Biology subjects

Fudenberg, G.

Publications and source records attributed to Fudenberg, G..

At least 19 recordsLinked to original sources

bioRxiv2026

CLASH (Chromatin Loop Across-sample Score Harmonizer) quantifies the relative contributions of genetic variation, methylation, and CTCF occupancy on chromatin loop strength across individuals

Three-dimensional genome organization constrains the regulatory interactions that govern vital cellular processes. Chromatin loops are key features of genome folding, yet it is unclear how genetic and epigenetic variation influences differential loop formation across individuals. Loops primarily form between two CTCF binding proteins, which recognize a specific motif at loop anchors. CTCF binding site motifs are frequently altered by base substitutions, structural variation, and 5-methylcytosine (mC) CpG methylation, yet no study has comprehensively profiled this variation across diverse individuals. Moreover, existing approaches relying on binary loop calls fail to capture subtle changes in genetic and epigenetic features, as well as CTCF occupancy, that drive variation in loop strength. Here, we combined high-resolution Hi-C, Fiber-seq, near telomere-to-telomere phased assemblies, and mC methylation maps across five lymphoblastoid cell lines to quantify how genetic and epigenetic variation shape genome folding. We used DiffHiC to identify 367 differential pixels and found that sequence variation, chromatin accessibility, and mC CpG methylation are each significantly associated with differential chromatin contacts. Next, we developed CLASH (Chromatin Loop Across-sample Score Harmonizer) to harmonize loop calls across samples and enable robust comparisons of loop strengths across individuals. CLASH substantially improved loop calls and loop score calibration with respect to the classification boundary over existing methods and confirmed a significant relationship between CTCF occupancy and loop strength. We then characterized independent contributions of sequence and epigenetic variation to differential loop formation, demonstrating that 57% of sequence variation- and 40% of methylation-associated effects on loop formation acted through CTCF occupancy. Together, we present a multimodal dataset and computational approach to facilitate the study of 3D genome structure across human populations.

genomics↗

bioRxiv2026

Sequence design for three-dimensional genome folding using Akita Semifreddo

Mammalian genomes display complex three-dimensional organization which is crucial for downstream processes like gene regulation. Local features of genome organization are largely driven by loop extrusion and manifest as boundaries, dots, and flames in genome contact maps. Still, the rational design of DNA sequences that produce desired folding patterns has not been demonstrated. Here, we present Akita Semifreddo, a framework that enables the rational in silico design of DNA sequences with programmable 3D folding outcomes. This combines a computationally efficient "half-frozen" version of the AkitaV2 genome folding model with the Ledidi sequence optimizer. We systematically demonstrate that this approach spans the full repertoire of known local folding features. We show that [~]2 kb synthetic sequences can be designed to induce boundaries, dots, and flames at desired strengths, with CTCF motif configurations consistent with their known mechanistic bases. We further demonstrate that weak boundaries can be designed through transcription-associated sequence features alone, without introducing CTCF motifs, and that strong boundaries can be suppressed by introducing SINE B2 retroelement-like sequences. Collectively, these results reveal a many-to-one relationship between DNA sequence and folding outcomes and uncover the biological basis of sequence features leveraged by our model. In short, Akita Semifreddo provides a platform for dissecting the sequence grammar of three-dimensional chromatin architecture and engineering synthetic regulatory landscapes.

genomics↗

bioRxiv2026

Structural variants in human congenital heart disease disrupt distal genomic regulatory contacts of developmental genes

Predicting the functional significance of structural variants (SVs) associated with genetic diseases remains challenging. To test the hypothesis that SVs from people with congenital heart disease (CHD) disrupt developmental chromatin interactions, we developed CardioAkita, a machine-learning model that predicts how variants alter 3D chromatin structure. Analyzing previously genotyped de novo SVs (dnSVs), we observed a positive association between CHD severity and CardioAkita scores across dozens of families. From whole-genome sequencing of three individuals with CHD we predicted disruptive dnSVs. Induced pluripotent stem cells engineered to harbor these variants confirmed CardioAkitas predictions of 3D chromatin changes, and further revealed aberrant expression of local genes including cardiac developmental genes, suggesting that chromatin reorganization plays a significant mechanistic role in the genetic etiology of CHD. Our findings highlight the potential for models of 3D chromatin organization to predict the pathogenicity and underlying mechanisms of SVs in human disease.

