Topological demarcation by HMGB2 is disrupted early upon senescence entry across cell types and induces CTCF clustering

AbstractAgeing-relevant processes, like cellular senescence, are characterized by complex, often stochastic, events giving rise to heterogeneous cell populations. We hypothesized that entry into senescence of different primary human cells can be triggered by one early molecular event affecting the spatial organization of chromosomes. To test this, we combined whole-genome chromosome conformation capture, population and single-cell transcriptomics, super-resolution imaging, and functional analyses applied on proliferating and replicatively-senescent populations from three distinct human cell types. We found a number of genes involved in DNA conformation maintenance being suppressed upon senescence across cell types. Of these, the abundant high mobility group (HMG) B1 and B2 nuclear factors are quantitatively removed from cell nuclei before typical senescence markers appear, and mark a subset of topologically-associating domain (TAD) boundaries. Their loss coincides with obvious reorganization of chromatin interactions via the dramatic spatial clustering of CTCF foci. HMGB2 knock-down recapitulates this senescence-induced CTCF clustering, while also affecting insulation at TAD boundaries. We accordingly propose that HMGB-mediated deregulation of chromosome conformation constitutes a primer for the ensuing senescent program across cell types.

Download Full-text

Spatial organization of the transcriptome in individual neurons

10.1101/2020.12.07.414060 ◽

2020 ◽

Author(s):

Guiping Wang ◽

Cheen-Euong Ang ◽

Jean Fan ◽

Andrew Wang ◽

Jeffrey R. Moffitt ◽

...

Keyword(s):

Spatial Organization ◽

Spatial Clustering ◽

Super Resolution ◽

Distribution Patterns ◽

Synaptic Activity ◽

Spatial Profiling ◽

Multiple Length Scales ◽

Neuronal Functions ◽

Genome Scale ◽

Micrometer Scale

AbstractNeurons are highly polarized cells with complex neurite morphology. Spatial organization and local translation of RNAs in dendrites and axons play an important role in many neuronal functions. Here we performed super-resolution spatial profiling of RNAs inside individual neurons at the genome scale using multiplexed error-robust fluorescence in situ hybridization (MERFISH), and mapped the spatial organization of up to ∼4,200 RNA species (genes) across multiple length scales, ranging from sub-micrometer to millimeters. Our data generated a quantitative intra-neuronal atlas of RNAs with distinct transcriptome compositions in somata, dendrites, and axons, and revealed diverse sub-dendritic distribution patterns of RNAs. Moreover, our spatial analysis identified distinct groups of genes exhibiting specific spatial clustering of transcripts at the sub-micrometer scale that were dependent on protein synthesis and differentially dependent on synaptic activity. Overall, these data provide a rich resource for characterizing the subcellular organization of the transcriptome in neurons with high spatial resolution.

Download Full-text

Systematic inference and comparison of multi-scale chromatin sub-compartments connects spatial organization to cell phenotypes

Nature Communications ◽

10.1038/s41467-021-22666-3 ◽

2021 ◽

Vol 12 (1) ◽

Cited By ~ 1

Author(s):

Yuanlong Liu ◽

Luca Nanni ◽

Stephanie Sungalee ◽

Marie Zufferey ◽

Daniele Tavernari ◽

...

Keyword(s):

Biological Activity ◽

Cell Lines ◽

Spatial Organization ◽

Cell Types ◽

Chromosome Conformation ◽

Algorithmic Approach ◽

Multi Scale ◽

Lineage Differentiation ◽

Data Resolution ◽

Cell Phenotypes

AbstractChromatin compartmentalization reflects biological activity. However, inference of chromatin sub-compartments and compartment domains from chromosome conformation capture (Hi-C) experiments is limited by data resolution. As a result, these have been characterized only in a few cell types and systematic comparisons across multiple tissues and conditions are missing. Here, we present Calder, an algorithmic approach that enables the identification of multi-scale sub-compartments at variable data resolution. Calder allows to infer and compare chromatin sub-compartments and compartment domains in >100 cell lines. Our results reveal sub-compartments enriched for poised chromatin states and undergoing spatial repositioning during lineage differentiation and oncogenic transformation.

