scholarly journals High-density spatial transcriptomics arrays for in situ tissue profiling

2019 ◽  
Author(s):  
Sanja Vickovic ◽  
Gökcen Eraslan ◽  
Johanna Klughammer ◽  
Linnea Stenbeck ◽  
Fredrik Salmén ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Expression Patterns ◽  
Cell Types ◽  
High Density ◽  
Rna Seq ◽  
Spatial Profiling ◽  
Tissue Profiling ◽  
Molecular Profiles

AbstractTissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays either lack global transcriptome information or are not at the single-cell level. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are then randomly deposited in individual wells on a slide. The barcoded beads are decoded and coupled to a specific spatial address. We then capture and spatially in situ label RNA from the same histological tissue sections placed on the bead array slide. HDST recovers hundreds of thousands of transcript-coupled barcodes per experiment at 2 μm resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to 2D spatial analysis of tissues at high resolution.

scholarly journals Finding cell-specific expression patterns in the early Ciona embryo with single-cell RNA-seq

2017 ◽  
Author(s):  
Garth R. Ilsley ◽  
Ritsuko Suyama ◽  
Takeshi Noda ◽  
Nori Satoh ◽  
Nicholas M. Luscombe
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Stage ◽  
Specific Expression ◽  
Temporal Gene Expression

AbstractSingle-cell RNA-seq has been established as a reliable and accessible technique enabling new types of analyses, such as identifying cell types and studying spatial and temporal gene expression variation and change at single-cell resolution. Recently, single-cell RNA-seq has been applied to developing embryos, which offers great potential for finding and characterising genes controlling the course of development along with their expression patterns. In this study, we applied single-cell RNA-seq to the 16-cell stage of the Ciona embryo, a marine chordate and performed a computational search for cell-specific gene expression patterns. We recovered many known expression patterns from our single-cell RNA-seq data and despite extensive previous screens, we succeeded in finding new cell-specific patterns, which we validated by in situ and single-cell qPCR.

scholarly journals Spatial charting of single cell transcriptomes in tissues

2021 ◽  
Author(s):  
Nicholas Navin ◽  
Runmin Wei ◽  
Siyuan He ◽  
Shanshan Bai ◽  
Emi Sei ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Spatial Information ◽  
Ductal Carcinoma ◽  
Single Cells ◽  
Cell Types ◽  
Spatial Structures ◽  
Tissue Sections ◽  
Normal Mouse Brain

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called SChart, that combines these two datasets to achieve single cell spatial mapping of cell types, cell states and continuous phenotypes. We applied SChart to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues to validate our approach. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied SChart to identify subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that SChart can accurately map single cells in diverse tissue types to resolve their spatial organization into cellular neighborhoods and tissue structures.

scholarly journals A spatial atlas of inhibitory cell types in mouse hippocampus

2018 ◽  
Author(s):  
Xiaoyan Qian ◽  
Kenneth D. Harris ◽  
Thomas Hauling ◽  
Dimitris Nicoloutsopoulos ◽  
Ana B. Muñoz-Manchado ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Memory Function ◽  
Expression Patterns ◽  
Ground Truth ◽  
Spatial Arrangement ◽  
Cell Types ◽  
Cell System ◽  
Inhibitory Neurons ◽  
Hippocampal Area

Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related cell types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages prior scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method to map the inhibitory neurons of hippocampal area CA1, a cell system critical for memory function, for which ground truth is available from extensive prior work identifying the laminar organization of subtly differing cell types. Our method confidently identified 16 interneuron classes, in a spatial arrangement closely matching ground truth. This method will allow identifying the spatial organization of fine cell types across the brain and other tissues.

scholarly journals Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

2020 ◽  
Author(s):  
Timothy J. Durham ◽  
Riza M. Daza ◽  
Louis Gevirtzman ◽  
Darren A. Cusanovich ◽  
William Stafford Noble ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Gene Expression Patterns ◽  
Rna Seq ◽  
Cell Type ◽  
Tissue Specific ◽  
C Elegans

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.

scholarly journals Spatial organization of the somatosensory cortex revealed by cyclic smFISH

