scholarly journals Heterogeneity and Intrinsic Variation in Spatial Genome Organization

2017 ◽  
Author(s):  
Elizabeth H. Finn ◽  
Gianluca Pegoraro ◽  
Hugo B. Brandão ◽  
Anne-Laure Valton ◽  
Marlies E. Oomen ◽  
...  
Keyword(s):  
Genome Organization ◽  
Single Cells ◽  
Human Fibroblasts ◽  
Intrinsic Variability ◽  
Cell Level ◽  
3D Genome ◽  
3D Space ◽  
A Cell ◽  
Spatial Genome Organization ◽  
Independent Behavior

AbstractThe genome is hierarchically organized in 3D space and its architecture is altered in differentiation, development and disease. Some of the general principles that determine global 3D genome organization have been established. However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are poorly characterized. Here, we systematically probe the heterogeneity in genome organization in human fibroblasts by combining high-resolution Hi-C datasets and high-throughput genome imaging. Optical mapping of several hundred genome interaction pairs at the single cell level demonstrates low steady-state frequencies of colocalization in the population and independent behavior of individual alleles in single nuclei. Association frequencies are determined by genomic distance, higher-order chromatin architecture and chromatin environment. These observations reveal extensive variability and heterogeneity in genome organization at the level of single cells and alleles and they demonstrate the coexistence of a broad spectrum of chromatin and genome conformations in a cell population.

scholarly journals Single-cell multi-omic profiling of chromatin conformation and DNA methylation

2019 ◽  
Author(s):  
Dong-Sung Lee ◽  
Chongyuan Luo ◽  
Jingtian Zhou ◽  
Sahaana Chandran ◽  
Angeline Rivkin ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
Cell Types ◽  
Cell Type ◽  
Cell Level ◽  
3D Genome ◽  
Heterogeneous Samples ◽  
Single Data

Abstract The ability to profile epigenomic features in single cells is facilitating the study of the variation in transcription regulation at the single cell level. Single cell methods have also facilitated the generation of cell-type resolved transcriptomic and epigenetic profiles of lineages derived from complex heterogeneous samples. However, integrating different epigenetic features remain challenging, as many current methods profile a single data type at at time. Furthermore, some epigenetic features, such as 3D genome organization, are intrinsically variable between single cells of the same lineage, so it remains unclear how well these methods may resolve cell-types from complex mixtures. Here we describe a method for profiling 3D genome organization and DNA methylation in single cells. This protocol accompanies Lee et al. (Nature Methods 2019) after peer review to aid potential users in applying the method to their own samples.

scholarly journals Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells

2019 ◽  
Author(s):  
Vijay Ramani ◽  
Xinxian Deng ◽  
Ruolan Qiu ◽  
Choli Lee ◽  
Christine M Disteche ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
Three Dimensional ◽  
Population Based ◽  
Order Structure ◽  
Chromosome Conformation ◽  
3D Genome ◽  
A Cell ◽  
Cell To Cell Variability

AbstractThe highly dynamic nature of chromosome conformation and three-dimensional (3D) genome organization leads to cell-to-cell variability in chromatin interactions within a cell population, even if the cells of the population appear to be functionally homogeneous. Hence, although Hi-C is a powerful tool for mapping 3D genome organization, this heterogeneity of chromosome higher order structure among individual cells limits the interpretive power of population based bulk Hi-C assays. Moreover, single-cell studies have the potential to enable the identification and characterization of rare cell populations or cell subtypes in a heterogeneous population. However, it may require surveying relatively large numbers of single cells to achieve statistically meaningful observations in single-cell studies. By applying combinatorial cellular indexing to chromosome conformation capture, we developed single-cell combinatorial indexed Hi-C (sci-Hi-C), a high throughput method that enables mapping chromatin interactomes in large number of single cells. We demonstrated the use of sci-Hi-C data to separate cells by karytoypic and cell-cycle state differences and to identify cellular variability in mammalian chromosomal conformation. Here, we provide a detailed description of method design and step-by-step working protocols for sci-Hi-C.

