Search bioRxiv⌕ Search

Biology subjects

Vollger, M. R.

Publications and source records attributed to Vollger, M. R..

At least 19 recordsLinked to original sources

FiberBrowser: a unified framework for single-molecule genomics

Single-molecule footprinting methods are rapidly transforming chromatin biology. They resolve nucleosome positioning, regulatory-factor occupancy, and accessibility on individual DNA fibers, revealing combinatorial heterogeneity that bulk measurements average away. Emerging footprinting methods leverage diverse enzyme systems and sequencing platforms, necessitating tools that can accommodate these systems. We present FiberBrowser, a unified platform that converts these diverse datasets into a common per-molecule representation of nucleosomes, accessible DNA, and subnucleosomal footprints for interactive and scripted analyses. Its inference engine, FiberHMM, weighs each observation against the assay's informative sites and sequence-specific modification probabilities, separating missing information from protection in four assays. FiberBrowser clusters, sorts and compares these calls across thousands of molecules in seconds, linking chromatin architecture to haplotype, CpG methylation and non-reference structural variants on the same molecules. Because the representation is independent of chemistry, models also transfer between assays. A classifier trained on Fiber-seq footprints identifies 12 scDAF-seq cells as lymphoblastoid without retraining, whereas models trained on raw modification patterns fail to transfer. FiberBrowser thus provides a unified, expandable analytical framework for single-molecule chromatin footprinting.

genomics↗

Structural polymorphism and population-variable coding capacity of HERV-K(HML-2) in human pangenomes

Approximately 8% of the human genome is derived from ancient retroviral infections. The most recently integrated of these endogenous retroviruses is the HERV-K(HML-2) clade, whose expression has been associated with cancer, amyotrophic lateral sclerosis, and embryogenesis. Studies of HERV expression, particularly HML-2, have relied predominantly on short-read sequencing. However, the high similarity among HML-2 proviruses prevents many short reads from being assigned uniquely to individual loci. We therefore compared haplotype-resolved long-read genome assemblies from 292 donors to resolve variation in proviral structure and coding capacity. Several loci previously thought to be fixed were structurally polymorphic. Tandem arrays occurred at 13 loci and contained up to six proviral copies in a single array. At 8q11.23, we identified a previously undescribed full-length provirus in one haplotype. All 583 other haplotypes carried a solo-LTR. We found that standard reference genomes failed to represent the coding capacity retained in many individuals, whose proviruses contained intact open reading frames despite disruptive mutations in the reference sequences. Short-read genotypes left 32.5% of the tested donor-variant pairs unresolved at sites associated with viral reading frames. These findings show why HML-2 expression must be interpreted in the context of the structural and coding alleles each individual carries.

genomics↗

Pangenome discovery and characterization of human protein-coding duplicated genes

Protein-coding genes mapping to high-identity segmental duplications (SDs) have been difficult to annotate and characterize and are the source of most previously unknown protein-coding genes being discovered as part of the human pangenome. Here, we combine long-read assembled human genomes (298) and long-read transcriptome data (5.6 billion full-length cDNA from 83 tissues) to phylogenetically interrogate 493 gene families discovering 2713 potentially copy number polymorphic genes not present in the human reference genome. For reference SD gene families where paralog specificity can be assigned, we find that 60.0% are expressed and maintain open reading frames, with 45.7% showing high expression in brain, embryo, or testis. We revise 386 gene models, including 150 that absent or different from current T2T-CHM13 gene annotation and 236 (35.1%) pseudogenes as protein-coding where we find evidence of transcription, an open reading frame, and chromatin-accessible promoters. We find that 24.2% of SD genes show evidence of constraint for both copy number and amino acid mutation. The majority of these constraint genes are ancestral, whereas only 16.2% of derived duplicated genes that emerged recently in the human lineage show evidence of constraint. The pangenome provides unparalleled specificity to understand genetic variation in SD genes allowing us to distinguish functional genes from pseudogenes and highlighting potential gene innovations that arose most recently in human evolution.

