scholarly journals Joint profiling of chromatin accessibility and gene expression in thousands of single cells

Science ◽  
2018 ◽  
Vol 361 (6409) ◽  
pp. 1380-1385 ◽  
Author(s):  
Junyue Cao ◽  
Darren A. Cusanovich ◽  
Vijay Ramani ◽  
Delasa Aghamirzaie ◽  
Hannah A. Pliner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Adult Mouse ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Cellular Biology ◽  
Proof Of Concept ◽  
Large Numbers ◽  
Regulatory Sites

Although we can increasingly measure transcription, chromatin, methylation, and other aspects of molecular biology at single-cell resolution, most assays survey only one aspect of cellular biology. Here we describe sci-CAR, a combinatorial indexing–based coassay that jointly profiles chromatin accessibility and mRNA (CAR) in each of thousands of single cells. As a proof of concept, we apply sci-CAR to 4825 cells, including a time series of dexamethasone treatment, as well as to 11,296 cells from the adult mouse kidney. With the resulting data, we compare the pseudotemporal dynamics of chromatin accessibility and gene expression, reconstruct the chromatin accessibility profiles of cell types defined by RNA profiles, and link cis-regulatory sites to their target genes on the basis of the covariance of chromatin accessibility and transcription across large numbers of single cells.

scholarly journals Massively multiplex single-cell Hi-C

2016 ◽  
Author(s):  
Vijay Ramani ◽  
Xinxian Deng ◽  
Kevin L Gunderson ◽  
Frank J Steemers ◽  
Christine M Disteche ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Cell Types ◽  
Cell Heterogeneity ◽  
Proof Of Concept ◽  
Chromosome Conformation ◽  
Large Numbers ◽  
Conformational Properties ◽  
Novel Method ◽  
Different Cell Types

AbstractWe present combinatorial single cell Hi-C, a novel method that leverages combinatorial cellular indexing to measure chromosome conformation in large numbers of single cells. In this proof-of-concept, we generate and sequence combinatorial single cell Hi-C libraries for two mouse and four human cell types, comprising a total of 9,316 single cells across 5 experiments. We demonstrate the utility of single-cell Hi-C data in separating different cell types, identify previously uncharacterized cell-to-cell heterogeneity in the conformational properties of mammalian chromosomes, and demonstrate that combinatorial indexing is a generalizable molecular strategy for single-cell genomics.

scholarly journals A human cell atlas of fetal chromatin accessibility

Science ◽  
2020 ◽  
Vol 370 (6518) ◽  
pp. eaba7612 ◽  
Author(s):  
Silvia Domcke ◽  
Andrew J. Hill ◽  
Riza M. Daza ◽  
Junyue Cao ◽  
Diana R. O’Day ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Cell ◽  
Single Cells ◽  
Complex Trait ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Cell Type Specific

The chromatin landscape underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of chromatin accessibility and gene expression in fetal tissues. For chromatin accessibility, we devised a three-level combinatorial indexing assay and applied it to 53 samples representing 15 organs, profiling ~800,000 single cells. We leveraged cell types defined by gene expression to annotate these data and cataloged hundreds of thousands of candidate regulatory elements that exhibit cell type–specific chromatin accessibility. We investigated the properties of lineage-specific transcription factors (such as POU2F1 in neurons), organ-specific specializations of broadly distributed cell types (such as blood and endothelial), and cell type–specific enrichments of complex trait heritability. These data represent a rich resource for the exploration of in vivo human gene regulation in diverse tissues and cell types.

scholarly journals Single-cell regulatory landscape and disease vulnerability map of adult Macaque cortex

2020 ◽  
Author(s):  
Ying Lei ◽  
Mengnan Cheng ◽  
Zihao Li ◽  
Zhenkun Zhuang ◽  
Liang Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Neurological Diseases ◽  
Single Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Nucleotide Polymorphisms ◽  
Cell Type

Non-human primates (NHP) provide a unique opportunity to study human neurological diseases, yet detailed characterization of the cell types and transcriptional regulatory features in the NHP brain is lacking. We applied a combinatorial indexing assay, sci-ATAC-seq, as well as single-nuclei RNA-seq, to profile chromatin accessibility in 43,793 single cells and transcriptomics in 11,477 cells, respectively, from prefrontal cortex, primary motor cortex and the primary visual cortex of adult cynomolgus monkey Macaca fascularis. Integrative analysis of these two datasets, resolved regulatory elements and transcription factors that specify cell type distinctions, and discovered area-specific diversity in chromatin accessibility and gene expression within excitatory neurons. We also constructed the dynamic landscape of chromatin accessibility and gene expression of oligodendrocyte maturation to characterize adult remyelination. Furthermore, we identified cell type-specific enrichment of differentially spliced gene isoforms and disease-associated single nucleotide polymorphisms. Our datasets permit integrative exploration of complex regulatory dynamics in macaque brain tissue at single-cell resolution.

