scholarly journals 3D Genome Structure Variation Across Cell Types Captured by Integrating Multi-omics

2019 ◽  
Author(s):  
Yang Xu ◽  
Tongye Shen ◽  
Rachel Patton McCord
Keyword(s):  
Chromosome Structure ◽  
Single Cells ◽  
Genome Structure ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Cell Identity ◽  
Histone Marks ◽  
3D Genome ◽  
The Impact ◽  
3D Genome Structure

AbstractBackground3D genome structure contributes to the establishment or maintenance of cell identity in part by organizing genes into spatial active or inactive compartments. Less is known about how compartment switching occurs across different cell types. Rather than analyze individual A/B compartment switches between pairs of cell types, here, we seek to identify coordinated changes in groups of compartment-scale interactions across a spectrum of cell types.ResultsTo characterize the impact of genome folding on cell identity, we integrated 35 Hi-C datasets with 125 DNase-seq, 244 RNA-seq, and 893 ChIP-seq datasets. We first find physical associations with the nuclear lamina inform the most dramatic changes in chromosome structure across cell types. By examining variations in chromosome structure, transcription, and chromatin accessibility, we further observe that certain sets of correlated chromosome structure contacts also co-vary in transcription and chromatin accessibility. Analyzing ChIP-seq signals, we find that sets of chromosome contacts that form and break in sync tend to share active or suppressive histone marks. Finally, we observe that similar principles appear to govern chromosome structure fluctuations across single cells as were found across cell types.ConclusionOur results suggest that cells adapt their chromosome structures, guided by variable associations with the lamina and histone marks, to allocate up-regulatory or down-regulatory resources to certain regions and achieve transcription and chromatin accessibility variation. Our study shows E-PCA can identify the major variable interaction sets within populations of single cells, across broad categories of normal cell types, and between cancer and non-cancerous cell types.

scholarly journals Radiation-induced DNA damage and repair effects on 3D genome organization

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jacob T. Sanders ◽  
Trevor F. Freeman ◽  
Yang Xu ◽  
Rosela Golloshi ◽  
Mary A. Stallard ◽  
...  
Keyword(s):  
Dna Damage ◽  
Gene Expression Regulation ◽  
Genome Structure ◽  
Cell Types ◽  
Dimensional Structure ◽  
X Rays ◽  
3D Genome ◽  
Radiation Induced ◽  
The Impact ◽  
3D Genome Structure

AbstractThe three-dimensional structure of chromosomes plays an important role in gene expression regulation and also influences the repair of radiation-induced DNA damage. Genomic aberrations that disrupt chromosome spatial domains can lead to diseases including cancer, but how the 3D genome structure responds to DNA damage is poorly understood. Here, we investigate the impact of DNA damage response and repair on 3D genome folding using Hi-C experiments on wild type cells and ataxia telangiectasia mutated (ATM) patient cells. We irradiate fibroblasts, lymphoblasts, and ATM-deficient fibroblasts with 5 Gy X-rays and perform Hi-C at 30 minutes, 24 hours, or 5 days after irradiation. We observe that 3D genome changes after irradiation are cell type-specific, with lymphoblastoid cells generally showing more contact changes than irradiated fibroblasts. However, all tested repair-proficient cell types exhibit an increased segregation of topologically associating domains (TADs). This TAD boundary strengthening after irradiation is not observed in ATM deficient fibroblasts and may indicate the presence of a mechanism to protect 3D genome structure integrity during DNA damage repair.

scholarly journals Radiation-Induced DNA Damage and Repair Effects on 3D Genome Organization

2019 ◽  
Author(s):  
Jacob T. Sanders ◽  
Trevor F. Freeman ◽  
Yang Xu ◽  
Rosela Golloshi ◽  
Mary A. Stallard ◽  
...  
Keyword(s):  
Dna Damage ◽  
Gene Expression Regulation ◽  
Genome Structure ◽  
Cell Types ◽  
Dimensional Structure ◽  
X Rays ◽  
3D Genome ◽  
Radiation Induced ◽  
The Impact ◽  
3D Genome Structure

