Single Cell Nuclear Sequencing of Healthy and Diseased Pancreas: The Coming-of-Age of Single Nucleus RNA Sequencing

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

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Complementary Roles for Single-Nucleus and Single-Cell RNA Sequencing in Kidney Disease Research

Journal of the American Society of Nephrology ◽

10.1681/asn.2019020112 ◽

2019 ◽

Vol 30 (4) ◽

pp. 712-713 ◽

Cited By ~ 11

Author(s):

Eoin D. O’Sullivan ◽

Katie J. Mylonas ◽

Jeremy Hughes ◽

David A. Ferenbach

Keyword(s):

Kidney Disease ◽

Single Cell ◽

Rna Sequencing ◽

Disease Research ◽

Single Cell Rna Sequencing ◽

Single Nucleus

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A survey of the mouse hindbrain in the fed and fasted state using single-nucleus RNA sequencing

10.1101/2021.03.11.434948 ◽

2021 ◽

Author(s):

Georgina K.C. Dowsett ◽

Brian Y.H. Lam ◽

John Tadross ◽

Irene Cimino ◽

Debra Rimmington ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

Area Postrema ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Fasted State ◽

Single Nucleus ◽

Human Use ◽

Obesity Drugs

AbstractObjectiveThe area postrema (AP) and the nucleus tractus solitaris (NTS), located in the hindbrain, are key nuclei that sense and integrate peripheral nutritional signals and, consequently, regulate feeding behaviour. While single cell transcriptomics have been used in mice to reveal the gene expression profile and heterogeneity of key hypothalamic populations, similar in-depth studies have not yet been performed in the hindbrain.MethodsUsing single-nucleus RNA sequencing, we provide a detailed survey of 16,034 cells within the AP and NTS of the mouse, in the fed and fasted state.ResultsOf these, 8910 are neurons that group into 30 clusters, with 4289 coming from mice fedad libitumand 4621 from overnight fasted mice. 7124 nuclei are from non-neuronal cells, including oligodendrocytes, astrocytes and microglia. Interestingly, we identified that the oligodendrocyte population was particularly transcriptionally sensitive to an overnight fast. The receptors GLP1R, GIPR, GFRAL and CALCR, which bind GLP1, GIP, GDF15 and amylin respectively, are all expressed in the hindbrain and are major targets for anti-obesity therapeutics. We characterise the transcriptomes of these four populations and show that their gene expression profiles are not dramatically altered by an overnight fast. Notably, we find that roughly half of cells that express GIPR are oligodendrocytes. Additionally, we profile POMC expressing neurons within the hindbrain and demonstrate that 84% of POMC neurons express either PCSK1, PSCK2 or both, implying that melanocortin peptides are likely produced by these neurons.ConclusionWe provide a detailed single-cell level characterisation of AP and NTS cells expressing receptors for key anti-obesity drugs that are either already approved for human use or are in clinical trials. This resource will help delineate the mechanisms underlying the effectiveness of these compounds, and also prove useful in the continued search for other novel therapeutic targets.

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Adversarial domain translation networks enable fast and accurate large-scale atlas-level single-cell data integration

10.1101/2021.11.16.468892 ◽

2021 ◽

Author(s):

