scholarly journals Single-cell RNA-seq landscape midbrain cell responses to red spotted grouper nervous necrosis virus infection

2021 ◽  
Vol 17 (6) ◽  
pp. e1009665
Author(s):  
Qing Wang ◽  
Cheng Peng ◽  
Min Yang ◽  
Fengqi Huang ◽  
Xuzhuo Duan ◽  
...  
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Neuronal Cell ◽  
Cell Types ◽  
Infected Fish ◽  
Nerve Tissue ◽  
Nervous Necrosis Virus ◽  
Epinephelus Coioides ◽  
Rna Seq ◽  
Necrosis Virus

Viral nervous necrosis (VNN) is an acute and serious fish disease caused by nervous necrosis virus (NNV) which has been reported massive mortality in more than fifty teleost species worldwide. VNN causes damage of necrosis and vacuolation to central nervous system (CNS) cells in fish. It is difficult to identify the specific type of cell targeted by NNV, and to decipher the host immune response because of the functional diversity and highly complex anatomical and cellular composition of the CNS. In this study, we found that the red spotted grouper NNV (RGNNV) mainly attacked the midbrain of orange-spotted grouper (Epinephelus coioides). We conducted single-cell RNA-seq analysis of the midbrain of healthy and RGNNV-infected fish and identified 35 transcriptionally distinct cell subtypes, including 28 neuronal and 7 non-neuronal cell types. An evaluation of the subpopulations of immune cells revealed that macrophages were enriched in RGNNV-infected fish, and the transcriptional profiles of macrophages indicated an acute cytokine and inflammatory response. Unsupervised pseudotime analysis of immune cells showed that microglia transformed into M1-type activated macrophages to produce cytokines to reduce the damage to nerve tissue caused by the virus. We also found that RGNNV targeted neuronal cell types was GLU1 and GLU3, and we found that the key genes and pathways by which causes cell cytoplasmic vacuoles and autophagy significant enrichment, this may be the major route viruses cause cell death. These data provided a comprehensive transcriptional perspective of the grouper midbrain and the basis for further research on how viruses infect the teleost CNS.

scholarly journals Full-Length Transcriptome: A Reliable Alternative for Single-Cell RNA-Seq Analysis in the Spleen of Teleost Without Reference Genome

2021 ◽  
Vol 12 ◽  
Author(s):  
Lixing Huang ◽  
Ying Qiao ◽  
Wei Xu ◽  
Linfeng Gong ◽  
Rongchao He ◽  
...  
Keyword(s):  
Data Analysis ◽  
B Cells ◽  
Single Cell ◽  
Reference Genome ◽  
Immune Cell ◽  
Cell Types ◽  
Full Length ◽  
Cell Populations ◽  
Epinephelus Coioides ◽  
Rna Seq

Fish is considered as a supreme model for clarifying the evolution and regulatory mechanism of vertebrate immunity. However, the knowledge of distinct immune cell populations in fish is still limited, and further development of techniques advancing the identification of fish immune cell populations and their functions are required. Single cell RNA-seq (scRNA-seq) has provided a new approach for effective in-depth identification and characterization of cell subpopulations. Current approaches for scRNA-seq data analysis usually rely on comparison with a reference genome and hence are not suited for samples without any reference genome, which is currently very common in fish research. Here, we present an alternative, i.e. scRNA-seq data analysis with a full-length transcriptome as a reference, and evaluate this approach on samples from Epinephelus coioides-a teleost without any published genome. We show that it reconstructs well most of the present transcripts in the scRNA-seq data achieving a sensitivity equivalent to approaches relying on genome alignments of related species. Based on cell heterogeneity and known markers, we characterized four cell types: T cells, B cells, monocytes/macrophages (Mo/MΦ) and NCC (non-specific cytotoxic cells). Further analysis indicated the presence of two subsets of Mo/MΦ including M1 and M2 type, as well as four subsets in B cells, i.e. mature B cells, immature B cells, pre B cells and early-pre B cells. Our research will provide new clues for understanding biological characteristics, development and function of immune cell populations of teleost. Furthermore, our approach provides a reliable alternative for scRNA-seq data analysis in teleost for which no reference genome is currently available.

scholarly journals Reference Transcriptomes of Porcine Peripheral Immune Cells Created Through Bulk and Single-Cell RNA Sequencing

2021 ◽  
Vol 12 ◽  
Author(s):  
Juber Herrera-Uribe ◽  
Jayne E. Wiarda ◽  
Sathesh K. Sivasankaran ◽  
Lance Daharsh ◽  
Haibo Liu ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Peripheral Blood ◽  
Cell Types ◽  
Cell Populations ◽  
Rna Seq ◽  
Cell Type ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B-cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B-cell, conventional CD4 and CD8 αβ T-cells, NK cells, and γδ T-cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T-cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

