scholarly journals Characterization of germ cell differentiation in the male mouse through single-cell RNA sequencing

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
S. Lukassen ◽  
E. Bosch ◽  
A. B. Ekici ◽  
A. Winterpacht
Keyword(s):  
Cell Differentiation ◽  
Germ Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Male Mouse ◽  
Germ Cell Differentiation ◽  
Single Cell Rna Sequencing

scholarly journals Revealing cellular and molecular transitions in neonatal germ cell differentiation using single cell RNA sequencing

Development ◽  
2019 ◽  
Vol 146 (6) ◽  
pp. dev174953 ◽  
Author(s):  
Jinyue Liao ◽  
Shuk Han Ng ◽  
Alfred Chun Luk ◽  
Hoi Ching Suen ◽  
Yan Qian ◽  
...  
Keyword(s):  
Cell Differentiation ◽  
Germ Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Germ Cell Differentiation ◽  
Single Cell Rna Sequencing

scholarly journals MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii406-iii406
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Ahmed Gilani ◽  
Bridget Sanford ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing ◽  
Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

scholarly journals Integrated Single-Cell RNA-Sequencing Analysis of Aquaporin 5-Expressing Mouse Lung Epithelial Cells Identifies GPRC5A as a Novel Validated Type I Cell Surface Marker

Cells ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 2460 ◽  
Author(s):  
Masafumi Horie ◽  
Alessandra Castaldi ◽  
Mitsuhiro Sunohara ◽  
Hongjun Wang ◽  
Yanbin Ji ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cell ◽  
Rna Sequencing ◽  
Surface Marker ◽  
Mouse Lung ◽  
Type I ◽  
Cell Markers ◽  
Lung Epithelial ◽  
Single Cell Rna Sequencing

Molecular and functional characterization of alveolar epithelial type I (AT1) cells has been challenging due to difficulty in isolating sufficient numbers of viable cells. Here we performed single-cell RNA-sequencing (scRNA-seq) of tdTomato+ cells from lungs of AT1 cell-specific Aqp5-Cre-IRES-DsRed (ACID);R26tdTomato reporter mice. Following enzymatic digestion, CD31-CD45-E-cadherin+tdTomato+ cells were subjected to fluorescence-activated cell sorting (FACS) followed by scRNA-seq. Cell identity was confirmed by immunofluorescence using cell type-specific antibodies. After quality control, 92 cells were analyzed. Most cells expressed ‘conventional’ AT1 cell markers (Aqp5, Pdpn, Hopx, Ager), with heterogeneous expression within this population. The remaining cells expressed AT2, club, basal or ciliated cell markers. Integration with public datasets identified three robust AT1 cell- and lung-enriched genes, Ager, Rtkn2 and Gprc5a, that were conserved across species. GPRC5A co-localized with HOPX and was not expressed in AT2 or airway cells in mouse, rat and human lung. GPRC5A co-localized with AQP5 but not pro-SPC or CC10 in mouse lung epithelial cell cytospins. We enriched mouse AT1 cells to perform molecular phenotyping using scRNA-seq. Further characterization of putative AT1 cell-enriched genes revealed GPRC5A as a conserved AT1 cell surface marker that may be useful for AT1 cell isolation.

scholarly journals Expressed barcodes enable clonal characterization of chemotherapeutic responses in chronic lymphocytic leukemia

2019 ◽  
Author(s):  
Aziz Al’Khafaji ◽  
Catherine Gutierrez ◽  
Eric Brenner ◽  
Russell Durrett ◽  
Kaitlyn E. Johnson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
Single Cell ◽  
Rna Sequencing ◽  
Genetic Alterations ◽  
Response To Therapy ◽  
Lymphocytic Leukemia ◽  
Single Cell Rna Sequencing ◽  
Cancer Cell Population

