Transcriptomic profiling maps anatomically patterned subpopulations among single embryonic cardiac cells
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE89468 | GEO | 2016/11/10
SECONDARY ACCESSION(S): PRJNA352266
REPOSITORIES: GEO
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Project description:Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1,166 single murine heart cells at embryonic day 8.5 (e8.5), e9.5, and e10.5, respectively. We segregated these cells by type using unsupervised bioinformatics analysis and identified chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0% ± 3.2% and 91.2% ± 2.8% accuracy, respectively (99.4% ± 1.0% and 99.1% ± 1.1% if a ±1 zone margin is permitted) and predicted the second heart field distribution of Isl-1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.
| S-EPMC5130110 | biostudies-literature
Project description:Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1166 single murine heart cells at embryonic days (e)8.5, 9.5, and 10.5, respectively. We segregated these cells by type using unsupervised bioinformatic analysis and identified novel chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0+/-3.2% and 91.2+/-2.8% accuracy respectively (99.4+/-1.0% and 99.1+/-1.1% if a +/-1 zone margin is permitted) and predicted the second heart field distribution of Isl1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.
2016-11-10 | GSE89465 | GEO
Project description:Embryonic gene expression intricately reflects anatomical context, developmental stage, and cell type. To address whether the precise spatial origins of cardiac cells can be deduced solely from their transcriptional profiles, we established a genome-wide expression database from 118, 949, and 1166 single murine heart cells at embryonic days (e)8.5, 9.5, and 10.5, respectively. We segregated these cells by type using unsupervised bioinformatic analysis and identified novel chamber-specific genes. Using a random forest algorithm, we reconstructed the spatial origin of single e9.5 and e10.5 cardiomyocytes with 92.0+/-3.2% and 91.2+/-2.8% accuracy respectively (99.4+/-1.0% and 99.1+/-1.1% if a +/-1 zone margin is permitted) and predicted the second heart field distribution of Isl1-lineage descendants. When applied to Nkx2-5-/- cardiomyocytes from murine e9.5 hearts, we showed their transcriptional alteration and lack of ventricular phenotype. Our database and zone classification algorithm will enable the discovery of novel mechanisms in early cardiac development and disease.
2016-11-10 | GSE76118 | GEO
Project description:Transcriptomic profiling maps anatomically patterned subpopulations among single embryonic cardiac cells
| PRJNA352266 | ENA
Project description:RationaleThe cardiac conduction system (CCS) consists of distinct components including the sinoatrial node, atrioventricular node, His bundle, bundle branches, and Purkinje fibers. Despite an essential role for the CCS in heart development and function, the CCS has remained challenging to interrogate because of inherent obstacles including small cell numbers, large cell-type heterogeneity, complex anatomy, and difficulty in isolation. Single-cell RNA-sequencing allows for genome-wide analysis of gene expression at single-cell resolution.ObjectiveAssess the transcriptional landscape of the entire CCS at single-cell resolution by single-cell RNA-sequencing within the developing mouse heart.Methods and resultsWild-type, embryonic day 16.5 mouse hearts (n=6 per zone) were harvested and 3 zones of microdissection were isolated, including: Zone I-sinoatrial node region; Zone II-atrioventricular node/His region; and Zone III-bundle branch/Purkinje fiber region. Tissue was digested into single-cell suspensions, cells isolated, mRNA reverse transcribed, and barcoded before high-throughput sequencing and bioinformatics analyses. Single-cell RNA-sequencing was performed on over 22 000 cells, and all major cell types of the murine heart were successfully captured including bona fide clusters of cells consistent with each major component of the CCS. Unsupervised weighted gene coexpression network analysis led to the discovery of a host of novel CCS genes, a subset of which were validated using fluorescent in situ hybridization as well as whole-mount immunolabeling with volume imaging (iDISCO+) in 3 dimensions on intact mouse hearts. Further, subcluster analysis unveiled isolation of distinct CCS cell subtypes, including the clinically relevant but poorly characterized transitional cells that bridge the CCS and surrounding myocardium.ConclusionsOur study represents the first comprehensive assessment of the transcriptional profiles from the entire CCS at single-cell resolution and provides a characterization in the context of development and disease.
| S-EPMC6675655 | biostudies-literature
Project description:Human cardiac-derived c-kit+ stromal cells (CSCs) have demonstrated efficacy in preclinical trials for the treatment of heart failure and myocardial dysfunction. Unfortunately, large variability in patient outcomes and cell populations remains a problem. Previous research has demonstrated that the reparative capacity of CSCs may be linked to the age of the cells: CSCs derived from neonate patients increase cardiac function and reduce fibrosis. However, age-dependent differences between CSC populations have primarily been explored with bulk sequencing methods. In this work, we hypothesized that differences in CSC populations and subsequent cell therapy outcomes may arise from differing cell subtypes within donor CSC samples. We performed single-cell RNA sequencing on four neonatal CSC (nCSC) and five child CSC (cCSC) samples. Subcluster analysis revealed cCSC-enriched clusters upregulated in several fibrosis- and immune response-related genes. Module-based analysis identified upregulation of chemotaxis and ribosomal activity-related genes in nCSCs and upregulation of immune response and fiber synthesis genes in cCSCs. Further, we identified versican and integrin alpha 2 as potential markers for a fibrotic cell subtype. By investigating differences in patient-derived CSC populations at the single-cell level, this research aims to identify and characterize CSC subtypes to better optimize CSC-based therapy and improve patient outcomes.