Download Full-text

Hi–C interaction graph analysis reveals the impact of histone modifications in chromatin shape

Applied Network Science ◽

10.1007/s41109-021-00396-1 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Emre Sefer

Keyword(s):

Histone Modifications ◽

Spatial Organization ◽

Three Dimensional ◽

Cell Types ◽

Interaction Graph ◽

Chromosome Conformation ◽

A Genome ◽

Topologically Associated Domains ◽

Wide Scale ◽

The Impact

AbstractChromosome conformation capture experiments such as Hi–C map the three-dimensional spatial organization of genomes in a genome-wide scale. Even though Hi–C interactions are not biased towards any of the histone modifications, previous analysis has revealed denser interactions around many histone modifications. Nevertheless, simultaneous effects of these modifications in Hi–C interaction graph have not been fully characterized yet, limiting our understanding of genome shape. Here, we propose ChromatinCoverage and its extension TemporalPrizeCoverage methods to decompose Hi–C interaction graph in terms of known histone modifications. Both methods are based on set multicover with pairs, where each Hi–C interaction is tried to be covered by histone modification pairs. We find 4 histone modifications H3K4me1, H3K4me3, H3K9me3, H3K27ac to be significantly predictive of most Hi–C interactions across species, cell types and cell cycles. The proposed methods are quite effective in predicting Hi–C interactions and topologically-associated domains in one species, given it is trained on another species or cell types. Overall, our findings reveal the impact of subset of histone modifications in chromatin shape via Hi–C interaction graph.

Download Full-text

Systematic evaluation of chromosome conformation capture assays

10.1101/2020.12.26.424448 ◽

2020 ◽

Author(s):

Betul Akgol Oksuz ◽

Liyan Yang ◽

Sameer Abraham ◽

Sergey V. Venev ◽

Nils Krietenstein ◽

...

Keyword(s):

Spatial Organization ◽

Cell Types ◽

Chromosome Conformation Capture ◽

Chromatin Interaction ◽

Systematic Evaluation ◽

Chromosome Conformation ◽

3D Genome ◽

Experimental Parameters ◽

Genome Features ◽

Multiple Cell

AbstractChromosome conformation capture (3C)-based assays are used to map chromatin interactions genome-wide. Quantitative analyses of chromatin interaction maps can lead to insights into the spatial organization of chromosomes and the mechanisms by which they fold. A number of protocols such as in situ Hi-C and Micro-C are now widely used and these differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of experimental parameters of 3C-based protocols. We find that different protocols capture different 3D genome features with different efficiencies. First, the use of cross-linkers such as DSG in addition to formaldehyde improves signal-to-noise allowing detection of thousands of additional loops and strengthens the compartment signal. Second, fragmenting chromatin to the level of nucleosomes using MNase allows detection of more loops. On the other hand, protocols that generate larger multi-kb fragments produce stronger compartmentalization signals. We confirmed our results for multiple cell types and cell cycle stages. We find that cell type-specific quantitative differences in chromosome folding are not detected or underestimated by some protocols. Based on these insights we developed Hi-C 3.0, a single protocol that can be used to both efficiently detect chromatin loops and to quantify compartmentalization. Finally, this study produced ultra-deeply sequenced reference interaction maps using conventional Hi-C, Micro-C and Hi-C 3.0 for commonly used cell lines in the 4D Nucleome Project.

Download Full-text

Chromatin Interaction Changes during the iPSC-NPC Model to Facilitate the Study of Biologically Significant Genes Involved in Differentiation

Genes ◽

10.3390/genes11101176 ◽

2020 ◽

Vol 11 (10) ◽

pp. 1176

Author(s):

Won-Young Choi ◽

Ji-Hyun Hwang ◽

Jin-Young Lee ◽

Ann-Na Cho ◽

Andrew J Lee ◽

...

