Biology subjects

Alber, F.

Publications and source records attributed to Alber, F..

15 recordsLinked to original sources

bioRxiv2026

Decoding single-cell replication states from imaging data reveals locus-specific subnuclear position dependencies of replication initiation

Replication timing (RT) is a fundamental feature of genome regulation, tightly linked to chromatin state and three-dimensional (3D) nuclear organization. Yet how the reproducible population-level timing program emerges from stochastic replication decisions in individual cells remains unclear, because it requires measuring RT and 3D genome organization jointly in the same cell. Here, we introduce RepTile, the first systematic framework that infers allele-resolved, single-cell replication states directly from multiplexed FISH and chromosome tracing experiments. By extracting replication information from spot-count distributions while correcting for genomic and spatial detection biases, RepTile infers cell-cycle progression, locus-specific replication timing, cell-to-cell heterogeneity in replication timing, and replication states of individual allele-resolved locus copies within their native three-dimensional nuclear context. Using RepTile on mouse embryonic stem cells, we find that the association between replication timing and subnuclear position observed in population-level genomic experiments conceals fundamentally different locus-specific behaviors. We found two classes of chromatin regions: "position-sensitive" and "position-insensitive". Position-sensitive regions replicate at different times depending on their subnuclear location, typically firing earliest when positioned in their canonical locale. Strikingly, this holds even when the canonical locale is repressive, such as the nuclear envelope. On the other hand, position-insensitive loci replicate at their characteristic times regardless of subnuclear position. These classes map onto distinct regulatory regimes, which are particularly pronounced at replication initiation zones (IZ): position-sensitive IZs are enriched in domains that replicate constitutively early or late across cell types, whereas position-insensitive IZs are enriched in domains that switch RT developmentally and contain early replication control elements (ERCEs), cis-regulatory elements known to govern IZ firing times. Together, these results challenge the view that subnuclear location broadly defines replication timing, indicating that positional dependence is specific to constitutive domains, while developmental domains carry intrinsic cis-acting programs that decouple their replication from subnuclear location.

genomics↗

bioRxiv2025

map3C: a computational tool for processing multiomic single-cell Hi-C data

SummaryThe emergence of multiomic single-cell Hi-C methods, which simultaneously profile chromatin conformation and other modalities such as gene expression or DNA methylation, creates tremendous opportunities for studying the genomes structure-function relationships. Existing tools for processing multiomic single-cell Hi-C datasets have certain limitations for downstream bioinformatics analysis. We present map3C, a software tool designed to address these limitations. We demonstrate that map3C improves the quality of multiomic single-cell Hi-C data for analysis and its utility for identifying structural variant locations in the genome.

bioinformatics↗

bioRxiv2024

Prediction of single-cell chromatin compartments from single-cell chromosome structures by MaxComp

The genome is partitioned into distinct chromatin compartments with at least two main classes, a transcriptionally active A and an inactive B compartment, corresponding mostly to the segregation of euchromatin and heterochromatin. Chromatin within the same compartment has a higher tendency to interact with itself than with regions in opposing compartments. A/B compartments are traditionally derived from ensemble Hi-C contact matrices through principal component analysis of their covariance matrices. However, defining compartments in single cells from single-cell Hi-C maps is non trivial due to sparsity of the data and the fact that homologous copies are typically not resolved. Here we present an unsupervised approach, named MaxComp, to determine single-cell A/B compartments from geometric considerations in 3D chromosome structures, either from multiplexed FISH imaging or from models derived from Hi-C data. By representing each single-cell structure as an undirected graph with edge-weights encoding structural information, the problem of predicting chromosome compartments can be transformed to an alternative form of the Max-cut problem, a semidefinite graph programming method (SPD) to determine an optimal division of a chromosome structure graph into two structural compartments. Our results show that compartment annotations from principal component analysis of ensemble Hi-C data can be perfectly reproduced as population averages of our single-cell compartment predictions. We therefore prove that compartment predictions can be achieved from geometric considerations alone using 3D coordinates of chromatin regions together with information about their nuclear microenvironment. Our results reveal substantial cell-to-cell heterogeneity of compartments in a cell population, which substantially differs between individual genomic regions. Moreover, by applying our approach to multiplexed FISH tracing experiments, our method sheds light on the relationship between single-cell compartment annotations and gene transcriptional activity in single cells. Overall our approach provides new insights into single-cell chromatin condensation, relationship between population and single-cell chromatin compartmentalization, the cell-to-cell variations of chromatin compartments and its impact on gene transcription. Author SummaryChromosome conformation capture and imaging techniques revealed the segregation of genomic chromatin into at least two functional compartments. Hi-C contact frequency matrices show checkerboard-like patterns indicating that chromatin regions are divided into at least two states, possibly a result of phase separation. Chromatin regions in the same state have preferential interactions with each other, often over extended sequence distances, while interactions to regions in the opposing state are minimized. Principal component analysis (PCA) on ensemble Hi-C contact frequency matrices can identify these compartment states. However, because the compartment annotations are derived from a cell population, this method cannot provide information about compartments in single cells. Here in this study, we introduce an unsupervised method to predict single-cell compartments using graph-based programming, which utilizes only structural information in single cells. Our results demonstrate that PCA-based ensemble compartment annotations can be reproduced as population averages of our single-cell compartment predictions. Moreover, our results reveal the cell-to-cell heterogeneity of compartments in a cell population, which shows significant disparities among different chromatin regions. Moreover, by applying our approach to multiplexed FISH tracing experiments, our method reveals the relationship between single-cell compartment annotations and gene transcriptional activity in single cells. Finally, our approach also allows us to relate chromatin structural features in single cells with compartment properties. Comparison with other existing approaches showed that our method produces overall better compartmentalization scores in single cells.