genomics↗

Short-Read Sequencing Benchmarking with Donor-Specific Assemblies

BackgroundHigh-throughput short-read sequencing has become a core technology for genomics, but the rapid expansion of available platforms has made it increasingly important to benchmark them under standardized conditions. A major challenge is that conventional reference-based comparisons confound true sequencing errors with inherited variation and reference bias, making it difficult to isolate platform-intrinsic performance. ResultsWe benchmarked nine short-read chemistries across seven DNA sequencers using two highly characterized benchmark samples, HG002 and COLO829BL, together with donor-specific assemblies to measure sequencing errors against sample-matched genomic references. This strategy separated authentic platform errors from biological divergence and revealed substantial differences in substitution, indel, read-position, and sequence-context error profiles. Element AVITI UltraQ and Roche SBX-D showed the lowest substitution error rates, whereas Ultima and Roche chemistries exhibited the strongest indel-associated biases. We also found pronounced platform-specific effects in low-complexity regions and trinucleotide contexts, including homopolymer-associated errors and context-dependent substitution skews that are directly relevant to rare-variant detection. In addition, we show that donor-specific references are essential for unbiased base-quality recalibration because they minimize reference bias and more faithfully support cross-platform comparison and low-frequency variant-calling thresholds. ConclusionsDonor-specific assembly-based benchmarking provides a robust framework for measuring true short-read sequencing errors and comparing platforms on a common, sample-matched basis. Our results establish a comprehensive reference for the community and show that authentic error profiles can guide platform selection, quality filtering, and improved detection of rare somatic variation.

bioinformatics↗

Epigenetic conditioning improves sequence-based modeling of gene regulation across cell types and alleles

Epigenetic state modulates gene regulation in a manner not always predictable from DNA sequence alone, yet current genomic deep learning models do not leverage epigenetic state as input. We present MethylSeqNet, a model that conditions pretrained sequence embeddings on CpG methylation, a stable epigenetic mark increasingly available from long-read sequencing data. Using a novel conditioning mechanism enabling scalability and interpretability, MethylSeqNet improves predictions in cases where differential epigenetic state drives regulatory variation. We show improvements over a sequence-only baseline for cell-type-specific chromatin accessibility and transcription. Epigenetic conditioning enables prediction of phenomena not encoded in allele sequence, including parent-of-origin imprinting, random monoallelic activity, and X-inactivation. We highlight a promising application of methylation conditioning by predicting the effects of a structural rearrangement in one rare disease patient case study. In silico motif insertion analysis confirms that MethylSeqNet learns methylation-dependent regulatory grammar, establishing a paradigm for integrating epigenetic information into genomic deep learning with immediate applications in rare disease interpretation.

genomics↗

Single-molecule variation in telomeric sequence and structure across humans

The repetitive architectures of telomeric and subtelomeric regions have obscured studies of their genetic variation and chromatin organization across the human population. Here, we integrate near-complete diploid genome assemblies from 212 individuals with matched long-read sequencing data to construct an atlas of 316,146 telomere-spanning molecules across 12,080 chromosome-end-resolved telomere arrays. This atlas reveals that nearly every chromosome end harbors a structured and unique pattern of telomere variant repeats (TVR), or TVR code, with subtelomere-proximal TVR codes being heritable, somatically stable, and influenced by subtelomeric TAR1 regulatory elements. Despite ongoing cycles of telomere shortening and elongation in the germline, proximal TVR codes are maintained across the human population. These TVR codes expose rare telomerase-independent events that lengthen telomeres in the germline, including interchromosomal telomere exchange and recurrent internal duplications within telomere arrays. Furthermore, single-molecule chromatin fiber sequencing across 26,972 molecules spanning the telomere-subtelomere boundary confirms that TVR-rich regions adopt telomeric chromatin but introduce discrete discontinuities into otherwise compact telomeric chromatin fibers. Together, our results link chromosome-end sequence variation to telomere cap formation and telomerase-independent telomere extension mechanisms in the human germline.

genomics↗

Donor-specific assemblies enhance somatic structural variant detection in complex genomic regions

