Targeted mutations on 3D hub loci alter spatial interaction environment

Many disease-related genotype variations (GVs) reside in non-gene coding regions and the mechanisms of their association with diseases are largely unknown. A possible impact of GVs on disease formation is to alter the spatial organization of chromosome. However, the relationship between GVs and 3D genome structure has not been studied at the chromosome scale. The kilobase resolution of chromosomal structures measured by Hi-C have provided an unprecedented opportunity to tackle this problem. Here we proposed a network-based method to capture global properties of the chromosomal structure. We uncovered that genome organization is scale free and the genomic loci interacting with many other loci in space, termed as hubs, are critical for stabilizing local chromosomal structure. Importantly, we found that cancer-specific GVs target hubs to drastically alter the local chromosomal interactions. These analyses revealed the general principles of 3D genome organization and provided a new direction to pinpoint genotype variations in non-coding regions that are critical for disease formation.

Download Full-text

Shaping of the 3D genome by the ATPase machine cohesin

Experimental & Molecular Medicine ◽

10.1038/s12276-020-00526-2 ◽

2020 ◽

Vol 52 (12) ◽

pp. 1891-1897

Author(s):

Yoori Kim ◽

Hongtao Yu

Keyword(s):

Genome Organization ◽

Spatial Organization ◽

Atp Hydrolysis ◽

Molecular Level ◽

Genome Structure ◽

Genome Replication ◽

Biological Processes ◽

Direct Visualization ◽

Interphase Chromatin ◽

3D Genome

AbstractThe spatial organization of the genome is critical for fundamental biological processes, including transcription, genome replication, and segregation. Chromatin is compacted and organized with defined patterns and proper dynamics during the cell cycle. Aided by direct visualization and indirect genome reconstruction tools, recent discoveries have advanced our understanding of how interphase chromatin is dynamically folded at the molecular level. Here, we review the current understanding of interphase genome organization with a focus on the major regulator of genome structure, the cohesin complex. We further discuss how cohesin harnesses the energy of ATP hydrolysis to shape the genome by extruding chromatin loops.

Download Full-text

The 3D Genome Structure of Single Cells

Annual Review of Biomedical Data Science ◽

10.1146/annurev-biodatasci-020121-084709 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Tianming Zhou ◽

Ruochi Zhang ◽

Jian Ma

Keyword(s):

Single Cell ◽

Data Science ◽

Spatial Organization ◽

Method Development ◽

Single Cells ◽

Genome Structure ◽

Computational Method ◽

Publication Date ◽

3D Genome ◽

Genome Features

The spatial organization of the genome in the cell nucleus is pivotal to cell function. However, how the 3D genome organization and its dynamics influence cellular phenotypes remains poorly understood. The very recent development of single-cell technologies for probing the 3D genome, especially single-cell Hi-C (scHi-C), has ushered in a new era of unveiling cell-to-cell variability of 3D genome features at an unprecedented resolution. Here, we review recent developments in computational approaches to the analysis of scHi-C, including data processing, dimensionality reduction, imputation for enhancing data quality, and the revealing of 3D genome features at single-cell resolution. While much progress has been made in computational method development to analyze single-cell 3D genomes, substantial future work is needed to improve data interpretation and multimodal data integration, which are critical to reveal fundamental connections between genome structure and function among heterogeneous cell populations in various biological contexts. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Download Full-text

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

10.1101/103358 ◽

2017 ◽

Cited By ~ 1

Author(s):

Nan Hua ◽

Harianto Tjong ◽

Hanjun Shin ◽

Ke Gong ◽

Xianghong Jasmine Zhou ◽

...

Keyword(s):

High Performance ◽

Spatial Organization ◽

Genome Structure ◽

Probabilistic Approach ◽

Population Based ◽

Chromatin Interaction ◽

3D Analysis ◽

3D Genome ◽

A Genome ◽

Contact Frequency

ABSTRACTHi-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 genome’s 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.

Download Full-text

The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions

10.1101/112268 ◽

2017 ◽

Cited By ~ 34

Author(s):

Yanli Wang ◽

Bo Zhang ◽

Lijun Zhang ◽

Lin An ◽

Jie Xu ◽

...

