Droplet-based Single-cell Total RNA-seq Reveals Differential Non-Coding Expression and Splicing Patterns during Mouse Development

In recent years, single-cell transcriptome sequencing has revolutionized biology, allowing for the unbiased characterization of cellular subpopulations. However, most methods amplify the termini of polyadenylated transcripts capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding, short non-coding and non-polyadenylated protein-coding transcripts. Additionally, most workflows do not sequence the full transcript hindering the analysis of alternative splicing. We therefore developed VASA- seq to detect the total transcriptome in single cells. VASA-seq is compatible with both plate- based formats and droplet microfluidics. We applied VASA-seq to over 30,000 single cells in the developing mouse embryo during gastrulation and early organogenesis. The dynamics of the total single-cell transcriptome result in the discovery of novel cell type markers many based on non-coding RNA, an in vivo cell cycle analysis and an improved RNA velocity characterization. Moreover, it provides the first comprehensive analysis of alternative splicing during mammalian development.

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Single cell transcriptome atlas of mouse mammary epithelial cells across development

Breast Cancer Research ◽

10.1186/s13058-021-01445-4 ◽

2021 ◽

Vol 23 (1) ◽

Author(s):

Bhupinder Pal ◽

Yunshun Chen ◽

Michael J. G. Milevskiy ◽

François Vaillant ◽

Lexie Prokopuk ◽

...

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Developmental Stages ◽

Mammary Epithelial Cells ◽

Expression Profiles ◽

Single Cells ◽

Chromatin Accessibility ◽

Mammary Epithelial ◽

Cell Transcriptome ◽

Single Cell Transcriptome

Abstract Background Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. Methods The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. Results The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. Conclusions This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

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BAMM-SC: A Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies

10.1101/392662 ◽

2018 ◽

Author(s):

Zhe Sun ◽

Li Chen ◽

Hongyi Xin ◽

Qianhui Huang ◽

Anthony R Cillo ◽

...

Keyword(s):

Single Cell ◽

Single Cells ◽

R Package ◽

Clustering Methods ◽

Model Framework ◽

Bayesian Hierarchical ◽

Bayesian Mixture ◽

Population Scale ◽

Cell Transcriptome ◽

Single Cell Transcriptome

AbstractThe recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we have developed a BAyesiany Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. Specifically, BAMM-SC takes raw data as input and can account for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from extensive simulations and application of BAMM-SC to in-house scRNA-seq datasets using blood, lung and skin cells from humans or mice demonstrated that BAMM-SC outperformed existing clustering methods with improved clustering accuracy and reduced impact from batch effects. BAMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/~Cwec47/singlecell.html.

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sNucDrop-Seq: Dissecting cell-type composition and neuronal activity state in mammalian brains by massively parallel single-nucleus RNA-Seq

10.1101/154476 ◽

2017 ◽

Author(s):

Peng Hu ◽

Emily Fabyanic ◽

Zhaolan Zhou ◽

Hao Wu

Keyword(s):

Single Cell ◽

Neuronal Activity ◽

Low Cost ◽

Single Cells ◽

High Sensitivity ◽

Droplet Microfluidics ◽

Massively Parallel ◽

Rna Seq ◽

Single Nucleus

Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues, such as adult mammalian brains, is challenging. Here, we integrate sucrose-gradient assisted nuclear purification with droplet microfluidics to develop a highly scalable single-nucleus RNA-Seq approach (sNucDrop-Seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ~11,000 nuclei isolated from adult mouse cerebral cortex, we demonstrate that sNucDrop-Seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity, but also enables analysis of long non-coding RNAs and transient states such as neuronal activity-dependent transcription at single-cell resolution in vivo.

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Pooled CRISPR screening with single-cell transcriptome read-out

10.1101/083774 ◽

2016 ◽

Cited By ~ 3

Author(s):

Paul Datlinger ◽

Christian Schmidl ◽

André F Rendeiro ◽

Peter Traxler ◽

Johanna Klughammer ◽

...

Keyword(s):

Single Cell ◽

Selectable Marker ◽

Single Cells ◽

Transcriptome Profiling ◽

Genetic Screens ◽

Biological Mechanisms ◽

Guide Rna ◽

New Gene ◽

Cell Transcriptome ◽

Single Cell Transcriptome

AbstractCRISPR-based genetic screens have revolutionized the search for new gene functions and biological mechanisms. However, widely used pooled screens are limited to simple read-outs of cell proliferation or the production of a selectable marker protein. Arrayed screens allow for more complex molecular read-outs such as transcriptome profiling, but they provide much lower throughput. Here we demonstrate CRISPR genome editing together with single-cell RNA sequencing as a new screening paradigm that combines key advantages of pooled and arrayed screens. This approach allowed us to link guide-RNA expression to the associated transcriptome responses in thousands of single cells using a straightforward and broadly applicable screening workflow.