scholarly journals Linking transcriptome and chromatin accessibility in nanoliter droplets for single-cell sequencing

2019 ◽  
Author(s):  
Song Chen ◽  
Blue B Lake ◽  
Kun Zhang
Keyword(s):  
Mrna Expression ◽  
Single Cell ◽  
Adult Mouse ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Single Cell Sequencing ◽  
Single Nucleus

Linked profiling of transcriptome and chromatin accessibility from single cells can provide unprecedented insights into cellular status. Here we developed a droplet-based Single-Nucleus chromatin Accessibility and mRNA Expression sequencing (SNARE-seq) assay, that we used to profile neonatal and adult mouse cerebral cortices. To demonstrate the strength of single-cell dual-omics profiling, we reconstructed transcriptome and epigenetic landscapes of cell types, uncovered lineage-specific accessible sites, and connected dynamics of promoter accessibility with transcription during neurogenesis.

scholarly journals A human cell atlas of fetal gene expression

Science ◽  
2020 ◽  
Vol 370 (6518) ◽  
pp. eaba7721 ◽  
Author(s):  
Junyue Cao ◽  
Diana R. O’Day ◽  
Hannah A. Pliner ◽  
Paul D. Kingsley ◽  
Mei Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Cell ◽  
Human Gene ◽  
Single Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Fundamental Interest ◽  
Organ Specific ◽  
Expression Program

The gene expression program underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of gene expression and chromatin accessibility in fetal tissues. For gene expression, we applied three-level combinatorial indexing to >110 samples representing 15 organs, ultimately profiling ~4 million single cells. We leveraged the literature and other atlases to identify and annotate hundreds of cell types and subtypes, both within and across tissues. Our analyses focused on organ-specific specializations of broadly distributed cell types (such as blood, endothelial, and epithelial), sites of fetal erythropoiesis (which notably included the adrenal gland), and integration with mouse developmental atlases (such as conserved specification of blood cells). These data represent a rich resource for the exploration of in vivo human gene expression in diverse tissues and cell types.

scholarly journals EpiRegio: analysis and retrieval of regulatory elements linked to genes

2020 ◽  
Vol 48 (W1) ◽  
pp. W193-W199 ◽  
Author(s):  
Nina Baumgarten ◽  
Dennis Hecker ◽  
Sivarajan Karunanithi ◽  
Florian Schmidt ◽  
Markus List ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Association Studies ◽  
Web Server ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Genome Wide Association Studies ◽  
Coding Regions ◽  
Genomic Regions

Abstract A current challenge in genomics is to interpret non-coding regions and their role in transcriptional regulation of possibly distant target genes. Genome-wide association studies show that a large part of genomic variants are found in those non-coding regions, but their mechanisms of gene regulation are often unknown. An additional challenge is to reliably identify the target genes of the regulatory regions, which is an essential step in understanding their impact on gene expression. Here we present the EpiRegio web server, a resource of regulatory elements (REMs). REMs are genomic regions that exhibit variations in their chromatin accessibility profile associated with changes in expression of their target genes. EpiRegio incorporates both epigenomic and gene expression data for various human primary cell types and tissues, providing an integrated view of REMs in the genome. Our web server allows the analysis of genes and their associated REMs, including the REM’s activity and its estimated cell type-specific contribution to its target gene’s expression. Further, it is possible to explore genomic regions for their regulatory potential, investigate overlapping REMs and by that the dissection of regions of large epigenomic complexity. EpiRegio allows programmatic access through a REST API and is freely available at https://epiregio.de/.

