Similar Datasets
Project description:The advent of single cell (Sc) genomics has challenged the dogma of haematopoiesis as a tree-like structure of stepwise lineage commitment through distinct and increasingly restricted progenitor populations. Instead, analysis of ScRNA-seq has proposed that the earliest events in human hematopoietic stem cell (HSC) differentiation are characterized by only subtle molecular changes, with hematopoietic stem and progenitor cells (HSPCs) existing as a continuum of low-primed cell-states that gradually transition into a specific lineage (CLOUD-HSPCs). Here, we combine ScRNA-seq, ScATAC-seq and cell surface proteomics to dissect the heterogeneity of CLOUD-HSPCs at different stages of human life. Within CLOUD-HSPCs, pseudotime ordering of both mRNA and chromatin data revealed a bifurcation of megakaryocyte/erythroid and lympho/myeloid trajectories immediately downstream a subpopulation with an HSC-specific enhancer signature. Importantly, both HSCs and lineage-restricted progenitor populations could be prospectively isolated based on correlation of their molecular signatures with CD35 and CD11A expression, respectively. Moreover, we describe the changes that occur in this heterogeneity as hematopoiesis develops from neonatal to aged bone marrow, including an increase of HSCs and depletion of lympho-myeloid biased MPPs. Thus, this study dissects the heterogeneity of human CLOUD-HSPCs revealing distinct HSPC-states of relevance in homeostatic settings such as ageing.
2023-09-27 | GSE173075 | GEO
Project description:The advent of single cell (Sc) genomics has challenged the dogma of haematopoiesis as a tree-like structure of stepwise lineage commitment through distinct and increasingly restricted progenitor populations. Instead, analysis of ScRNA-seq has proposed that the earliest events in human hematopoietic stem cell (HSC) differentiation are characterized by only subtle molecular changes, with hematopoietic stem and progenitor cells (HSPCs) existing as a continuum of low-primed cell-states that gradually transition into a specific lineage (CLOUD-HSPCs). Here, we combine ScRNA-seq, ScATAC-seq and cell surface proteomics to dissect the heterogeneity of CLOUD-HSPCs at different stages of human life. Within CLOUD-HSPCs, pseudotime ordering of both mRNA and chromatin data revealed a bifurcation of megakaryocyte/erythroid and lympho/myeloid trajectories immediately downstream a subpopulation with an HSC-specific enhancer signature. Importantly, both HSCs and lineage-restricted progenitor populations could be prospectively isolated based on correlation of their molecular signatures with CD35 and CD11A expression, respectively. Moreover, we describe the changes that occur in this heterogeneity as hematopoiesis develops from neonatal to aged bone marrow, including an increase of HSCs and depletion of lympho-myeloid biased MPPs. Thus, this study dissects the heterogeneity of human CLOUD-HSPCs revealing distinct HSPC-states of relevance in homeostatic settings such as ageing.
2023-09-27 | GSE173076 | GEO
Project description:One of the keys to achieving skin regeneration lies within understanding the heterogeneity of neonatal fibroblasts, which support skin regeneration. However, the molecular underpinnings regulating the cellular states and fates of these cells are not fully understood. To investigate this, we performed a parallel multiomics analysis by processing neonatal murine skin for single-cell Assay for Transposase-Accessible Chromatin sequencing and single-cell RNA sequencing separately. Our approach revealed that fibroblast clusters could be sorted into papillary and reticular lineages on the basis of transcriptome profiling, as previously reported. However, single-cell Assay for Transposase-Accessible Chromatin sequencing analysis of neonatal fibroblast lineage markers, such as Dpp4/Cd26, Corin, and Dlk1 along with markers of myofibroblasts, revealed accessible chromatin in all fibroblast populations despite their lineage-specific transcriptome profiles. These results suggest that accessible chromatin does not always translate to gene expression and that many fibroblast lineage markers reflect a fibroblast state, which includes neonatal papillary fibroblasts, reticular fibroblasts, and myofibroblasts. This analysis also provides a possible explanation as to why these marker genes can be promiscuously expressed in different fibroblast populations under different conditions. Our single-cell Assay for Transposase-Accessible Chromatin sequencing analysis also revealed that the functional lineage restriction between dermal papilla and adipocyte fates is regulated by distinct chromatin landscapes. Finally, we have developed a webtool for our multiomics analysis: https://skinregeneration.org/scatacseq-and-scrnaseq-data-from-thompson-et-al-2021-2/.