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Single Cell Transcriptome Conservation in Cryopreserved Cells and Tissues

10.1101/067884 ◽

2016 ◽

Author(s):

Amy Guillaumet-Adkins ◽

Gustavo Rodríguez-Esteban ◽

Elisabetta Mereu ◽

Alberto Villanueva ◽

August Vidal ◽

...

Keyword(s):

Single Cell ◽

Future Study ◽

Paradigm Shift ◽

Single Cells ◽

Sample Preservation ◽

Preservation Method ◽

Cell Transcriptome ◽

Single Cell Transcriptome ◽

Study Designs ◽

Processing Steps

AbstractA variety of single cell RNA preparation procedures have been described. So far these protocols require fresh starting material, hindering complex study designs. We describe a sample preservation method that maintains transcripts in viable single cells and so allows to disconnect time and place of sampling from subsequent processing steps. To demonstrate the potential, we sequenced single cell transcriptomes from >1,000 fresh and conserved cells. Our results confirmed that the conservation process did not alter transcriptional profiles. This substantially broadens the scope of applications in single cell transcriptomics and could lead to a paradigm shift in future study designs.

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Functional In vivo Single-cell Transcriptome (FIST) Analysis Reveals Molecular Properties of Light-Sensitive Neurons in Mouse V1

10.1101/382002 ◽

2018 ◽

Author(s):

Jianwei Liu ◽

Na Pan ◽

Le Sun ◽

Mengdi Wang ◽

Junjing Zhang ◽

...

Keyword(s):

Patch Clamp ◽

Single Cell ◽

Three Dimensional ◽

Whole Cell ◽

Mrna Sequencing ◽

Layer 2 ◽

Cell Transcriptome ◽

Single Cell Transcriptome ◽

Live Mouse

ABSTRACTVision formation is classically based on projections from the retinal ganglion cells (RGC) to the lateral geniculate nucleus (LGN) and the primary visual cortex (V1). Although the cellular information of the retina and the LGN has been widely studied, the transcriptome profiles of single neurons with specific functions in V1 still remain unknown. Some neurons in mouse V1 are tuned to light stimulus. To determine the molecular properties of light-stimulated neurons in layer 2/3 of V1, we developed a method of functional in vivo single-cell transcriptome (FIST) analysis that integrates sensory evoked calcium imaging, whole-cell electrophysiological patch-clamp recordings, single-cell mRNA sequencing and three-dimensional morphological characterization in a live mouse, based on a two-photon microscope system. In our study, 58 individual cells from layer 2/3 of V1 were identified as either light-sensitive (LS) or non-light-sensitive (NS) by single-cell light-evoked calcium evaluation and action potential spiking. The contents of every single cell after individual functional tests were aspirated through the patch-clamp pipette for mRNA sequencing. Furthermore, the three-dimensional (3-D) morphological characterizations of the neurons were reconstructed in the live mouse after the whole-cell recordings. Our sequencing results indicated that V1 neurons with high expression of genes related to transmission regulation, such as Rtn4r, Nr4a1, and genes involved in membrane transport, such as Na+/K+ ATPase, NMDA-type glutamatergic receptor, preferentially respond to light stimulation. Our findings demonstrate the ability of FIST analysis to characterize the functional, morphological and transcriptomic properties of a single cell in alive animal, thereby providing precise neuronal information and predicting its network contribution in the brain.

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Single cell transcriptomics identifies a unique adipocyte population that regulates bone marrow environment

10.1101/754481 ◽

2019 ◽

Author(s):

Leilei Zhong ◽

Lutian Yao ◽

Robert J. Tower ◽

Yulong Wei ◽

Zhen Miao ◽

...

Keyword(s):

Bone Marrow ◽

Single Cell ◽

De Novo ◽

Bone Homeostasis ◽

Genetic Ablation ◽

Lineage Differentiation ◽

Vessel Structure ◽

Cell Transcriptome ◽

Single Cell Transcriptome

AbstractBone marrow mesenchymal lineage cells are a heterogeneous cell population involved in bone homeostasis and diseases such as osteoporosis. While it is long postulated that they originate from mesenchymal stem cells (MSCs), the true identity of MSCs and their in vivo bifurcated differentiation routes into osteoblasts and adipocytes remain poorly understood. Here, by employing single cell transcriptome analysis, we identified MSCs and delineated their bi-lineage differentiation paths in young, adult and aging mice. Among several newly discovered mesenchymal subpopulations, one is a distinct population of adipose-lineage cells that we named marrow environment regulating adipose cells (MERAs). MERAs are non-proliferative, post-progenitor cells that express many mature adipocyte markers but are devoid of lipid droplets. They are abundant in the bone marrow of young mice, acting as pericytes and stromal cells that form numerous connections among themselves and with other cells inside bone, including endothelial cells. Genetic ablation of MERAs disrupts marrow vessel structure, promotes de novo bone formation. Taken together, MERAs represent a unique population of adipose lineage cells that exist only in the bone marrow with critical roles in regulating bone and vessel homeostasis.

