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 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 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 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 Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage

2020 ◽  
Vol 16 (12) ◽  
pp. e1008476
Author(s):  
Samuel P. Ingram ◽  
Nicholas T. Henthorn ◽  
John W. Warmenhoven ◽  
Norman F. Kirkby ◽  
Ranald I. Mackay ◽  
...  
Keyword(s):  
Dna Damage ◽  
Cell Fate ◽  
Genome Structure ◽  
Cell Types ◽  
Genome Organisation ◽  
Geometric Clustering ◽  
Radiation Induced ◽  
In Silico Models

Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.

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.

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

scholarly journals Repeat elements organize 3D genome structure and mediate transcription in the filamentous fungusEpichloë festucae

2018 ◽  
Author(s):  
David J Winter ◽  
Austen RD Ganley ◽  
Carolyn A Young ◽  
Ivan Liachko ◽  
Christopher L Schardl ◽  
...  
Keyword(s):  
Genome Structure ◽  
Regulation Of Gene Expression ◽  
Three Dimensional ◽  
Structural Features ◽  
Dimensional Structure ◽  
In Planta ◽  
Repeat Elements ◽  
Symbiotic Relationships ◽  
3D Genome ◽  
Transcriptional Changes

AbstractStructural features of genomes, including the three-dimensional arrangement of DNA in the nucleus, are increasingly seen as key contributors to the regulation of gene expression. However, studies on how genome structure and nuclear organization influence transcription have so far been limited to a handful of model species. This narrow focus limits our ability to draw general conclusions about the ways in which three-dimensional structures are encoded, and to integrate information from three-dimensional data to address a broader gamut of biological questions. Here, we generate a complete and gapless genome sequence for the filamentous fungus,Epichloë festucae. Coupling it with RNAseq and HiC data, we investigate how the structure of the genome contributes to the suite of transcriptional changes that anEpichloëspecies needs to maintain symbiotic relationships with its grass host. Our results reveal a unique “patchwork” genome, in which repeat-rich blocks of DNA with discrete boundaries are interspersed by gene-rich sequences. In contrast to other species, the three-dimensional structure of the genome is anchored by these repeat blocks, which act to isolate transcription in neighbouring gene-rich regions. Genes that are differentially expressed in planta are enriched near the boundaries of these repeat-rich blocks, suggesting that their three-dimensional orientation partly encodes and regulates the symbiotic relationship formed by this organism.

scholarly journals Assessment of DNA Damage after Photodynamic Therapy Using a Metallophthalocyanine Photosensitizer

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
A. El-Hussein ◽  
M. Harith ◽  
H. Abrahamse
Keyword(s):  
Dna Damage ◽  
Photodynamic Therapy ◽  
Adaptive Response ◽  
Uv Light ◽  
Cell Types ◽  
Surrounding Tissue ◽  
Target Tissue ◽  
X Rays ◽  
Integrity Of Dna ◽  
Mcf 7

Photodynamic therapy (PDT) is a chemotherapeutic approach that utilizes a bifunctional reagent, a photosensitizer (PS) that localizes to the target tissue relative to the surrounding tissue and is toxic when exposed to laser light. PDT rapidly induces cell death, inflammatory and immune reactions, and damage of the microvasculature. DNA damage results from a variety of factors including UV-light, X-rays, ionizing radiation, toxins, chemicals, or reactive oxygen species. The aim of this study was to determine the effect of PDT as well as the influence of presensitization leading to the adaptive response (AR) on the integrity of DNA. Lung (A549), breast (MCF-7), and esophageal (SNO) cancer cells and Zn sulfophthalocyanine as PS with irradiation conditions of 10 J/cm2at 636 nm were used. Subcellular localization of PS, cell morphology, and viability after PDT and DNA damage were determined. A significant decrease in viability and marked DNA damage was observed in all 3 cancer cell types in response to PDT while the adaptive response was demonstrated to significantly decrease the effectiveness of the PDT.

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.

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