bioinformatics↗

bioRxiv2023

Mega-Enhancer Bodies Organize Neuronal Long Genes in the Cerebellum

Exceptionally long genes and cis-regulatory enhancers are selectively activated in mammalian brain neurons, and these loci are mutation hotspots in neurological disorders. However, the organization of these large genomic elements at the level of chromosome folding, beyond local enhancer-promoter interactions, remains poorly understood. Here, we report the discovery of a nuclear subcompartment in the mouse cerebellum formed by near-megabase long enhancers and their associated long genes encoding synaptic or signaling proteins. Genomic regions within this subcompartment reside in the outer-half of the nucleus, separated from other transcriptionally active structures. Using an in vivo CRISPR genetic mini-screen, we uncover a specific role for the transcription factor Etv1 in coupling the compartmentalization of neuronal long genes with their expression. Together, our study defines mechanisms that organize transcriptionally active genes across chromosomes in the mammalian brain.

neuroscience↗

bioRxiv2023

Conformational analysis of chromosome structures reveals vital role of chromosome morphology in gene function

The 3D conformations of chromosomes are highly variant and stochastic between single cells. Recent progress in multiplexed 3D FISH imaging, single cell Hi-C and genome structure modeling allows a closer analysis of the structural variations of chromosomes between cells to infer the functional implications of structural heterogeneity. Here, we introduce a two-step dimensionality reduction method to classify a population of single cell 3D chromosome structures, either from simulation or imaging experiment, into dominant conformational clusters with distinct chromosome morphologies. We found that almost half of all structures for each chromosome can be described by 5-10 dominant chromosome morphologies, which play a fundamental role in establishing conformational variation of chromosomes. These morphologies are conserved in different cell types, but vary in their relative proportion of structures. Chromosome morphologies are distinguished by the presence or absence of characteristic chromosome territory domains, which expose some chromosomal regions to varying nuclear environments in different morphologies, such as nuclear positions and associations to nuclear speckles, lamina, and nucleoli. These observations point to distinct functional variations for the same chromosomal region in different chromosome morphologies. We validated chromosome conformational clusters and their associated subnuclear locations with data from DNA-MERFISH imaging and single cell sci-HiC data. Our method provides an important approach to assess the variation of chromosome structures between cells and link differences in conformational states with distinct gene functions.

genomics↗

bioRxiv2022

Cryomilling Tethered Chromatin Conformation Capture reveal new insights into inter-chromosomal interactions

Traditional methods used to map the three-dimensional organization of chromatin in-situ generally involve chromatin conformation capture by formaldehyde crosslinking, followed by detergent solubilization and enzymatic digestion of DNA. Ligation of proximal DNA fragments followed by next generation sequencing (NGS) generates contact information that enables a global view of the chromatin conformation. Here, we explore the use of cryomilling to physically fragmentize the cells under cryogenic conditions to probe chromatin interactions in the cryomilled cell fragments by the tethered chromatin conformation capture (TCC). Our results show that cryomilling TCC (CTCC) can generate a global contact map similar to that obtained with in-situ Hi-C. This result suggests that summation of chromatin interactions mapped in individual subcellular fragments can reconstitute the global contact map of intact cells in an ensemble manner, paving the way for chromatin conformation analyses of solid tissue by CTCC. Compared with the conventional in-situ methods such as Hi-C, CTCC shows more uniform access to different subcompartments of the folded genome. On the other hand, most inter-chromosomal (trans) contacts are diminished or lost in CTCC except for a group of unique trans contacts that remain intact throughout the cryomilling and in- vitro crosslinking steps. These apparently ultra-stable trans interactions have much enhanced signal in CTCC due to the elimination of signals of most, presumably weak and transient trans interactions. Systematic and comparative analyses between CTCC and in-situ Hi-C provide further insights into the chromatin structure organization and reveal a generally unentangled chromosome interface and the existence of stable inter-chromosomal contacts that may represent intermingled inter-chromosomal interfaces.

