Single Cell Sequencing Data of Mouse Spinal Cord with Dorsal Column Lesion and Astrocyte-Specific Ryk conditional Knockout
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ABSTRACT: After the data quality control, a total of 18,203 captured cells were subjected to clustering analysis by leiden and visualized in lower dimension by uniform manifold approximation and projection (UMAP). The results showed that they could be clustered into 17 distinct cell clusters. According to the highest differentially expressed genes (DEGs) and canonical markers used in prior studies, we annotated these 17 clusters as 13 major cell types with distinct expression profiles): Astrocytes (ASC, containing 3 clusters: Astro_2, Astro_5, and Astro_7), microglia (MG, containing 2 clusters: Microglial_6 and Microglial_10), oligodendrocytes (containing 2 clusters: Oligo_4 and Oligo_8), endothelial cells (containing 1 cluster: Endothelial_1), pericytes (Pericytes_9), fibroblasts (Fibroblasts_14), neuronal cells (Neuronal_3), oligodendrocyte progenitor cells (OPC_11), Schwann cells (schwan cells_15), red blood cells (RBC_17), immune cells (Immuno_12), myeloid cells (myeloid Cells_16)
Project description:To identify clear mesencbhymal cell clusters, sequencing libraries of embryonic lung cells were prepared using the 10x Genomics Chromium system. After quality control samples were integrated. The cells were visualized in two dimensions according to their gene expression profiles using Uniform Manifold Approximation and Projection (UMAP).
Project description:To identify clear mesenchymal cell clusters, sequencing libraries of embryonic lung cells were prepared using the 10x Genomics Chromium system. After quality control samples were integrated. The cells were visualized in two dimensions according to their gene expression profiles using Uniform Manifold Approximation and Projection (UMAP).
Project description:We performed single-cell RNA seq analysis on skin biopsies from six acne patients with a total of 32,966 cells from lesional skin and 29,202 cells from non-lesional skin using 10X Genomics. Gene expression data derived from cells in both lesional and non-lesional skin were aligned and projected onto a two-dimensional space using UMAP (Uniform Manifold Approximation and Projection). Unsupervised clustering revealed eight major clusters corresponding to seven different cell types lymphocytes, myeloid cells, keratinocytes, fibroblasts, endothelial cells, smooth muscle cells, and melanocytes.
Project description:We optimized Voltage-Seq which combines, all-optical physiology, spatial mapping, on-site classification, and RNA-transcriptomics to robustly increase the throughput of synaptic connectivity testing and targeted molecular classification of postsynaptic neurons. Single-cell RNA-sequencing was performed on spatial- and voltage-recorded neurons in the mouse PAG. Uniform Manifold Approximation and Projection (UMAP) clustered cells as excitatory or inhibitory, and further differential expression analyses highlighted putative marker genes of GABAergic neurons. These sequencing results were in agreement with in-situ hybridization (ISH) and neuronal activity recordings.
Project description:We analyzed over 40,000 cells from nine pediatric MPAL BM samples to generate a single-cell transcriptomic landscape of B/Myeloid (B/My) and T/Myeloid (T/My) MPAL blasts and associated microenvironment cells. Cell clusters were identified using principal component analysis and uniform manifold approximation and projection (UMAP). Supervised differentially expressed gene (DEG) analysis was performed to identify B/My and T/My MPAL blast-specific signatures. MPAL sample transcriptome profiles were compared with normal BM stem and immune cells to identify MPAL-specific dysregulation. We have for the first time described the single-cell transcriptomic landscape of pediatric MPAL and have demonstrated that B/My and T/My MPAL have unique scRNA-seq profiles distinct from each other with expected overlap with AML and their respective ALL subtype.
Project description:To gain insights into the nature of human age-associated B cells (ABCs), we sorted peripheral B cells from a patient with new-onset SLE and performed droplet-based scRNA-seq. Seven distinct clusters were revealed by unsupervised clustering with a two-dimensional uniform manifold approximation and projection (UMAP). These clusters were assigned to known peripheral B cell subsets including transitional B cells, naïve B cells, activated naïve B cells, ABCs, memory B cells, plasmablasts, and plasma cells by comparing differentially expressed genes with established landmark genes. ABCs preferentially expressed genes encoding key surface markers CD19, CD86, FCRLA, FCRL3/5, FCGR2B, MS4A1 and ITGAX. We found 43 differentially expressed TFs: 27 upregulated and 16 downregulated.
Project description:As cortical organoids consist of a heterogeneous population of cell-types, 6-month-old DM1 and Rett syndrome cortical organoids were subjected to single cell RNA-seq (scRNA-seq) analysis to determine which cell type(s) CELF2’s RNA targets are expressed in. Unsupervised clustering was implemented on the combined dataset of 8595 cells from control, DM600, and DM1200 cortical organoids that consisted of ~2865 cells per organoid line and ~17,575 reads per cell to identify genotype-specific clusters at 6-months post-differentiation. Uniform Manifold Approximation and Projection (UMAP) for dimension reduction revealed clear differences between control and DM1 organoids. From the expression of established cell-type specific gene markers, smaller sub-clusters were combined to represent four major cell classes: neural progenitors, intermediate neural progenitors, glutamatergic cortical neurons, and glial cells.
Project description:To gain insights into the global and local transcriptomic changes underlying defective production of CD42a+ iHPCs in RUNX1+/-, we performed scRNA SEQ on sorted CD42a- and CD42a+ iHPCs from L1 and L1-C. There were on average 11,328 reads per cell with an average of 2,081 genes expressed. To identify and analyze distinct subpopulations in the control and RUNX1+/- iHPCs, dimension reduction was performed and cell clustering was visualized using uniform manifold approximation and projection (UMAP)
Project description:10X genomics single cell analysis of yHSC vs oHSC from Gfplc3/Gfplc3 mice with index sorted SMART-Seq2 sequencing to map AThi oHSC vs ATlo oHSC based on GFP-LC3 marker levels. 10X Genomics data harmonized by nearest neighbor integration and uniform manifold approximation and projection (UMAP) representation distinguished yHSC from oHSC, with the largest transcriptional differences observed in the G0/G1 cell cycle phase cluster. Within oHSCs, AThi oHSCs were almost exclusively observed in the G0/G1 cluster, whereas ATlo oHSCs were spread across the activation continuum, with cells still in the G0/G1 cluster found more proximal to S cluster cells.
Project description:We performed single-cell RNA sequencing on esophageal PDOs from 4 non-EoE control patients to investigate the molecular heterogeneity of human esophageal organoids. Seurat’s unsupervised dimensionality reduction and clustering along with uniform manifold approximation and projection visualization showed 4 distinct cell clusters in esophageal PDOs cultures with or without IL13