scholarly journals Stable heteroplasmy at the single cell level is facilitated by inter-cellular exchange of mtDNA

2014 ◽  
Author(s):  
Anitha D Jayaprakash ◽  
Erica Benson ◽  
Swapna Gone ◽  
Raymond Liang ◽  
Jaehee Shim ◽  
...  
Keyword(s):  
Cell Lines ◽  
Rare Variants ◽  
Single Cells ◽  
Cell Level ◽  
Daughter Cells ◽  
Mtdna Haplotypes ◽  
A Cell ◽  
Multiple Cell ◽  
Total Dna ◽  
The Stability

Eukaryotic cells carry two genomes, nuclear (nDNA) and mitochondrial (mtDNA), which are ostensibly decoupled in their replication, segregation and inheritance. It is increasingly appreciated that heteroplasmy, the occurrence of multiple mtDNA haplotypes in a cell, plays an important biological role, but its features are not well understood. Accurately determining the diversity of mtDNA has been difficult, due to the relatively small amount of mtDNA in each cell (< 1% of the total DNA), the intercellular variability of mtDNA content and mtDNA pseudogenes (Numts) in nDNA. To understand the nature of heteroplasmy, we developed Mseek, a novel technique to purify and sequence mtDNA. Mseek yields high purity (> 90%) mtDNA and its ability to detect rare variants is limited only by sequencing depth, providing unprecedented sensitivity and specificity. Using Mseek, we confirmed the ubiquity of heteroplasmy by analyzing mtDNA from a diverse set of cell lines and human samples. Applying Mseek to colonies derived from single cells, we find heteroplasmy is stably maintained in individual daughter cells over multiple cell divisions. We hypothesized that the stability of heteroplasmy could be facilitated by inter-cellular exchange of mtDNA. We explicitly demonstrate this exchange by co-culturing cell lines with distinct mtDNA haplotypes. Our results shed new light on the maintenance of heteroplasmy and provide a novel platform to investigate features of heteroplasmy in normal and diseased states.

scholarly journals Multiscale and integrative single-cell Hi-C analysis with Higashi

2020 ◽  
Author(s):  
Ruochi Zhang ◽  
Tianming Zhou ◽  
Jian Ma
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
Representation Learning ◽  
3D Genome ◽  
Extensive Evaluation ◽  
Genome Features ◽  
And Function ◽  
Cell Variation ◽  
Cell To Cell Variability

The advent of single-cell Hi-C (scHi-C) technologies offers an unprecedented opportunity to unveil cell-to-cell variability of 3D genome organization. However, the development of computational methods that can effectively enhance scHi-C data quality and extract 3D genome features in single cells remains a major challenge. Here, we report Higashi, a new algorithm that enables robust analysis of scHi-C data based on hypergraph representation learning. Extensive evaluation and integrative analysis demonstrate that Higashi significantly outperforms existing methods for embedding and imputation of scHi-C data. Higashi is uniquely able to reveal multiscale 3D genome features (such as compartmentalization and TAD-like domain boundaries), allowing markedly refined analysis of structure and function connections at single-cell resolution. We show that Higashi can also be applied to the recently developed single-cell co-assays that jointly profile scHi-C and additional epigenomic features. Higashi enables much improved delineation of functionally important cell-to-cell variation of 3D genome organization using scHi-C data.

scholarly journals Weak interactions in higher-order chromatin organization

2020 ◽  
Vol 48 (9) ◽  
pp. 4614-4626 ◽  
Author(s):  
Omar L Kantidze ◽  
Sergey V Razin
Keyword(s):  
Genome Organization ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
Weak Interactions ◽  
Three Dimensional ◽  
Dna Supercoiling ◽  
3D Genome ◽  
Protein Dna Interactions ◽  
Spatial Genome Organization ◽  
Hierarchical Folding