2018 ◽  
Author(s):  
Simone Codeluppi ◽  
Lars E. Borm ◽  
Amit Zeisel ◽  
Gioele La Manno ◽  
Josina A. van Lunteren ◽  
...  
Keyword(s):  
Single Cell ◽  
Somatosensory Cortex ◽  
Single Molecule ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cell Types ◽  
Cellular Organization ◽  
New Methods ◽  
The Brain

The global efforts towards the creation of a molecular census of the brain using single-cell transcriptomics is generating a large catalog of molecularly defined cell types lacking spatial information. Thus, new methods are needed to map a large number of cell-specific markers simultaneously on large tissue areas. Here, we developed a cyclic single molecule fluorescence in situ hybridization methodology and defined the cellular organization of the somatosensory cortex using markers identified by single-cell transcriptomics.

scholarly journals Single cell RNA-seq study of wild type and Hox9,10,11 mutant developing uterus

2018 ◽  
Author(s):  
Michael L. Mucenski ◽  
Robert Mahoney ◽  
Mike Adam ◽  
Andrew S. Potter ◽  
S. Steven Potter
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Hox Genes ◽  
Expression Patterns ◽  
Wild Type Mouse ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Wild Type ◽  
Mouse Uterus

AbstractThe uterus is a remarkable organ that must guard against infections while maintaining the ability to support growth of a fetus without rejection. The Hoxa10 and Hoxa11 genes have previously been shown to play essential roles in uterus development and function. In this report we show that the Hoxc9,10,11 genes play a redundant role in the formation of uterine glands. In addition, we use single cell RNA-seq to create a high resolution gene expression atlas of the developing wild type mouse uterus. Cell types and subtypes are defined, for example dividing endothelial cells into arterial, venous, capillary, and lymphatic, while epithelial cells separate into luminal and glandular subtypes. Further, a surprising heterogeneity of stromal and myocyte cell types are identified. Transcription factor codes and ligand/receptor interactions are characterized. We also used single cell RNA-seq to globally define the altered gene expression patterns in all developing uterus cell types for two Hox mutants, with 8 or 9 mutant Hox genes. The mutants show a striking disruption of Wnt signaling as well as the Cxcl12/Cxcr4 ligand/receptor axis.Summary statementA single cell RNA-seq study of the developing mouse uterus defines cellular heterogeneities, lineage specific gene expression programs and perturbed pathways in Hox9,10,11 mutants.

scholarly journals Cell Dissociation from Butterfly Pupal Wing Tissues for Single-Cell RNA Sequencing

2020 ◽  
Vol 3 (4) ◽  
pp. 72
Author(s):  
Anupama Prakash ◽  
Antónia Monteiro
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cells ◽  
Expression Patterns ◽  
Cell Types ◽  
Rna Seq ◽  
Bicyclus Anynana ◽  
Single Cell Sequencing ◽  
Pupal Wing

Butterflies are well known for their beautiful wings and have been great systems to understand the ecology, evolution, genetics, and development of patterning and coloration. These color patterns are mosaics on the wing created by the tiling of individual units called scales, which develop from single cells. Traditionally, bulk RNA sequencing (RNA-seq) has been used extensively to identify the loci involved in wing color development and pattern formation. RNA-seq provides an averaged gene expression landscape of the entire wing tissue or of small dissected wing regions under consideration. However, to understand the gene expression patterns of the units of color, which are the scales, and to identify different scale cell types within a wing that produce different colors and scale structures, it is necessary to study single cells. This has recently been facilitated by the advent of single-cell sequencing. Here, we provide a detailed protocol for the dissociation of cells from Bicyclus anynana pupal wings to obtain a viable single-cell suspension for downstream single-cell sequencing. We outline our experimental design and the use of fluorescence-activated cell sorting (FACS) to obtain putative scale-building and socket cells based on size. Finally, we discuss some of the current challenges of this technique in studying single-cell scale development and suggest future avenues to address these challenges.

scholarly journals Single-cell RNA-seq reveals cell type-specific transcriptional signatures at the maternal–foetal interface during pregnancy