Structural variants (SVs) contribute substantially to genomic variation and disease, but detecting somatic SVs (sSVs) remains difficult due to reference bias, mosaicism, and enrichment in repetitive regions. Linear reference genomes, like GRCh38 and CHM13, do not fully capture individual genomic structure, which can obscure true somatic variation. Donor-specific assemblies (DSAs) generated from the same genome where sSVs are being assayed provide a personalized alternative, yet their performance for sSV detection has not been systematically assessed. As part of the Somatic Mosaicism across Human Tissues (SMaHT) Network, we benchmark a DSA for sSV discovery in the COLO829 melanoma cell line with a matched normal sample from the same individual. We compare sSV detection across GRCh38, CHM13, and the COLO829BL_DSA using three different sSV callers (Delly, Severus, and Sniffles2) and sequence data from multiple long-read platforms. The COLO829BL_DSA identifies 1.8-fold more manually validated sSVs than linear references, in regions both shared with GRCh38 and CHM13 and unique to the COLO829BL_DSA. Variants detected only with the COLO829BL_DSA are often found in satellite and other repeat-rich regions that are difficult to resolve using standard references. In addition, several COLO829BL_DSA-specific sSVs are located in genes, some of which are associated with cancer. Overall, these results underscore the utility of DSAs in improving sSV detection.

genomics↗

rustybam: a composable toolkit for alignment analysis and visualization with SafFire

SummaryWe present rustybam, a Rust-based command-line toolkit for CIGAR-aware manipulation of PAF and BAM alignments, and SafFire, a browser-based tool for interactive genome comparison visualization with annotation overlays. rustybams composable subcommands provide overlap resolution, coordinate liftover, alignment splitting at structural variants, scaffolding, and identity statistics. Availability and implementationBoth tools are open source under the MIT license. rustybam is available via Bioconda (https://anaconda.org/bioconda/rustybam), crates.io, and GitHub (https://github.com/vollgerlab/rustybam). SafFire is hosted at https://vollgerlab.com/SafFire/ with source code at https://github.com/vollgerlab/SafFire.

bioinformatics↗

NPEPPS segmental duplication drives position effect expression of TBC1D3 in the human brain

In humans, the TBC1D3 gene family is thought to play a critical role in the expansion of the frontal cortex by promoting neuronal proliferation during brain development. This gene family shows some of the greatest structural heterozygosity ([~]97%) with haplotype copy numbers ranging from 3-39 among different human haplotypes. This raises the question as to how a gene so crucial in the evolutionary expansion of the human frontal cortex can be so variable in the human population. Here, we characterize the regulatory architecture that explains this paradox. We show that 45-96% of TBC1D3 expression is attributable to a single paralog located at the most telomeric position at the edge of a cluster of TBC1D3 genes. We find that its >3-fold higher expression relative to other copies is driven by a 110 kbp segmental duplication that occurred [~]8.9 million years ago, relocating a partial duplication of the puromycin-sensitive aminopeptidase gene (NPEPPS), including its promoter, adjacent to this TBC1D3 locus. Using neurospheres and comparative transcriptomics of iPSC-derived cultures, we show that expression of NPEPPSP1-TBC1D3 increases as neurons differentiate as a result of alternative splicing and differential polyadenylation usage. While the fusion exists in other ape lineages, we show subsequent deletion of the NPEPPSP1 promoter in Gorilla and a separate, lineage-specific duplication in the Pan lineage ablated the production of this fusion product, rendering this position effect of TBC1D3 specific to humans.

genomics↗

A telomere-to-telomere map of somatic mutation burden and functional impact in cancer

Oncogenesis involves widespread genetic and epigenetic alterations, yet the full spectrum of somatic variation genome-wide remains unresolved. We generated a near-telomere-to-telomere (T2T) diploid assembly of a donor paired with deep short- and long-read sequencing of their melanoma. This revealed that 16% of somatic variants occur in sequences absent from GRCh38, with satellite repeats acting as hotspots for UV-induced damage due to sequence-intrinsic mutability and inefficient repair. Centromere kinetochore domains emerged as focal sites of structural, genetic, and epigenetic variation, leading to remodeling of centromere kinetochore binding domains during tumor evolution. Single-molecule telomere reconstructions uncovered cycles of attrition, deletion, and telomerase-mediated extension that shape cancer telomeres. Finally, diploid chromatin maps exposed that copy number alterations and epimutations, rather than point mutations, predominate in rewiring cancer regulatory programs. These findings define the full landscape of a cancers somatic variation and their functional impact, establishing a blueprint for T2T studies of mosaicism.