Keyword(s):

Genome Organization ◽

Target Genes ◽

Genome Structure ◽

Regulatory Elements ◽

Genomic Region ◽

Genome Browser ◽

Chromatin Interaction ◽

Interaction Data ◽

3D Genome ◽

Chromatin Interactions

ABSTRACTRecent advent of 3C-based technologies such as Hi-C and ChIA-PET provides us an opportunity to explore chromatin interactions and 3D genome organization in an unprecedented scale and resolution. However, it remains a challenge to visualize chromatin interaction data due to its size and complexity. Here, we introduce the 3D Genome Browser (http://3dgenome.org), which allows users to conveniently explore both publicly available and their own chromatin interaction data. Users can also seamlessly integrate other “omics” data sets, such as ChIP-Seq and RNA-Seq for the same genomic region, to gain a complete view of both regulatory landscape and 3D genome structure for any given gene. Finally, our browser provides multiple methods to link distal cis-regulatory elements with their potential target genes, including virtual 4C, ChIA-PET, Capture Hi-C and cross-cell-type correlation of proximal and distal DNA hypersensitive sites, and therefore represents a valuable resource for the study of gene regulation in mammalian genomes.

Download Full-text

Ranking of non-coding pathogenic variants and putative essential regions of the human genome

Nature Communications ◽

10.1038/s41467-019-13212-3 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 13

Author(s):

Alex Wells ◽

David Heckerman ◽

Ali Torkamani ◽

Li Yin ◽

Jonathan Sebat ◽

...

Keyword(s):

Genome Organization ◽

Regulatory Elements ◽

Structural Features ◽

Loss Of Function ◽

3D Genome ◽

Coding Regions ◽

Pathogenic Variants ◽

Machine Learning Model ◽

Using Data

AbstractA gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. Here we train a machine learning model using functional, mutational and structural features, including new genome essentiality metrics, 3D genome organization and enhancer reporter data to identify deleterious variants in non-coding regions. We assess the model for functional correlates by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements in over 3 Mb of genome sequence. Finally, we explore two user cases that involve indels and the disruption of enhancers associated with a developmental disease. We rank variants in the non-coding genome according to their predicted deleteriousness. The model prioritizes non-coding regions associated with regulation of important genes and with cell viability, an in vitro surrogate of essentiality.

Download Full-text

L1 and B1 repeats blueprint the spatial organization of chromatin

10.1101/802173 ◽

2019 ◽

Cited By ~ 3

Author(s):

J. Yuyang Lu ◽

Lei Chang ◽

Tong Li ◽

Ting Wang ◽

Yafei Yin ◽

...

Keyword(s):

Dna Sequences ◽

Mammalian Cells ◽

Spatial Organization ◽

Genome Structure ◽

Three Dimensional ◽

Order Structure ◽

Basic Principles ◽

Heterochromatin Protein ◽

3D Genome ◽

Genomic Repeats

SUMMARYDespite extensive mapping of three-dimensional (3D) chromatin structures, the basic principles underlying genome folding remain unknown. Here, we report a fundamental role for L1 and B1 retrotransposons in shaping the macroscopic 3D genome structure. Homotypic clustering of B1 and L1 repeats in the nuclear interior or at the nuclear and nucleolar peripheries, respectively, segregates the genome into mutually exclusive nuclear compartments. This spatial segregation of L1 and B1 is conserved in mouse and human cells, and occurs dynamically during establishment of the 3D chromatin structure in early embryogenesis and the cell cycle. Depletion of L1 transcripts drastically disrupts the spatial distributions of L1- and B1-rich compartments. L1 transcripts are strongly associated with L1 DNA sequences and induce phase separation of the heterochromatin protein HP1α. Our results suggest that genomic repeats act as the blueprint of chromatin macrostructure, thus explaining the conserved higher-order structure of chromatin across mammalian cells.

Download Full-text

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1512577113 ◽

2016 ◽

Vol 113 (12) ◽

pp. E1663-E1672 ◽

Cited By ~ 110

Author(s):

Harianto Tjong ◽

Wenyuan Li ◽

Reza Kalhor ◽

Chao Dai ◽

Shengli Hao ◽

...

Keyword(s):

Genome Organization ◽

Driving Forces ◽

Genome Structure ◽

Probabilistic Approach ◽

Population Based ◽

3D Genome ◽

Structural Variability ◽

Chromatin Interactions ◽

A Genome ◽

Spatial Genome Organization

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.

