Biology subjects

Demeulemeester, J.

Publications and source records attributed to Demeulemeester, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Chromosomal instability shapes spatial and temporal phenotypic diversity in a malignant peripheral nerve sheath tumour

Understanding the spatial and temporal dynamics of tumour evolution is crucial for determining the drivers of cancer progression. Linking genotype to phenotype across a tumour remains challenging, however. Here, we use single-cell and spatial multi-omics to comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its multifocal recurrence. Combining the native barcoding system from extensive heterogeneity in copy number alterations with mutation data, we resolve the evolutionary tree of this tumour, revealing a branching structure suggestive of ongoing chromosomal instability. We show that gene dosage effects contribute to phenotypic diversity and scale predominantly linearly with copy number. Using spatial genomics assisted by laser capture microdissection and spatial transcriptomics, we performed in situ lineage tracing in this human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment. These findings demonstrate the potential of combined bulk, single-cell and spatial techniques to dissect cancer evolution in time and space and link genotype to phenotype in detail.

genomics↗

bioRxiv2026

Modeling cis-regulatory variation in human brain enhancers across a large Parkinson's Disease cohort

Genome-wide association studies (GWAS) have linked more than a hundred non-coding genomic loci to Parkinsons disease (PD) risk. Deciphering their functional impact on gene regulation requires cell type-aware modeling approaches to assess the effects of sequence variation on enhancer function and target gene expression. To address this challenge, we generated a comprehensive matched dataset from 190 human donors (115 controls and 75 PD), comprising long-read whole-genome sequencing alongside single nucleus multiome atlases (snATAC-seq and snRNA-seq for 3.1 and 1.1 million nuclei respectively) of the anterior cingulate cortex and substantia nigra. By integrating chromatin accessibility quantitative trait loci (caQTL), DNA methylation QTL (meQTL), and allele-specific chromatin accessibility (ASCA), we identified 53,841 high-confidence cis-acting genetic variants that modulate cell type-specific enhancer accessibility in one or both brain regions. We further demonstrate that sequence-to-function models can accurately predict the impact of these variants directly from the genomic sequence. Novel explainability approaches allowed stratifying these variants according to their regulatory function, with the majority disrupting specific transcription factor binding sites in a cell type specific manner. Integrating these "enhancer variants" (EV) with eQTL mapping and gene locus modeling linked a subset of EVs to their target genes. Finally, we applied these models to prioritize regulatory variants at known PD GWAS loci, bypassing statistical limitations in rare disease-relevant populations like dopaminergic neurons. All together, we establish a unique resource and new sequence modeling strategies to interpret functional non-coding variation in the human brain.

genomics↗

bioRxiv2026

LRSomatic: a highly scalable and robust pipeline for somatic variant calling in long-read sequencing data

MotivationLong-read sequencing is increasingly used in cancer research and clinical genomics due to its ability to resolve complex genomic variation and previously inaccessible regions of the genome. However, dedidated workflows for comprehensive somatic variant analysis from long-read whole-genome data remain scarce, limiting uptake in cancer genomics. ResultsWe present LRSomatic, a Nextflow-based, nf-core-compliant pipeline supporting somatic SNV, indel, structural variant, and copy number calling from PacBio HiFi and ONT data. LRSomatic supports paired tumor-normal and tumor-only designs, as well as integration of epigenetic integration via Fiber-seq. Benchmarked on COLO829 and HG008 reference cell lines, LRSomatic achieves state-of-the-art performance across both platforms and variant types. Applied to a case of clear cell sarcoma, it recovers all identified driver alterations, including the pathognomonic EWSR1::ATF1 fusion, and resolves haplotype-specific chromatin accessibility via Fiber-seq. Availability and ImplementationFreely available at https://github.com/intgenomicslab/lrsomatic, implemented in Nextflow DSL2, supported via Docker and Singularity.

bioinformatics↗

bioRxiv2025

Long-read single-cell genome, transcriptome and open chromatin profiling links genotype to phenotypes.