genomics↗

bioRxiv2026

The ChIP-FRiP pipeline quantifies co-binding and reveals how antibody background contributes to cohesin ChIP-seq patterns

Loop extruding cohesin complexes are positioned by CTCF barriers to generate locus-specific 3D genome folding patterns. Quantifying cohesin accumulation at CTCF sites is crucial for deriving insight into loop extrusion and its consequences. Here we confronted expectations from loop extrusion simulations with experimental data by developing a pipeline, ChIP-FRiP, and analysis framework to reliably quantify cohesin positioning. We used ChIP-FRiP to uniformly re-process 140 cohesin ChIP-seq datasets from 13 publicly available studies. This analysis revealed that non-specific antibody binding can skew measurements of cohesin positioning. To mitigate this bias, we developed a biochemical model of background ChIP-seq signal and a strategy to estimate and correct this background using spike-in ChIP-seq data and relative protein abundance before and after depletion. Our results establish a framework for comparative analysis, demonstrating that accurate background correction is requisite for interpreting the roles of cohesin cofactors in cohesin positioning.

genomics↗

bioRxiv2026

The role of cohesin loading at enhancers in the flux of loop extrusion and long-range transcriptional control

Enhancers have been proposed to act as privileged loading sites for cohesin, raising the idea that they actively fold the genome to engage distal target promoters for transcription. Supporting this idea, NIPBL/MAU2, which is required for cohesin loading, binds at enhancers in mouse embryonic stem cells. However, we find that driving cohesin recruitment near an enhancer strongly inhibits transcription from its target distal promoter, indicating that strong focal cohesin loading at enhancers is not compatible with their long-range regulatory functions. Quantitative experiments and biophysical modeling further indicate that cohesin loading at enhancers does not make major contributions to genome-wide cohesin binding and chromosome folding patterns. Instead, cohesin must load throughout the genome to extrude it, regardless of enhancer proximity, with the major determinants of cohesin traffic being extrusion barriers such as transcription and clustered CTCF sites. These findings indicate that enhancer function is largely ancillary to the general mechanisms of chromosome folding, informing further study of the relationship between genome architecture and transcriptional regulation.

molecular biology↗

bioRxiv2025

Mechanistic Genome Folding at Scale through the Differentiable Loop Extrusion Model

The spatial folding of the genome shapes gene regulation by controlling which loci interact, yet inferring the mechanisms behind these 3D structures from contact maps remains difficult. Cohesin-mediated loop extrusion is a key organizer of domains and loops, but existing methods either predict contacts without mechanistic insight or simulate extrusion with limited scalability. We present the differentiable loop extrusion model (dLEM), a scalable framework that reformulates extrusion as a smooth, trainable process. dLEM represents extrusion through position-specific velocity profiles for leftward and rightward cohesin movement. Fitting dLEM to chromosome conformation capture data yields a one-dimensional, interpretable description of extrusion dynamics that aligns with genomic and epigenomic features. dLEM parameters also capture architectural changes under CTCF and WAPL perturbations, enabling genome-wide prediction of extrusion disruptions. Extending our observations, we demonstrate that dLEM can be seamlessly incorporated into deep learning models to infer extrusion parameters directly from sequence and chromatin features, reducing model complexity by nearly three orders of magnitude while preserving predictive accuracy. Indeed, when incorporated into deep dLEM, dLEM acts as a biophysically-motivated layer for long range genomic communication, and together they provide a predictive, interpretable framework linking 1D genomic features to 3D chromatin folding and its response to sequence and chromatin state, with dLEMs mechanistic modeling enabling prediction of trans factor perturbation effects.

genomics↗

bioRxiv2025

NIPBL dosage shapes genome folding by tuning the rate of cohesin loop extrusion

Genome folding is not static, but emerges from dynamic processes that control transcription, replication, recombination, and repair. DNA loop extrusion by cohesin is central to genome organization, yet it remains unclear how cells can tune extrusion kinetics to achieve precise and functional chromosome folding patterns. Here we discover extrusion rate acts as a tunable biophysical parameter in cells, quantitatively dialed by the respective dosage of the cohesin cofactors NIPBL and PDS5. Modulation of extrusion rate can offset changes in cohesin lifetime to buffer steady-state chromosome structure and transcriptional states, even in the face of abnormal extrusion dynamics. These findings provide a long-sought mechanistic basis for the genetic interactions between cohesin cofactors and the molecular origin of haploinsufficiency in cohesinopathies, such as Cornelia de Lange syndrome.

