RNA-seq analysis of cells (siglecF+CD11C+, MHCII-high or MHC-low) from bleomycin-treated and control mouse lungs
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA437904 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Cell suspensions were prepared from lungs dissociated at baseline, at 14 days, and at 28 days after injury. Cells (siglecF+CD11C+ and MHCII-high or -low) were isolated with FACS. RNA-seq was performed with sorted cells.
2018-10-24 | GSE111690 | GEO
Project description:We previously reported that a synthetic Nod1 ligand, FK565, induced coronary arteritis in mice similar to Kawasaki disease. However, the molecular mechanisms underlying this site-specific inflammation have remained elusive. In this study, we found that CD11c+MHC class II+ cells accumulated in the heart of FK565-treated mice prior to arteritis development. We used microarray analysis to detail gene expression of CD11c+MHC class II+ cells. To obtain gene expression profile of CD11c+MHC class II+ cells, we isolated these cells from hearts of FK565-treated mice. Briefly, female mice at 8weeks age were administered 500 μg of FK565 subcutaneously at day 0 and day 3. At day6, murine hearts were removed and digested with collagenase. CD11c+MHC II+ cells were sorted as PI–CD45+Ly6G–NK1.1–CD11b+CD11c+MHC II+ using FACS Aria cell sorter (BD Biosciences). Sorted cells were subjected to RNA preparation. Two independent replicates from ten mice were made.
2015-03-31 | E-GEOD-60506 | biostudies-arrayexpress
Project description:Profile of gene expression of lungs from bleomycin-treated C129svJ mice.
2010-06-05 | E-GEOD-452 | biostudies-arrayexpress
Project description:We previously reported that a synthetic Nod1 ligand, FK565, induced coronary arteritis in mice similar to Kawasaki disease. However, the molecular mechanisms underlying this site-specific inflammation have remained elusive. In this study, we found that CD11c+MHC class II+ cells accumulated in the heart of FK565-treated mice prior to arteritis development. We used microarray analysis to detail gene expression of CD11c+MHC class II+ cells.
2015-03-31 | GSE60506 | GEO
Project description:Profile of gene expression of lungs from bleomycin-treated C129svJ mice. Keywords: parallel sample
2003-06-11 | GSE452 | GEO
Project description:Profile of gene expression of lungs from bleomycin-treated A/J mice.
2010-06-05 | E-GEOD-451 | biostudies-arrayexpress
Project description:Profile of gene expression of lungs from bleomycin-treated A/J mice. Keywords: parallel sample
2003-06-11 | GSE451 | GEO
Project description:The peritoneal cavity is home to various immune cells. Previous studies have investigated the heterogenous nature of peritoneal myeloid mononuclear cells. However, up to this date, there are no clear criteria to distinguish peritoneal macrophages and dendritic cells (DCs). In the present study, we delineate the subsets of myeloid mononuclear cells in the mouse peritoneal cavity. Considering phenotypical, functional, and ontogenic features, peritoneal myeloid mononuclear cells are divided into 5 subsets: large peritoneal macrophages (LPMs), small peritoneal macrophages (SPMs), DCs, and 2 MHCII+CD11c+CD115+ subpopulations (i.e., MHCII+CD11c+CD115+CD14-CD206- and MHCII+CD11c+CD115+CD14+CD206+). Among them, 2 subsets of competent antigen presenting cells are demonstrated with distinct functional characteristics, one being DCs and the other being MHCII+CD11c+CD115+CD14-CD206- cells. DCs are able to promote fully activated T cells and superior in expanding cytokine producing inflammatory T cells, whereas MHCII+CD11c+CD115+CD14-CD206- cells generate partially activated T cells and possess a greater ability to induce regulatory T cells under TGF-β and retinoic acid conditions. While the development of DCs and MHCII+CD11c+CD115+CD14-CD206- cells are responsive to the treatment of FLT3L and GM-CSF, the numbers of LPMs, SPMs, and MHCII+CD11c+CD115+CD14+CD206+ cells are only influenced by the injection of GM-CSF. In addition, the analysis of transcriptomes reveals that the gene expression profile of MHCII+CD11c+CD115+CD14+CD206+ cells share high similarity with that of SPMs. Collectively, our study identifies 2 distinct subpopulations of MHCII+CD11c+CD115+ cells, (i) MHCII+CD11c+CD115+CD14-CD206- cells closely related to DCs and (ii) MHCII+CD11c+CD115+CD14+CD206+ cells to SPMs.
2019-07-01 | GSE130424 | GEO
Project description:RNA-seq libraries for splenic and colonic MHCII+ APCs and colonic CD11b+, CD11c+, CD11b+CD11c+ MNP/DC
| PRJNA591565 | ENA
Project description:Purpose: Explore whether bleomycin treatment will induce changes of metabolic genes expression via next-generation sequencing (NGS) in mouse lung tissues. Methods: Four groups of wild type mice were intratracheally injected with 25 µl PBS or bleomycin (15 mg/kg) after anesthetization. 10 days after bleomycin treatment, lung tissues were removed for RNA collection. Three samples per group were mixed to one sample and used for next RNA purification. RNA samples were then used for high-throughput sequencing according to standard operation based on RNA BGISEQ-500. Results: Using an optimized data analysis workflow, we mapped about 21.9 million sequence reads per sample to the mouse genome (build mm10) and identified 1024 upregulated and 936 downregulated genes in lungs of bleomycin-treated mice. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude. Altered expression of 20 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered metabolic changes of many carbohydrates, amino acid and fatty acid. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in metabolism profiling. Conclusions: Our study represents the first detailed analysis of metabolic changes in lungs of bleomycin-treated mice with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based metabolic genes characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
2019-02-19 | GSE123808 | GEO