Current single-cell multiomics methods typically provide limited genomic information, constraining genotype-phenotype studies. To address this gap, we developed SPLONGGET (Single-cell Profiling of LONG-read Genome, Epigenome, and Transcriptome), which integrates 10X Genomics barcoding with Oxford Nanopore sequencing to simultaneously profile genome, chromatin accessibility, and full-length transcriptomes in thousands of single cells. By retaining all tagmentation fragments during library preparation, SPLONGGET delivers whole-genome coverage, supports target enrichment for effective single-cell genotyping, and remains backwards compatible with existing short-read workflows. SPLONGGET enables comprehensive calling of small variants, structural variants, and copy number alterations. Applying SPLONGGET to paediatric B-cell acute lymphoblastic leukaemia revealed clonal dynamics and the phenotypic effects of somatic variants. Notably, we evidence parallel evolution of immune escape variants with four distinct splice site mutations and loss of heterozygosity in the CAR T-cell therapy CD19 target. In conclusion, SPLONGGET enables integrated high-throughput analysis of genetic variation and molecular phenotypes using off-the-shelf kits, offering a timely and powerful tool to study genetically heterogeneous samples, such as tumours but also ageing normal tissues.

genomics↗

bioRxiv2025

An optimised computational approach for the identification of somatic structural variants in cancer

Structural variants play a critical role in tumorigenesis. At present, these events are most commonly identified using short-read whole-genome sequencing data, and a number of computational tools are available for this purpose. Consensus approaches have been used to improve precision, but may reduce sensitivity. The optimal number and combination of callers remains unclear, in part due to the lack of gold standard real-world datasets for validation. Here, we benchmark the performance of Delly, GRIDSS, LUMPY, Manta and SvABA, using a validation set of consensus calls from the Pan-Cancer Analysis of Whole Genomes Consortium. Manta showed the best standalone performance, identifying 88% of the validation set calls, and was included in all of the best-performing caller combinations. A consensus approach comprising Delly, GRIDSS, Manta and SvABA was selected as the optimum approach from those tested. We provide a NextFlow implementation of our optimised consensus approach as a resource for the cancer genomics community.

genomics↗

bioRxiv2025

MYC-induced oncogenesis is dependent on acidic patches within its N-terminal intrinsically disordered domain.

MYC is one of the most enticing therapeutic targets for cancer but clinical-grade inhibitors are still lacking. By site-saturation mutagenesis screening, we identified several evolutionarily conserved acidic patches within the intrinsically-disordered MYC N-terminus that were confirmed to be functionally essential in different cell models and in vivo. Beyond modulating MYCs global transcriptional activity, these negatively charged patches regulate the interaction with chromatin-modifying complexes including those with histone acetyl-transferase activity. One of the key interactions is established with the co-factor TRRAP, a subunit shared between several Histone Acetyl-Transferase complexes. The protein-protein binding between MYC and TRRAP predominantly relies on two of the N-terminal negative clusters that are located outside MYC-Box-II (MBII) and drive oncogenesis. Our work identifies a new multivalent MYC subdomain that presents new therapeutic vulnerabilities providing invaluable insights for the development of new therapeutic approaches.

cancer biology↗

bioRxiv2024

Focal Deletions of a Promoter Tether Activate the IRX3 Oncogene in T Cell Acute Lymphoblastic Leukemia

Oncogenes can be activated in cis through multiple mechanisms including enhancer hijacking events and noncoding mutations that create enhancers or promoters de novo. These paradigms have helped parse somatic variation of noncoding cancer genomes, thereby providing a rationale to identify noncanonical mechanisms of gene activation. Here we describe a novel mechanism of oncogene activation whereby focal copy number loss of an intronic element within the FTO gene leads to aberrant expression of IRX3, an oncogene in T cell acute lymphoblastic leukemia (T-ALL). Loss of this CTCF bound element downstream to IRX3 (+224 kb) leads to enhancer hijack of an upstream developmentally active super-enhancer of the CRNDE long noncoding RNA (-644 kb). Unexpectedly, the CRNDE super-enhancer interacts with the IRX3 promoter with no transcriptional output until it is untethered from the FTO intronic site. We propose that promoter tethering of oncogenes to inert regions of the genome is a previously unappreciated biological mechanism preventing tumorigenesis.

cancer biology↗

bioRxiv2023

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. We compared PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrated different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we performed CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We found that 38% of brain cells have at least one Mb-scale CNV, with some supported by bulk sequencing or single-cells from other brain regions. Our study highlights the importance of selecting whole genome amplification method and reference genome for CNV calling, while supporting the existence of somatic CNVs in healthy and diseased human brain.

