scholarly journals Single cell transcriptome atlas of the Drosophila larval brain

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Clarisse Brunet Avalos ◽  
G Larisa Maier ◽  
Rémy Bruggmann ◽  
Simon G Sprecher
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Marker Genes ◽  
Neural Cells ◽  
Larval Brain ◽  
Cell Diversity ◽  
Transcriptional Changes ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
The Brain

Cell diversity of the brain and how it is affected by starvation, remains largely unknown. Here, we introduce a single cell transcriptome atlas of the entire Drosophila first instar larval brain. We first assigned cell-type identity based on known marker genes, distinguishing five major groups: neural progenitors, differentiated neurons, glia, undifferentiated neurons and non-neural cells. All major classes were further subdivided into multiple subtypes, revealing biological features of various cell-types. We further assessed transcriptional changes in response to starvation at the single-cell level. While after starvation the composition of the brain remains unaffected, transcriptional profile of several cell clusters changed. Intriguingly, different cell-types show very distinct responses to starvation, suggesting the presence of cell-specific programs for nutrition availability. Establishing a single-cell transcriptome atlas of the larval brain provides a powerful tool to explore cell diversity and assess genetic profiles from developmental, functional and behavioral perspectives.

scholarly journals High-throughput single-cell transcriptome profiling of plant cell types

2018 ◽  
Author(s):  
Christine N. Shulse ◽  
Benjamin J. Cole ◽  
Gina M. Turco ◽  
Yiwen Zhu ◽  
Siobhan M. Brady ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Transcriptome Profiling ◽  
Cell Types ◽  
Marker Genes ◽  
Single Cell Rna Sequencing ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Heterogeneous Tissues ◽  
Genomic Basis

AbstractSingle-cell transcriptome analysis of heterogeneous tissues can provide high-resolution windows into the genomic basis and spatiotemporal dynamics of developmental processes. Here we demonstrate the feasibility of high-throughput single-cell RNA sequencing of plant tissue using the Drop-seq approach. Profiling of >4,000 individual cells from the Arabidopsis root provides transcriptomes and marker genes for a diversity of cell types and illuminates the gene expression changes that occur across endodermis development.

scholarly journals Single cell transcriptome profiling of the human alcohol-dependent brain

2019 ◽  
Author(s):  
Eric Brenner ◽  
Gayatri R. Tiwari ◽  
Yunlong Liu ◽  
Amy Brock ◽  
R. Dayne Mayfield
Keyword(s):  
Alcohol Dependence ◽  
Single Cell ◽  
Cell Types ◽  
Health Concern ◽  
Cell Type ◽  
Altered Expression ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
The Brain ◽  
Alcohol Dependent

AbstractBackgroundAlcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain.ResultsWe utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16,000 nuclei isolated from prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes, and microglia.ConclusionsTo our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species, and the first such analysis in humans for any addictive substance. These findings greatly advance understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

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 Single-cell transcriptome analysis reveals differential nutrient absorption functions in human intestine

2019 ◽  
Vol 217 (2) ◽  
Author(s):  
Yalong Wang ◽  
Wanlu Song ◽  
Jilian Wang ◽  
Ting Wang ◽  
Xiaochen Xiong ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Intestine ◽  
Hormone Secretion ◽  
Cell Types ◽  
Nutrient Absorption ◽  
Marker Genes ◽  
Human Intestine ◽  
Colon And Rectum ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

The intestine plays an important role in nutrient digestion and absorption, microbe defense, and hormone secretion. Although major cell types have been identified in the mouse intestinal epithelium, cell type–specific markers and functional assignments are largely unavailable for human intestine. Here, our single-cell RNA-seq analyses of 14,537 epithelial cells from human ileum, colon, and rectum reveal different nutrient absorption preferences in the small and large intestine, suggest the existence of Paneth-like cells in the large intestine, and identify potential new marker genes for human transient-amplifying cells and goblet cells. We have validated some of these insights by quantitative PCR, immunofluorescence, and functional analyses. Furthermore, we show both common and differential features of the cellular landscapes between the human and mouse ilea. Therefore, our data provide the basis for detailed characterization of human intestine cell constitution and functions, which would be helpful for a better understanding of human intestine disorders, such as inflammatory bowel disease and intestinal tumorigenesis.

scholarly journals Single cell transcriptome profiling of the human alcohol-dependent brain

2020 ◽  
Vol 29 (7) ◽  
pp. 1144-1153
Author(s):  
Eric Brenner ◽  
Gayatri R Tiwari ◽  
Manav Kapoor ◽  
Yunlong Liu ◽  
Amy Brock ◽  
...  
Keyword(s):  
Alcohol Dependence ◽  
Single Cell ◽  
Cell Types ◽  
Health Concern ◽  
Cell Type ◽  
Altered Expression ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
The Brain ◽  
Alcohol Dependent

Abstract Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

scholarly journals High-Throughput Single-Cell Transcriptome Profiling of Plant Cell Types

Cell Reports ◽  
2019 ◽  
Vol 27 (7) ◽  
pp. 2241-2247.e4 ◽  
Author(s):  
Christine N. Shulse ◽  
Benjamin J. Cole ◽  
Doina Ciobanu ◽  
Junyan Lin ◽  
Yuko Yoshinaga ◽  
...  
Keyword(s):  
Single Cell ◽  
Plant Cell ◽  
High Throughput ◽  
Transcriptome Profiling ◽  
Cell Types ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

scholarly journals Single-cell transcriptomes of pancreatic preinvasive lesions and cancer reveal acinar metaplastic cells’ heterogeneity