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

2017 ◽  
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.

scholarly journals Comprehensive analysis of immune evasion in breast cancer by single-cell RNA-seq

2018 ◽  
Author(s):  
Jianhua Yin ◽  
Zhisheng Li ◽  
Chen Yan ◽  
Enhao Fang ◽  
Ting Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Tumor Cells ◽  
Immune Cells ◽  
Cell Types ◽  
Rna Seq ◽  
Breast Cancer Patients ◽  
Numerous Cell ◽  
Cancer Tumor

AbstractThe tumor microenvironment is composed of numerous cell types, including tumor, immune and stromal cells. Cancer cells interact with the tumor microenvironment to suppress anticancer immunity. In this study, we molecularly dissected the tumor microenvironment of breast cancer by single-cell RNA-seq. We profiled the breast cancer tumor microenvironment by analyzing the single-cell transcriptomes of 52,163 cells from the tumor tissues of 15 breast cancer patients. The tumor cells and immune cells from individual patients were analyzed simultaneously at the single-cell level. This study explores the diversity of the cell types in the tumor microenvironment and provides information on the mechanisms of escape from clearance by immune cells in breast cancer.One Sentence SummaryLandscape of tumor cells and immune cells in breast cancer by single cell RNA-seq

scholarly journals Single-cell RNA-seq analysis maps the development of human fetal retina

2018 ◽  
Author(s):  
Yufeng Lu ◽  
Wenyang Yi ◽  
Qian Wu ◽  
Suijuan Zhong ◽  
Zhentao Zuo ◽  
...  
Keyword(s):  
Single Cell ◽  
Visual Information ◽  
Developmental Trajectories ◽  
Retinal Development ◽  
Neuronal Cell ◽  
Cell Types ◽  
Retinal Cell ◽  
Rna Seq ◽  
Fetal Retina ◽  
The Impact

AbstractVision starts with image formation at the retina, which contains diverse neuronal cell types that extract, process, and relay visual information to higher order processing centers in the brain. Though there has been steady progress in defining retinal cell types, very little is known about retinal development in humans, which starts well before birth. In this study, we performed transcriptomic profiling of developing human fetal retina from gestational weeks 12 to 27 using single-cell RNA-seq (scRNA-seq) and used pseudotime analysis to reconstruct the developmental trajectories of retinogenesis. Our analysis reveals transcriptional programs driving differentiation down four different cell types and suggests that Müller glia (MG) can serve as embryonic progenitors in early retinal development. In addition, we also show that transcriptional differences separate retinal progenitor cells (RPCs) into distinct subtypes and use this information to reconstruct RPC developmental trajectories and cell fate. Our results support a hierarchical program of differentiation governing cell-type diversity in the developing human retina. In summary, our work details comprehensive molecular classification of retinal cells, reconstructs their relationships, and paves the way for future mechanistic studies on the impact of gene regulation upon human retinogenesis.

scholarly journals Reference transcriptomes of porcine peripheral immune cells created through bulk and single-cell RNA sequencing

2021 ◽  
Author(s):  
Juber Herrera-Uribe ◽  
Jayne E Wiarda ◽  
Sathesh K Sivasankaran ◽  
Lance Daharsh ◽  
Haibo Liu ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Immune Cells ◽  
Peripheral Blood ◽  
Cell Types ◽  
Cell Populations ◽  
Rna Seq ◽  
Cell Type ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B cell, conventional CD4 and CD8 αβ T cells, NK cells, and γδ T cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

scholarly journals treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruizhu Huang ◽  
Charlotte Soneson ◽  
Pierre-Luc Germain ◽  
Thomas S.B. Schmidt ◽  
Christian Von Mering ◽  
...  
Keyword(s):  
Single Cell ◽  
Synthetic Data ◽  
Cell Types ◽  
Data Driven ◽  
Rna Seq ◽  
Hierarchical Trees

AbstracttreeclimbR is for analyzing hierarchical trees of entities, such as phylogenies or cell types, at different resolutions. It proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single-cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

scholarly journals Annotating cell types in human single-cell RNA-seq data with CellO

2021 ◽  
Vol 2 (3) ◽  
pp. 100705
Author(s):  
Matthew N. Bernstein ◽  
Colin N. Dewey
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Rna Seq

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

Single-cell RNA-seq profiling of individual Biomphalaria glabrata immune cells with a focus on immunologically relevant transcripts

2021 ◽  
Author(s):  
Hongyu Li ◽  
Abdullah A. Gharamah ◽  
Jacob R. Hambrook ◽  
Xinzhong Wu ◽  
Patrick C. Hanington
Keyword(s):  
Single Cell ◽  
Immune Cells ◽  
Biomphalaria Glabrata ◽  
Rna Seq
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