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Paper Readig 01 Single-Cell Transcriptional Profiling of Aortic Endothelium Identifies a Hierarchy from Endovascular Progenitors to Differentiated Cells  Samuel W. Lukowski, Jatin Patel, Stacey B. Andersen, ..., Ingrid Winkler, Joseph E. Powell, Kiarash Khosrotehrani cell reports The heterogeneity of endothelial in circulatory system is still unclear. Previously, a population termed endovascular progenitor ( EVP) has been defined with a stringent cell surface marker profile (CD34+CD45-CD31loVEGFR2-), which can transform to a definitive differentiated (D) endothelial cell (VEGFR2+CD31+). In this paper, Samuel et al. used single-cell RNA sequence to characterize the gene expression of two distinct endothelial cell populations in the mice aorta and to demonstrate an endothelial hierarchy from progenitor population to mature endothelial cell. They dissect the descending aorta of mice and sort Lin-CD34+ cell to perform sequencing. The scRNA-seq data contains a total of 6111 cells from three pools of 30 mouse samples and includes 4 clusters, such as two terminally differentiated endothelial, one mesenchymal phenotype of endothelial and one cardiac muscle. Then a differential expression analysis and marker genes indicate that clusters one and two correspond to transcriptionally distinct population of endothelial cells at different stages of differentiation. A machine learning approach, LASSO regression approach, was used to produce a list of genes that explain the greatest amount deviance. Subsequently, they performed pairwise Spearman’s correlation between single-cell clusters and bulk transcriptome data to support the result of cluster classification. Meanwhile, a linear modeling approach provides new insights to reveal the top genes with significant changes in expression between D and EVP populations. Weighted gene correlation network analysis (WGCNA) detect two robust modules in each cell population. Further, they demonstrated the EVP population had significantly higher mitochondrial activity compared to D by flow cytometry. Finally, a cell fate trajectory shows that EVP and D cells exist as a continuum of differentiation states. https://www./science/article/pii/S2211124719305820?via%3Dihub 02 A human liver cell atlas reveals heterogeneity and epithelial progenitors  Nadim Aizarani, Antonio Saviano, Sagar, Laurent Mailly, Sarah Durand, Josip S. Herman, Patrick Pessaux, Thomas F. Baumert & Dominic Grün Nature The liver as a central metabolic coordinator, can regulate glucose and lipid metabolism, protein synthesis, and bile synthesis. With the increasing incidences of liver diseases and mortality, the cellular composition of the liver needs to understand. In this paper, Nadim et al. used mCEL-seq for single-cell RNA sequencing of 10372 cells from normal liver tissue from nine human donors, who underwent liver resections for colorectal cancer metastasis or cholangiocarcinoma, to construct a human liver cell atlas. Of note, they designed a protocol for generating scRNA-seq data from cryopreserved cells and used RaceID3 for the identification of cell type. A couple of cell types were defined, including hepatocytes, cholangiocytes (EPCAM+), LSECs (CLEC4G+), MaVECs, Kupffer cells, immune cells and so on. They compare the signature of two type of non-parenchymal cells, involving macrovascular endothelial cells (MaVECs) and liver sinusoidal endothelial cells. Then they used diffusion pseudo-time to infer continuous transcriptome-wide zonation and apply self-organizing maps to infer co-expression modules. The approach recovers zonated expression patterns of landmark genes. Besides, they demonstrate an unexpected variety of immune cell subtypes in human liver, including MS4A1+CD37+ B cells, NK cells, and NKT cells. Finally, they fight to search for genuine liver progenitor cells due to the powerful regeneration ability of liver. They found a gradient of TROP2 expression in EPCAM+ cells and TROP2int population harbous the progenitor population. About hepatocellular carcinoma (HCC),scRNA-seq of patient-derived HCC reveals cancer-specific gene signatures and perturbed cellular phenotypes. https://www./articles/s41586-019-1373-2 END |
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