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Yehuda Schlesinger ◽  
Oshri Yosefov-Levi ◽  
Dror Kolodkin-Gal ◽  
Roy Zvi Granit ◽  
Luriano Peters ◽  
...  
Keyword(s):  
Single Cell ◽  
Malignant Lesion ◽  
Tumor Development ◽  
Initial Step ◽  
Cell Types ◽  
Tumor Formation ◽  
Specific Cell ◽  
Preinvasive Lesions ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Acinar metaplasia is an initial step in a series of events that can lead to pancreatic cancer. Here we perform single-cell RNA-sequencing of mouse pancreas during the progression from preinvasive stages to tumor formation. Using a reporter gene, we identify metaplastic cells that originated from acinar cells and express two transcription factors, Onecut2 and Foxq1. Further analyses of metaplastic acinar cell heterogeneity define six acinar metaplastic cell types and states, including stomach-specific cell types. Localization of metaplastic cell types and mixture of different metaplastic cell types in the same pre-malignant lesion is shown. Finally, single-cell transcriptome analyses of tumor-associated stromal, immune, endothelial and fibroblast cells identify signals that may support tumor development, as well as the recruitment and education of immune cells. Our findings are consistent with the early, premalignant formation of an immunosuppressive environment mediated by interactions between acinar metaplastic cells and other cells in the microenvironment.

scholarly journals Quantitative single-cell transcriptome-based ranking of engineered AAVs in human retinal explants

2021 ◽  
Author(s):  
Zhouhuan Xi ◽  
Bilge E. Ozturk ◽  
Molly E. Johnson ◽  
Leah C. Byrne
Keyword(s):  
Single Cell ◽  
Viral Vector ◽  
Cell Types ◽  
Adeno Associated Virus ◽  
Altered Expression ◽  
Gene Therapies ◽  
Retinal Tissue ◽  
Retinal Explants ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Gene therapy is a rapidly developing field, and adeno-associated virus (AAV) is a leading viral vector candidate for therapeutic gene delivery. Newly engineered AAVs with improved abilities are now entering the clinic. It has proven challenging, however, to predict the translational potential of gene therapies developed in animal models, due to cross-species differences. Human retinal explants are the only available model of fully developed human retinal tissue, and are thus important for the validation of candidate AAV vectors. In this study, we evaluated 18 wildtype and engineered AAV capsids in human retinal explants using a recently developed single-cell RNA-Seq AAV engineering pipeline (scAAVengr). Human retinal explants retained the same major cell types as fresh retina, with similar expression of cell-specific markers, except for a cone population with altered expression of cone-specific genes. The efficiency and tropism of AAVs in human explants were quantified, with single-cell resolution. The top performing serotypes, K91, K912, and 7m8, were further validated in non-human primate and human retinal explants. Together, this study provides detailed information about the transcriptome profiles of retinal explants, and quantifies the infectivity of leading AAV serotypes in human retina, accelerating the translation of retinal gene therapies to the clinic.

scholarly journals Meta-Analysis of cortical inhibitory interneurons markers landscape and their performances in scRNA-seq studies.

2021 ◽  
Author(s):  
Lorenzo Martini ◽  
Roberta Bardini ◽  
Stefano Di Carlo
Keyword(s):  
Single Cell ◽  
Meta Analysis ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Marker Genes ◽  
Inhibitory Interneurons ◽  
Rna Seq ◽  
Circuit Function ◽  
The Brain

The mammalian cortex contains a great variety of neuronal cells. In particular, GABAergic interneurons, which play a major role in neuronal circuit function, exhibit an extraordinary diversity of cell types. In this regard, single-cell RNA-seq analysis is crucial to study cellular heterogeneity. To identify and analyze rare cell types, it is necessary to reliably label cells through known markers. In this way, all the related studies are dependent on the quality of the employed marker genes. Therefore, in this work, we investigate how a set of chosen inhibitory interneurons markers perform. The gene set consists of both immunohistochemistry-derived genes and single-cell RNA-seq taxonomy ones. We employed various human and mouse datasets of the brain cortex, consequently processed with the Monocle3 pipeline. We defined metrics based on the relations between unsupervised cluster results and the marker expression. Specifically, we calculated the specificity, the fraction of cells expressing, and some metrics derived from decision tree analysis like entropy gain and impurity reduction. The results highlighted the strong reliability of some markers but also the low quality of others. More interestingly, though, a correlation emerges between the general performances of the genes set and the experimental quality of the datasets. Therefore, the proposed method allows evaluating the quality of a dataset in relation to its reliability regarding the inhibitory interneurons cellular heterogeneity study.

scholarly journals Mesenchymal Stromal Cells in the Bone Marrow Niche Consist of Multi-Populations With Distinct Transcriptional and Epigenetic Properties

2021 ◽  
Author(s):  
Sanshiro Kanazawa ◽  
Hironori Hojo ◽  
Shinsuke Ohba ◽  
Junichi Iwata ◽  
Makoto Komura ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Single Cell ◽  
Expression Profiles ◽  
Marker Genes ◽  
Mouse Bone Marrow ◽  
Bone Marrow Niche ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Abstract Although multiple studies have investigated the mesenchymal stem and progenitor cells (MSCs) that give rise to mature bone marrow, high heterogeneity in their morphologies and properties causes difficulties in molecular separation of their distinct populations. In this study, by taking advantage of the resolution of the single cell transcriptome, we analyzed Sca-1 and PDGFR-α fraction in the mouse bone marrow tissue. The single cell transcriptome enabled us to further classify the population into seven populations according to their gene expression profiles. We then separately obtained the seven populations based on candidate marker genes, and specified their gene expression properties and epigenetic landscape by ATAC-seq. Our findings will enable to elucidate the stem cell niche signal in the bone marrow microenvironment, reconstitute bone marrow in vitro, and shed light on the potentially important role of identified subpopulation in various clinical applications to the treatment of bone- and bone marrow-related diseases.

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