scholarly journals Stromal Heterogeneity in the Human Proliferative Endometrium—A Single-Cell RNA Sequencing Study

2021 ◽  
Vol 11 (6) ◽  
pp. 448
Author(s):  
Suzanna Queckbörner ◽  
Carolina von Grothusen ◽  
Nageswara Rao Boggavarapu ◽  
Roy Mathew Francis ◽  
Lindsay C. Davies ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Bioinformatic Analysis ◽  
Matrix Composition ◽  
Cellular Interactions ◽  
Novel Therapy ◽  
Single Cell Rna Sequencing ◽  
Endometrial Regeneration

The endometrium undergoes regular regeneration and stromal proliferation as part of the normal menstrual cycle. To better understand cellular interactions driving the mechanisms in endometrial regeneration we employed single-cell RNA sequencing. Endometrial biopsies were obtained during the proliferative phase of the menstrual cycle from healthy fertile women and processed to single-cell suspensions which were submitted for sequencing. In addition to known endometrial cell types, bioinformatic analysis revealed multiple stromal populations suggestive of specific stromal niches with the ability to control inflammation and extracellular matrix composition. Ten different stromal cells and two pericyte subsets were identified. Applying different R packages (Seurat, SingleR, Velocyto) we established cell cluster diversity and cell lineage/trajectory, while using external data to validate our findings. By understanding healthy regeneration in the described stromal compartments, we aim to identify points of further investigation and possible targets for novel therapy development for benign gynecological disorders affecting endometrial regeneration and proliferation such as endometriosis and Asherman’s syndrome.

scholarly journals Stromal Heterogeneity in the Proliferative Endometrial Functionalis - A single-cell approach

2020 ◽  
Author(s):  
Suzanna Queckbörner ◽  
Carolina von Grothusen ◽  
Nageswara Boggavarapu ◽  
Lindsay C. Davies ◽  
Kristina Gemzell-Danielsson
Keyword(s):  
Menstrual Cycle ◽  
Single Cell ◽  
Cell Lineage ◽  
Matrix Composition ◽  
Cellular Interactions ◽  
Novel Therapy ◽  
Stromal Compartment ◽  
External Data ◽  
Normal Menstrual Cycle ◽  
Endometrial Regeneration

AbstractThe endometrium undergoes regular regeneration and stromal proliferation as part of the normal menstrual cycle. To better understand cellular interactions driving the mechanisms in endometrial regeneration we employed single-cell RNA sequencing. Endometrial samples were obtained during the proliferative phase of the menstrual cycle from healthy women aged 24–32 years. Within the stromal compartment multiple stromal populations were found, suggestive of specific stromal niches that control inflammation and extracellular matrix composition. Ten different stromal cell and two pericyte subsets were identified. Applying different R packages (Seurat, SingleR, Velocyto) we determined cell cluster diversity and cell lineage/trajectory while using external data to validate our findings. By understanding healthy regeneration in the described stromal compartments, we aim to identify points of intervention for novel therapy development in order to treat benign gynaecological disorders affecting endometrial regeneration and proliferation e.g. endometriosis and Asherman’s syndrome.

Using single-cell RNA sequencing to unravel cell lineage relationships in the respiratory tract

2020 ◽  
Vol 48 (1) ◽  
pp. 327-336 ◽  
Author(s):  
L.E. Zaragosi ◽  
M. Deprez ◽  
P. Barbry
Keyword(s):  
Respiratory Tract ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Neuroendocrine Cells ◽  
Basal Cells ◽  
Multiciliated Cells ◽  
Single Cell Rna Sequencing ◽  
Rare Cells ◽  
Genetic Labeling

The respiratory tract is lined by a pseudo-stratified epithelium from the nose to terminal bronchioles. This first line of defense of the lung against external stress includes five main cell types: basal, suprabasal, club, goblet and multiciliated cells, as well as rare cells such as ionocytes, neuroendocrine and tuft/brush cells. At homeostasis, this epithelium self-renews at low rate but is able of fast regeneration upon damage. Airway epithelial cell lineages during regeneration have been investigated in the mouse by genetic labeling, mainly after injuring the epithelium with noxious agents. From these approaches, basal cells have been identified as progenitors of club, goblet and multiciliated cells, but also of ionocytes and neuroendocrine cells. Single-cell RNA sequencing, coupled to lineage inference algorithms, has independently allowed the establishment of comprehensive pictures of cell lineage relationships in both mouse and human. In line with genetic tracing experiments in mouse trachea, studies using single-cell RNA sequencing (RNAseq) have shown that basal cells first differentiate into club cells, which in turn mature into goblet cells or differentiate into multiciliated cells. In the human airway epithelium, single-cell RNAseq has identified novel intermediate populations such as deuterosomal cells, ‘hybrid’ mucous-multiciliated cells and progenitors of rare cells. Novel differentiation dynamics, such as a transition from goblet to multiciliated cells have also been discovered. The future of cell lineage relationships in the respiratory tract now resides in the combination of genetic labeling approaches with single-cell RNAseq to establish, in a definitive manner, the hallmarks of cellular lineages in normal and pathological situations.