molecular biology↗

bioRxiv2025

Ab-trapping - a peripheral staining artifact in antibody-based microscopy and genomics

Antibodies (Ab) are essential for detecting specific epitopes in microscopy and genomics, but can produce artifacts leading to erroneous interpretations. Here, we characterize a novel artifact, Ab-trapping, in which antibodies bind at the periphery of a cellular structure and do not diffuse further into its interior. This causes anomalous peripheral staining for multiple critical targets, including endogenous or ectopically expressed nuclear proteins like nucleolar proteins, histone variants and their modifications like H3K9me2. Ab-trapping can affect any assay relying on Ab diffusion, including immunofluorescence microscopy and recent genomics approaches like CUT&Tag. Critically, computational modeling and experimental validation reveal that Ab-trapping is caused by high epitope abundance, high Ab affinity, and low diffusion rates. Consequently, its effects can be mitigated by using alternative Abs and optimizing incubation conditions. Ab-trapping is therefore a considerable artifact that should be considered when designing experiments and interpreting results.

cell biology↗

bioRxiv2024

Dynamic barriers modulate cohesin positioning and genome folding at fixed occupancy

In mammalian interphase cells, genomes are folded by cohesin loop extrusion limited by directional CTCF barriers. This interplay leads to the enrichment of cohesin at barriers, isolation between neighboring topologically associating domains, and elevated contact frequency between convergent CTCF barriers across the genome. However, recent in vivo measurements present a puzzle: reported residence times for CTCF on chromatin are in the range of a few minutes, while lifetimes for cohesin are much longer. Can the observed features of genome folding result from the action of relatively transient barriers? To address this question, we developed a dynamic barrier model, where CTCF sites switch between bound and unbound states with rates that can be directly compared with biophysical measurements. Using this model, we investigated how barrier dynamics would impact observables for a range of experimental genomic and imaging datasets, including ChIP-seq, Hi-C, and microscopy. We found the interplay of CTCF and cohesin binding timescales influence the strength of each of these features, leaving a signature of barrier dynamics even in the population-averaged snapshots offered by genomic datasets. First, in addition to barrier occupancy, barrier bound times are crucial for instructing features of genome folding. Second, the ratio of boundary to extruder lifetime greatly alters simulated ChIP-seq and simulated Hi-C. Third, large-scale changes in chromosome morphology observed experimentally after increasing extruder lifetime require dynamic barriers. By integrating multiple sources of experimental data, our biophysical model argues that CTCF barrier bound times effectively approach those of cohesin extruder lifetimes. Together, we demonstrate how models that are informed by biophysically measured protein dynamics broaden our understanding of genome folding.

genomics↗

bioRxiv2024

Synergy between cis-regulatory elements can render cohesin dispensable for distal enhancer function

Enhancers are critical genetic elements controlling transcription from promoters, but the mechanisms by which they convey regulatory information across large genomic distances remain elusive. Here, we engineered pluripotent stem cells in which cohesin loop extrusion can be inducibly disrupted without causing confounding cell cycle defects. While evident, transcriptional dysregulation was cell-type specific, and not all loci with distal enhancers depend equally on cohesin extrusion. Using comparative genome editing, we demonstrate that enhancer-promoter communication across as little as 20 kilobases can rely on cohesin. However, promoter-proximal regulatory elements can support long-range, cohesin-independent enhancer action - either upon disabling extrusion or across strong CTCF insulators. Finally, transcriptional dynamics and the emergence of new embryonic cell types in response to differentiation cues remained largely robust to disrupting cohesin extrusion. Beyond establishing novel experimental strategies to study cohesin functions in enhancer biology, our work provides mechanistic insight accounting for both cell type- and genomic context-specificity.

