Biology subjects

Bonder, M. J.

Publications and source records attributed to Bonder, M. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Cell-specific regulatory circuits connect genetic variation to disease susceptibility

Genome-wide association studies have identified thousands of variants associated with immune-related diseases, yet most lie in non-coding regions, complicating mechanistic interpretation. Regulatory quantitative trait loci (QTLs), such as expression QTLs (eQTLs) and chromatin accessibility QTLs (caQTLs), offer a powerful framework for prioritization and interpretation of these disease-associated genetic variants. When analyzed together, they offer deeper insights into the regulatory architecture underlying disease. We generated same-cell, single-cell multi-omics data, integrating transcriptomic and chromatin accessibility information, from 563,100 matched peripheral blood mononuclear cells collected from 264 individuals, either unstimulated or stimulated for 24h with C. albicans (CA). Across six major immune cell types, we mapped both cis-eQTLs and -caQTLs, identifying 1,571 eGenes and 28,862 caPeaks, with 41% and 11% showing a stimulation-dependent effect. Finally, to dissect the regulatory mechanisms underlying these QTL effects, we applied two complementary strategies: 1. overlapping caQTLs with eQTLs; 2. applying SCENIC+ to identify regulatory triplets containing a transcription factor, the chromatin region it may bind to and the candidate target genes it thereby may regulate. With the first approach, we identified 1,861 dual-acting QTLs. These dual-QTLs showed 1.9-fold stronger enrichment for immune-related disease associations than single-modality QTLs, highlighting their relevance for disease interpretation. With the second approach, we found 62,932 regulatory triplets, of which 1.7% were under genetic control. By then leveraging the SCENIC+-derived TF activity measurements we could study how genetic variants can rewire TF control of gene expression, ultimately shaping inter-individual variation in disease risk. Together, our network-based approach offers new insights into the cellular contexts and gene programs perturbed in disease, providing a foundation for prioritizing therapeutic targets and informing strategies for disease prevention.

immunology↗

bioRxiv2026

Cell-to-cell variability and gain of methylation at polycomb CpG islands as a hallmark of aging

Aging is a complex multifactorial process that affects cellular function and tissue homeostasis over time. Despite extensive research, the molecular mechanisms driving cellular aging remain poorly understood1,2. Many studies have focused on changes in DNA methylation as an indicator of aging3. In particular, the degree of methylation at polycomb CpG islands has been shown to be predictive of phenotypic changes associated with aging4,5. Since many age-related pathological processes, are thought to be of single-cell origin (e.g. cancer), we questioned whether polycomb DNA methylation also occurs preferentially in a subset of cells within the overall population. Using single-cell whole-genome methylation data from multiple ages and tissues, we identify Average Polycomb CpG Methylation as a hallmark of cellular aging. This revealed that aging occurs at varying rates within specific cells, with faster proliferating cells showing accelerated levels. Gene expression analysis in "young" and "old" single cells identified changes in immune response, translation regulation, tumorigenesis, neurodegeneration and other cellular processes associated with aging. These results challenge traditional models of homogeneous cellular aging and suggest that aging itself is a highly individualized process at the single-cell level that may be driven by programmed changes in polycomb CpG island DNA methylation.

genomics↗

bioRxiv2025

High cell-type specificity of eQTLs revealed by single-nucleus analyses of brain and blood

Identifying causal mechanisms from genome-wide association studies (GWAS) requires an understanding of how disease-associated genetic variants influence gene expression in specific cell types. Here, we present scMetaBrain, a large-scale single-nucleus RNA-sequencing (snRNA-seq) resource derived using 1,260 samples from 785 individuals spanning 10 brain datasets. By analyzing 3.9 million transcriptomes, we identified 19,371 unique expression quantitative trait locus (eQTL) genes (eGenes) at a major cell type level, with the largest number of eQTLs observed in excitatory neurons. Notably, 31% of the eQTLs detected were highly cell-type-specific, with most restricted to excitatory neurons (69%). We compared the eQTLs with bulk RNA-seq datasets across different tissues and with a newly generated single nucleus dataset of 123 donors from peripheral blood mononuclear cells. We observed that differences in eQTL effect sizes between brain cell types are often as large as comparing eQTLs between brain tissue and non-brain tissue from bulk RNA-seq studies. Furthermore, we observe that eQTL effect size agreement was highest for cell types with similar function, even when comparing brain to blood cells. This suggests that that bulk analyses substantially overestimate eQTL agreement, likely due to tissue-level averaging of cellular regulatory effects. Through colocalization, we prioritized 662 genes for 11 brain-related traits and prioritized a single cell type in 68% of genes. Our findings demonstrate that eQTL effects are far more cell-type-specific than previously recognized, underscoring the need to expand single-cell eQTL studies across diverse tissues and cell types to fully capture the regulatory architecture of genetic variants.

