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

2021 ◽  
Author(s):  
Ruochi Zhang ◽  
Tianming Zhou ◽  
Jian Ma
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Three Dimensional ◽  
Representation Learning ◽  
Specific Gene ◽  
Separate Analysis ◽  
3D Genome ◽  
Genome Features ◽  
Single Nucleus ◽  
Cell To Cell Variability

AbstractSingle-cell Hi-C (scHi-C) can identify cell-to-cell variability of three-dimensional (3D) chromatin organization, but the sparseness of measured interactions poses an analysis challenge. Here we report Higashi, an algorithm based on hypergraph representation learning that can incorporate the latent correlations among single cells to enhance overall imputation of contact maps. Higashi outperforms existing methods for embedding and imputation of scHi-C data and is able to identify multiscale 3D genome features in single cells, such as compartmentalization and TAD-like domain boundaries, allowing refined delineation of their cell-to-cell variability. Moreover, Higashi can incorporate epigenomic signals jointly profiled in the same cell into the hypergraph representation learning framework, as compared to separate analysis of two modalities, leading to improved embeddings for single-nucleus methyl-3C data. In an scHi-C dataset from human prefrontal cortex, Higashi identifies connections between 3D genome features and cell-type-specific gene regulation. Higashi can also potentially be extended to analyze single-cell multiway chromatin interactions and other multimodal single-cell omics data.

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 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 Chrom3D: three-dimensional genome modeling from Hi-C and nuclear lamin-genome contacts

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Jonas Paulsen ◽  
Monika Sekelja ◽  
Anja R. Oldenburg ◽  
Alice Barateau ◽  
Nolwenn Briand ◽  
...  
Keyword(s):  
Single Cells ◽  
Nuclear Periphery ◽  
Three Dimensional ◽  
Modeling Framework ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Spatial Features ◽  
Nuclear Lamin ◽  
Topologically Associated Domains ◽  
User Friendly

Abstract Current three-dimensional (3D) genome modeling platforms are limited by their inability to account for radial placement of loci in the nucleus. We present Chrom3D, a user-friendly whole-genome 3D computational modeling framework that simulates positions of topologically-associated domains (TADs) relative to each other and to the nuclear periphery. Chrom3D integrates chromosome conformation capture (Hi-C) and lamin-associated domain (LAD) datasets to generate structure ensembles that recapitulate radial distributions of TADs detected in single cells. Chrom3D reveals unexpected spatial features of LAD regulation in cells from patients with a laminopathy-causing lamin mutation. Chrom3D is freely available on github.

scholarly journals Understanding 3D Genome Organization and Its Effect on Transcriptional Gene Regulation Under Environmental Stress in Plant: A Chromatin Perspective

2021 ◽  
Vol 9 ◽  
Author(s):  
Suresh Kumar ◽  
Simardeep Kaur ◽  
Karishma Seem ◽  
Santosh Kumar ◽  
Trilochan Mohapatra
Keyword(s):  
Gene Expression ◽  
Environmental Stress ◽  
Genome Organization ◽  
Regulation Of Gene Expression ◽  
Three Dimensional ◽  
Regulatory Elements ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Chromatin Architecture ◽  
Capture Techniques

The genome of a eukaryotic organism is comprised of a supra-molecular complex of chromatin fibers and intricately folded three-dimensional (3D) structures. Chromosomal interactions and topological changes in response to the developmental and/or environmental stimuli affect gene expression. Chromatin architecture plays important roles in DNA replication, gene expression, and genome integrity. Higher-order chromatin organizations like chromosome territories (CTs), A/B compartments, topologically associating domains (TADs), and chromatin loops vary among cells, tissues, and species depending on the developmental stage and/or environmental conditions (4D genomics). Every chromosome occupies a separate territory in the interphase nucleus and forms the top layer of hierarchical structure (CTs) in most of the eukaryotes. While the A and B compartments are associated with active (euchromatic) and inactive (heterochromatic) chromatin, respectively, having well-defined genomic/epigenomic features, TADs are the structural units of chromatin. Chromatin architecture like TADs as well as the local interactions between promoter and regulatory elements correlates with the chromatin activity, which alters during environmental stresses due to relocalization of the architectural proteins. Moreover, chromatin looping brings the gene and regulatory elements in close proximity for interactions. The intricate relationship between nucleotide sequence and chromatin architecture requires a more comprehensive understanding to unravel the genome organization and genetic plasticity. During the last decade, advances in chromatin conformation capture techniques for unravelling 3D genome organizations have improved our understanding of genome biology. However, the recent advances, such as Hi-C and ChIA-PET, have substantially increased the resolution, throughput as well our interest in analysing genome organizations. The present review provides an overview of the historical and contemporary perspectives of chromosome conformation capture technologies, their applications in functional genomics, and the constraints in predicting 3D genome organization. We also discuss the future perspectives of understanding high-order chromatin organizations in deciphering transcriptional regulation of gene expression under environmental stress (4D genomics). These might help design the climate-smart crop to meet the ever-growing demands of food, feed, and fodder.

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 MEDALT: single-cell copy number lineage tracing enabling gene discovery

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fang Wang ◽  
Qihan Wang ◽  
Vakul Mohanty ◽  
Shaoheng Liang ◽  
Jinzhuang Dou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Copy Number ◽  
Speciation Analysis ◽  
Population Based ◽  
Lineage Tracing ◽  
Breast Cancer Patients ◽  
Lineage Tree ◽  
History Of ◽  
A Cell

AbstractWe present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT.

scholarly journals Order and stochasticity in the folding of individual Drosophila genomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sergey V. Ulianov ◽  
Vlada V. Zakharova ◽  
Aleksandra A. Galitsyna ◽  
Pavel I. Kos ◽  
Kirill E. Polovnikov ◽  
...  
Keyword(s):  
Random Walk ◽  
High Resolution ◽  
3D Genome ◽  
Topologically Associating Domains ◽  
Chromatin Folding ◽  
A Cell ◽  
Single Nucleus ◽  
High Level ◽  
Cell To Cell Variability

AbstractMammalian and Drosophila genomes are partitioned into topologically associating domains (TADs). Although this partitioning has been reported to be functionally relevant, it is unclear whether TADs represent true physical units located at the same genomic positions in each cell nucleus or emerge as an average of numerous alternative chromatin folding patterns in a cell population. Here, we use a single-nucleus Hi-C technique to construct high-resolution Hi-C maps in individual Drosophila genomes. These maps demonstrate chromatin compartmentalization at the megabase scale and partitioning of the genome into non-hierarchical TADs at the scale of 100 kb, which closely resembles the TAD profile in the bulk in situ Hi-C data. Over 40% of TAD boundaries are conserved between individual nuclei and possess a high level of active epigenetic marks. Polymer simulations demonstrate that chromatin folding is best described by the random walk model within TADs and is most suitably approximated by a crumpled globule build of Gaussian blobs at longer distances. We observe prominent cell-to-cell variability in the long-range contacts between either active genome loci or between Polycomb-bound regions, suggesting an important contribution of stochastic processes to the formation of the Drosophila 3D genome.

Sign in / Sign up

Export Citation Format

Share Document