| S-EPMC9203604 | biostudies-literature
Project description:A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.
| S-EPMC4687963 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-03-11 | GSE260995 | GEO
Project description:Cancer cells frequently exhibit chromosomal abnormalities. Specific cytogenetic aberrations often are predictors of outcome, especially in hematologic neoplasms, such as monosomy 7 in myeloid malignancies. The functional consequences of aneuploidy at the cellular level are difficult to assess because of a lack of convenient markers to distinguish abnormal from diploid cells. We performed single-cell RNA sequencing (scRNA-seq) to study hematopoietic stem and progenitor cells from the bone marrow of 4 healthy donors and 5 patients with bone marrow failure and chromosome gain or loss. In total, transcriptome sequences were obtained from 391 control cells and 588 cells from patients. We characterized normal hematopoiesis as binary differentiation from stem cells to erythroid and myeloid-lymphoid pathways. Aneuploid cells were distinguished from diploid cells in patient samples by computational analyses of read fractions and gene expression of individual chromosomes. We confirmed assignment of aneuploidy to individual cells quantitatively, by copy-number variation, and qualitatively, by loss of heterozygosity. When we projected patients' single cells onto the map of normal hematopoiesis, diverse patterns were observed, broadly reflecting clinical phenotypes. Patients' monosomy 7 cells showed downregulation of genes involved in immune response and DNA damage checkpoint and apoptosis pathways, which may contribute to the clonal expansion of monosomy 7 cells with accumulated gene mutations. scRNA-seq is a powerful technique through which to infer the functional consequences of chromosome gain and loss and explore gene targets for directed therapy.
| S-EPMC5746166 | biostudies-literature
Project description:The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8+ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand-receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.
| S-EPMC9296597 | biostudies-literature
Project description:The mammary gland is very intricately and well organized into distinct tissues, including epithelia, endothelia, adipocytes, and stromal and immune cells. Many mammary gland diseases, such as breast cancer, arise from abnormalities in the mammary epithelium, which is mainly composed of two distinct lineages, the basal and luminal cells. Because of the limitation of traditional transcriptome analysis of bulk mammary cells, the hierarchy and heterogeneity of mammary cells within these two lineages remain unclear. To this end, using single-cell RNA-Seq coupled with FACS analysis and principal component analysis, we determined gene expression profiles of mammary epithelial cells of virgin and pregnant mice. These analyses revealed a much higher heterogeneity among the mammary cells than has been previously reported and enabled cell classification into distinct subgroups according to signature gene markers present in each group. We also identified and verified a rare CDH5+ cell subpopulation within a basal cell lineage as quiescent mammary stem cells (MaSCs). Moreover, using pseudo-temporal analysis, we reconstructed the developmental trajectory of mammary epithelia and uncovered distinct changes in gene expression and in biological functions of mammary cells along the developmental process. In conclusion, our work greatly refines the resolution of the cellular hierarchy in developing mammary tissues. The discovery of CDH5+ cells as MaSCs in these tissues may have implications for our understanding of the initiation, development, and pathogenesis of mammary tumors.
| S-EPMC5986215 | biostudies-other
Project description:Extensive epigenetic reprogramming occurs during preimplantation embryo development. However, it remains largely unclear how the drastic epigenetic reprogramming contributes to transcriptional regulatory network during this period. Here, we develop a single-cell multiomics sequencing technology (scNOMeRe-seq) that enables profiling of genome-wide chromatin accessibility, DNA methylation and RNA expression in the same individual cell. We apply this method to depict a single-cell multiomics map of mouse preimplantation development. We find that genome-wide DNA methylation remodeling facilitates the reconstruction of genetic lineages in early embryos. Further, we construct a zygotic genome activation (ZGA)-associated regulatory network and reveal coordination among multiple epigenetic layers, transcription factors and repeat elements that instruct proper ZGA. Cell fates associated cis-regulatory elements are activated stepwise in post-ZGA stages. Trophectoderm (TE)-specific transcription factors play dual roles in promoting the TE program while repressing the inner cell mass (ICM) program during the ICM/TE separation.
| S-EPMC7902657 | biostudies-literature
Project description:BackgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single-cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single-cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single-cell technologies are not yet established, in the context of BPs.ResultsWe performed integrative analyses of novel human single-cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.ConclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.
| S-EPMC6230222 | biostudies-literature