scholarly journals The accessible chromatin landscape of the hippocampus at single-cell resolution

2018 ◽  
Author(s):  
John R. Sinnamon ◽  
Kristof A. Torkenczy ◽  
Michael W. Linhoff ◽  
Sarah Vitak ◽  
Hannah A. Pliner ◽  
...  
Keyword(s):  
Single Cell ◽  
Hippocampal Neurons ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Cell Type Specificity ◽  
High Quality ◽  
Rapid Processing ◽  
Accessible Chromatin

ABSTRACTHere we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq), a software suite,scitools, for the rapid processing and visualization of single-cell combinatorial indexing datasets, and a valuable resource of hippocampal regulatory networks at single-cell resolution. We utilized sci-ATAC-seq to produce 2,346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. Using this dataset, we identified eight distinct major clusters of cells representing both neuronal and non-neuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. We then applied a recently described co-accessibility framework,Cicero, which identified 146,818 links between promoters and putative distal regulatory DNA. Identified co-accessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we carried out an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared to nuclei from hippocampal tissue. This dataset and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.

scholarly journals Single cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob M Musser ◽  
Detlev Arendt ◽  
Maria Ina Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Sea Urchins ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Larval Body ◽  
Single Cell Rna Sequencing

Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of genes shared by this population of neurons in sea urchin and vertebrate endocrine pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we show that Pdx1 is necessary for the acquisition of the neuronal identity of these cells. We hypothesize that a network similar to the one orchestrated by Pdx1 in the sea urchin neurons was active in an ancestral cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.

scholarly journals Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhe Cui ◽  
Ya Cui ◽  
Yan Gao ◽  
Tao Jiang ◽  
Tianyi Zang ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Support Vector ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Copy Numbers ◽  
Genome Wide ◽  
Accessible Chromatin

Single-cell Assay Transposase Accessible Chromatin sequencing (scATAC-seq) has been widely used in profiling genome-wide chromatin accessibility in thousands of individual cells. However, compared with single-cell RNA-seq, the peaks of scATAC-seq are much sparser due to the lower copy numbers (diploid in humans) and the inherent missing signals, which makes it more challenging to classify cell type based on specific expressed gene or other canonical markers. Here, we present svmATAC, a support vector machine (SVM)-based method for accurately identifying cell types in scATAC-seq datasets by enhancing peak signal strength and imputing signals through patterns of co-accessibility. We applied svmATAC to several scATAC-seq data from human immune cells, human hematopoietic system cells, and peripheral blood mononuclear cells. The benchmark results showed that svmATAC is free of literature-based markers and robust across datasets in different libraries and platforms. The source code of svmATAC is available at https://github.com/mrcuizhe/svmATAC under the MIT license.

scholarly journals Functional Inference of Gene Regulation using Single-Cell Multi-Omics

2021 ◽  
Author(s):  
Vinay K Kartha ◽  
Fabiana M Duarte ◽  
Yan Hu ◽  
Sai Ma ◽  
Jennifer G Chew ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Regulatory Networks ◽  
Immunological Response ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Human Blood Cells ◽  
Functional Inference ◽  
Omic Data

Cells require coordinated control over gene expression when responding to environmental stimuli. Here, we apply scATAC-seq and scRNA-seq in resting and stimulated human blood cells. Collectively, we generate ~91,000 single-cell profiles, allowing us to probe the cis -regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multi-omic data, we develop FigR - a framework to computationally pair scATAC-seq with scRNA-seq cells, connect distal cis -regulatory elements to genes, and infer gene regulatory networks (GRNs) to identify candidate TF regulators. Utilizing these paired multi-omic data, we define Domains of Regulatory Chromatin (DORCs) of immune stimulation and find that cells alter chromatin accessibility prior to production of gene expression at time scales of minutes. Further, the construction of the stimulation GRN elucidates TF activity at disease-associated DORCs. Overall, FigR enables the elucidation of regulatory interactions across single-cell data, providing new opportunities to understand the function of cells within tissues.

scholarly journals Single cell RNA sequencing of theStrongylocentrotus purpuratuslarva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

2021 ◽  
Author(s):  
Periklis Paganos ◽  
Danila Voronov ◽  
Jacob Musser ◽  
Detlev Arendt ◽  
Maria I. Arnone
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Sea Urchin ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Molecular Fingerprint ◽  
Distinct Cell ◽  
Single Cell Rna Sequencing ◽  
Cell Diversity

AbstractIdentifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identified 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these revealed a highly detailed portrait of cell diversity across the larva, including the identification of 12 distinct neuronal cell types. Moreover, we corroborated co-expression of key regulatory genes previously shown to drive sea urchin gene regulatory networks, and revealed additional domains in which these regulatory networks are likely to function within the larva. Lastly, we recovered a neuronal cell type co-expressingPdx-1andBrn1/2/4, which had previously been shown to share similar gene expression with vertebrate pancreas. Our results extend this finding, revealing twenty transcription factors shared by this population of neurons in sea urchin and vertebrate pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we generate a draft of the Pdx-1 regulatory network in these cells, and hypothesize this network was present in an ancestral deuterostome neuron before being co-opted into the pancreas developmental lineage in vertebrates.

scholarly journals Spatially mapped single-cell chromatin accessibility

2019 ◽  
Author(s):  
Casey A. Thornton ◽  
Ryan M. Mulqueen ◽  
Andrew Nishida ◽  
Kristof A. Torkenczy ◽  
Eve G. Lowenstein ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Information ◽  
Three Dimensional ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Artery Occlusion ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Spatially Resolved ◽  
Typical Experiment

AbstractHigh-throughput single-cell epigenomic assays can resolve the heterogeneity of cell types and states in complex tissues, however, spatial orientation within the network of interconnected cells is lost. Here, we present a novel method for highly scalable, spatially resolved, single-cell profiling of chromatin states. We use high-density multiregional sampling to perform single-cell combinatorial indexing on Microbiopsies Assigned to Positions for the Assay for Transposase Accessible Chromatin (sciMAP-ATAC) to produce single-cell data of an equivalent quality to non-spatially resolved single-cell ATAC-seq, where each cell is localized to a three-dimensional position within the tissue. A typical experiment comprises between 96 and 384 spatially mapped tissue positions, each producing 10s to over 100 individual single-cell ATAC-seq profiles, and a typical resolution of 214 cubic microns; with the ability to tune the resolution and cell throughput to suit each target application. We apply sciMAP-ATAC to the adult mouse primary somatosensory cortex, where we profile cortical lamination and demonstrate the ability to analyze data from a single tissue position or compare a single cell type in adjacent positions. We also profile the human primary visual cortex, where we produce spatial trajectories through the cortex. Finally, we characterize the spatially progressive nature of cerebral ischemic infarct in the mouse brain using a model of transient middle cerebral artery occlusion. We leverage the spatial information to identify novel and known transcription factor activities that vary by proximity to the ischemic infarction core with cell type specificity.

scholarly journals Defining developmental diversification of diencephalon neurons through single-cell gene expression profiling

2018 ◽  
Author(s):  
Qiuxia Guo ◽  
James Y. H. Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Form Complex ◽  
Molecular Features ◽  
Close Relationship ◽  
Cell Groups

ABSTRACTThe embryonic diencephalon gives rise to diverse neuronal cell types, which form complex integration centers and intricate relay stations of the vertebrate forebrain. Prior anecdotal gene expression studies suggest several developmental compartments within the developing diencephalon. In the current study, we utilized single-cell RNA sequencing to profile transcriptomes of dissociated cells from the diencephalon of E12.5 mouse embryos. Through analysis of unbiased transcriptional data, we identified the divergence of different progenitors, intermediate progenitors, and emerging neuronal cell types. After mapping the identified cell groups to their spatial origins, we were able to characterize the molecular features across different cell types and cell states, arising from various diencephalic compartments. Furthermore, we reconstructed the developmental trajectory of different cell lineages within the diencephalon. This allowed the identification of the genetic cascades and gene regulatory networks underlying the progression of the cell cycle, neurogenesis, and cellular diversification. The analysis provides new insights into the molecular mechanism underlying the specification and amplification of thalamic progenitor cells. In addition, the single-cell-resolved trajectories not only confirm a close relationship between the rostral thalamus and prethalamus, but also uncover an unexpected close relationship between the caudal thalamus, epithalamus and rostral pretectum. Our data provide a useful resource for the systematic study of cell heterogeneity and differentiation kinetics within the developing diencephalon.

scholarly journals A single-cell catalogue of regulatory states in the ageing Drosophila brain

2017 ◽  
Author(s):  
Kristofer Davie ◽  
Jasper Janssens ◽  
Duygu Koldere ◽  
Uli Pech ◽  
Sara Aibar ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Neuronal Cell ◽  
Cell Types ◽  
Disease Mutations ◽  
Drosophila Brain ◽  
Gene Regulatory ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
The Brain

