Similar Datasets
Project description:Here we use single nuclei RNA sequencing (snRNA-seq) of replacement teeth and adjacent oral lamina in Lake Malawi cichlids, species with lifelong whole-tooth replacement, to make two main discoveries. First, despite hundreds of millions of years of evolution, we demonstrate conservation of cell type gene expression across vertebrate teeth (fish, mouse, human). Second, we used an approach that combines marker gene expression and developmental potential of dental cells to uncover the transcriptional signature of stem-like cells in regenerating teeth. Our work underscores the importance of a comparative framework in the study of vertebrate oral and regenerative biology.
2022-02-08 | GSE193286 | GEO
Project description:Here we use single nuclei RNA sequencing (snRNA-seq) of replacement teeth and adjacent oral lamina in Lake Malawi cichlids, species with lifelong whole-tooth replacement, to make two main discoveries. First, despite hundreds of millions of years of evolution, we demonstrate conservation of cell type gene expression across vertebrate teeth (fish, mouse, human). Second, we used an approach that combines marker gene expression and developmental potential of dental cells to uncover the transcriptional signature of stem-like cells in regenerating teeth. Our work underscores the importance of a comparative framework in the study of vertebrate oral and regenerative biology.
2022-02-08 | GSE193285 | GEO
Project description:Single cell RNA sequencing reveals deep homology of dental cell types across vertebrates
| PRJNA795669 | ENA
Project description:Single cell RNA sequencing reveals deep homology of dental cell types across vertebrates [TJ]
| PRJNA795670 | ENA
Project description:Single cell RNA sequencing reveals deep homology of dental cell types across vertebrates [JPOOL]
| PRJNA795671 | ENA
Project description:Dental epithelial stem cells give rise to four types of dental epithelial cells: inner enamel epithelium (IEE), outer enamel epithelium (OEE), stratum intermedium (SI), and stellate reticulum (SR). IEE cells further differentiate into enamel-forming ameloblasts, which play distinct roles, and are essential for enamel formation. These are conventionally classified by their shape, although their transcriptome and biological roles are yet to be fully understood. Here, we aimed to use single-cell RNA sequencing to clarify the heterogeneity of dental epithelial cell types. Unbiased clustering of 6,260 single cells from incisors of postnatal day 7 mice classified them into two clusters of ameloblast, IEE/OEE, SI/SR, and two mesenchymal populations. Secretory-stage ameloblasts expressed Amel and Enam were divided into Dspp + and Ambn + ameloblasts. Pseudo-time analysis indicated Dspp + ameloblasts differentiate into Ambn + ameloblasts. Further, Dspp and Ambn could be stage-specific markers of ameloblasts. Gene ontology analysis of each cluster indicated potent roles of cell types: OEE in the regulation of tooth size and SR in the transport of nutrients. Subsequently, we identified novel dental epithelial cell marker genes, namely Pttg1, Atf3, Cldn10, and Krt15. The results not only provided a resource of transcriptome data in dental cells but also contributed to the molecular analyses of enamel formation.
| S-EPMC7490294 | biostudies-literature
Project description:BackgroundDifferentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question.ResultsWe present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved.ConclusionsSingle-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.
| S-EPMC4480509 | biostudies-literature
Project description:BackgroundThe pathophysiological mechanisms of diabetic retinopathy (DR), a blinding disease, are intricate. DR was thought to be a microvascular disease previously. However, growing studies have indicated that the retinal microglia-induced inflammation precedes microangiopathy. The binary concept of microglial M1/M2 polarization paradigms during inflammatory activation has been debated. In this study, we confirmed microglia had the most significant changes in early DR using single-cell RNA sequencing.MethodsA total of five retinal specimens were collected from donor SD rats. Changes in various cells of the retina at the early stage of DR were analyzed using single-cell sequencing technology.ResultsWe defined three new microglial subtypes at cellular level, including two M1 types (Egr2+ M1 and Egr2- M1) and one M2 type. We also revealed the anatomical location between these subtypes, the dynamic changes of polarization phenotypes, and the possible activation sequence and mutual activation regulatory mechanism of different cells. Furthermore, we constructed an inflammatory network involving microglia, blood-derived macrophages and other retinal nonneuronal cells. The targeted study of new disease-specific microglial subtypes can shorten the time for drug screening and clinical application, which provided insight for the early control and reversal of DR.ConclusionsWe found that microglia show the most obvious differential expression changes in early DR and reveal the changes in microglia in a high-glucose microenvironment at the single-cell level. Our comprehensive analysis will help achieve early reversal and control the occurrence and progression of DR.
| S-EPMC10895757 | biostudies-literature
Project description:Transcription factors and signaling pathways that regulate stem cells and specialized hormone-producing cells in the pituitary gland have been the subject of intense study and have yielded a mechanistic understanding of pituitary organogenesis and disease. However, the regulation of stem cell proliferation and differentiation, the heterogeneity among specialized hormone-producing cells, and the role of nonendocrine cells in the gland remain important, unanswered questions. Recent advances in single-cell RNA sequencing (scRNAseq) technologies provide new avenues to address these questions. We performed scRNAseq on ∼13,663 cells pooled from six whole pituitary glands of 7-week-old C57BL/6 male mice. We identified pituitary endocrine and stem cells in silico, as well as other support cell types such as endothelia, connective tissue, and red and white blood cells. Differential gene expression analyses identify known and novel markers of pituitary endocrine and stem cell populations. We demonstrate the value of scRNAseq by in vivo validation of a novel gonadotrope-enriched marker, Foxp2. We present novel scRNAseq data of in vivo pituitary tissue, including data from agnostic clustering algorithms that suggest the presence of a somatotrope subpopulation enriched in sterol/cholesterol synthesis genes. Additionally, we show that incomplete transcriptome annotation can cause false negatives on some scRNAseq platforms that only generate 3' transcript end sequences, and we use in vivo data to recover reads of the pituitary transcription factor Prop1. Ultimately, scRNAseq technologies represent a significant opportunity to address long-standing questions regarding the development and function of the different populations of the pituitary gland throughout life.
| S-EPMC6240904 | biostudies-literature
Project description:Owing to the high mortality rates of heart failure (HF), a more detailed description of the HF becomes extremely urgent. Since the pathogenesis of HF remain elusive, a thorough identification of the genetic factors will provide novel insights into the molecular basis of this cardiac dysfunction. In our research, we performed publicly available transcriptome profiling datasets, including non-failure (NF), dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) hearts tissues. Through principal component analysis (PCA), gene differential expression analysis, gene set enrichment analysis (GSEA), and gene Set Variation Analysis (GSVA), we figured out the candidate genes noticeably altered in HF, the specific biomarkers of endothelial cell (EC) and cardiac fibrosis, then validated the differences of the inflammation-related cell adhesion molecules (CAMs), extracellular matrix (ECM) genes, and immune responses. Taken together, our results suggested the EC and fibroblast could be activated in response to HF. DCM and ICM had both commonality and specificity in the pathogenesis of HF. Higher inflammation in ICM might related to autocrine CCL3/CCL4-CCR5 interaction induced chemokine signaling activation. Furthermore, the activities of neutrophil and macrophage were higher in ICM than DCM. These findings identified features of the landscape of previously underestimated cellular, transcriptomic heterogeneity between ICM and DCM.
| S-EPMC8766768 | biostudies-literature