Abstract The detailed principles of the hierarchical folding of eukaryotic chromosomes have been revealed during the last two decades. Along with structures composing three-dimensional (3D) genome organization (chromatin compartments, topologically associating domains, chromatin loops, etc.), the molecular mechanisms that are involved in their establishment and maintenance have been characterized. Generally, protein–protein and protein–DNA interactions underlie the spatial genome organization in eukaryotes. However, it is becoming increasingly evident that weak interactions, which exist in biological systems, also contribute to the 3D genome. Here, we provide a snapshot of our current understanding of the role of the weak interactions in the establishment and maintenance of the 3D genome organization. We discuss how weak biological forces, such as entropic forces operating in crowded solutions, electrostatic interactions of the biomolecules, liquid-liquid phase separation, DNA supercoiling, and RNA environment participate in chromosome segregation into structural and functional units and drive intranuclear functional compartmentalization.

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

2016 ◽  
Vol 113 (12) ◽  
pp. E1663-E1672 ◽  
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.

scholarly journals Sci-Hi-C: A single-cell Hi-C method for mapping 3D genome organization in large number of single cells

Methods ◽  
2020 ◽  
Vol 170 ◽  
pp. 61-68 ◽  
Author(s):  
Vijay Ramani ◽  
Xinxian Deng ◽  
Ruolan Qiu ◽  
Choli Lee ◽  
Christine M. Disteche ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Organization ◽  
Single Cells ◽  
3D Genome

scholarly journals HP1 drives de novo 3D genome reorganization in early Drosophila embryos

Nature ◽  
2021 ◽  
Author(s):  
Fides Zenk ◽  
Yinxiu Zhan ◽  
Pavel Kos ◽  
Eva Löser ◽  
Nazerke Atinbayeva ◽  
...  
Keyword(s):  
Genome Organization ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Early Embryo ◽  
Heterochromatin Protein ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Genome Reorganization

AbstractFundamental features of 3D genome organization are established de novo in the early embryo, including clustering of pericentromeric regions, the folding of chromosome arms and the segregation of chromosomes into active (A-) and inactive (B-) compartments. However, the molecular mechanisms that drive de novo organization remain unknown1,2. Here, by combining chromosome conformation capture (Hi-C), chromatin immunoprecipitation with high-throughput sequencing (ChIP–seq), 3D DNA fluorescence in situ hybridization (3D DNA FISH) and polymer simulations, we show that heterochromatin protein 1a (HP1a) is essential for de novo 3D genome organization during Drosophila early development. The binding of HP1a at pericentromeric heterochromatin is required to establish clustering of pericentromeric regions. Moreover, HP1a binding within chromosome arms is responsible for overall chromosome folding and has an important role in the formation of B-compartment regions. However, depletion of HP1a does not affect the A-compartment, which suggests that a different molecular mechanism segregates active chromosome regions. Our work identifies HP1a as an epigenetic regulator that is involved in establishing the global structure of the genome in the early embryo.

scholarly journals Leukocytes with chromosome Y loss have reduced abundance of the cell surface immunoprotein CD99

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonas Mattisson ◽  
Marcus Danielsson ◽  
Maria Hammond ◽  
Hanna Davies ◽  
Caroline J. Gallant ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cells ◽  
Surface Protein ◽  
Protein Abundance ◽  
Blood Leukocytes ◽  
Chromosome Y ◽  
Increased Risk ◽  
A Cell ◽  
Pseudoautosomal Regions ◽  
Male Specific

AbstractMosaic loss of chromosome Y (LOY) in immune cells is a male-specific mutation associated with increased risk for morbidity and mortality. The CD99 gene, positioned in the pseudoautosomal regions of chromosomes X and Y, encodes a cell surface protein essential for several key properties of leukocytes and immune system functions. Here we used CITE-seq for simultaneous quantification of CD99 derived mRNA and cell surface CD99 protein abundance in relation to LOY in single cells. The abundance of CD99 molecules was lower on the surfaces of LOY cells compared with cells without this aneuploidy in all six types of leukocytes studied, while the abundance of CD proteins encoded by genes located on autosomal chromosomes were independent from LOY. These results connect LOY in single cells with immune related cellular properties at the protein level, providing mechanistic insight regarding disease vulnerability in men affected with mosaic chromosome Y loss in blood leukocytes.

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