scholarly journals Single-Cell Atlas of Adult Testis in Protogynous Hermaphroditic Orange-Spotted Grouper, Epinephelus coioides

2021 ◽  
Vol 22 (22) ◽  
pp. 12607
Author(s):  
Xi Wu ◽  
Yang Yang ◽  
Chaoyue Zhong ◽  
Tong Wang ◽  
Yanhong Deng ◽  
...  
Keyword(s):  
Single Cell ◽  
Germ Cells ◽  
Expression Patterns ◽  
Somatic Cells ◽  
Human Testis ◽  
Marker Genes ◽  
Specific Marker ◽  
Epinephelus Coioides ◽  
Male Germ Cells ◽  
Adult Testis

Spermatogenesis is a process of self-renewal and differentiation in spermatogonial stem cells. During this process, germ cells and somatic cells interact intricately to ensure long-term fertility and accurate genome propagation. Spermatogenesis has been intensely investigated in mammals but remains poorly understood with regard to teleosts. Here, we performed single-cell RNA sequencing of ~9500 testicular cells from the male, orange-spotted grouper. In the adult testis, we divided the cells into nine clusters and defined ten cell types, as compared with human testis data, including cell populations with characteristics of male germ cells and somatic cells, each of which expressed specific marker genes. We also identified and profiled the expression patterns of four marker genes (calr, eef1a, s100a1, vasa) in both the ovary and adult testis. Our data provide a blueprint of male germ cells and supporting somatic cells. Moreover, the cell markers are candidates that could be used for further cell identification.

scholarly journals Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

2021 ◽  
Author(s):  
Yixuan Qiu ◽  
Jiebiao Wang ◽  
Jing Lei ◽  
Kathryn Roeder
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
R Package ◽  
Supplementary Information ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Correlation Pattern ◽  
Tissue Samples ◽  
Bulk Data

Abstract Motivation Marker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. Results To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementation We implement this method as an R package markerpen, hosted on CRAN (https://CRAN.R-project.org/package=markerpen). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Revealing immune responses in the Mycobacterium avium subsp. paratuberculosis-infected THP-1 cells using single cell RNA-sequencing

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254194
Author(s):  
Hong-Tae Park ◽  
Woo Bin Park ◽  
Suji Kim ◽  
Jong-Sung Lim ◽  
Gyoungju Nah ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Single Cell ◽  
Mycobacterium Avium ◽  
Expression Patterns ◽  
Cell Types ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Cytokines And Chemokines

Mycobacterium avium subsp. paratuberculosis (MAP) is a causative agent of Johne’s disease, which is a chronic and debilitating disease in ruminants. MAP is also considered to be a possible cause of Crohn’s disease in humans. However, few studies have focused on the interactions between MAP and human macrophages to elucidate the pathogenesis of Crohn’s disease. We sought to determine the initial responses of human THP-1 cells against MAP infection using single-cell RNA-seq analysis. Clustering analysis showed that THP-1 cells were divided into seven different clusters in response to phorbol-12-myristate-13-acetate (PMA) treatment. The characteristics of each cluster were investigated by identifying cluster-specific marker genes. From the results, we found that classically differentiated cells express CD14, CD36, and TLR2, and that this cell type showed the most active responses against MAP infection. The responses included the expression of proinflammatory cytokines and chemokines such as CCL4, CCL3, IL1B, IL8, and CCL20. In addition, the Mreg cell type, a novel cell type differentiated from THP-1 cells, was discovered. Thus, it is suggested that different cell types arise even when the same cell line is treated under the same conditions. Overall, analyzing gene expression patterns via scRNA-seq classification allows a more detailed observation of the response to infection by each cell type.

scholarly journals Testes of DAZL null sheep lack spermatogonia and maintain normal somatic cells

2019 ◽  
Author(s):  
Zachariah McLean ◽  
Sarah Jane Appleby ◽  
Jingwei Wei ◽  
Russell Grant Snell ◽  
Björn Oback
Keyword(s):  
Germ Cell ◽  
Somatic Cell ◽  
Germ Cells ◽  
Genetic Improvement ◽  
Rna Binding ◽  
Somatic Cells ◽  
Marker Genes ◽  
Specific Marker ◽  
Loss Of Function ◽  
Fetal Fibroblasts