Jia Zhao ◽

Gefei Wang ◽

Jingsi Ming ◽

Zhixiang Lin ◽

Yang Wang ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Large Scale ◽

Superior Performance ◽

Brain Atlas ◽

Unified Framework ◽

Fine Grained ◽

Wide Range ◽

Shared Information ◽

Single Nucleus

The rapid emergence of large-scale atlas-level single-cell RNA-sequencing (scRNA-seq) datasets from various sources presents remarkable opportunities for broad and deep biological investigations through integrative analyses. However, harmonizing such datasets requires integration approaches to be not only computationally scalable, but also capable of preserving a wide range of fine-grained cell populations. We created Portal, a unified framework of adversarial domain translation to learn harmonized representations of datasets. With innovation in model and algorithm designs, Portal achieves superior performance in preserving biological variation during integration, while having significantly reduced running time and memory compared to existing approaches, achieving integration of millions of cells in minutes with low memory consumption. We demonstrate the efficiency and accuracy of Portal using diverse datasets ranging from mouse brain atlas projects, the Tabula Muris project, and the Tabula Microcebus project. Portal has broad applicability and in addition to integrating multiple scRNA-seq datasets, it can also integrate scRNA-seq with single-nucleus RNA-sequencing (snRNA-seq) data. Finally, we demonstrate the utility of Portal by applying it to the integration of cross-species datasets with limited shared-information between them, and are able to elucidate biological insights into the similarities and divergences in the spermatogenesis process between mouse, macaque, and human.

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Equivalent high-resolution identification of neuronal cell types with single-nucleus and single-cell RNA-sequencing

10.1101/239749 ◽

2017 ◽

Cited By ~ 6

Author(s):

Trygve E. Bakken ◽

Rebecca D. Hodge ◽

Jeremy M. Miller ◽

Zizhen Yao ◽

Thuc N. Nguyen ◽

...

Keyword(s):

High Resolution ◽

Single Cell ◽

Rna Sequencing ◽

Transcriptional Profiling ◽

Neuronal Cell ◽

Cell Types ◽

Matched Pair ◽

Rna Seq ◽

Nuclear Rna ◽

Single Nucleus

AbstractTranscriptional profiling of complex tissues by RNA-sequencing of single nuclei presents some advantages over whole cell analysis. It enables unbiased cellular coverage, lack of cell isolation-based transcriptional effects, and application to archived frozen specimens. Using a well-matched pair of single-nucleus RNA-seq (snRNA-seq) and single-cell RNA-seq (scRNA-seq) SMART-Seq v4 datasets from mouse visual cortex, we demonstrate that similarly high-resolution clustering of closely related neuronal types can be achieved with both methods if intronic sequences are included in nuclear RNA-seq analysis. More transcripts are detected in individual whole cells (∼11,000 genes) than nuclei (∼7,000 genes), but the majority of genes have similar detection across cells and nuclei. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

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Mutant IDH Inhibitors Induce Lineage Differentiation in IDH-mutant Oligodendroglioma

10.1101/2021.11.16.21266364 ◽

2021 ◽

Author(s):

Avishay Spitzer ◽

Simon Gritsch ◽

Hannah Weisman ◽

Nicolas Gonzalez Castro ◽

Masashi Nomura ◽

...

Keyword(s):

Cell Proliferation ◽

Single Cell ◽

Clinical Response ◽

Rna Sequencing ◽

Treatment Initiation ◽

Experimental Models ◽

Low Grade ◽

Lineage Differentiation ◽

Single Nucleus ◽

Sample Pair

Recent data showed promising signs of objective tumor responses in subsets of patients with low grade glioma treated with inhibitors of mutant IDH (IDHi). However, the molecular and cellular underpinnings of such responses are not known. Here, we profiled 6,039 transcriptomes by single-cell or single-nucleus RNA-sequencing isolated from three IDH-mutant oligodendroglioma patients with clinical response to IDHi. Importantly, the tissues were sampled on-drug, four weeks from treatment initiation and our dataset includes a matched pre- and on-treatment sample pair. We integrate our findings with analysis of 8,241 transcriptomes from seven untreated samples, 134 bulk samples from the TCGA and experimental models. We find that IDHi treatment induces a robust differentiation towards glial lineages, accompanied by a depletion of stem-like cells and a reduction of cell proliferation. Our study provides the first evidence in patients of the differentiating potential of IDHi on the cellular hierarchies that drive oligodendrogliomas.