genetics↗

bioRxiv2025

Epigenome-wide association study meta-analysis of wellbeing

Wellbeing is associated with both behavioral phenotypes as well as several key life outcomes, such as health, employment, and coping with stressful events. These phenotypes associated with wellbeing could be potential indicators of differential epigenetic patterns between individuals that differ in their levels of wellbeing. We performed the largest epigenome-wide (EWAS) meta-analysis of wellbeing to date by combining whole blood DNA methylation data (Illumina 450k array) from 13 cohorts from Europe, Australia, and the USA (N = 10,757 participants). After correcting for smoking and BMI, no epigenome-wide significant methylation sites were identified. We tested whether a weighted methylation score (MS) based on leave-one-cohort-out EWAS meta-analysis summary statistics predicted wellbeing in an independent cohort, and whether prediction was significant over and above the polygenic score (PGS) for wellbeing. The MS was associated with wellbeing (variance explained=0.22%, p=0.03) and was no longer significant after adding the polygenic score (PGS; variance explained=0.43%, p=0.0046, MS; variance explained=0.07%, p=0.2842). We further compared DNA methylation levels in 16 pairs of monozygotic twins discordant for wellbeing. These analyses revealed no significant within-pair DNA methylation differences at the top-sites from the meta-analysis or in MS. Our results suggest that larger EWAS meta-analyses with uniform phenotype assessment are required to identify methylation sites associated with wellbeing.

genomics↗

bioRxiv2025

Disease-associated variants are enriched for altering cell-type-specific gene co-expression relationships

Genes act within complex regulatory networks, and genetic variants can perturb these networks by altering gene co-expression. Here, we performed co-expression quantitative trait locus (co-eQTL) mapping using single-cell RNA-seq from the sc-eQTLGen consortium (1,330 donors, >2 million cells), enabling sensitive detection and prioritization of informative variant-gene-gene triplets. We identified co-eQTLs for 398 eGenes where a nearby genetic variant affected both the genes expression (cis-gene) and its co-expression with other genes, often implicating upstream regulators. For 181 genes, we inferred a likely upstream transcription factor, with motif disruption predicted for 41 genes. These upstream genes are more often loss-of-function intolerant and show more network connections, providing an explanation for why co-eQTL variants are 2.8x more strongly associated with immune diseases than classical eQTLs. These findings position co-eQTLs as mechanistic links between genetic variation and disease, revealing how variants can rewire cell-type-specific gene networks.

genetics↗

bioRxiv2025

Molecular co-accessibility identifies coordinated regulation between distant cis-regulatory elements

In metazoans, gene expression is typically regulated by a cis-regulatory landscape (CRL) composed of a promoter and multiple enhancers. How these cis-regulatory elements (CREs) coordinate their function across large genomic distances remains unclear. For example, is the simultaneous activation of multiple enhancers required to promote transcription? Here, we combined single-molecule footprinting with long-read sequencing to quantify how often chromatin accessibility and transcription factor binding co-occur across entire CRLs in the Drosophila genome. Analysis of thousands of individual DNA molecules at each locus revealed that CREs form a specific network with shared single-molecule chromatin accessibility profiles. Co-accessibility is not limited to adjacent CREs, and is frequently observed between CREs brought into proximity by chromatin looping. Co-accessible CREs exhibit strong coordination in their cell type-specific accessibility, linking enhancer activity with transcription activation. Our data uncover dependencies between CREs genome-wide, and suggest that coordinated enhancer activation is a widespread mechanism regulating gene expression.

genomics↗

bioRxiv2025

Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats

The intestinal microbiome influences health and disease. Its composition is affected by host genetics and environmental exposures. Understanding host genetic effects is critical but challenging in humans, due to the difficulty of detecting, mapping and interpreting them. To address this, we analysed host genetic effects in four cohorts of outbred laboratory rats exposed to distinct but controlled environments. We found that polygenic host genetic effects were consistent across environments. We identified three replicated microbiome-associated loci, one of which involved a sialyltransferase gene and Paraprevotella. We found a similar association in a human cohort, between ST6GAL1 and Paraprevotella, both of which have been linked with immune and infectious diseases. Moreover, we found evidence of indirect genetic effects on microbiome phenotypes, which substantially increased their total genetic variance. Finally, we identified a novel mechanism whereby indirect genetic effects can contribute to "missing heritability".

