Dataset Information

Generation of a Single-Cell RNAseq Atlas of Murine Salivary Gland Development.

ABSTRACT: Understanding the dynamic transcriptional landscape throughout organ development will provide a template for regenerative therapies. Here, we generated a single-cell RNA sequencing atlas of murine submandibular glands identifying transcriptional profiles that revealed cellular heterogeneity during landmark developmental events: end bud formation, branching morphogenesis, cytodifferentiation, maturation, and homeostasis. Trajectory inference analysis suggests plasticity among acinar and duct populations. We identify transcription factors correlated with acinar differentiation including Spdef, Etv1, and Xbp1, and loss of Ybx1, Eno1, Sox11, and Atf4. Furthermore, we characterize two intercalated duct populations defined by either Gfra3 and Kit, or Gstt1. This atlas can be used to investigate specific cell functions and comparative studies predicting common mechanisms involved in development of branching organs.

SUBMITTER: Hauser BR

PROVIDER: S-EPMC7718488 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Generation of a Single-Cell RNAseq Atlas of Murine Salivary Gland Development.

Hauser Belinda R BR Aure Marit H MH Kelly Michael C MC Hoffman Matthew P MP Chibly Alejandro M AM

iScience 20201120 12

Understanding the dynamic transcriptional landscape throughout organ development will provide a template for regenerative therapies. Here, we generated a single-cell RNA sequencing atlas of murine submandibular glands identifying transcriptional profiles that revealed cellular heterogeneity during landmark developmental events: end bud formation, branching morphogenesis, cytodifferentiation, maturation, and homeostasis. Trajectory inference analysis suggests plasticity among acinar and duct popu ...[more]

PMID: 33305192

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Project description:The liver is unique in both its ability to maintain immune homeostasis and in its potential for immune tolerance following solid organ transplantation. Single-cell RNA sequencing (scRNA seq) is a powerful approach to generate highly dimensional transcriptome data to understand cellular phenotypes. However, when scRNA data is produced by different groups, with different data models, different standards, and samples processed in different ways, it can be challenging to draw meaningful conclusions from the aggregated data. The goal of this study was to establish a method to combine 'human liver' scRNA seq datasets by 1) characterizing the heterogeneity between studies and 2) using the meta-atlas to define the dominant phenotypes across immune cell subpopulations in healthy human liver. Publicly available scRNA seq data generated from liver samples obtained from a combined total of 17 patients and ~32,000 cells were analyzed. Liver-specific immune cells (CD45+) were extracted from each dataset, and immune cell subpopulations (myeloid cells, NK and T cells, plasma cells, and B cells) were examined using dimensionality reduction (UMAP), differential gene expression, and ingenuity pathway analysis. All datasets co-clustered, but cell proportions differed between studies. Gene expression correlation demonstrated similarity across all studies, and canonical pathways that differed between datasets were related to cell stress and oxidative phosphorylation rather than immune-related function. Next, a meta-atlas was generated via data integration and compared against PBMC data to define gene signatures for each hepatic immune subpopulation. This analysis defined key features of hepatic immune homeostasis, with decreased expression across immunologic pathways and enhancement of pathways involved with cell death. This method for meta-analysis of scRNA seq data provides a novel approach to broadly define the features of human liver immune homeostasis. Specific pathways and cellular phenotypes described in this human liver immune meta-atlas provide a critical reference point for further study of immune mediated disease processes within the liver.

Dataset Information

Generation of a Single-Cell RNAseq Atlas of Murine Salivary Gland Development.

Publications

Generation of a Single-Cell RNAseq Atlas of Murine Salivary Gland Development.

Similar Datasets

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