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Project description:Introduction: The adaptive immune response mediated by T cells plays a vital role in the initiation and maintenance of blood pressure (BP) elevation. Memory T cells, which are antigen-specific T cells, can respond specifically to repeated hypertensive stimuli. Although the roles of memory T cells in animal models are well studied, their maintenance and functions in hypertensive patients are poorly understood. Method: Here, we focused on the circulating memory T cells of hypertensive patients. By using single-cell RNA sequencing technology, subsets of memory T cells were identified. Differentially expressed genes (DEGs) and functional pathways were explored for related biological functions in each population of memory T cells. Result and Discussion: Our study identified four subsets of memory T cells in the blood of hypertensive patients, with CD8 effector memory T (TEM) cells accounting for more cells and demonstrating more biological functions than CD4 TEM cells. CD8 TEM cells were further analyzed using single-cell RNA sequencing technology, and subpopulation 1 was demonstrated to contribute to BP elevation. The key marker genes CKS2, PLIN2, and CNBP were identified and validated by mass-spectrum flow cytometry. Our data suggest that CD8 TEM cells as well as the marker genes could be preventive targets for patients with hypertensive cardiovascular disease.
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Project description:Inflammatory response heterogeneity has impeded high-resolution dissection of diverse immune cell populations during activation. We characterize mouse cutaneous immune cells by single-cell RNA sequencing, after inducing inflammation using imiquimod and oxazolone dermatitis models. We identify 13 CD45+ subpopulations, which broadly represent most functionally characterized immune cell types. Oxazolone pervasively upregulates Jak2/Stat3 expression across T cells and antigen-presenting cells (APCs). Oxazolone also induces Il4/Il13 expression in newly infiltrating basophils, and Il4ra and Ccl24, most prominently in APCs. In contrast, imiquimod broadly upregulates Il17/Il22 and Ccl4/Ccl5. A comparative analysis of single-cell inflammatory transcriptional responses reveals that APC response to oxazolone is tightly restricted by cell identity, whereas imiquimod enforces shared programs on multiple APC populations in parallel. These global molecular patterns not only contrast immune responses on a systems level but also suggest that the mechanisms of new sources of inflammation can eventually be deduced by comparison to known signatures.
| S-EPMC7648132 | biostudies-literature
Project description:The heterogeneity of the developing pancreatic epithelium and low abundance of endocrine progenitors limit the information derived from traditional expression studies. To identify genes that characterize early developmental tissues composed of multiple progenitor lineages, we applied single-cell RNA-Seq to embryonic day (e)13.5 mouse pancreata and performed integrative analysis with single cell data from mature pancreas. We identified subpopulations expressing macrophage or endothelial markers and new pancreatic progenitor markers. We also identified potential α-cell precursors expressing glucagon (Gcg) among the e13.5 pancreatic cells. Despite their high Gcg expression levels, these cells shared greater transcriptomic similarity with other e13.5 cells than with adult α-cells, indicating their immaturity. Comparative analysis identified the sodium-dependent neutral amino acid transporter, Slc38a5, as a characteristic gene expressed in α-cell precursors but not mature cells. By immunofluorescence analysis, we observed SLC38A5 expression in pancreatic progenitors, including in a subset of NEUROG3+ endocrine progenitors and MAFB+ cells and in all GCG+ cells. Expression declined in α-cells during late gestation and was absent in the adult islet. Our results suggest SLC38A5 as an early marker of α-cell lineage commitment.
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Project description:Recently developed single-cell RNA sequencing methods allow the simultaneous profiling of the transcriptomes of thousands of individual cells. However, current methods still require advanced equipment or entail substantial waste of reagents. Here, we introduce magnetic bead-assisted parallel single-cell gene expression sequencing (MAPS-seq), a microwell-based method that pools samples before the reverse transcription step, increasing the ease of sample preparation and reducing reagent waste. Moreover, because this method uses universal reagents and standard molecular biology lab instruments, it is easy to implement, even in labs that have not previously conducted single-cell RNA sequencing. We validated our method by demonstrating that it can generate gene expression data at the single-cell level. We then applied the MAPS-seq method to analyze 237 human myelogenous leukemia cells treated with one of three different drugs or dimethyl sulfoxide. We observed transcriptional changes and identified marker genes that indicate a drug response. Furthermore, the MAPS-seq method produced data of comparable quality to those of existing single-cell RNA sequencing methods. Consequently, we expect that our method will provide researchers with a more accessible, less wasteful, and less burdensome method for investigating the transcriptomes of individual cells.
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