genetics↗

bioRxiv2024

Collective dynamics of DNA methylation during ageing

Ageing is the decline of physiological function over time. Statistical models termed ageing clocks can predict chronological and biological age from the longitudinal time evolution of DNA methylation. Here, we show that DNA methylation ageing is also manifest in how pairs of genomic loci evolve with respect to each other with age. Using sequencing data from a range of tissues in mouse we show that genomic correlations in DNA methylation during ageing are characterised by an enrichment of correlations between sites that are roughly 500 bp apart. We trace the origin of this behaviour to collective dynamics in the boundaries of CpG islands. We derive a simple, biophysical model that explains the origin due to a tilt in the competition between methylating and demethylating processes and an ensuing wetting-like phenomenon. Using Chip-seq data, we argue for a molecular mechanism based on a PRC2-dependent dilution of H3K27me3 during ageing. Our work gives a new perspective on epigenetic ageing, highlighting the importance of correlative as opposed to longitudinal dynamics.

genomics↗

bioRxiv2024

A genome-scale single cell CRISPRi map of trans gene regulation across human pluripotent stem cell lines

Population-scale resources of genetic, molecular, and cellular information form the basis for understanding human genomes, charting the heritable basis of disease, and tracing the effects of mutations. Pooled perturbation assays applied to cellular models, probing the effect of many perturbations coupled with an scRNA-seq readout (Perturb-seq), are especially potent references for interpreting disease-linked mutations or gene expression changes. However, the utility of existing maps has been limited by the comprehensiveness of perturbations possible, and the relevance of their cell line context. Here, we present the first genome-scale CRISPR interference (CRISPRi) perturbation map with single-cell RNA sequencing readout across many human genetic backgrounds in human pluripotent cells. To do so, we establish large-scale CRISPRi screening in human induced pluripotent stem cells from healthy donors, using over 20,000 guide RNAs to target 7,226 genes across 34 cell lines from 26 genetic backgrounds, and gather expression data from nearly 2 million cells. We comprehensively map trans expression changes induced by the target knockdowns, which complement co-expression patterns in unperturbed cells and facilitate the functional annotation of target genes to biological processes and complexes. Consistency of targeting protein complex members point to protein complexes as a nexus for aggregating transcriptional variation, revealing novel interaction partners. We characterise variation in perturbation effects across donors, with expression quantitative trait loci linked to higher genetic modulation of perturbation effects but overall low replication of trans effects due to knockdown of their corresponding cis regulators. This study pioneers population-scale CRISPR perturbations with single cell readouts that will fuel foundation models for the future of effective modulation of cellular disease phenotypes.

genetics↗

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↗

bioRxiv2023

Linking the gut microbiome to host DNA methylation by a discovery and replication epigenome-wide association study

Both gene methylation and the gut microbiome are partially determined by host genetics and partially by environment. We investigated the relations between gene methylation in blood and the abundance of common gut bacteria profiled by 16s rRNA gene sequencing in two population-based Dutch cohorts: LifeLines-Deep (LLD, n = 616, discovery) and the Netherlands Twin Register (NTR, n = 296, replication). In LLD, we also explored microbiome composition using data generated by shotgun metagenomic sequencing (n = 683). We then investigated if genetic and environmental factors can explain the methylation-microbiota associations in a set of 78 associated CpG-taxa pairs from the EWAS meta-analysis. In both cohorts, blood and stool samples were collected within 2 weeks of each other. Methylation was profiled in blood samples using the Illumina 450K array. Methylation and microbiome analysis pipelines were harmonized across cohorts. Epigenome-wide association study (EWAS) of microbial features were analysed using linear regression with adjustment for technical covariates. Discovery and replication analysis using 16s data identified two independent CpGs associated with the genus Eggerthella: cg16586104 (Pmeta-analysis = 3.21 x 10-11) and cg12234533 (Pmeta-analysis = 4.29 x 10-10). While we did not find human genetic variants that could explain the associated CpG-taxa/pathway pairs, we show that microbiome can mediate the effect of environmental factors on epigenetics. In this first association study linking epigenome to microbiome, we found and replicated the associations of two CpGs to the abundance of genus Eggerthella and identified microbiome as a mediator of the exposome.