AbstractMultiplying the germline would increase the number of offspring that can be produced from selected animals, accelerating genetic improvement for livestock breeding. This could be achieved by producing multiple chimaeric animals, each carrying a mix of donor and host germ cells in their gonads. However, such chimaeric germlines would produce offspring from both donor and host genotypes, limiting the rate of genetic improvement. To resolve this problem and produce chimaeras with absolute donor germline transmission, we have disrupted the RNA-binding protein DAZL and generated germ cell-deficient host animals. Using Cas9 mediated homology-directed repair (HDR), we introduced a DAZL loss-of-function mutation in male ovine fetal fibroblasts. Following manual single-cell isolation, 4/48 (8.3%) of donor cell strains were homozygously HDR-edited. Sequence-validated strains were used as nuclear donors for somatic cell cloning to generate three lambs, which died at birth. All DAZL-null male neonatal sheep lacked germ cells. Somatic cells within their testes were morphologically intact and expressed normal levels of somatic cell-specific marker genes, indicating that the germ cell niche remained intact. This extends the DAZL-mutant phenotype beyond mice into agriculturally relevant ruminants, providing a pathway for using absolute transmitters in rapid livestock improvement.

scholarly journals Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

2020 ◽  
Author(s):  
Yixuan Qiu ◽  
Jiebiao Wang ◽  
Jing Lei ◽  
Kathryn Roeder
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
R Package ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Correlation Pattern ◽  
Tissue Samples ◽  
Bulk Data ◽  
Tissue Marker

AbstractMotivationMarker genes, defined as genes that are expressed primarily in a single cell type, can be identified from the single cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern.ResultsTo capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list.Availability and implementationWe implement this method as an R package markerpen, hosted on https://github.com/yixuan/[email protected]

scholarly journals Transcriptome profiling of laser-captured germ cells and functional characterization of zbtb40 during MT-induced spermatogenesis in orange-spotted grouper (Epinephelus coioides)

2019 ◽  
Author(s):  
Xiaochun Liu ◽  
Xi Wu ◽  
Yang Yang ◽  
Chaoyue Zhong ◽  
Yin Guo ◽  
...  
Keyword(s):  
Germ Cells ◽  
Cellular Localization ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Functional Characterization ◽  
Transcriptome Profiling ◽  
Sex Reversal ◽  
Epinephelus Coioides ◽  
Isolated Cells ◽  
Male Germ Cells

Abstract Background: Spermatogenesis is an intricate process regulated by a finely organized network. The orange-spotted grouper (Epinephelus coioides) is a protogynous hermaphroditic fish, but the process of its spermatogenesis is not well-understood. In the present study, transcriptome sequencing of the male germ cells from orange-spotted grouper was performed to explore the molecular mechanisms underlying spermatogenesis. Results: In this study, the orange-spotted grouper was induced to change sex from female to male by 17alpha-methyltestosterone implantation. During the artificial spermatogenesis, different cell types from cysts containing spermatogonia, spermatocytes, spermatids, and spermatozoa were isolated by laser capture microdissection. Subsequently, transcriptomic analysis for the isolated cells were performed. A series of genes was used to verify and investigate the expression patterns in spermatogenesis. Furthermore, we also analyzed the expression of the same set of genes involved with steroid metabolism and sex throughout spermatogenesis (early-mid, late, and maturing stages) in the orange-spotted grouper. Several generally female-related genes took significantly changes in sex reversal hinted that the female-related genes in previously recognized may also play vital roles in spermatogenesis and sex reversal. In the transcriptomic data, we focused on zbtb family genes, which may be related to the process of spermatogenesis. Their expression patterns and cellular localization were examined, and the location of Eczbtb40 in different gonadal stages was investigated. We found that Eczbtb40 was expressed throughout spermatogenesis. These preliminary findings suggest that Eczbtb40 is highly conserved during vertebrate evolution and plays roles in spermatogenesis. Besides, the expression of Eczbtb40 and Eccyp17a1a overlapped in male germ cells, especially spermatogonium and spermatocyte, which suggested that Eczbtb40 might interact with Eccyp17a1a participant in spermatogenesis and sex reversal. Conclusions: The present study first depicted RNA sequencing of the male germ cells from orange-spotted grouper, and identified many important functional genes and pathways involved in spermatogenesis. The Eczbtb40 gene was subjected to molecular characterization and expression pattern analysis. These results will contribute to future studies of the molecular mechanism of spermatogenesis and sex reversal.

scholarly journals scClustViz – Single-cell RNAseq cluster assessment and visualization

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1522 ◽  
Author(s):  
Brendan T. Innes ◽  
Gary D. Bader
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Clustering Algorithms ◽  
Expression Patterns ◽  
Software Tool ◽  
Cell Types ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Single Experiment

Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is particularly valuable for characterization of tissue heterogeneity because it can be used to identify and classify all cell types in a tissue. This is generally done by clustering the data, based on the assumption that cells of a particular type share similar transcriptomes, distinct from other cell types in the tissue. However, nearly all clustering algorithms have tunable parameters which affect the number of clusters they will identify in data. The R Shiny software tool described here, scClustViz, provides a simple interactive graphical user interface for exploring scRNAseq data and assessing the biological relevance of clustering results. Given that cell types are expected to have distinct gene expression patterns, scClustViz uses differential gene expression between clusters as a metric for assessing the fit of a clustering result to the data at multiple cluster resolution levels. This helps select a clustering parameter for further analysis. scClustViz also provides interactive visualisation of: cluster-specific distributions of technical factors, such as predicted cell cycle stage and other metadata; cluster-wise gene expression statistics to simplify annotation of cell types and identification of cell type specific marker genes; and gene expression distributions over all cells and cell types. scClustViz provides an interactive interface for visualisation, assessment, and biological interpretation of cell-type classifications in scRNAseq experiments that can be easily added to existing analysis pipelines, enabling customization by bioinformaticians while enabling biologists to explore their results without the need for computational expertise. It is available at https://baderlab.github.io/scClustViz/.

scholarly journals Transcriptome profiling of laser-captured germ cells and functional characterization of zbtb40 during MT-induced spermatogenesis in orange-spotted grouper (Epinephelus coioides)

2019 ◽  
Author(s):  
Xiaochun Liu ◽  
Xi Wu ◽  
Yang Yang ◽  
Chaoyue Zhong ◽  
Yin Guo ◽  
...  
Keyword(s):  
Germ Cells ◽  
Cellular Localization ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Functional Characterization ◽  
Transcriptome Profiling ◽  
Sex Reversal ◽  
Epinephelus Coioides ◽  
Isolated Cells ◽  
Male Germ Cells

Abstract Background: Spermatogenesis is an intricate process regulated by a finely organized network. The orange-spotted grouper (Epinephelus coioides) is a protogynous hermaphroditic fish, but the process of its spermatogenesis is not well-understood. In the present study, transcriptome sequencing of the male germ cells from orange-spotted grouper was performed to explore the molecular mechanisms underlying spermatogenesis. Results: In this study, the orange-spotted grouper was induced to change sex from female to male by 17alpha-methyltestosterone implantation. During the artificial spermatogenesis, different cell types from cysts containing spermatogonia, spermatocytes, spermatids, and spermatozoa were isolated by laser capture microdissection. Subsequently, transcriptomic analysis for the isolated cells were performed. A series of genes was used to verify and investigate the expression patterns in spermatogenesis. Furthermore, we also analyzed the expression of the same set of genes involved with steroid metabolism and sex throughout spermatogenesis (early-mid, late, and maturing stages) in the orange-spotted grouper. Several generally female-related genes took significantly changes in sex reversal hinted that the female-related genes in previously recognized may also play vital roles in spermatogenesis and sex reversal. In the transcriptomic data, we focused on zbtb family genes, which may be related to the process of spermatogenesis. Their expression patterns and cellular localization were examined, and the location of Eczbtb40 in different gonadal stages was investigated. We found that Eczbtb40 was expressed throughout spermatogenesis. These preliminary findings suggest that Eczbtb40 is highly conserved during vertebrate evolution and plays roles in spermatogenesis. Besides, the expression of Eczbtb40 and Eccyp17a1a overlapped in male germ cells, especially spermatogonium and spermatocyte, which suggested that Eczbtb40 might interact with Eccyp17a1a participant in spermatogenesis and sex reversal. Conclusions: The present study first depicted RNA sequencing of the male germ cells from orange-spotted grouper, and identified many important functional genes and pathways involved in spermatogenesis. The Eczbtb40 gene was subjected to molecular characterization and expression pattern analysis. These results will contribute to future studies of the molecular mechanism of spermatogenesis and sex reversal.

scholarly journals Celda: A Bayesian model to perform bi-clustering of genes into modules and cells into subpopulations using single-cell RNA-seq data

2020 ◽  
Author(s):  
Zhe Wang ◽  
Shiyi Yang ◽  
Yusuke Koga ◽  
Sean E. Corbett ◽  
Evan Johnson ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Cell Population ◽  
Latent Dirichlet Allocation ◽  
Expression Patterns ◽  
Building Blocks ◽  
Marker Genes ◽  
Specific Marker ◽  
Rna Seq ◽  
Biological Functions

1AbstractComplex biological systems can be understood by dividing them into hierarchies. Each level of such a hierarchy is composed of different subunits which cooperate to perform distinct biological functions. Single-cell RNA-seq (scRNA-seq) has emerged as a powerful technique to quantify gene expression in individual cells and is being used to elucidate the molecular and cellular building blocks of complex tissues. We developed a novel Bayesian hierarchical model called Cellular Latent Dirichlet Allocation (Celda) to perform bi-clustering of co-expressed genes into modules and cells into subpopulations. This model can also quantify the relationship between different levels in a biological hierarchy by determining the contribution of each gene in each module, each module in each cell population, and each cell population in each sample. We used Celda to identify transcriptional modules and cell subpopulations in publicly-available peripheral blood mononuclear cell (PBMC) dataset. In addition to the major classes of cell types, Celda also identified a population of proliferating T-cells and a single plasma cell that was missed by other clustering methods in this dataset. Transcriptional modules captured consistency in expression patterns among genes linked to same biological functions. Furthermore, transcriptional modules provided direct insights on cell type specific marker genes, and helped understanding of subtypes of B- and T-cells. Overall, Celda presents a novel principled approach towards characterizing transcriptional programs and cellular and heterogeneity in single-cell data.