genomics↗

bioRxiv2021

Integrative Genome Modeling Platform reveals essentialityof rare contact events in 3D genome organizations

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional (3D) organization of genomes and key regulatory processes of genome function. However, it remains a major challenge to systematically integrate all available data sources to characterize the nuclear organization of genomes across different spatial scales. Here, we develop a multi-modal data integration approach to produce genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction, and spatial segregation of functionally related chromatin. By performing a quantitative assessment of the predictive power of genome structures generated from different data combinations, we demonstrate that multimodal data integration can compensate for systematic errors and missing values in some of the data and thus, greatly increases accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency inter-chromosomal contacts (e.g., "rare" contact events) to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multi-modal data integration for genome structure analysis, available through the Integrative Genome structure Modeling (IGM) software package that we introduce here.

biophysics↗

bioRxiv2021

Mapping the nuclear microenvironment of genes at agenome-wide scale

The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling--from ensemble Hi-C data--can provide a detailed description of the nuclear microenvironment of genes and its role on gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single cell models on a genome-wide scale, thereby revealing the structural variability between cells. We demonstrate that the structural microenvironment of a genomic region is linked to its functional potential in gene transcription, replication and chromatin compartmentalization. Some chromatin regions are distinguished by their strong preferences to a single microenvironment, due to associations to specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive 3-dimensional genome structures, which accurately reproduce data from TSA-seq, DamID, GPSeq and super-resolution imaging. Thus, our method considerably expands the range of Hi-C data analysis and is widely applicable.

genomics↗

bioRxiv2020

Assessment of scoring functions to rank the quality of 3D subtomogram clusters from cryo-electron tomography

Cryo-electron tomography provides the opportunity for unsupervised discovery of endogenous complexes in situ. This process usually requires particle picking, clustering and alignment of subtomograms to produce an average structure of the complex. When applied to heterogeneous samples, template-free clustering and alignment of subtomograms can potentially lead to the discovery of structures for unknown endogenous complexes. However, such methods require useful scoring functions to measure the quality of aligned subtomogram clusters, which can be compromised by contaminations from misclassified complexes and alignment errors. To our knowledge, a comprehensive survey to assess the effectiveness of scoring functions for ranking the quality of subtomogram clusters does not exist yet. Here, we provide such a study and assess a total of 15 scoring functions for evaluating the quality of the subtomogram clusters, which differ in the amount of structural misalignments and contaminations due to misclassified complexes. We assessed both experimental and simulated subtomograms as ground truth data sets. Our analysis shows that the robustness of scoring functions varies largely. Most scores are sensitive to the signal-to-noise ratio of subtomograms and often require Gaussian filtering as preprocessing for improved performance. Two scoring functions, Spectral SNR-based Fourier Shell Correlation and Pearson Correlation in the Fourier domain with missing wedge correction, show a robust ranking of subtomogram clusters even without any preprocessing and irrespective of SNR levels of subtomograms. Of these two scoring functions, Spectral SNR-based Fourier Shell Correlation was fastest to compute and is a better choice for handling large numbers of subtomograms. Our results provide a guidance for choosing a scoring function for template-free approaches to detect complexes from heterogeneous samples.

bioinformatics↗

bioRxiv2017

Quantitative imaging of chromatin decompaction in living cells

Chromatin organization is highly dynamic and regulates transcription. Upon transcriptional activation, chromatin is remodeled and referred to as \"open\", but quantitative and dynamic data of this decompaction process are lacking. Here, we have developed a quantitative high-resolution microscopy assay in living yeast cells to visualize and quantify chromatin dynamics using the GAL7-10-1 locus as a model system. Upon transcriptional activation of these three clustered genes, we detect an increase of the mean distance across this locus by >100 nm. This decompaction is linked to active transcription but is not sensitive to the histone deacetylase inhibitor trichostatin A or to deletion of the histone acetyl transferase Gcn5. By contrast, the deletion of SNF2 (encoding the ATPase of the SWI/SNF chromatin remodeling complex) or the deactivation of the histone chaperone complex FACT lead to a strongly reduced decompaction without significant effects on transcriptional induction. Our findings are consistent with nucleosome remodeling and eviction activities being major contributors to chromatin reorganization during transcription but also suggest that transcription can occur in the absence of detectable decompaction.

cell biology↗

bioRxiv2017

Quantitative methods to investigate the 4D dynamics of heterochromatic repair sites in Drosophila cells