genomics↗

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↗

bioRxiv2023

Single cell DNA methylation ageing in mouse blood

Ageing is the accumulation of changes and overall decline of the function of cells, organs and organisms over time. At the molecular and cellular level, the concept of biological age has been established and biomarkers of biological age have been identified, notably epigenetic DNA-methylation based clocks. With the emergence of single-cell DNA methylation profiling methods, the possibility to study biological age of individual cells has been proposed, and a first proof-of-concept study, based on limited single cell datasets mostly from early developmental origin, indicated the feasibility and relevance of this approach to better understand organismal changes and cellular ageing heterogeneity. Here we generated a large single-cell DNA methylation and matched transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages (10-101 weeks of age). We observed that the number of genes expressed increased at older ages, but gene specific changes were small. We next developed a robust single cell DNA methylation age predictor (scEpiAge), which can accurately predict age in a broad range of publicly available datasets, including very sparse data and it also predicts age in single cells. Interestingly, the DNA methylation age distribution is wider than technically expected in 19% of single cells, suggesting that epigenetic age heterogeneity is present in vivo and may relate to functional differences between cells. In addition, we observe differences in epigenetic ageing between the major blood cell types. Our work provides a foundation for better single-cell and sparse data epigenetic age predictors and highlights the significance of cellular heterogeneity during ageing. Highlights- Model to estimate DNA methylation age in single cells - Large multi-omics dataset of single cells from murine blood - Epigenetic age deviations from chronological age are greater than technical expected from technical variability - Number of genes expressed increases with chronological and epigenetic age

cell biology↗

bioRxiv2022

novoRNABreak: local assembly for novel splice junction and fusion transcript detection from RNA-seq data

We present novoRNABreak, a unified framework for cancer specific novel splice junction and fusion transcript detection in RNA-seq data obtained from human cancer samples. novoRNABreak is based on a local assembly model, which offers a tradeoff between the alignment-based and de novo whole transcriptome assembly (WTA) approaches, namely, being more sensitive in assembling novel junctions that cannot be directly aligned, and more efficient due to the strategy that focuses on junctions rather than full-length transcripts. The performance of novoRNABreak is demonstrated by a comprehensive set of experiments using synthetic data generated based on genome reference, as well as real RNA-seq data from breast cancer and prostate cancer samples. The results show that novoRNABreak can detect novel splice junctions and fusion transcripts efficiently with high sensitivity and reasonable specificity.

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

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↗

bioRxiv2022

PycoMeth: A toolbox for differential methylation testing from Nanopore methylation calls

AO_SCPLOWBSTRACTC_SCPLOWAdvances in base and methylation calling of Oxford Nanopore Technologies (ONT) sequencing data have opened up the possibility for joint profiling of genomic and epigenetic variation on the same long reads. Existing data storage and analysis frameworks that were developed for CpG-methylation arrays or short-read bisulfite sequencing data have severe shortcomings for handling of ONT data, failing to fully exploit methylation profiles obtained from long read technologies. To address these issues, we present pycoMeth, a toolbox to store, manage and analyse DNA methylation data obtained from long-read ONT sequencing data. Our toolbox centers around a new storage format called MetH5, which allows simultaneously for efficient storage of and rapid data access for read-level and reference-anchored methylation call data. Building on this storage format, we propose efficient algorithms for the segmentation and differential methylation testing of methylation calls from ONT data. Our methods draw from read-group and read-level information, as well as methylation call uncertainties, and allow for de novo discovery of methylation patterns and differentially methylated regions in a haplotyped multi-sample setting. We show that MetH5 is more efficient than existing solutions for storing ONT methylation calls, and carry out benchmarking for segmentation and differential methylation analysis, demonstrating increased performance and sensitivity of pycoMeth compared to existing solutions.

bioinformatics↗

bioRxiv2021

Single-Cell Atlas of Common Variable Immunodeficiency reveals germinal center-associated epigenetic dysregulation in B cell responses

Common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, is characterized by impaired terminal B-cell differentiation and defective antibody responses. Incomplete genetic penetrance and a wide range of phenotypic expressivity in CVID suggest the participation of additional pathogenic mechanisms. Monozygotic (MZ) twins discordant for CVID are uniquely valuable for studying the contribution of epigenetics to the disease. We used single-cell epigenomics and transcriptomics to create a cell census of naive-to-memory B cell differentiation in a pair of CVID-discordant MZ twins. Our analysis identifies DNA methylation, chromatin accessibility and transcriptional defects in memory B cells that mirror defective cell-cell communication defects following activation. These findings were validated in a cohort of CVID patients and healthy donors. Our findings provide a comprehensive multi-omics map of alterations in naive-to-memory B-cell transition in CVID and reveal links between the epigenome and immune cell cross-talk. Our resource, publicly available at the Human Cell Atlas, paves the way for future diagnosis and treatments of CVID patients.

immunology↗