scholarly journals scClustViz – Single-cell RNAseq cluster assessment and visualization

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1522 ◽  
Author(s):  
Brendan T. Innes ◽  
Gary D. Bader
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Clustering Algorithms ◽  
Expression Patterns ◽  
Software Tool ◽  
Cell Types ◽  
Marker Genes ◽  
Specific Marker ◽  
Cell Type ◽  
Single Experiment

Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is particularly valuable for characterization of tissue heterogeneity because it can be used to identify and classify all cell types in a tissue. This is generally done by clustering the data, based on the assumption that cells of a particular type share similar transcriptomes, distinct from other cell types in the tissue. However, nearly all clustering algorithms have tunable parameters which affect the number of clusters they will identify in data. The R Shiny software tool described here, scClustViz, provides a simple interactive graphical user interface for exploring scRNAseq data and assessing the biological relevance of clustering results. Given that cell types are expected to have distinct gene expression patterns, scClustViz uses differential gene expression between clusters as a metric for assessing the fit of a clustering result to the data at multiple cluster resolution levels. This helps select a clustering parameter for further analysis. scClustViz also provides interactive visualisation of: cluster-specific distributions of technical factors, such as predicted cell cycle stage and other metadata; cluster-wise gene expression statistics to simplify annotation of cell types and identification of cell type specific marker genes; and gene expression distributions over all cells and cell types. scClustViz provides an interactive interface for visualisation, assessment, and biological interpretation of cell-type classifications in scRNAseq experiments that can be easily added to existing analysis pipelines, enabling customization by bioinformaticians while enabling biologists to explore their results without the need for computational expertise. It is available at https://baderlab.github.io/scClustViz/.

scholarly journals Transcriptome profiling of laser-captured germ cells and functional characterization of zbtb40 during 17alpha-methyltestosterone-induced spermatogenesis in orange-spotted grouper (Epinephelus coioides)

2019 ◽  
Author(s):  
Xi Wu ◽  
Yang Yang ◽  
Chaoyue Zhong ◽  
Yin Guo ◽  
Shuisheng Li ◽  
...  
Keyword(s):  
Molecular Mechanism ◽  
Germ Cells ◽  
Cellular Localization ◽  
Expression Patterns ◽  
Functional Characterization ◽  
Cdna Libraries ◽  
Epinephelus Coioides ◽  
Rna Seq ◽  
Hormone Metabolism ◽  
Male Germ Cells

Abstract Background: Spermatogenesis is an intricate process regulated by a finely organized network. The orange-spotted grouper (Epinephelus coioides) is a protogynous hermaphroditic fish, but the regulatory mechanism of its spermatogenesis is not well-understood. In the present study, transcriptome sequencing of the male germ cells isolated from orange-spotted grouper was performed to explore the molecular mechanism underlying spermatogenesis. Results: In this study, the orange-spotted grouper was induced to change sex from female to male by 17alpha-methyltestosterone (MT) implantation. During the spermatogenesis, male germ cells (spermatogonia, spermatocytes, spermatids, and spermatozoa) were isolated by laser capture microdissection. Transcriptomic analysis for the isolated cells was performed. A total of 244,984,338 clean reads were generated from four cDNA libraries. Real-time PCR results of 13 genes related to sex differentiation and hormone metabolism indicated that transcriptome data are reliable. RNA-seq data showed that the female-related genes and genes involved in hormone metabolism were highly expressed in spermatogonia and spermatozoa, suggesting that these genes participate in the spermatogenesis. Interestingly, the expression of zbtb family genes showed significantly changes in the RNA-seq data, and their expression patterns were further examined during spermatogenesis. The analysis of cellular localization of Eczbtb40 and the co-localization of Eczbtb40 and Eccyp17a1 in different gonadal stages suggested that Eczbtb40 might interact with Eccyp17a1 during spermatogenesis. Conclusions: For the first time, our study investigated the transcriptome of the male germ cells from orange-spotted grouper, and identified functional genes, GO terms, and KEGG pathways involved in spermatogenesis. Furthermore, Eczbtb40 was first characterized and predicted the role during spermatogenesis. These data will contribute to future studies on the molecular mechanism of spermatogenesis in teleosts.

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