molecular biology↗

bioRxiv2024

The physical chemistry of interphase loop extrusion

Loop extrusion constitutes a universal mechanism of genome organization, whereby structural maintenance of chromosomes (SMC) protein complexes load onto the chromatin fiber and generate DNA loops of increasingly-larger sizes until their eventual release. In mammalian interphase cells, loop extrusion is mediated by the cohesin complex, which is dynamically regulated by the interchange of multiple accessory proteins. Although these regulators bind the core cohesin complex only transiently, their disruption can dramatically alter cohesin dynamics, gene expression, chromosome morphology and contact patterns. Still, a theory of how cohesin regulators and their molecular interplay with the core complex modulate genome folding remains at large. Here we derive a model of cohesin loop extrusion from first principles, based on in vivo measurements of the abundance and dynamics of cohesin regulators. We systematically evaluate potential chemical reaction networks that describe the association of cohesin with its regulators and with the chromatin fiber. Remarkably, experimental observations are consistent with only a single biochemical reaction cycle, which results in a unique minimal model that may be fully parameterized by quantitative protein measurements. We demonstrate how distinct roles for cohesin regulators emerge simply from the structure of the reaction network, and how their dynamic exchange can regulate loop extrusion kinetics over time-scales that far exceed their own chromatin residence times. By embedding our cohesin biochemical reaction network within biophysical chromatin simulations, we evidence how variations in regulatory protein abundance can alter chromatin architecture across multiple length- and time-scales. Predictions from our model are corroborated by biophysical and biochemical assays, optical microscopy observations, and Hi-C conformation capture techniques. More broadly, our theoretical and numerical framework bridges the gap between in vitro observations of extrusion motor dynamics at the molecular scale and their structural consequences at the genome-wide level.

genomics↗

bioRxiv2024

Interpreting the CTCF-mediated sequence grammar of genome folding with AkitaV2

Interphase mammalian genomes are folded in 3D with complex locus-specific patterns that impact gene regulation. CTCF (CCCTC-binding factor) is a key architectural protein that binds specific DNA sites, halts cohesin-mediated loop extrusion, and enables long-range chromatin interactions. There are hundreds of thousands of annotated CTCF-binding sites in mammalian genomes; disruptions of some result in distinct phenotypes, while others have no visible effect. Despite their importance, the determinants of which CTCF sites are necessary for genome folding and gene regulation remain unclear. Here, we update and utilize Akita, a convolutional neural network model, to extract the sequence preferences and grammar of CTCF contributing to genome folding. Our analyses of individual CTCF sites reveal four predictions: (i) only a small fraction of genomic sites are impactful, (ii) insulation strength is highly dependent on sequences flanking the core CTCF binding motif, (iii) core and flanking sequences are broadly compatible, and (iv) core and flanking nucleotides contribute largely additively to overall strength. Our analysis of collections of CTCF sites make two predictions for multi-motif grammar: (i) insulation strength depends on the number of CTCF sites within a cluster, and (ii) pattern formation is governed by the orientation and spacing of these sites, rather than any inherent specialization of the CTCF motifs themselves. In sum, we present a framework for using neural network models to probe the sequences instructing genome folding and provide a number of predictions to guide future experimental inquiries. Author SummaryMammalian genomes are spatially organized in 3D with profound consequences for all processes involving DNA. CTCF is a key genome organizer, recognizing numerous sites and creating a variety of contact patterns across the genome. Despite the importance of CTCF, the sequence determinants and grammar of how individual sites collectively instruct genome folding remain unclear. This work leverages the ability of Akita, a deep neural network, to make high-throughput predictions for genome folding after DNA sequence perturbations. Using Akita, we make several experimentally testable predictions. First, only a minority of annotated sites individually impact folding, and flanking DNA sequences greatly modulate their impact. Second, multiple sites together influence folding based on their number, orientation, and spacing. In sum, we provide a roadmap for interpreting neural networks to better understand genome folding and important considerations for the design of experiments.

genomics↗

bioRxiv2023

Pairtools: from sequencing data to chromosome contacts

The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools - a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. Pairtools provides both crucial core tools as well as auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for multi-way contacts, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.

bioinformatics↗

bioRxiv2022

Cooltools: enabling high-resolution Hi-C analysis in Python

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

bioinformatics↗

bioRxiv2022

Bioframe: Operations on Genomic Intervals in Pandas Dataframes

MotivationGenomic intervals are one of the most prevalent data structures in computational genome biology, and used to represent features ranging from genes, to DNA binding sites, to disease variants. Operations on genomic intervals provide a language for asking questions about relationships between features. While there are excellent interval arithmetic tools for the command line, they are not smoothly integrated into Python, one of the most popular general-purpose computational and visualization environments. ResultsBioframe is a library to enable flexible and performant operations on genomic interval dataframes in Python. Bioframe extends the Python data science stack to use cases for computational genome biology by building directly on top of two of the most commonly-used Python libraries, numpy and pandas. The bioframe API enables flexible name and column orders, and decouples operations from data formats to avoid unnecessary conversions, a common scourge for bioinformaticians. Bioframe achieves these goals while maintaining high performance and a rich set of features. Availability and implementationBioframe is open-source under MIT license, cross-platform, and can be installed from the Python package index. The source code is maintained by Open2C on Github at https://github.com/open2c/bioframe.