genomics↗

A complete diploid human genome benchmark for personalized genomics

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein-coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2-7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

genomics↗

Genetic diversity and regulatory features of human-specific NOTCH2NL duplications

NOTCH2NL (NOTCH2-N-terminus-like) genes arose from ape-specific chromosome 1 segmental duplications implicated in human brain cortical expansion, including an incomplete NOTCH2 gene. Genetic characterization of these loci and their regulation is complicated because they are embedded in large, nearly identical duplications that predispose to recurrent microdeletion syndromes. Using near-complete long-read assemblies generated from 70 human and 12 ape haploid genomes, we show independent recurrent duplication among apes with protein-coding copies emerging in humans 2.2-3.7 million years ago. We distinguish NOTCH2NL paralogs present in every human haplotype (NOTCH2NLA) from copy number variable ones. We also characterize large-scale structural variation, including gene conversion, for 28% of haplotypes leading to a previously undescribed paralog, NOTCH2tv. Finally, we apply Fiber-seq and long-read transcript sequencing to human dorsal forebrain organoids to characterize the regulatory landscape and find that the most fixed paralogs, NOTCH2 and NOTCH2NLA, harbor the greatest number of paralog-specific elements potentially driving their regulation.

genomics↗

Integrating Single-Molecule Sequencing and Deep Learning to Predict Haplotype-Specific 3D Chromatin Organization in a Mendelian Condition

The three-dimensional (3D) architecture of the genome plays a crucial role in gene regulation and various human diseases. Short-read sequencing methods for measuring 3D genome organization are powerful, but they lack the ability to resolve individual human haplotypes or structurally complex regions. To address this, we present FiberFold, a deep learning model that combines convolutional neural networks and transformer architectures to accurately predict cell-type-specific and haplotype-specific 3D genome organization using multi-omic data from a single, long-read sequencing assay, Fiber-seq. By applying FiberFold to a cell line with allelic X-inactivation, we show that Topologically Associated Domains (TADs) are attenuated on the inactive chrX. Furthermore, FiberFold predicts significant changes to TADs surrounding a 13;X balanced translocation in a patient with a rare Mendelian disease. FiberFold showcases the power of integrating long-read epigenomic sequencing with deep learning tools to investigate fundamental chromatin biology as well as the molecular basis of human disease.

genomics↗

Deaminase-assisted single-molecule and single-cell chromatin fiber sequencing

Gene regulation is mediated by the co-occupancy of numerous proteins along individual chromatin fibers. However, our tools for deeply profiling how proteins co-occupy individual fibers, especially at the single-cell level, remain limited. We present Deaminase-Assisted single-molecule chromatin Fiber sequencing (DAF-seq), which leverages a non-specific double-stranded DNA deaminase toxin A (SsDddA) to efficiently stencil protein occupancy along DNA molecules via selective deamination of accessible cytidines, which are preserved via C-to-T transitions upon DNA amplification. We demonstrate that DAF-seq enables [~]200,000-fold enrichment of target loci for single-molecule footprinting at near single-nucleotide resolution, enabling the precise delineation of the regulatory logic guiding neighboring proteins to cooperatively occupy chromatin fibers. Furthermore, DAF-seq enables the synchronous identification of single-molecule chromatin and genetic architectures - resolving the functional impact of rare somatic variants, as well as transitional chromatin states guiding haplotype-selective promoter actuation. Finally, we demonstrate that single-cell DAF-seq enables the accurate reconstruction of the diploid genome and epigenome from a single cell, revealing that a cells accessible regulatory landscape can diverge by as much as 63% while still retaining the cells identity. Overall, DAF-seq enables the comprehensive characterization of protein occupancy and chromatin accessibility across entire chromosomes with single-nucleotide, single-molecule, single-haplotype, and single-cell precision.