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Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease

Nature Communications ◽

10.1038/s41467-020-19737-2 ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Marta Olah ◽

Vilas Menon ◽

Naomi Habib ◽

Mariko F. Taga ◽

Yiyi Ma ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Single Cell ◽

Rna Sequencing ◽

Independent Set ◽

Neurosurgical Procedures ◽

Human Microglia ◽

Single Cell Rna Sequencing ◽

Single Nucleus ◽

Disease Related Genes

AbstractThe extent of microglial heterogeneity in humans remains a central yet poorly explored question in light of the development of therapies targeting this cell type. Here, we investigate the population structure of live microglia purified from human cerebral cortex samples obtained at autopsy and during neurosurgical procedures. Using single cell RNA sequencing, we find that some subsets are enriched for disease-related genes and RNA signatures. We confirm the presence of four of these microglial subpopulations histologically and illustrate the utility of our data by characterizing further microglial cluster 7, enriched for genes depleted in the cortex of individuals with Alzheimer’s disease (AD). Histologically, these cluster 7 microglia are reduced in frequency in AD tissue, and we validate this observation in an independent set of single nucleus data. Thus, our live human microglia identify a range of subtypes, and we prioritize one of these as being altered in AD.

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Single‐Cell, Single‐Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity

Hepatology Communications ◽

10.1002/hep4.1854 ◽

2021 ◽

Author(s):

Tallulah S. Andrews ◽

Jawairia Atif ◽

Jeff C. Liu ◽

Catia T. Perciani ◽

Xue‐Zhong Ma ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Human Liver ◽

Single Nucleus

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Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation

10.1101/585901 ◽

2019 ◽

Cited By ~ 3

Author(s):

Alan Selewa ◽

Ryan Dohn ◽

Heather Eckart ◽

Stephanie Lozano ◽

Bingqing Xie ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Time Course ◽

Cell Types ◽

Heart Tissue ◽

Intact Cells ◽

Tissue Samples ◽

Single Nucleus ◽

Induced Pluripotent

ABSTRACTA comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3’ RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of time-series transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. We compared the detected cell types from primary tissue with iPSC-derived cardiomyocytes profiled with DroNc-seq. Our data confirm that DroNc-seq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.

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Single-nucleus transcriptomic atlas of spinal cord neuron in human

10.1101/2021.09.28.462103 ◽

2021 ◽

Author(s):

Donghang Zhang ◽

Yiyong Wei ◽

Jin Liu ◽

Hongjun Chen ◽

Jin Li ◽

...

Keyword(s):

Spinal Cord ◽

Single Cell ◽

Rna Sequencing ◽

Marker Genes ◽

Molecular Evidence ◽

Functional Heterogeneity ◽

Spinal Cord Neurons ◽

Human Spinal Cord ◽

Neuronal Types ◽

Single Nucleus

Despite the recognized importance of spinal cord in sensory processing, motor behaviors and/or neural diseases, the underlying neuronal clusters remain elusive. Recently, several studies attempted to define the neuronal types and functional heterogeneity in spinal cord using single cell and/or single-nucleus RNA-sequencing in varied animal models. However, the molecular evidence of neuronal heterogeneity in human spinal cord has not been established yet. Here we sought to classify spinal cord neurons from human donors by high-throughput single-nucleus RNA-sequencing. The functional heterogeneity of identified cell types and signaling pathways that connecting neuronal subtypes were explored. Moreover, we also compared human results with previous single-cell transcriptomic profiles of mouse spinal cord. As a result, we generated the first comprehensive atlas of human spinal cord neurons and defined 18 neuronal clusters. In addition to identification of the new and functionally-distinct neuronal subtypes, our results also provide novel marker genes for previously known neuronal types. The comparation with mouse transcriptomic profiles revealed an overall similarity in the cellular composition of spinal cord between the two species. In summary, these results illustrate the complexity and diversity of neuronal types in human spinal cord and will provide an important resource for future researches to explore the molecular mechanism underlying several spinal cord physiology and diseases.

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