scholarly journals Bayesian gamma-negative binomial modeling of single-cell RNA sequencing data

BMC Genomics ◽  
2020 ◽  
Vol 21 (S9) ◽  
Author(s):  
Siamak Zamani Dadaneh ◽  
Paul de Figueiredo ◽  
Sing-Hoi Sze ◽  
Mingyuan Zhou ◽  
Xiaoning Qian
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Data Augmentation ◽  
Negative Binomial ◽  
Cell Lineage ◽  
Simulated Data ◽  
Molecular Heterogeneity ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Zero Counts

Abstract Background Single-cell RNA sequencing (scRNA-seq) is a powerful profiling technique at the single-cell resolution. Appropriate analysis of scRNA-seq data can characterize molecular heterogeneity and shed light into the underlying cellular process to better understand development and disease mechanisms. The unique analytic challenge is to appropriately model highly over-dispersed scRNA-seq count data with prevalent dropouts (zero counts), making zero-inflated dimensionality reduction techniques popular for scRNA-seq data analyses. Employing zero-inflated distributions, however, may place extra emphasis on zero counts, leading to potential bias when identifying the latent structure of the data. Results In this paper, we propose a fully generative hierarchical gamma-negative binomial (hGNB) model of scRNA-seq data, obviating the need for explicitly modeling zero inflation. At the same time, hGNB can naturally account for covariate effects at both the gene and cell levels to identify complex latent representations of scRNA-seq data, without the need for commonly adopted pre-processing steps such as normalization. Efficient Bayesian model inference is derived by exploiting conditional conjugacy via novel data augmentation techniques. Conclusion Experimental results on both simulated data and several real-world scRNA-seq datasets suggest that hGNB is a powerful tool for cell cluster discovery as well as cell lineage inference.

scholarly journals Single Cell RNA Sequencing of Blood Outgrowth Endothelial Cells from Patients with Low Von Willebrand Factor Reveal Multiple Novel Signaling Pathways

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 982-982
Author(s):  
Christopher J. Ng ◽  
Alice Liu ◽  
Katrina J. Ashworth ◽  
Kenneth L. Jones ◽  
Jorge Di Paola
Keyword(s):  
Endothelial Cells ◽  
Single Cell ◽  
Signaling Pathways ◽  
Rna Sequencing ◽  
Cell Lines ◽  
Mixed Model ◽  
Transcriptional Profiling ◽  
Bioinformatic Analysis ◽  
Single Cell Rna Sequencing ◽  
Age Range

Abstract Background The mechanisms that determine low VWF levels in patients with VWF levels between 30-50 IU/dL and no mutations in VWF are poorly understood. Hypothesis/Objective We hypothesize that the study of blood outgrowth endothelial cells (BOECs) from individuals with low VWF levels may reveal unique transcriptional profiles that contribute to the low VWF levels seen in these patients. Methods BOEC Derivation: Patients with low VWF levels and mucocutaneous bleeding (MCB) (30-50 IU/dL) were enrolled in an IRB-approved study. The mononuclear layer from whole blood was isolated and plated onto collagen coated plates. After extended incubation, BOECs were validated by visual inspection and flow cytometry. Endothelial Transcriptional Characterization: A total of 9 cells lines including those from individuals with low VWF and HUVEC and BOECs from individuals with normal VWF levels as control were assayed via single cell RNA sequencing. Bioinformatic analysis included generalized transcriptional expression, Ingenuity Pathway Analysis (IPA), and expression of VWF. RNA-sequencing expression data was filtered according to a standardized algorithm. Cells that were defined as monocytes (TYROBP expression > 2 copies) were excluded. Following monocyte exclusions, cells were determined to be of endothelial origin if they demonstrated the presence of transcripts of PECAM1, CDH5, ROBO4, ESAM, TIE1, or NOTCH4 as previously described by Butler et al. (Cell Reports 2016). Results BOEC Derivation: A total of eight BOEC lines were generated, 6 from individuals with MCB and VWF levels between 30-50 IU/dL (5:1 female: male ratio, age range 11-54 years) and 2 from healthy controls (2 female, age range 22-39 years) with normal VWF levels and no symptoms of MCB. Transcriptional Profiling of single endothelial cells from Low VWF Individuals: A 3D T-SNE plot that assesses unbiased differences in gene expression profiling was generated with each cell line represented by a different color (Figure 1A) demonstrating that individual cell lines have significant differences in their underlying transcriptional profiling. VWF Expression in Low VWF Samples: Overall expression of VWF was significantly decreased in low VWF BOEC samples (5.341 transcripts/cell) vs. control (9.076 transcripts/cell) ECs (figure 1B), P<0.0001. Further, histogram and mixed model (multiple gaussian) analysis of VWF expression revealed changes in generalized expression of VWF in Low VWF BOECs compatible with multiple populations of VWF-expressing BOECs, demonstrating cell mosaicism within each sample. IPA Analysis of Low VWF vs Control BOECs: IPA analysis demonstrated 64 pathways with a z-score difference >1 in Low VWF BOECs when compared to control BOECs (table 1), including multiple signaling pathways such as PI3kinase and AKT as well as several cytoskeleton pathways. Conclusions Single cell RNA sequencing of Low VWF BOECs reveal significant differences in transcriptional profiling when compared to control endothelial cell lines (control BOECs + HUVEC). BOECs from individuals with Low VWF levels demonstrate significantly lower VWF transcript expression than the control endothelial cells. Interestingly, BOECs from low VWF patients show significant differences in VWF transcript number within cells from the same individual demonstrating a degree of mosaicism previously described in murine endothelial cells. Finally, there are multiple cellular pathways that are differentially regulated in Low VWF BOECs as compared to control endothelial cells. Disclosures Ng: CSL Behring: Consultancy; Shire: Consultancy.