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.

scholarly journals OCHROdb: a comprehensive, quality checked database of open chromatin regions from sequencing data

2018 ◽  
Author(s):  
Parisa Shooshtari ◽  
Samantha Feng ◽  
Viswateja Nelakuditi ◽  
Justin Foong ◽  
Michael Brudno ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Large Scale ◽  
Target Genes ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Sequencing Data ◽  
Genomic Regions ◽  
Multiple Samples ◽  
Regulatory Sites

ABSTRACTInternational consortia, including ENCODE, Roadmap Epigenomics, Genomics of Gene Regulation and Blueprint Epigenome have made large-scale datasets of open chromatin regions publicly available. While these datasets are extremely useful for studying mechanisms of gene regulation in disease and cell development, they only identify open chromatin regions in individual samples. A uniform comparison of accessibility of the same regulatory sites across multiple samples is necessary to correlate open chromatin accessibility and expression of target genes across matched cell types. Additionally, although replicate samples are available for majority of cell types, a comprehensive replication-based quality checking of individual regulatory sites is still lacking. We have integrated 828 DNase-I hypersensitive sequencing samples, which we have uniformly processed and then clustered their regulatory regions across all samples. We checked the quality of open-chromatin regions using our replication test. This has resulted in a comprehensive, quality-checked database of Open CHROmatin (OCHROdb) regions for 194 unique human cell types and cell lines which can serve as a reference for gene regulatory studies involving open chromatin. We have made this resource publicly available: users can download the whole database, or query it for their genomic regions of interest and visualize the results in an interactive genome browser.

Dpp signaling thresholds in the dorsal ectoderm of the Drosophila embryo

Development ◽  
2000 ◽  
Vol 127 (15) ◽  
pp. 3305-3312 ◽  
Author(s):  
H.L. Ashe ◽  
M. Mannervik ◽  
M. Levine
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Histone Acetyltransferase ◽  
Cell Types ◽  
Drosophila Embryo ◽  
Present Evidence ◽  
Drosophila Homolog ◽  
Dorsal Ectoderm ◽  
Transgenic Embryos ◽  
Different Cell Types

The dorsal ectoderm of the Drosophila embryo is subdivided into different cell types by an activity gradient of two TGF(β) signaling molecules, Decapentaplegic (Dpp) and Screw (Scw). Patterning responses to this gradient depend on a secreted inhibitor, Short gastrulation (Sog) and a newly identified transcriptional repressor, Brinker (Brk), which are expressed in neurogenic regions that abut the dorsal ectoderm. Here we examine the expression of a number of Dpp target genes in transgenic embryos that contain ectopic stripes of Dpp, Sog and Brk expression. These studies suggest that the Dpp/Scw activity gradient directly specifies at least three distinct thresholds of gene expression in the dorsal ectoderm of gastrulating embryos. Brk was found to repress two target genes, tailup and pannier, that exhibit different limits of expression within the dorsal ectoderm. These results suggest that the Sog inhibitor and Brk repressor work in concert to establish sharp dorsolateral limits of gene expression. We also present evidence that the activation of Dpp/Scw target genes depends on the Drosophila homolog of the CBP histone acetyltransferase.

scholarly journals CCPLS reveals cell-type-specific spatial dependence of transcriptomes in single cells

2022 ◽  
Author(s):  
Takaho Tsuchiya ◽  
Hiroki Hori ◽  
Haruka Ozaki
Keyword(s):  
Gene Expression ◽  
Single Cells ◽  
Cell Types ◽  
Regression Modeling ◽  
Transcriptome Data ◽  
Cell Type ◽  
Neighboring Cell ◽  
Expression Variability ◽  
Cell Expression ◽  
Cell Cell

Motivation: Cell-cell communications regulate internal cellular states of the cell, e.g., gene expression and cell functions, and play pivotal roles in normal development and disease states. Furthermore, single-cell RNA sequencing methods have revealed cell-to-cell expression variability of highly variable genes (HVGs), which is also crucial. Nevertheless, the regulation on cell-to-cell expression variability of HVGs via cell-cell communications is still unexplored. The recent advent of spatial transcriptome measurement methods has linked gene expression profiles to the spatial context of single cells, which has provided opportunities to reveal those regulations. The existing computational methods extract genes with expression levels that are influenced by neighboring cell types based on the spatial transcriptome data. However, limitations remain in the quantitativeness and interpretability: it neither focuses on HVGs, considers cooperation of neighboring cell types, nor quantifies the degree of regulation with each neighboring cell type. Results: Here, we propose CCPLS (Cell-Cell communications analysis by Partial Least Square regression modeling), which is a statistical framework for identifying cell-cell communications as the effects of multiple neighboring cell types on cell-to-cell expression variability of HVGs, based on the spatial transcriptome data. For each cell type, CCPLS performs PLS regression modeling and reports coefficients as the quantitative index of the cell-cell communications. Evaluation using simulated data showed our method accurately estimated effects of multiple neighboring cell types on HVGs. Furthermore, by applying CCPLS to the two real datasets, we demonstrate CCPLS can be used to extract biologically interpretable insights from the inferred cell-cell communications.

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