Download Full-text

3DGV: Immersive Exploration of 3D Genome Structures using Virtual Reality

10.1101/855379 ◽

2019 ◽

Author(s):

Éric Zhang ◽

Chrisostomos Drogaris ◽

Antoine Gédon ◽

Aaron Sossin ◽

Rajae Faraj ◽

...

Keyword(s):

Virtual Reality ◽

Genome Organization ◽

Spatial Organization ◽

Genomic Data ◽

Regulatory Mechanisms ◽

3D Genome ◽

Open Platform ◽

3D Objects ◽

Link Type ◽

Genome Viewer

The analysis of 3D genomic data is expected to revolutionize our understanding of genome organization and regulatory mechanisms. Yet, the complex spatial organization of this information can be difficult to interpret with 2D viewers. Virtual Reality (VR) technologies offer an opportunity to rethink our methods to visualize and navigate 3D objects. In this paper, we introduce the Virtual Reality 3D Genome Viewer (3DGV), an open platform to experiment and develop VR solutions to explore 3D genome structures.Availabilityhttp://3dgv.cs.mcgill.ca/

Download Full-text

Comparing 3D genome organization in multiple species using Phylo-HMRF

10.1101/552505 ◽

2019 ◽

Cited By ~ 1

Author(s):

Yang Yang ◽

Yang Zhang ◽

Bing Ren ◽

Jesse Dixon ◽

Jian Ma

Keyword(s):

Genome Organization ◽

Genome Mapping ◽

Mammalian Species ◽

Genome Structure ◽

Replication Timing ◽

Primate Species ◽

Spatial Constraints ◽

Evolutionary Patterns ◽

3D Genome ◽

And Function

AbstractRecent developments in whole-genome mapping approaches for the chromatin interactome (such as Hi-C) have offered new insights into 3D genome organization. However, our knowledge of the evolutionary patterns of 3D genome structures in mammalian species remains surprisingly limited. In particular, there are no existing phylogenetic-model based methods to analyze chromatin interactions as continuous features across different species. Here we develop a new probabilistic model, named phylogenetic hidden Markov random field (Phylo-HMRF), to identify evolutionary patterns of 3D genome structures based on multi-species Hi-C data by jointly utilizing spatial constraints among genomic loci and continuous-trait evolutionary models. The effectiveness of Phylo-HMRF is demonstrated in both simulation evaluation and application to real Hi-C data. We used Phylo-HMRF to uncover cross-species 3D genome patterns based on Hi-C data from the same cell type in four primate species (human, chimpanzee, bonobo, and gorilla). The identified evolutionary patterns of 3D genome organization correlate with features of genome structure and function, including long-range interactions, topologically-associating domains (TADs), and replication timing patterns. This work provides a new framework that utilizes general types of spatial constraints to identify evolutionary patterns of continuous genomic features and has the potential to reveal the evolutionary principles of 3D genome organization.

Download Full-text

MyoD is a 3D genome structure organizer for muscle cell identity

Nature Communications ◽

10.1038/s41467-021-27865-6 ◽

2022 ◽

Vol 13 (1) ◽

Author(s):

Ruiting Wang ◽

Fengling Chen ◽

Qian Chen ◽

Xin Wan ◽

Minglei Shi ◽

...

Keyword(s):

Muscle Cell ◽

Genome Organization ◽

Genome Structure ◽

Three Dimensional ◽

Cell Lineage ◽

Muscle Cells ◽

Cell Type ◽

Cell Identity ◽

3D Genome ◽

A Genome

AbstractThe genome exists as an organized, three-dimensional (3D) dynamic architecture, and each cell type has a unique 3D genome organization that determines its cell identity. An unresolved question is how cell type-specific 3D genome structures are established during development. Here, we analyzed 3D genome structures in muscle cells from mice lacking the muscle lineage transcription factor (TF), MyoD, versus wild-type mice. We show that MyoD functions as a “genome organizer” that specifies 3D genome architecture unique to muscle cell development, and that H3K27ac is insufficient for the establishment of MyoD-induced chromatin loops in muscle cells. Moreover, we present evidence that other cell lineage-specific TFs might also exert functional roles in orchestrating lineage-specific 3D genome organization during development.

Download Full-text