neuroscience↗

bioRxiv2023

A multi-omics genome-and-transcriptome single-cell atlas of human preimplantation embryogenesis reveals the cellular and molecular impact of chromosome instability

The frequent acquisition of genomic abnormalities in human preimplantation embryos is a leading cause of pregnancy loss, but does not necessarily prohibit healthy offspring. However, the impact of genomic abnormalities on cellular states and development of the early human embryo remains largely unclear. Here, we characterise aneuploidy and reconstruct gene regulatory networks in human preimplantation embryos, and investigate gene expression and developmental perturbations instigated by aneuploidy using single-cell genome-and-transcriptome sequencing (G&T-seq). At the genomic level, we show that acquired numerical and structural chromosomal aberrations are frequent across all stages of early embryogenesis and in all cell lineages. At the transcriptome level, we identify regulators of cell identity and uncover a network of 248 transcription factors from 10 major gene regulatory modules that characterise the distinct lineages of human preimplantation embryos. By integrating single-cell DNA-with RNA-information, we unveil how expression levels are affected by losses or gains of the corresponding genes in embryonic cells across human preimplantation development, as well as how copy-number aberrant transcription factor genes perturb the expression of their cognate target genes in euploid regions. Furthermore, we reveal a majority of aneuploid cells show a developmental delay and reduced fitness, indicating cell competition within the mosaic diploid-aneuploid embryo, which may contribute to selection against aneuploid cells and the birth of healthy offspring from mosaic diploid-aneuploid embryos. In summary, our multi-modal analyses provide unprecedented insights into early human embryo development.

developmental biology↗

bioRxiv2023

Single-cell Genome-and-Transcriptome sequencing without upfront whole-genome amplification reveals cell state plasticity of melanoma subclones

Single-cell multi-omics methods are enabling the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at both the single-cell and pseudo-bulk level when compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Moreover, applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method enabling the exploration of genetic alterations and their functional consequences in single cells at scale.

genomics↗

bioRxiv2022

Enhancer grammar of liver cell types and hepatocyte zonation states

Cell type identity is encoded by gene regulatory networks (GRN), in which transcription factors (TFs) bind to enhancers to regulate target gene expression. In the mammalian liver, lineage TFs have been characterized for the main cell types, including hepatocytes. Hepatocytes cover a relatively broad cellular state space, as they differ significantly in their metabolic state, and function, depending on their position with respect to the central or portal vein in a liver lobule. It is unclear whether this spatially defined cellular state space, called zonation, is also governed by a well-defined gene regulatory code. To address this challenge, we have mapped enhancer-GRNs across liver cell types at high resolution, using a combination of single cell multiomics, spatial omics, GRN inference, and deep learning. We found that cell state changes in transcription and chromatin accessibility in hepatocytes, liver sinusoidal endothelial cells and hepatic stellate cells depend on zonation. Enhancer-GRN mapping suggests that zonation states in hepatocytes are driven by the repressors Tcf7l1 and Tbx3, that modulate the core hepatocyte GRN, controlled by Hnf4a, Cebpa, Hnf1a, Onecut1 and Foxa1, among others. To investigate how these TFs cooperate with cell type TFs, we performed an in vivo massively parallel reporter assay on 12,000 hepatocyte enhancers and used these data to train a hierarchical deep learning model (called DeepLiver) that exploits both enhancer accessibility and activity. DeepLiver confirms Cebpa, Onecut, Foxa1, Hnf1a and Hnf4a as drivers of enhancer specificity in hepatocytes; Tcf7l1/2 and Tbx3 as regulators of the zonation state; and Hnf4a, Hnf1a, AP-1 and Ets as activators. Finally, taking advantage of in silico mutagenesis predictions from DeepLiver and enhancer assays, we confirmed that the destruction of Tcf7l1/2 or Tbx3 motifs in zonated enhancers abrogates their zonation bias. Our study provides a multi-modal understanding of the regulatory code underlying hepatocyte identity and their zonation state, that can be exploited to engineer enhancers with specific activity levels and zonation patterns.