ABSTRACTThe three-dimensional structure of chromosomes plays an important role in gene expression regulation and also influences the repair of radiation-induced DNA damage. Genomic aberrations that disrupt chromosome spatial domains can lead to diseases including cancer, but how the 3D genome structure responds to DNA damage is poorly understood. Here, we investigate the impact of DNA damage response and repair on 3D genome folding using Hi-C experiments on wild type cells and ataxia telangiectasia mutated (ATM) patient cells. Fibroblasts, lymphoblasts, and ATM-deficient fibroblasts were irradiated with 5 Gy X-rays and Hi-C was performed after 30 minutes, 24 hours, or 5 days after irradiation. 3D genome changes after irradiation were cell type-specific, with lymphoblastoid cells generally showing more contact changes than irradiated fibroblasts. However, all tested repair-proficient cell types exhibited an increased segregation of topologically associating domains (TADs). This TAD boundary strengthening after irradiation was not observed in ATM deficient fibroblasts and may indicate the presence of a mechanism to protect 3D genome structure integrity during DNA damage repair.

scholarly journals HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random Walk

2018 ◽  
Author(s):  
Jingtian Zhou ◽  
Jianzhu Ma ◽  
Yusi Chen ◽  
Chuankai Cheng ◽  
Bokan Bao ◽  
...  
Keyword(s):  
Random Walk ◽  
Single Cell ◽  
Clustering Algorithm ◽  
Single Cell Analysis ◽  
Single Cells ◽  
Genome Structure ◽  
Real Data ◽  
Cell Types ◽  
3D Genome ◽  
Cell Clustering

3D genome structure plays a pivotal role in gene regulation and cellular function. Single-cell analysis of genome architecture has been achieved using imaging and chromatin conformation capture methods such as Hi-C. To study variation in chromosome structure between different cell types, computational approaches are needed that can utilize sparse and heterogeneous single-cell Hi-C data. However, few methods exist that are able to accurately and efficiently cluster such data into constituent cell types. Here, we describe HiCluster, a single-cell clustering algorithm for Hi-C contact matrices that is based on imputations using linear convolution and random walk. Using both simulated and real data as benchmarks, HiCluster significantly improves clustering accuracy when applied to low coverage Hi-C datasets compared to existing methods. After imputation by HiCluster, structures similar to topologically associating domains (TADs) could be identified within single cells, and their consensus boundaries among cells were enriched at the TAD boundaries observed in bulk samples. In summary, HiCluster facilitates visualization and comparison of single-cell 3D genomes.

scholarly journals Constricted migration is associated with stable 3D genome structure differences in melanoma cells

2019 ◽  
Author(s):  
Rosela Golloshi ◽  
Trevor F. Freeman ◽  
Priyojit Das ◽  
Thomas Isaac Raines ◽  
Rebeca San Martin ◽  
...  
Keyword(s):  
Chromosome Structure ◽  
Metastatic Cancer ◽  
Genome Structure ◽  
Collagen Matrix ◽  
Phenotypic Differences ◽  
3D Genome ◽  
Expression Of Genes ◽  
Structure Changes ◽  
3D Genome Structure ◽  
Nuclear Deformations

AbstractTo spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation and DNA repair, here we investigate how confined migration affects or is affected by 3D genome structure. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Using Hi-C, we observe differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. These sequentially constricted cells also show more nuclear deformations and altered behavior in a 3D collagen matrix. Our observations reveal a relationship between chromosome structure changes, metastatic gene signatures, and the altered nuclear appearance of aggressive melanoma.