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Andrew C. Nelson ◽  
Arne W. Mould ◽  
Elizabeth K. Bikoff ◽  
Elizabeth J. Robertson
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Giant Cells ◽  
Maternal Blood ◽  
Rna Seq ◽  
Mammalian Embryo ◽  
Growth And Survival ◽  
Trophoblast Stem Cells

AbstractGrowth and survival of the mammalian embryo within the uterine environment depends on the placenta, a highly complex vascularized organ comprised of both maternal and foetal tissues. Recent experiments demonstrate that the zinc finger transcriptional repressorPrdm1/Blimp1 is essential for specification of spiral artery trophoblast giant cells (SpA-TGCs) that invade and remodel maternal blood vessels. To learn more about functional contributions made by Blimp1+ cell lineages here we perform the first single-cell RNA-seq analysis of the placenta. Cell types of both foetal and maternal origin are profiled. Comparisons with microarray datasets from mutant placenta andin vitrodifferentiated trophoblast stem cells allow us to identify Blimp1-dependent transcripts enriched in SpA-TGCs. Our experiments provide new insights into the functionally distinct cell types present at the maternal–foetal interface and advance our knowledge of dynamic gene expression patterns controlling placental morphogenesis and vascular mimicry.

scholarly journals A probabilistic model-based bi-clustering method for single-cell transcriptomic data analysis

2017 ◽  
Author(s):  
Sha Cao ◽  
Tao Sheng ◽  
Xin Chen ◽  
Qin Ma ◽  
Chi Zhang
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Computational Techniques ◽  
Rna Seq ◽  
Transcriptomic Data ◽  
Large Numbers ◽  
A Cell ◽  
Multiple Cell ◽  
Cell Data

AbstractWe present here novel computational techniques for tackling four problems related to analyses of single-cell RNA-Seq data: (1) a mixture model for coping with multiple cell types in a cell population; (2) a truncated model for handling the unquantifiable errors caused by large numbers of zeros or low-expression values; (3) a bi-clustering technique for detection of sub-populations of cells sharing common expression patterns among subsets of genes; and (4) detection of small cell sub-populations with distinct expression patterns. Through case studies, we demonstrated that these techniques can derive high-resolution information from single-cell data that are not feasible using existing techniques.

scholarly journals Single-cell molecular and cellular architecture of the mouse neurohypophysis

2019 ◽  
Author(s):  
Qiyu Chen ◽  
Dena Leshkowitz ◽  
Janna Blechman ◽  
Gil Levkowitz
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Adult Male ◽  
Spatial Organization ◽  
Cell Types ◽  
Intermediate Lobe ◽  
Posterior Lobe ◽  
Single Cell Rna Sequencing ◽  
The Brain

AbstractThe neurohypophysis (NH), located at the posterior lobe of the pituitary, is a major neuroendocrine tissue, which mediates osmotic balance, blood pressure, reproduction, and lactation by means of releasing the neurohormones oxytocin and arginine-vasopressin from the brain into the peripheral blood circulation. The major cellular components of the NH are hypothalamic axonal termini, fenestrated endothelia and pituicytes, the resident astroglia. However, despite the physiological importance of the NH, the exact molecular signature defining neurohypophyseal cell types and in particular the pituicytes, remains unclear. Using single cell RNA sequencing, we captured seven distinct cell types in the NH and intermediate lobe (IL) of adult male mouse. We revealed novel pituicyte markers showing higher specificity than previously reported. Single molecule in situ hybridization revealed spatial organization of the major cell types implying intercellular communications. We present a comprehensive molecular and cellular characterization of neurohypophyseal cell-types serving as a valuable resource for further functional research.Significance StatementThe neurohypophysis (NH) is a major neuroendocrine interface, which allows the brain to regulate the function of peripheral organs in response to specific physiological demands. Despite its importance, a comprehensive molecular description of cell identities in the NH is still lacking. Utilizing single cell RNA sequencing technology, we identified the transcriptomes of five major neurohypophyseal cell types in the adult male mice and mapped the spatial distribution of selected cell types in situ. We revealed an unexpected cellular heterogeneity of the neurohypophysis and provide novel molecular markers for neurohypophyseal cell types with higher specificity than previously reported.

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