Keyword(s):

Gene Regulation ◽

Cell Fate ◽

Spatial Organization ◽

Spinal Cord Injuries ◽

Cell Types ◽

Regulatory Elements ◽

Chromatin Interaction ◽

Patient Specific ◽

Differentiation Process ◽

Chromosome Conformation

Given the difficulties of obtaining diseased cells, differentiation of neurons from patient-specific human induced pluripotent stem cells (iPSCs) with neural progenitor cells (NPCs) as intermediate precursors is of great interest. While cellular and transcriptomic changes during the differentiation process have been tracked, little attention has been given to examining spatial re-organization, which has been revealed to control gene regulation in various cells. To address the regulatory mechanism by 3D chromatin structure during neuronal differentiation, we examined the changes that take place during differentiation process using two cell types that are highly valued in the study of neurodegenerative disease - iPSCs and NPCs. In our study, we used Hi-C, a derivative of chromosome conformation capture that enables unbiased, genome-wide analysis of interaction frequencies in chromatin. We showed that while topologically associated domains remained mostly the same during differentiation, the presence of differential interacting regions in both cell types suggested that spatial organization affects gene regulation of both pluripotency maintenance and neuroectodermal differentiation. Moreover, closer analysis of promoter–promoter pairs suggested that cell fate specification is under the control of cis-regulatory elements. Our results are thus a resourceful addition in benchmarking differentiation protocols and also provide a greater appreciation of NPCs, the common precursors from which required neurons for applications in neurodegenerative diseases such as Parkinson’s disease, Alzheimer’s disease, schizophrenia and spinal cord injuries are utilized.

Download Full-text

Predicting three-dimensional genome organization with chromatin states

10.1101/282095 ◽

2018 ◽

Cited By ~ 1

Author(s):

Yifeng Qi ◽

Bin Zhang

Keyword(s):

Genome Organization ◽

De Novo ◽

Three Dimensional ◽

Super Resolution ◽

Cell Types ◽

Quantitative Agreement ◽

Chromosome Conformation ◽

Chromatin Loops ◽

Chromatin Folding ◽

Super Resolution Microscopy

ABSTRACTWe introduce a computational model to simulate chromatin structure and dynamics. Starting from one-dimensional genomics and epigenomics data that are available for hundreds of cell types, this model enables de novo prediction of chromatin structures at five-kilo-base resolution. Simulated chromatin structures recapitulate known features of genome organization, including the formation of chromatin loops, topologically associating domains (TADs) and compartments, and are in quantitative agreement with chromosome conformation capture experiments and super-resolution microscopy measurements. Detailed characterization of the predicted structural ensemble reveals the dynamical flexibility of chromatin loops and the presence of cross-talk among neighboring TADs. Analysis of the model’s energy function uncovers distinct mechanisms for chromatin folding at various length scales.

Download Full-text

A unified framework for inferring the multi-scale organization of chromatin domains from Hi-C

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008834 ◽

2021 ◽

Vol 17 (3) ◽

pp. e1008834

Author(s):

Ji Hyun Bak ◽

Min Hyeok Kim ◽

Lei Liu ◽

Changbong Hyeon

Keyword(s):

Statistical Physics ◽

Spatial Organization ◽

Building Blocks ◽

Cell Types ◽

Specific Pattern ◽

Unified Framework ◽

Global Pattern ◽

Chromatin Domains ◽

Chromosome Conformation ◽

Multi Scale

Chromosomes are giant chain molecules organized into an ensemble of three-dimensional structures characterized with its genomic state and the corresponding biological functions. Despite the strong cell-to-cell heterogeneity, the cell-type specific pattern demonstrated in high-throughput chromosome conformation capture (Hi-C) data hints at a valuable link between structure and function, which makes inference of chromatin domains (CDs) from the pattern of Hi-C a central problem in genome research. Here we present a unified method for analyzing Hi-C data to determine spatial organization of CDs over multiple genomic scales. By applying statistical physics-based clustering analysis to a polymer physics model of the chromosome, our method identifies the CDs that best represent the global pattern of correlation manifested in Hi-C. The multi-scale intra-chromosomal structures compared across different cell types uncover the principles underlying the multi-scale organization of chromatin chain: (i) Sub-TADs, TADs, and meta-TADs constitute a robust hierarchical structure. (ii) The assemblies of compartments and TAD-based domains are governed by different organizational principles. (iii) Sub-TADs are the common building blocks of chromosome architecture. Our physically principled interpretation and analysis of Hi-C not only offer an accurate and quantitative view of multi-scale chromatin organization but also help decipher its connections with genome function.