genomics↗

bioRxiv2022

System-wide mapping of neuropeptide-GPCR interactions in C. elegans

Neuropeptides are ancient, widespread signaling molecules that underpin almost all brain functions. They constitute a broad ligand-receptor network, mainly by binding to G protein-coupled receptors (GPCRs). However, the organization of the peptidergic network and roles of many neuropeptides remain elusive, as our insight into neuropeptide-receptor interactions is limited and many peptide GPCRs in animal models and humans are still orphan receptors. Here we report a genome-wide neuropeptide-GPCR interaction map in C. elegans. By reverse pharmacology screening of over 55,384 possible interactions, we identify 461 cognate peptide-GPCR couples that uncover a broad signaling network with specific and complex combinatorial interactions encoded across and within single peptidergic genes. These interactions provide insights into neuropeptide functions and evolution. Combining our dataset with phylogenetic analysis supports peptide-receptor co-evolution and conservation of at least 14 bilaterian peptidergic systems in C. elegans. This resource lays a foundation for system-wide analysis of the peptidergic network. HighlightsO_LISystem-wide reverse pharmacology deorphanizes 68 C. elegans peptide GPCRs C_LIO_LIDiscovery of 461 peptide-GPCR pairs and additional ligands for characterized GPCRs C_LIO_LINeuropeptides show specific and complex combinatorial receptor interactions C_LIO_LIPeptide-GPCR pairs support long-range conservation and expansion of peptide systems C_LI

neuroscience↗

bioRxiv2022

The evolution of two transmissible leukaemias colonizing the coasts of Europe

Transmissible cancers are malignant cell clones that spread among individuals through transfer of living cancer cells. Several such cancers, collectively known as bivalve transmissible neoplasia (BTN), are known to infect and cause leukaemia in marine bivalve molluscs. This is the case of BTN clones affecting the common cockle, Cerastoderma edule, which inhabits the Atlantic coasts of Europe and north-west Africa. To investigate the origin and evolution of contagious cancers in common cockles, we collected 6,854 C. edule specimens and diagnosed 390 cases of BTN. We then generated a reference genome for the species and assessed genomic variation in the genomes of 61 BTN tumours. Analysis of tumour-specific variants confirmed the existence of two cockle BTN lineages with independent clonal origins, and gene expression patterns supported their status as haemocyte-derived marine leukaemias. Examination of mitochondrial DNA sequences revealed several mitochondrial capture events in BTN, as well as co-infection of cockles by different tumour lineages. Mutational analyses identified two lineage-specific mutational signatures, one of which resembles a signature associated with DNA alkylation. Karyotypic and copy number analyses uncovered genomes marked by pervasive instability and polyploidy. Whole-genome duplication, amplification of oncogenes CCND3 and MDM2, and deletion of the DNA alkylation repair gene MGMT, are likely drivers of BTN evolution. Characterization of satellite DNA identified elements with vast expansions in the cockle germ line, yet absent from BTN tumours, suggesting ancient clonal origins. Our study illuminates the evolution of contagious cancers under the sea, and reveals long-term tolerance of extreme instability in neoplastic genomes.

evolutionary biology↗

bioRxiv2022

Crowd-sourced benchmarking of single-sample tumour subclonal reconstruction

Tumours are dynamically evolving populations of cells. Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumour evolution, allowing assessment of how cancers initiate, progress and respond to selective pressures. A plethora of subclonal reconstruction algorithms have been created, but their relative performance across the varying biological and technical features of real-world cancer genomic data is unclear. We therefore launched the ICGC-TCGA DREAM Somatic Mutation Calling -- Tumour Heterogeneity and Evolution Challenge. This seven-year community effort used cloud-computing to benchmark 31 containerized subclonal reconstruction algorithms on 51 simulated tumours. Each algorithm was scored for accuracy on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance significantly more than tumour features, but purity-adjusted read-depth, copy number state and read mappability were associated with performance of most algorithms on most tasks. No single algorithm was a top performer for all seven tasks and existing ensemble strategies were surprisingly unable to outperform the best individual methods, highlighting a key research need. All containerized methods, evaluation code and datasets are available to support further assessment of the determinants of subclonal reconstruction accuracy and development of improved methods to understand tumour evolution.