scholarly journals DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning

2019 ◽  
Author(s):  
Ron Schwessinger ◽  
Matthew Gosden ◽  
Damien Downes ◽  
Richard Brown ◽  
Jelena Telenius ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Large Scale ◽  
Genome Structure ◽  
Chromatin Interaction ◽  
3D Genome ◽  
Chromatin Interactions ◽  
Genome Wide ◽  
Chromatin Folding ◽  
The Impact ◽  
3D Genome Structure

AbstractUnderstanding 3D genome structure requires high throughput, genome-wide approaches. However, assays for all vs. all chromatin interaction mapping are expensive and time consuming, which severely restricts their usage for large-scale mutagenesis screens or for mapping the impact of sequence variants. Computational models sophisticated enough to grasp the determinants of chromatin folding provide a unique window into the functional determinants of 3D genome structure as well as the effects of genome variation.A chromatin interaction predictor should work at the base pair level but also incorporate large-scale genomic context to simultaneously capture the large scale and intricate structures of chromatin architecture. Similarly, to be a flexible and generalisable approach it should also be applicable to data it has not been explicitly trained on. To develop a model with these properties, we designed a deep neuronal network (deepC) that utilizes transfer learning to accurately predict chromatin interactions from DNA sequence at megabase scale. The model generalizes well to unseen chromosomes and works across cell types, Hi-C data resolutions and a range of sequencing depths. DeepC integrates DNA sequence context on an unprecedented scale, bridging the different levels of resolution from base pairs to TADs. We demonstrate how this model allows us to investigate sequence determinants of chromatin folding at genome-wide scale and to predict the importance of regulatory elements and the impact of sequence variations.

scholarly journals Simultaneous quantification of protein-DNA contacts and transcriptomes in single cells

2019 ◽  
Author(s):  
Koos Rooijers ◽  
Corina M. Markodimitraki ◽  
Franka J. Rang ◽  
Sandra S. de Vries ◽  
Alex Chialastri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mammalian Cells ◽  
Single Cells ◽  
Critical Role ◽  
Nuclear Lamina ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Expression Variability ◽  
The Impact

AbstractThe epigenome plays a critical role in regulating gene expression in mammalian cells. However, understanding how cell-to-cell heterogeneity in the epigenome influences gene expression variability remains a major challenge. Here we report a novel method for simultaneous single-cell quantification of protein-DNA contacts with DamID and transcriptomics (scDamID&T). This method enables quantifying the impact of protein-DNA contacts on gene expression from the same cell. By profiling lamina-associated domains (LADs) in human cells, we reveal different dependencies between genome-nuclear lamina (NL) association and gene expression in single cells. In addition, we introduce the E. coli methyltransferase, Dam, as an in vivo marker of chromatin accessibility in single cells and show that scDamID&T can be utilized as a general technology to identify cell types in silico while simultaneously determining the underlying gene-regulatory landscape. With this strategy the effect of chromatin states, transcription factor binding, and genome organization on the acquisition of cell-type specific transcriptional programs can be quantified.

Hi-CO: 3D genome structure analysis with nucleosome resolution

2021 ◽  
Author(s):  
Masae Ohno ◽  
Tadashi Ando ◽  
David G. Priest ◽  
Yuichi Taniguchi
Keyword(s):  
Structure Analysis ◽  
Genome Structure ◽  
3D Genome ◽  
3D Genome Structure

3D genome structure reconstruction from chromosomal contact data

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.

The 3D Genome Structure of Single Cells

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.

scholarly journals Repeat elements organise 3D genome structure and mediate transcription in the filamentous fungus Epichloë festucae

PLoS Genetics ◽  
2018 ◽  
Vol 14 (10) ◽  
pp. e1007467 ◽  
Author(s):  
David J. Winter ◽  
Austen R. D. Ganley ◽  
Carolyn A. Young ◽  
Ivan Liachko ◽  
Christopher L. Schardl ◽  
...  
Keyword(s):  
Filamentous Fungus ◽  
Genome Structure ◽  
Repeat Elements ◽  
3D Genome ◽  
Epichloë Festucae ◽  
3D Genome Structure
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