Heterochromatin is mostly composed of long stretches of repeated DNA sequences prone to ectopic recombination during double-strand break (DSB) repair. In Drosophila, safe homologous recombination (HR) repair of heterochromatic DSBs relies on a striking relocalization of repair sites to the nuclear periphery. Central to understanding heterochromatin repair is the ability to investigate the 4D dynamics (movement in space and time) of repair sites. A specific challenge of these studies is preventing phototoxicity and photobleaching effects while imaging the sample over long periods of time, and with sufficient time points and Z-stacks to track repair foci over time. Here we describe an optimized approach for high-resolution live imaging of heterochromatic DSBs in Drosophila cells, with a specific emphasis on the fluorescent markers and imaging setup used to capture the motion of repair foci over long time periods. We detail approaches that minimize photobleaching and phototoxicity with a DeltaVision widefield deconvolution microscope, and image-processing techniques for signal recovery post-imaging using SoftWorX and Imaris software. We present a method to derive mean square displacement (MSD) curves revealing some of the biophysical properties of the motion. Finally, describe a method in R to identify tracts of directed motions in mixed trajectories. These approaches enable a deeper understanding of the mechanisms of heterochromatin dynamics and genome stability in the three-dimensional context of the nucleus, and have broad applicability in the field of nuclear dynamics.

cell biology↗

bioRxiv2017

Specific Virus-Host Genome Interactions Revealed By Tethered Chromosome Conformation Capture

Viruses have evolved a variety of mechanisms to interact with host cells for their adaptive benefits, including subverting host immune responses and hijacking host DNA replication/transcription machineries [1-3]. Although interactions between viral and host proteins have been studied extensively, little is known about how the vial genome may interact with the host genome and how such interactions could affect the activities of both the virus and the host cell. Since the three-dimensional organization of a genome can have significant impact on genomic activities such as transcription and replication, we hypothesize that such structure-based regulation of genomic functions also applies to viral genomes depending on their association with host genomic regions and their spatial locations inside the nucleus. Here, we used Tethered Chromosome Conformation Capture (TCC) to investigate viral-host genome interactions between the adenovirus and human lung fibroblast cells. We found viral-host genome interactions were enriched in certain active chromatin regions and chromatin domains marked by H3K27me3. The contacts by viral DNA seems to impact the structure and function of the host genome, leading to remodeling of the fibroblast epigenome. Our study represents the first comprehensive analysis of viral-host interactions at the genome structure level, revealing unexpectedly specific virus-host genome interactions. The non-random nature of such interactions indicates a deliberate but poorly understood mechanism for targeting of host DNA by foreign genomes.

microbiology↗

bioRxiv2017

PGS: a dynamic and automated population-based genome structure software

Hi-C technologies are widely used to investigate the spatial organization of genomes. However, the structural variability of the genome is a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range/interchromosomal interactions. We pioneered a probabilistic approach for generating a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genomes organization in space and time. We provide a user-friendly software package, called PGS, that runs on local machines and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and also provides tools to extract and analyze the 3D coordinates of specific domains.

bioinformatics↗

bioRxiv2017

The 3D genome organization of Drosophila melanogaster through data integration

Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of 3D genome structural models, it is important to integrate all available sources of experimental information about a genomes organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete 3D genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our 3D geome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about the genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of differnet chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. To our knowledge our approach is the first that allows systematic integration of Hi-C and lamina DamID data for complete 3D genome structure calculation, while also explicitly considering genome structural variability.

bioinformatics↗

bioRxiv2017

Comprehensive characterization of neutrophil genome topology

Neutrophils are responsible for the first line of defense against invading pathogens. Their nuclei are uniquely structured as multiple lobes that establish a highly constrained nuclear environment. Here we found that neutrophil differentiation was not associated with large-scale changes in the number and sizes of topologically associating domains. However, neutrophil genomes were enriched for long-range genomic interactions that spanned multiple topologically associating domains. Population-based simulation of spherical and toroid genomes revealed declining radii of gyration for neutrophil chromosomes. We found that neutrophil genomes were highly enriched for heterochromatic genomic interactions across vast genomic distances, a process named super-contraction. Super-contraction involved genomic regions located in the heterochromatic compartment in both progenitors and neutrophils or genomic regions that switched from the euchromatic to the heterochromatic compartment during neutrophil differentiation. Super-contraction was accompanied by the repositioning of centromeres, pericentromeres and Long-Interspersed Nuclear Elements (LINEs) to the neutrophil nuclear lamina. We found that Lamin-B Receptor expression was required to attach centromeric and pericentromeric repeats but not LINE-1 elements to the lamina. Differentiating neutrophils also repositioned ribosomal DNA and mini-nucleoli to the lamina: a process that was closely associated with sharply reduced ribosomal RNA expression. We propose that large-scale chromatin reorganization involving super-contraction and recruitment of heterochromatin and nucleoli to the nuclear lamina facilitate the folding of the neutrophil genome into a confined geometry imposed by a multi-lobed nuclear architecture.

molecular biology↗