bioinformatics↗

bioRxiv2021

Analysis of long and short enhancers in melanoma cell states

Understanding how enhancers drive cell type specificity and efficiently identifying them is essential for the development of innovative therapeutic strategies. In melanoma, the melanocytic (MEL) and the mesenchymal-like (MES) states present themselves with different responses to therapy, making the identification of specific enhancers highly relevant. Using massively parallel reporter assay (MPRA) in a panel of patient-derived melanoma lines (MM lines), we set to identify and decipher melanoma enhancers by first focusing on regions with state specific H3K27 acetylation close to differentially expressed genes. A more in-depth evaluation of those regions was then pursued by investigating the activity of ATAC-seq peaks found therein along with a full tiling of the acetylated regions with 190 bp sequences. Activity was observed in more than 60% of the selected regions and we were able to precisely locate the active regions within ATAC-seq peaks. Comparison of sequence content with activity, using the deep learning model DeepMEL2, revealed that AP-1 alone is responsible for the MES enhancer activity, while SOX and MITF both influence MEL enhancer activity with SOX being required to achieve high levels of activity. Overall, our MPRA assays shed light on the relationship between long and short sequences in terms of their sequence content, enhancer activity, and specificity as reporters across melanoma cell states.

genomics↗

bioRxiv2021

Aberrant integration of Hepatitis B virus DNA promotes major restructuring of human hepatocellular carcinoma genome architecture

Most cancers are characterized by the somatic acquisition of genomic rearrangements during tumour evolution that eventually drive the oncogenesis. There are different mutational mechanisms causing structural variation, some of which are specific to particular cancer types. Here, using multiplatform sequencing technologies, we identify and characterize a remarkable mutational mechanism in human hepatocellular carcinoma caused by Hepatitis B virus, by which DNA molecules from the virus are inserted into the tumour genome causing dramatic changes in its configuration, including non-homologous chromosomal fusions and megabase-size telomeric deletions. This aberrant mutational process, present in at least 8% of all HCC tumours, is active early during liver cancer evolution and can provide the driver rearrangements that a cancer clone requires to survive and grow.

cancer biology↗

bioRxiv2021

Biallelic mutations in cancer genomes reveal local mutational determinants

The infinite sites model of molecular evolution requires that every position in the genome is mutated at most once1. It is a cornerstone of tumour phylogenetic analysis2, and is often implied when calling, phasing and interpreting variants3,4 or studying the mutational landscape as a whole5. Here we identify 20,555 biallelic mutations, where the same base is mutated independently on both parental copies, in 722 (26.0%) bulk sequencing samples from the Pan-Cancer Analysis of Whole Genomes study (PCAWG). Biallelic mutations reveal UV damage hotspots at ETS and NFAT binding sites, and hypermutable motifs in POLE-mutant and other cancers. We formulate recommendations for variant calling and provide frameworks to model and detect biallelic mutations. These results highlight the need for accurate models of mutation rates and tumour evolution, as well as their inference from sequencing data.

cancer biology↗

bioRxiv2020

A neural crest stem cell-like state drives nongenetic resistance to targeted therapy in melanoma

The ability to predict the future behaviour of an individual cancer is crucial for precision cancer medicine and, in particular, for the development of strategies that prevent acquisition of resistance to anti-cancer drugs. Therapy resistance, which often develops from a heterogeneous pool of drug-tolerant cells known as minimal residual disease (MRD), is thought to mainly occur through acquisition of genetic alterations. Increasing evidence, however, indicates that drug resistance might also be acquired though nongenetic mechanisms. A key emerging question is therefore whether specific molecular and/or cellular features of the MRD ecosystem determine which of these two distinct resistance trajectories will eventually prevail. We show herein that, in melanoma exposed to MAPK-therapeutics, the presence of a neural crest stem cell (NCSC) subpopulation in MRD concurred with the rapid development of resistance through nongenetic mechanisms. Emergence of this drug-tolerant population in MRD relies on a GDNF-dependent autocrine and paracrine signalling cascade, which activates the AKT survival pathway in a Focal-adhesion kinase-(FAK) dependent manner. Ablation of this subpopulation through inhibition of FAK/SRC-signalling delayed relapse in patient-derived tumour xenografts. Strikingly, all tumours that eventually escaped this treatment exhibited resistance-conferring genetic alterations and increased sensitivity to ERK-inhibition. These findings firmly establish that nongenetic reprogramming events contribute to therapy resistance in melanoma and identify a clinically-compatible approach that abrogates such a trajectory. Importantly, these data demonstrate that the cellular composition of MRD deterministically imposes distinct drug resistance evolutionary paths and highlight key principles that may permit more effective pre-emptive therapeutic interventions.

cancer biology↗