Faculty Opinions recommendation of Joint profiling of chromatin accessibility and gene expression in thousands of single cells.

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.

Download Full-text

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

10.1101/2020.05.14.087601 ◽

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.

Download Full-text

A human cell atlas of fetal gene expression

Science ◽

10.1126/science.aba7721 ◽

2020 ◽

Vol 370 (6518) ◽

pp. eaba7721 ◽

Cited By ~ 4

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.

Download Full-text

Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells

Nature Biotechnology ◽

10.1038/s41587-021-00927-2 ◽

2021 ◽

Author(s):

Eleni P. Mimitou ◽

Caleb A. Lareau ◽

Kelvin Y. Chen ◽

Andre L. Zorzetto-Fernandes ◽

Yuhan Hao ◽

...

Keyword(s):

Gene Expression ◽

Single Cells ◽

Chromatin Accessibility ◽

Protein Levels

Download Full-text

Manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics

10.1101/130336 ◽

2017 ◽

Author(s):

Joshua D. Welch ◽

Alexander J. Hartemink ◽

Jan F. Prins

Keyword(s):

Gene Expression ◽

Single Cell ◽

Epigenetic Modification ◽

Single Cells ◽

Embryonic Stem ◽

Genomic Data ◽

Chromatin Accessibility ◽

Data Sets ◽

Cell Transcriptome ◽

Dynamic Interplay

AbstractSingle cell genomic techniques promise to yield key insights into the dynamic interplay between gene expression and epigenetic modification. However, the experimental difficulty of performing multiple measurements on the same cell currently limits efforts to combine multiple genomic data sets into a united picture of single cell variation. We show that it is possible to construct cell trajectories, reflecting the changes that occur in a sequential biological process, from single cell ATAC-seq, bisulfite sequencing, and ChIP-seq data. In addition, we present an approach called MATCHER that computationally circumvents the experimental difficulties inherent in performing multiple genomic measurements on a single cell by inferring correspondence between single cell transcriptomic and epigenetic measurements performed on different cells of the same type. MATCHER works by first learning a separate manifold for the trajectory of each kind of genomic data, then aligning the manifolds to infer a shared trajectory in which cells measured using different techniques are directly comparable. Using scM&T-seq data, we confirm that MATCHER accurately predicts true single cell correlations between DNA methylation and gene expression without using known cell correspondence information. We also used MATCHER to infer correlations among gene expression, chromatin accessibility, and histone modifications in single mouse embryonic stem cells. These results reveal the dynamic interplay between epigenetic changes and gene expression underlying the transition from pluripotency to differentiation priming. Our work is a first step toward a united picture of heterogeneous transcriptomic and epigenetic states in single cells.

Download Full-text

Protocol for scChaRM-seq: Simultaneous profiling of gene expression, DNA methylation, and chromatin accessibility in single cells

STAR Protocols ◽

10.1016/j.xpro.2021.100972 ◽

2021 ◽

Vol 2 (4) ◽

pp. 100972

Author(s):

Rui Yan ◽

Xin Cheng ◽

Fan Guo

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Single Cells ◽

Chromatin Accessibility

Download Full-text

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

10.1101/529388 ◽

2019 ◽

Cited By ~ 1

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.

Download Full-text

Quantitative control of noise in mammalian gene expression by dynamic histone regulation

eLife ◽

10.7554/elife.65654 ◽

2021 ◽

Vol 10 ◽

Author(s):

Deng Tan ◽

Rui Chen ◽

Yuejian Mo ◽

Shu Gu ◽

Jiao Ma ◽

...

Keyword(s):

Gene Expression ◽

Single Cells ◽

Expression System ◽

Transcriptional Activator ◽

Chromatin Accessibility ◽

Dynamic Regulation ◽

Endogenous Gene ◽

Dual Functional ◽

Fluctuation Noise ◽

Noise In Gene Expression

Fluctuation ('noise') in gene expression is critical for mammalian cellular processes. Numerous mechanisms contribute to its origins, yet the mechanisms behind large fluctuations that are induced by single transcriptional activators remain elusive. Here, we probed putative mechanisms by studying the dynamic regulation of transcriptional activator binding, histone regulator inhibitors, chromatin accessibility, and levels of mRNAs and proteins in single cells. Using a light-induced expression system, we showed that the transcriptional activator could form an interplay with dual functional co-activator/histone acetyltransferases CBP/p300. This interplay resulted in substantial heterogeneity in H3K27ac, chromatin accessibility, and transcription. Simultaneous attenuation of CBP/p300 and HDAC4/5 reduced heterogeneity in the expression of endogenous genes, suggesting that this mechanism is universal. We further found that the noise was reduced by pulse-wide modulation of transcriptional activator binding possibly as a result of alternating the epigenetic states. Our findings suggest a mechanism for the modulation of noise in synthetic and endogenous gene expression systems.

Download Full-text