bioinformatics↗

bioRxiv2022

Reconstructing the 3D genome organization of Neanderthals reveals that chromatin folding shaped phenotypic and sequence divergence

Changes in gene regulation were a major driver of the divergence of archaic hominins (AHs)--Neanderthals and Denisovans--and modern humans (MHs). The three-dimensional (3D) folding of the genome is critical for regulating gene expression; however, its role in recent human evolution has not been explored because the degradation of ancient samples does not permit experimental determination of AH 3D genome folding. To fill this gap, we apply novel deep learning methods for inferring 3D genome organization from DNA sequence to Neanderthal, Denisovan, and diverse MH genomes. Using the resulting 3D contact maps across the genome, we identify 167 distinct regions with diverged 3D genome organization between AHs and MHs. We show that these 3D-diverged loci are enriched for genes related to the function and morphology of the eye, supra-orbital ridges, hair, lungs, immune response, and cognition. Despite these specific diverged loci, the 3D genome of AHs and MHs is more similar than expected based on sequence divergence, suggesting that the pressure to maintain 3D genome organization constrained hominin sequence evolution. We also find that 3D genome organization constrained the landscape of AH ancestry in MHs today: regions more tolerant of 3D variation are enriched for introgression in modern Eurasians. Finally, we identify loci where modern Eurasians have inherited novel 3D genome folding patterns from AH ancestors and validate folding differences in a high-frequency locus using Hi-C, revealing a putative molecular mechanism for phenotypes associated with archaic introgression. In summary, our application of deep learning to predict archaic 3D genome organization illustrates the potential of inferring molecular phenotypes from ancient DNA to reveal previously unobservable biological differences.

evolutionary biology↗

bioRxiv2021

Genome-wide variability in recombination activity is associated with meiotic chromatin organization

BackgroundRecombination enables reciprocal exchange of genomic information between parental chromosomes and successful segregation of homologous chromosomes during meiosis. Errors in this process lead to negative health outcomes, while variability in recombination rate affects genome evolution. In mammals, most crossovers occur in hotspots defined by PRDM9 motifs, though PRDM9 binding sites are not all equally hot. We hypothesize that dynamic patterns of meiotic genome folding are linked to recombination activity. ResultsWe apply an integrative bioinformatics approach to analyze how three-dimensional (3D) chromosomal organization during meiosis relates to rates of double-strandbreak (DSB) and crossover formation at PRDM9 hotspots. We show that active, spatially accessible genomic regions during meiotic prophase are associated with DSB-favoured hotspots, which further adopt a transient locally active configuration in early prophase. Conversely, crossover formation is depleted among DSBs in spatially accessible regions during meiotic prophase, particularly within gene bodies. We also find evidence that active chromatin regions have smaller average loop sizes in mammalian meiosis. Collectively, these findings establish that differences in chromatin architecture along chromosomal axes are associated with variable recombination activity. ConclusionsWe propose an updated framework describing how 3D organization of brush-loop chromosomes during meiosis may modulate recombination.

genomics↗

bioRxiv2019

Molecular basis of CTCF binding polarity in genome folding

Current models propose that boundaries of mammalian topologically associating domains (TADs) arise from the ability of the CTCF protein to stop extrusion of chromatin loops by cohesin proteins (Merkenschlager & Nora, 2016; Fudenberg, Abdennur, Imakaev, Goloborodko, & Mirny, 2017). While the orientation of CTCF motifs determines which pairs of CTCF sites preferentially stabilize DNA loops (de Wit et al., 2015; Guo et al., 2015; Rao et al., 2014; Vietri Rudan et al., 2015), the molecular basis of this polarity remains mysterious. Here we report that CTCF positions cohesin but does not control its overall binding or dynamics on chromatin by single molecule live imaging. Using an inducible complementation system, we found that CTCF mutants lacking the N-terminus cannot insulate TADs properly, despite normal binding. Cohesin remained at CTCF sites in this mutant, albeit with reduced enrichment. Given that the orientation of the CTCF motif presents the CTCF N-terminus towards cohesin as it translocates from the interior of TADs, these observations provide a molecular explanation for how the polarity of CTCF binding sites determines the genomic distribution of chromatin loops.

molecular biology↗