Download Full-text

Advantages of using graph databases to explore chromatin conformation capture experiments

BMC Bioinformatics ◽

10.1186/s12859-020-03937-0 ◽

2021 ◽

Vol 22 (S2) ◽

Author(s):

Daniele D’Agostino ◽

Pietro Liò ◽

Marco Aldinucci ◽

Ivan Merelli

Keyword(s):

Web Application ◽

High Throughput Sequencing ◽

Cell Types ◽

Graph Database ◽

Graph Databases ◽

Sources Of Information ◽

Chromosome Conformation ◽

Wide Scale ◽

User Friendly ◽

Different Cell Types

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.

Download Full-text

A new method for high-resolution imaging of Ku foci to decipher mechanisms of DNA double-strand break repair

The Journal of Cell Biology ◽

10.1083/jcb.201303073 ◽

2013 ◽

Vol 202 (3) ◽

pp. 579-595 ◽

Cited By ~ 136

Author(s):

Sébastien Britton ◽

Julia Coates ◽

Stephen P. Jackson

Keyword(s):

High Resolution ◽

Single Molecule ◽

Anticancer Agents ◽

Spatial Organization ◽

System Development ◽

Super Resolution ◽

Strand Break ◽

Resistance Mechanisms ◽

Original Method ◽

Immune System Development

DNA double-strand breaks (DSBs) are the most toxic of all genomic insults, and pathways dealing with their signaling and repair are crucial to prevent cancer and for immune system development. Despite intense investigations, our knowledge of these pathways has been technically limited by our inability to detect the main repair factors at DSBs in cells. In this paper, we present an original method that involves a combination of ribonuclease- and detergent-based preextraction with high-resolution microscopy. This method allows direct visualization of previously hidden repair complexes, including the main DSB sensor Ku, at virtually any type of DSB, including those induced by anticancer agents. We demonstrate its broad range of applications by coupling it to laser microirradiation, super-resolution microscopy, and single-molecule counting to investigate the spatial organization and composition of repair factories. Furthermore, we use our method to monitor DNA repair and identify mechanisms of repair pathway choice, and we show its utility in defining cellular sensitivities and resistance mechanisms to anticancer agents.

Download Full-text

3D genome structure reconstruction from chromosomal contact data

10.32469/10355/67541 ◽

2017 ◽

Author(s):

◽

Tuan Anh Trieu

Keyword(s):

High Resolution ◽

Genome Structure ◽

Cell Types ◽

3D Models ◽

Graphic User Interface ◽

Soft Constraints ◽

Chromosome Conformation ◽

3D Genome ◽

Manual Adjustment ◽

The Relationship

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Different cell types of an organism have the same DNA sequence, but they can function differently because their difference in 3D organization allows them to express different genes and has different cellular functions. Understanding the 3D organization of the genome is the key to understand functions of the cell. Chromosome conformation capture techniques like Hi-C and TCC that can capture interactions between proximal chromosome fragments have allowed the study of 3D genome organization in high resolution and high through-put. My work focuses on developing computational methods to reconstruct 3D genome structures from Hi-C data. I presented three methods to reconstruct 3D genome and chromosome structures. The first method can build 3D genome models from soft constraints of contacts and non-contacts. This method utilizes the concept of contact and non-contact to reconstruct 3D models without translating interaction frequencies into physical distances. The translation is commonly used by other methods even though it makes a strong assumption about the relationship between interaction frequencies and physical distances. In synthetic dataset, when the relationship was known, my method performed comparably with other methods assuming the relationship. This shows the potential of my method for real Hi-C datasets where the relationship is unknown. The limitation of the method is that it has parameters requiring manual adjustment. I developed the second method to reconstruct 3D genome models. This method utilizes a commonly used function to translate interaction frequencies to physical distances to build 3D models. I proposed a novel way to derive soft constraints to handle inconsistency in the data and to make the method robust. Building 3D models at high resolution is a more challenging problem as the number of constraints is small and the feasible space is larger. I introduced a third method to build 3D chromosome models at high resolution. The method reconstructs models at low resolution and then uses them to guide the reconstruction of models at high resolution. The last part of my work is the development of a comprehensive tool with intuitive graphic user interface to analyze Hi-C data, reconstruct and analyze 3D models.

Download Full-text