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 ◽  
...  

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.

Science ◽  
2020 ◽  
Vol 370 (6518) ◽  
pp. eaba7612 ◽  
Author(s):  
Silvia Domcke ◽  
Andrew J. Hill ◽  
Riza M. Daza ◽  
Junyue Cao ◽  
Diana R. O’Day ◽  
...  

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.


2019 ◽  
Author(s):  
Koos Rooijers ◽  
Corina M. Markodimitraki ◽  
Franka J. Rang ◽  
Sandra S. de Vries ◽  
Alex Chialastri ◽  
...  

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.


2020 ◽  
Author(s):  
Ying Lei ◽  
Mengnan Cheng ◽  
Zihao Li ◽  
Zhenkun Zhuang ◽  
Liang Wu ◽  
...  

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.


2021 ◽  
Author(s):  
Xuelei Lai ◽  
Romain Blanc-Mathieu ◽  
Loic GrandVuillemin ◽  
Ying Huang ◽  
Arnaud Stigliani ◽  
...  

Pioneer transcription factors (TFs) are a special category of TFs with the capacity to bind to closed chromatin regions in which DNA is wrapped around histones and often highly methylated. Subsequently, they are able to modify the chromatin state to initiate gene expression. In plants, LEAFY (LFY) is a master floral regulator and has been suggested to act as a pioneer TF in Arabidopsis. Here, we demonstrate that LFY is able to bind both methylated and non-methylated DNA using a combination of in vitro genome-wide binding experiments and structural modeling. Comparisons between regions bound by LFY in vivo and chromatin accessibility data suggest that LFY binds a subset of regions occupied by nucleosomes. We confirm that LFY is able to bind nucleosomal DNA in vitro using reconstituted nucleosomes. Finally, we show that constitutive LFY expression in seedling tissues is sufficient to induce chromatin accessibility in the LFY direct target genes, APETALA1 and AGAMOUS. Taken together, our study suggests that LFY possesses key pioneer TF features that contribute to launch the floral gene expression program.


Science ◽  
2018 ◽  
Vol 361 (6409) ◽  
pp. 1380-1385 ◽  
Author(s):  
Junyue Cao ◽  
Darren A. Cusanovich ◽  
Vijay Ramani ◽  
Delasa Aghamirzaie ◽  
Hannah A. Pliner ◽  
...  

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.


2014 ◽  
Vol 25 (22) ◽  
pp. 3699-3708 ◽  
Author(s):  
Anyimilehidi Mazo-Vargas ◽  
Heungwon Park ◽  
Mert Aydin ◽  
Nicolas E. Buchler

Time-lapse fluorescence microscopy is an important tool for measuring in vivo gene dynamics in single cells. However, fluorescent proteins are limited by slow chromophore maturation times and the cellular autofluorescence or phototoxicity that arises from light excitation. An alternative is luciferase, an enzyme that emits photons and is active upon folding. The photon flux per luciferase is significantly lower than that for fluorescent proteins. Thus time-lapse luminescence microscopy has been successfully used to track gene dynamics only in larger organisms and for slower processes, for which more total photons can be collected in one exposure. Here we tested green, yellow, and red beetle luciferases and optimized substrate conditions for in vivo luminescence. By combining time-lapse luminescence microscopy with a microfluidic device, we tracked the dynamics of cell cycle genes in single yeast with subminute exposure times over many generations. Our method was faster and in cells with much smaller volumes than previous work. Fluorescence of an optimized reporter (Venus) lagged luminescence by 15–20 min, which is consistent with its known rate of chromophore maturation in yeast. Our work demonstrates that luciferases are better than fluorescent proteins at faithfully tracking the underlying gene expression.


2020 ◽  
Author(s):  
Feng Tian ◽  
Fan Zhou ◽  
Xiang Li ◽  
Wenping Ma ◽  
Honggui Wu ◽  
...  

SummaryBy circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs.HighlightsGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetusDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DTMeasuring chromatin open regions in single cells with high detectability by METATACIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM


2022 ◽  
Author(s):  
Takaho Tsuchiya ◽  
Hiroki Hori ◽  
Haruka Ozaki

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.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Elliott Swanson ◽  
Cara Lord ◽  
Julian Reading ◽  
Alexander T Heubeck ◽  
Palak C Genge ◽  
...  

Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: integrated cellular indexing of chromatin landscape and epitopes, called ICICLE-seq. We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures transcriptomics (scRNA-seq), epitopes, and chromatin accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.


2021 ◽  
Author(s):  
Juan Jauregui-Lozano ◽  
Kimaya Bakhle ◽  
Vikki M. Weake

AbstractThe chromatin landscape defines cellular identity in multicellular organisms with unique patterns of DNA accessibility and histone marks decorating the genome of each cell type. Thus, profiling the chromatin state of different cell types in an intact organism under disease or physiological conditions can provide insight into how chromatin regulates cell homeostasisin vivo. To overcome the many challenges associated with characterizing chromatin state in specific cell types, we developed an improved approach to isolateDrosophilanuclei tagged with GFP expressed under Gal4/UAS control. Using this protocol, we profiled chromatin accessibility using Omni-ATAC, and examined the distribution of histone marks using ChIP-seq and CUT&Tag in adult photoreceptor neurons. We show that the chromatin landscape of photoreceptors reflects the transcriptional state of these cells, demonstrating the quality and reproducibility of our approach for profiling the transcriptome and epigenome of specific cell types inDrosophila.


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