SummaryThe diversity of cell types and regulatory states in the brain, and how these change during ageing, remains largely unknown. Here, we present a single-cell transcriptome catalogue of the entire adult Drosophila melanogaster brain sampled across its lifespan. Both neurons and glia age through a process of “regulatory erosion”, characterized by a strong decline of RNA content, and accompanied by increasing transcriptional and chromatin noise. We identify more than 50 cell types by specific transcription factors and their downstream gene regulatory networks. In addition to neurotransmitter types and neuroblast lineages, we find a novel neuronal cell state driven by datilografo and prospero. This state relates to neuronal birth order, the metabolic profile, and the activity of a neuron. Our single-cell brain catalogue reveals extensive regulatory heterogeneity linked to ageing and brain function and will serve as a reference for future studies of genetic variation and disease mutations.

scholarly journals Droplet-based combinatorial indexing for massive scale single-cell epigenomics

2019 ◽  
Author(s):  
Caleb A. Lareau ◽  
Fabiana M. Duarte ◽  
Jennifer G. Chew ◽  
Vinay K. Kartha ◽  
Zach D. Burkett ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Droplet Microfluidics ◽  
Massive Scale ◽  
Single Cell Profiling ◽  
Bone Marrow Derived Cells ◽  
Accessible Chromatin

AbstractWhile recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution, the throughput and quality of these methods have limited the widespread adoption of these technologies. Here, we describe a droplet microfluidics platform for single-cell assay for transposase accessible chromatin (scATAC-seq) for high-throughput single-cell profiling of chromatin accessibility. We use this approach for the unbiased discovery of cell types and regulatory elements within the mouse brain. Further, we extend the throughput of this approach by pairing combinatorial indexing with droplet microfluidics, enabling single-cell studies at a massive scale. With this approach, we measure chromatin accessibility across resting and stimulated human bone marrow derived cells to reveal changes in the cis- and trans- regulatory landscape across cell types and upon stimulation conditions at single-cell resolution. Altogether, we describe a total of 502,207 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

scholarly journals A rapid and robust method for single cell chromatin accessibility profiling

2018 ◽  
Author(s):  
Xi Chen ◽  
Ricardo J Miragaia ◽  
Kedar Nath Natarajan ◽  
Sarah A Teichmann
Keyword(s):  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Single Cell Level ◽  
Cell Type ◽  
Cell Level ◽  
Regulatory Regions ◽  
Cell Type Specific ◽  
Accessible Chromatin

AbstractThe assay for transposase-accessible chromatin using sequencing (ATAC-seq) is widely used to identify regulatory regions throughout the genome. However, very few studies have been performed at the single cell level (scATAC-seq) due to technical challenges. Here we developed a simple and robust plate-based scATAC-seq method, combining upfront bulk Tn5 tagging with single-nuclei sorting. We demonstrated that our method worked robustly across various systems, including fresh and cryopreserved cells from primary tissues. By profiling over 3,000 splenocytes, we identify distinct immune cell types and reveal cell type-specific regulatory regions and related transcription factors.

scholarly journals The regulatory landscape of Arabidopsis thaliana roots at single-cell resolution

2020 ◽  
Author(s):  
Michael W. Dorrity ◽  
Cris Alexandre ◽  
Morgan Hamm ◽  
Anna-Lena Vigil ◽  
Stanley Fields ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Cell Types ◽  
Analytical Framework ◽  
Chromatin Accessibility ◽  
Poor Correlation ◽  
Cell Type ◽  
Tissue Heterogeneity ◽  
Shared Information ◽  
Regulatory Landscape

AbstractIn plants, chromatin accessibility – the primary mark of regulatory DNA – is relatively static across tissues and conditions. This scarcity of accessible sites that are dynamic or tissue-specific may be due in part to tissue heterogeneity in previous bulk studies. To assess the effects of tissue heterogeneity, we apply single-cell ATAC-seq to A. thaliana roots and identify thousands of differentially accessible sites, sufficient to resolve all major cell types of the root. However, even this vast increase relative to bulk studies in the number of dynamic sites does not resolve the poor correlation at individual loci between accessibility and expression. Instead, we find that the entirety of a cell’s regulatory landscape and its transcriptome each capture cell type identity independently. We leverage this shared information on cell identity to integrate accessibility and transcriptome data in order to characterize developmental progression, endoreduplication and cell division in the root. We further use the combined data to characterize cell type-specific motif enrichments of large transcription factor families and to link the expression of individual family members to changing accessibility at specific loci, taking the first steps toward resolving the direct and indirect effects that shape gene expression. Our approach provides an analytical framework to infer the gene regulatory networks that execute plant development.

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