Biology subjects

Rausch, T.

Publications and source records attributed to Rausch, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Hierarchical classification of hematologic malignancies using epigenetic and genetic information

Molecular testing in hematology requires different assays for disease subgroup identification, risk stratification and selection of appropriate treatment regimens. Yet, molecular tests are not necessarily standardized between diagnostic laboratories, resulting in varying turnaround times and potentially divergent results. To resolve this issue and enable single-assay molecular testing, we have developed a hierarchical classification framework that combines epigenetic and genetic data from whole genome nanopore sequencing (WGNS) with machine learning to determine disease entities, epigenetic subgroups (epitypes) and genetic aberrations in hematopoietic neoplasms. We curated DNA methylation data from 5,420 samples and trained a classifier allowing entity-level diagnostics featuring 21 conditions, including healthy controls, acute and chronic myeloid and lymphoid neoplasms. This classifier was subsequently combined with entity-specific epitype classifiers predicting 44 therapeutically or prognostically relevant states, followed by integration of genetic data. Benchmarking of the combined (epi-)genetic testing strategy using WGNS confirmed high accuracy in the detection of diagnostic groups and risk stratification, and identified diagnosis-defining molecular alterations that were not reported by standard-of-care work-up.

cancer 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

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↗

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↗

bioRxiv2024

Complex genetic variation in nearly complete human genomes

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

genomics↗

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

Crossovers are regulated by a conserved and disordered synaptonemal complex domain

To ensure the accurate segregation of homologous chromosomes and enhance the genetic diversity in the progeny, meiosis depends on the formation of crossovers between homologous chromosomes. The number and distribution of these crossovers must be precisely regulated through crossover assurance and interference to prevent chromosome missegregation and genomic instability. Here we show that the regulation of crossovers depends on a disordered domain within the synaptonemal complex, which is highly conserved. This domain is located at the C-terminus of the central element protein SYP-4 in C. elegans. While not necessary for synapsis, the C-terminus of SYP-4 is crucial for both crossover assurance and interference. Although the SYP-4 C-terminus contains many potential phosphorylation sites, we found that phosphorylation is not the primary regulator of crossover events. Instead, we discovered that nine conserved phenylalanines recruit a pro-crossover factor predicted to be an E3 ligase and regulate the physical properties of the synaptonemal complex. We propose that this conserved and disordered domain plays a crucial role in maintaining the synaptonemal complex in an activated state to promote crossing-over. This activation allows the synaptonemal complex to regulate the number and distribution of crossovers along chromosomes, thereby protecting the genome for future generations.

cell biology↗

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

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↗

bioRxiv2024

SVarp: pangenome-based structural variant discovery

The linear human reference genome that we use today does not represent the haplotypic diversity of the global human population. This raises bias in genomic read alignment and limits our ability to call large structural variations (SV), especially at highly polymorphic loci. Thus, many SV alleles remain unresolved. Recent efforts to transition to a graph-based reference genome resulted in the generation of the first draft human pangenome reference, but tools to call SVs relative to the pangenome reference are presently lacking. In this study, we present the SVarp algorithm, aiming to discover haplotype resolved SVs on top of a pangenome reference using long sequencing reads. SVarp outputs local assemblies of SV alleles, termed svtigs, instead of a VCF file of SV breakpoints, which we propose as a general exchange format allowing for flexible downstream analyses. In order to assess the accuracy of svtigs, we used simulated and real human genomes. Simulations allowed us to make exact breakpoint comparisons against the true callsets. We observed [~]96% recall with deletions, insertions and duplications larger than 1,000bp, showing that SVarp can reliably detect genomic structural variants not yet represented in the graph. On the other hand, we compared SVarp output for ONT sequencing data at 20X coverage against independent genome assemblies of the same samples and found that [~]82% of our svtig predictions are validated by the assemblies by a match with more than 85% sequence identity. SVarp was implemented using C++ and its source code is available at https://github.com/asylvz/SVarp under MIT license.

bioinformatics↗

bioRxiv2024

MAPK activity and MAP kinase phosphatase 2 (AtMKP2) protein stability under altered glutathione homeostasis in Arabidopsis thaliana

Mitogen-activated protein kinases (MAPKs) are important signaling players involved in various responses to diverse environmental stresses. MAP kinase phosphatases (MKPs) are crucial negative regulators of MAPKs and control the intensity and duration of MAPK activation. It has been shown that transgenic tobacco plants with increased glutathione content display an oxidative shift and have constitutively active immunity-related MAPKs. The mechanism by which glutathione can activate or keep these MAPKs in activated state is unclear. In this study, it is shown that the Arabidopsis stress-related MAPKs, AtMPK3 and AtMPK6 are hypersensitive to a pathogen-associated molecular pattern flg22 in the cat2-1 line, under the conditions causing an altered glutathione homeostasis and elevated oxidative stress responses in this background. As AtMKP2 is the only dual specificity phosphatase deactivating AtMPK3 and AtMPK6 in response to oxidative stress, the stability of the wild-type AtMKP2 protein and the mutant version of the protein with the substitution of the cys109 in the active site with serine has been studied in wild type (Col-0) and cat2-1 background. The results indicate that AtMKP2 is a stable protein in both genetic backgrounds, whereas the active site cys109 stabilizes the protein under severe oxidative stress conditions and can be glutathionylated in vitro.

plant biology↗

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

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

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-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↗

bioRxiv2020

De novo assembly of 64 haplotype-resolved human genomes of diverse ancestry and integrated analysis of structural variation

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.

genetics↗

bioRxiv2020

Pangenome-based genome inference

AO_SCPLOWBSTRACTC_SCPLOWTypical analysis workflows map reads to a reference genome in order to detect genetic variants. Generating such alignments introduces references biases, in particular against insertion alleles absent in the reference and comes with substantial computational burden. In contrast, recent k-mer-based genotyping methods are fast, but struggle in repetitive or duplicated regions of the genome. We propose a novel algorithm, called PanGenie, that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation. The given haplotypes enable our method to take advantage of linkage information to aid genotyping in regions poorly covered by unique k-mers and provides access to regions otherwise inaccessible by short reads. Compared to classic mapping-based approaches, our approach is more than 4x faster at 30x coverage and at the same time, reached significantly better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (> 50bp), where we are able to genotype > 99.9% of all tested variants with over 90% accuracy at 30x short-read coverage, where the best competing tools either typed less than 60% of variants or reached accuracies below 70%. PanGenie now enables the inclusion of this commonly neglected variant type in downstream analyses.

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↗