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Targeting individual cells by barcode in pooled sequence libraries

10.1101/178681 ◽

2017 ◽

Cited By ~ 1

Author(s):

Navpreet Ranu ◽

Alexandra-Chloé Villani ◽

Nir Hacohen ◽

Paul C. Blainey

Keyword(s):

Single Cell ◽

Mononuclear Cells ◽

Single Cells ◽

Dna Barcodes ◽

Rna Seq ◽

Enrichment Method ◽

Peripheral Blood Mononuclear ◽

Efficient Sampling ◽

Cell Transcriptome ◽

Single Cell Transcriptome

There is rising interest in applying single-cell transcriptome analysis and other single-cell sequencing methods to resolve differences between cells. Pooled processing of thousands of single cells is now routinely practiced by introducing cell-specific DNA barcodes early in cell processing protocols1-5. However, researchers must sequence a large number of cells to sample rare subpopulations6-8, even when fluorescence-activated cell sorting (FACS) is used to pre-enrich rare cell populations. Here, a new molecular enrichment method is used in conjunction with FACS enrichment to enable efficient sampling of rare dendritic cell (DC) populations, including the recently identified AXL+SIGLEC6+ (AS DCs) subset7, within a 10X Genomics single-cell RNA-Seq library. DC populations collectively represent 1-2% of total peripheral blood mononuclear cells (PBMC), with AS DC representing only 1-3% of human blood DCs and 0.01-0.06% of total PBMCs.

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Single-cell transcriptome profiling of the Ciona larval brain

10.1101/319327 ◽

2018 ◽

Cited By ~ 1

Author(s):

Sarthak Sharma ◽

Wei Wang ◽

Alberto Stolfi

Keyword(s):

Single Cell ◽

Single Cells ◽

Expression Patterns ◽

Transcriptome Profiling ◽

Specific Gene ◽

Larval Brain ◽

Rnaseq Data ◽

Cell Type Specific ◽

Cell Transcriptome ◽

Single Cell Transcriptome

AbstractThe tadpole-type larva of Ciona has emerged as an intriguing model system for the study of neurodevelopment. The Ciona intestinalis connectome has been recently mapped, revealing the smallest central nervous system (CNS) known in any chordate, with only 177 neurons. This minimal CNS is highly reminiscent of larger CNS of vertebrates, sharing many conserved developmental processes, anatomical compartments, neuron subtypes, and even specific neural circuits. Thus, the Ciona tadpole offers a unique opportunity to understand the development and wiring of a chordate CNS at single-cell resolution. Here we report the use of single-cell RNAseq to profile the transcriptomes of single cells isolated by fluorescence-activated cell sorting (FACS) from the whole brain of Ciona robusta (formerly intestinalis Type A) larvae. We have also compared these profiles to bulk RNAseq data from specific subsets of brain cells isolated by FACS using cell type-specific reporter plasmid expression. Taken together, these datasets have begun to reveal the compartment- and cell-specific gene expression patterns that define the organization of the Ciona larval brain.

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Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation

Science ◽

10.1126/science.aat7554 ◽

2019 ◽

Vol 363 (6425) ◽

pp. eaat7554 ◽

Cited By ~ 159

Author(s):

Marta Joana Costa Jordão ◽

Roman Sankowski ◽

Stefanie M. Brendecke ◽

Sagar ◽

Giuseppe Locatelli ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Myeloid Cell ◽

Innate Immune ◽

Functional Studies ◽

Cell Diversity ◽

Single Cell Profiling ◽

Cell Transcriptome ◽

Single Cell Transcriptome

The innate immune cell compartment is highly diverse in the healthy central nervous system (CNS), including parenchymal and non-parenchymal macrophages. However, this complexity is increased in inflammatory settings by the recruitment of circulating myeloid cells. It is unclear which disease-specific myeloid subsets exist and what their transcriptional profiles and dynamics during CNS pathology are. Combining deep single-cell transcriptome analysis, fate mapping, in vivo imaging, clonal analysis, and transgenic mouse lines, we comprehensively characterized unappreciated myeloid subsets in several CNS compartments during neuroinflammation. During inflammation, CNS macrophage subsets undergo self-renewal, and random proliferation shifts toward clonal expansion. Last, functional studies demonstrated that endogenous CNS tissue macrophages are redundant for antigen presentation. Our results highlight myeloid cell diversity and provide insights into the brain’s innate immune system.

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