpopulation to account for only a small proportion of leukemia cells initially with a substantial expansion at relapse suggesting resistance to first line therapy. Chemotherapy resistance is functionally corroborated through in vitro and in vivo drug testing. We thus report the discovery of inherently treatment-resistant stem-like T-ALL cell populations underscoring the potential for devising future therapeutic strategies aimed at targeting stemness pathways in pediatric T-ALL. Key PointsO_LISingle-cell full-length RNA sequencing reveals dormant, treatment-resistant cells expanding upon T cell acute lymphoblastic leukemia relapse. C_LIO_LIStem-like T-ALL cells exhibit a shared gene regulatory network conferring chemotherapy resistance and relapse. C_LI

cancer biology↗

bioRxiv2024

Integrating Multi-Modal Cancer Data Using Deep Latent Variable Path Modelling

Cancers are commonly characterised by a complex pathology encompassing genetic, microscopic and macroscopic features, which can be probed individually using imaging and omics technologies. Integrating this data to obtain a full understanding of pathology remains challenging. We introduce a new method called Deep Latent Variable Path Modelling (DLVPM), which combines the representational power of deep learning with the capacity of path modelling to identify relationships between interacting elements in a complex system. To evaluate the capabilities of DLVPM, we initially trained a foundational model to map dependencies between SNV, Methylation, miRNA-Seq, RNA-Seq and Histological data using Breast Cancer data from The Cancer Genome Atlas (TCGA). This method exhibited superior performance in mapping associations between data types compared to classical path modelling. We additionally performed successful applications of the model to: stratify single-cell data, identify synthetic lethal interactions using CRISPR-Cas9 screens derived from cell-lines, and detect histologic-transcriptional associations using spatial transcriptomic data. Results from each of these data types can then be understood with reference to the same holistic model of illness.

cancer biology↗

bioRxiv2024

Long-read sequencing and structural variant characterization in 1,019 samples from the 1000 Genomes Project

Structural variants (SVs) contribute significantly to human genetic diversity and disease1-4. Previously, SVs have remained incompletely resolved by population genomics, with short-read sequencing facing limitations in capturing the whole spectrum of SVs at nucleotide resolution5-7. Here we leveraged nanopore sequencing8 to construct an intermediate coverage resource of 1,019 long-read genomes sampled within 26 human populations from the 1000 Genomes Project. By integrating linear and graph-based approaches for SV analysis via pangenome graph-augmentation, we uncover 167,291 sequence-resolved SVs in these samples, considerably advancing SV characterization compared to population-wide short-read sequencing studies3,4. Our analysis details diverse SV classes--deletions, duplications, insertions, and inversions--at population-scale. LINE-1 and SVA retrotransposition activities frequently mediate transductions9,10 of unique sequences, with both mobile element classes transducing sequences at either the 3'- or 5'-end, depending on the source element locus. Furthermore, analyses of SV breakpoint junctions suggest a continuum of homology-mediated rearrangement processes are integral to SV formation, and highlight evidence for SV recurrence involving repeat sequences. Our open-access dataset underscores the transformative impact of long-read sequencing in advancing the characterisation of polymorphic genomic architectures, and provides a resource for guiding variant prioritisation in future long-read sequencing-based disease studies.

genomics↗

bioRxiv2023

Break-induced replication underlies formation of inverted triplications and generates unexpected diversity in haplotype structures

BackgroundThe duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a type of complex genomic rearrangement (CGR) hypothesized to result from replicative repair of DNA due to replication fork collapse. It is often mediated by a pair of inverted low-copy repeats (LCR) followed by iterative template switches resulting in at least two breakpoint junctions in cis. Although it has been identified as an important mutation signature of pathogenicity for genomic disorders and cancer genomes, its architecture remains unresolved and is predicted to display at least four structural variation (SV) haplotypes. ResultsHere we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the genomic DNA of 24 patients with neurodevelopmental disorders identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted SV haplotypes. Using a combination of short-read genome sequencing (GS), long- read GS, optical genome mapping and StrandSeq the haplotype structure was resolved in 18 samples. This approach refined the point of template switching between inverted LCRs in 4 samples revealing a DNA segment of [~]2.2-5.5 kb of 100% nucleotide similarity. A prediction model was developed to infer the LCR used to mediate the non-allelic homology repair. ConclusionsThese data provide experimental evidence supporting the hypothesis that inverted LCRs act as a recombinant substrate in replication-based repair mechanisms. Such inverted repeats are particularly relevant for formation of copy-number associated inversions, including the DUP-TRP/INV-DUP structures. Moreover, this type of CGR can result in multiple conformers which contributes to generate diverse SV haplotypes in susceptible loci.

genetics↗

bioRxiv2023

Cell type-specific consequences of mosaic structural variants in hematopoietic stem and progenitor cells

The functional impact and cellular context of mosaic structural variants (mSVs) in normal tissues is understudied. Utilizing Strand-seq, we sequenced 1,133 single cell genomes from 19 human donors of increasing age, revealing a heterogeneous mSV landscape in hematopoietic stem and progenitor cells (HSPCs). While mSV clonal expansions are confined to individuals over 60, de novo mSV formation occurs consistently across age, frequently leading to megabase-scale segmental aneuploidies. Cells harboring subclonal mosaicism show evidence for increased mSV formation. To enable high-resolution cell-typing of each Strand-seq library, we generated single-cell MNase-seq reference datasets for eight distinct HSPCs. Subclonal mSVs frequently exhibit enrichment in myeloid progenitors, and single-cell multiomic analysis suggests that these mSVs result in recurrent dysregulation of pathways related to proliferation and metabolism, including Ras signaling and lipid metabolism. The comprehensive mSV landscape identified in this study implicates mSVs in cell type-specific molecular phenotypes, establishing a foundation for deciphering links between mSVs, aging, and disease risk.

genomics↗

bioRxiv2023

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

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 standardised 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 normalisation module, integration of the scNOVA 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 enables reproducible computational processing of Strand-seq data, which are increasingly used in human genetics and single cell genomics, towards production environments. Availability and ImplementationMosaicatcher v2 is a standardised 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. Contactjan.korbel@embl.de Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

A comprehensive catalog of 3D genome organization in diverse human genomes facilitates understanding of the impact of structural variation on chromatin structure

The human genome is packaged into the three-dimensional (3D) nucleus and organized into functional units known as topologically associating domains (TADs) and chromatin loops. Recent studies show that the 3D genome can be modified by genome structural variants (SVs) through disrupting higher-order chromatin organizations such as TADs, which play an essential role in insulating genes from aberrant regulation by regulatory elements outside TADs. Here, we have developed an integrative Hi-C analysis pipeline to generate a comprehensive catalog of TADs, TAD boundaries, and loops in human genomes to fill the gap of limited resources. We identified 2,293 TADs and 6,810 sub-TADs missing in the previously released TADs of GM12878. We then quantified the impact of SVs overlapping with TAD boundaries and observed that two SVs could significantly alter chromatin architecture leading to abnormal expression and splicing of genes associated with human diseases.

genomics↗