genomics↗

The regulatory potential of transposable elements in maize

The genomes of flowering plants consist largely of transposable elements (TEs), some of which modulate gene regulation and function. However, the repetitive nature of TEs and difficulty of mapping individual TEs by short-read-sequencing have hindered our understanding of their regulatory potential. We demonstrate that long-read chromatin fiber sequencing (Fiber-seq) comprehensively identifies accessible chromatin regions (ACRs) and CpG methylation across the maize genome. We uncover stereotypical ACR patterns at young TEs that degenerate with evolutionary age, resulting in TE-enhancers preferentially marked by a novel plant-specific epigenetic feature: simultaneous hyper-CpG methylation and chromatin accessibility. We show that TE ACRs are co-opted as gene promoters and that ACR-containing TEs can facilitate gene amplification. Lastly, we uncover a pervasive epigenetic signature - hypo-5mCpG methylation and diffuse chromatin accessibility - directing TEs to specific loci, including the loci that sparked McClintocks discovery of TEs.

genomics↗

Resolving the chromatin impact of mosaic variants with targeted Fiber-seq

Accurately quantifying the functional consequences of non-coding mosaic variants requires the pairing of DNA sequence with both accessible and closed chromatin architectures along individual DNA molecules--a pairing that cannot be achieved using traditional fragmentation-based chromatin assays. We demonstrate that targeted single-molecule chromatin fiber sequencing (Fiber-seq) achieves this, permitting single-molecule, long-read genomic and epigenomic profiling across targeted >100 kilobase loci with [~]10-fold enrichment over untargeted sequencing. Targeted Fiber-seq reveals that pathogenic expansions of the DMPK CTG repeat that underlie Myotonic Dystrophy 1 are characterized by somatic instability and disruption of multiple nearby regulatory elements, both of which are repeat length-dependent. Furthermore, we reveal that therapeutic adenine base editing of the segmentally duplicated {gamma}-globin (HBG1/HBG2) promoters in primary human hematopoietic cells induced towards an erythroblast lineage increases the accessibility of the HBG1 promoter as well as neighboring regulatory elements. Overall, we find that these non-protein coding mosaic variants can have complex impacts on chromatin architectures, including extending beyond the regulatory element harboring the variant.

genomics↗

A haplotype-resolved view of human gene regulation

Diploid human cells contain two non-identical genomes, and differences in their regulation underlie human development and disease. We present Fiber-seq Inferred Regulatory Elements (FIRE) and show that FIRE provides a more comprehensive and quantitative snapshot of the accessible chromatin landscape across the 6 Gbp diploid human genome, overcoming previously unrecognized biases in existing regulatory element catalogs. FIRE enables comprehensive detection of haplotype-selective chromatin accessibility (HSCA), exposing novel imprinted elements lacking underlying parent-of-origin CpG methylation differences, and gene regulatory modules that permit genes to escape X chromosome inactivation. We uncover that the human leukocyte antigen (HLA) locus harbors the most HSCA in immune cells, where we resolve specific transcription factor (TF) binding events disrupted by disease-associated variants. Finally, we demonstrate that the regulatory landscape of a cell is littered with autosomal somatic chromatin epimutations that are propagated by clonal expansions to create mitotically stable and non-genetically deterministic chromatin alterations.

genomics↗

Synchronized long-read genome, methylome, epigenome, and transcriptome for resolving a Mendelian condition

Resolving the molecular basis of a Mendelian condition (MC) remains challenging owing to the diverse mechanisms by which genetic variants cause disease. To address this, we developed a synchronized long-read genome, methylome, epigenome, and transcriptome sequencing approach, which enables accurate single-nucleotide, insertion-deletion, and structural variant calling and diploid de novo genome assembly, and permits the simultaneous elucidation of haplotype-resolved CpG methylation, chromatin accessibility, and full-length transcript information in a single long-read sequencing run. Application of this approach to an Undiagnosed Diseases Network (UDN) participant with a chromosome X;13 balanced translocation of uncertain significance revealed that this translocation disrupted the functioning of four separate genes (NBEA, PDK3, MAB21L1, and RB1) previously associated with single-gene MCs. Notably, the function of each gene was disrupted via a distinct mechanism that required integration of the four omes to resolve. These included nonsense-mediated decay, fusion transcript formation, enhancer adoption, transcriptional readthrough silencing, and inappropriate X chromosome inactivation of autosomal genes. Overall, this highlights the utility of synchronized long-read multi-omic profiling for mechanistically resolving complex phenotypes.

genetics↗