AbstractThe remarkable evolutionary capacity of cancer is a major challenge to current therapeutic efforts. Fueling this evolution is its vast clonal heterogeneity and ability to adapt to diverse selective pressures. Although the genetic and transcriptional mechanisms underlying these responses have been independently evaluated, the ability to couple genetic alterations present within individual clones to their respective transcriptional or functional outputs has been lacking in the field. To this end, we developed a high-complexity expressed barcode library that integrates DNA barcoding with single-cell RNA sequencing through use of the CROP-seq sgRNA expression/capture system, and which is compatible with the COLBERT clonal isolation workflow for subsequent genomic and epigenomic characterization of specific clones of interest. We applied this approach to study chronic lymphocytic leukemia (CLL), a mature B cell malignancy notable for its genetic and transcriptomic heterogeneity and variable disease course. Here, we demonstrate the clonal composition and gene expression states of HG3, a CLL cell line harboring the common alteration del(13q), in response to front-line cytotoxic therapy of fludarabine and mafosfamide (an analog of the clinically used cyclophosphamide). Analysis of clonal abundance and clonally-resolved single-cell RNA sequencing revealed that only a small fraction of clones consistently survived therapy. These rare highly drug tolerant clones comprise 94% of the post-treatment population and share a stable, pre-existing gene expression state characterized by upregulation of CXCR4 and WNT signaling and a number of DNA damage and cell survival genes. Taken together, these data demonstrate at unprecedented resolution the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population. Further, this approach provides a template for the high-resolution study of thousands of clones and the respective gene expression states underlying their response to therapy.

scholarly journals VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data

2019 ◽  
Vol 36 (2) ◽  
pp. 546-551 ◽  
Author(s):  
Kyungsoo Kim ◽  
Sunmo Yang ◽  
Sang-Jun Ha ◽  
Insuk Lee
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Cell Differentiation ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Signaling Molecules ◽  
Single Cell Rna Sequencing ◽  
Functional States

Abstract Motivation The immune system has diverse types of cells that are differentiated or activated via various signaling pathways and transcriptional regulation upon challenging conditions. Immunophenotyping by flow and mass cytometry are the major approaches for identifying key signaling molecules and transcription factors directing the transition between the functional states of immune cells. However, few proteins can be evaluated by flow cytometry in a single experiment, preventing researchers from obtaining a comprehensive picture of the molecular programs involved in immune cell differentiation. Recent advances in single-cell RNA sequencing (scRNA-seq) have enabled unbiased genome-wide quantification of gene expression in individual cells on a large scale, providing a new and versatile analytical pipeline for studying immune cell differentiation. Results We present VirtualCytometry, a web-based computational pipeline for evaluating immune cell differentiation by exploiting cell-to-cell variation in gene expression with scRNA-seq data. Differentiating cells often show a continuous spectrum of cellular states rather than distinct populations. VirtualCytometry enables the identification of cellular subsets for different functional states of differentiation based on the expression of marker genes. Case studies have highlighted the usefulness of this subset analysis strategy for discovering signaling molecules and transcription factors for human T-cell exhaustion, a state of T-cell dysfunction, in tumor and mouse dendritic cells activated by pathogens. With more than 226 scRNA-seq datasets precompiled from public repositories covering diverse mouse and human immune cell types in normal and disease tissues, VirtualCytometry is a useful resource for the molecular dissection of immune cell differentiation. Availability and implementation www.grnpedia.org/cytometry

Single-cell RNA sequencing reveals species-specific time spans of cell cycle transitions in early oogenesis

2021 ◽  
Author(s):  
Zheng-Hui Zhao ◽  
Tie-Gang Meng ◽  
Hong-Yong Zhang ◽  
Yi Hou ◽  
Heide Schatten ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Germ Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Germ Cells ◽  
Cell Cycle Regulators ◽  
Sequencing Data ◽  
Interspecies Differences ◽  
Single Cell Rna Sequencing ◽  
Female Germ Cell

Abstract Oogenesis is a highly regulated process and its basic cellular events are evolutionarily conserved. However, the time spans of oogenesis differ substantially among species. To explore these interspecies differences in oogenesis, we performed single-cell RNA-sequencing on mouse and monkey female germ cells and downloaded the single-cell RNA-sequencing data of human female germ cells. The cell cycle analyses indicate that the period and extent of cell cycle transitions are significantly different between the species. Moreover, hierarchical clustering of critical cell cycle genes and the interacting network of cell cycle regulators also exhibit distinguished patterns across species. We propose that differences in the regulation of cell cycle transitions may underlie female germ cell developmental allochrony between species. A better understanding of the cell cycle transition machinery will provide new insights into the interspecies differences in female germ cell developmental time spans.

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