scholarly journals Deciphering cell lineage specification during male sex determination with single-cell RNA sequencing

2017 ◽  
Author(s):  
Isabelle Stévant ◽  
Yasmine Neirjinck ◽  
Christelle Borel ◽  
Jessica Escoffier ◽  
Lee B. Smith ◽  
...  
Keyword(s):  
Sex Determination ◽  
Single Cell ◽  
Progenitor Cells ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Time Course ◽  
Cell Lineage ◽  
Lineage Specification ◽  
Cell Fate Decisions ◽  
Single Cell Rna Sequencing

SummaryThe gonad is a unique biological system for studying cell fate decisions. However, major questions remain regarding the identity of somatic progenitor cells and the transcriptional events driving cell differentiation. Using time course single cell RNA sequencing on XY mouse gonads during sex determination, we identified a single population of somatic progenitor cells prior sex determination. A subset of these progenitors differentiate into Sertoli cells, a process characterized by a highly dynamic genetic program consisting of sequential waves of gene expression. Another subset of multipotent cells maintains their progenitor state but undergo significant transcriptional changes that restrict their competence towards a steroidogenic fate required for the differentiation of fetal Leydig cells. These results question the dogma of the existence of two distinct somatic cell lineages at the onset of sex determination and propose a new model of lineage specification from a unique progenitor cell population.

scholarly journals Deciphering Cell Lineage Specification during Male Sex Determination with Single-Cell RNA Sequencing

Cell Reports ◽  
2018 ◽  
Vol 22 (6) ◽  
pp. 1589-1599 ◽  
Author(s):  
Isabelle Stévant ◽  
Yasmine Neirijnck ◽  
Christelle Borel ◽  
Jessica Escoffier ◽  
Lee B. Smith ◽  
...  
Keyword(s):  
Sex Determination ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Lineage ◽  
Lineage Specification ◽  
Single Cell Rna Sequencing ◽  
Male Sex

Using Single-Cell and Spatial Transcriptomes to Understand Stem Cell Lineage Specification During Early Embryo Development

2020 ◽  
Vol 21 (1) ◽  
pp. 163-181
Author(s):  
Guangdun Peng ◽  
Guizhong Cui ◽  
Jincan Ke ◽  
Naihe Jing
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cell Lineage ◽  
Stem Cell Differentiation ◽  
Early Embryo ◽  
Stem Cell Lineage ◽  
Single Cell Rna Sequencing ◽  
Cell Organization

Embryonic development and stem cell differentiation provide a paradigm to understand the molecular regulation of coordinated cell fate determination and the architecture of tissue patterning. Emerging technologies such as single-cell RNA sequencing and spatial transcriptomics are opening new avenues to dissect cell organization, the divergence of morphological and molecular properties, and lineage allocation. Rapid advances in experimental and computational tools have enabled researchers to make many discoveries and revisit old hypotheses. In this review, we describe the use of single-cell RNA sequencing in studies of molecular trajectories and gene regulation networks for stem cell lineages, while highlighting the integratedexperimental and computational analysis of single-cell and spatial transcriptomes in the molecular annotation of tissue lineages and development during postimplantation gastrulation.

scholarly journals Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Madhav Mantri ◽  
Gaetano J. Scuderi ◽  
Roozbeh Abedini-Nassab ◽  
Michael F. Z. Wang ◽  
David McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Differentiation ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cellular Interactions ◽  
Chicken Heart ◽  
Spatially Resolved ◽  
Expression Of Genes ◽  
Single Cell Rna Sequencing

AbstractSingle-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions in cardiac lineages defines transcriptional differences between epithelial and mesenchymal cells within the epicardial lineage. Using spatially resolved expression analysis, we identify anatomically restricted expression programs, including expression of genes implicated in congenital heart disease. Last, we discover a persistent enrichment of the small, secreted peptide, thymosin beta-4, throughout coronary vascular development. Overall, our study identifies an intricate interplay between cellular differentiation and morphogenesis.

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