|
| Status |
Public on Mar 26, 2021 |
| Title |
RNA-Seq Pneumocystis infection 3W |
| Sample type |
SRA |
| |
|
| Source name |
Lung CD45+ cells
|
| Organism |
Mus musculus |
| Characteristics |
strain: C57BL/6
cell type: Lung-derived CD45+ cells
age: 6-8 week
duration of infected with pneumocystis: 3 weeks
|
| Treatment protocol |
For Pneumocystis infection, 1×106 Pneumocystis cysts contained in 100μl PBS were injected through trachea of each mouse. Control mice were transtracheally injected with 100μl PBS.
|
| Extracted molecule |
polyA RNA |
| Extraction protocol |
Single cell suspensions were isolated from mouse lungs by collagenase digestion.
CD45+ cells were sorted by BD FACS ARIA II cell sorter from lung cell suspensions. Single-cell 5’ RNA-Seq libraries were generated using Single Cell 5’ Library and Gel Bead Kit and Chromium Controller (10x Genomics) according to the manufacturer’s protocol.
single-cell RNA Seq
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
| |
|
| Data processing |
The Cell Ranger software was obtained from 10x Genomics website https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest. Alignment, filtering, barcode counting, and UMI counting were performed with cellranger count module to generate feature-barcode matrix and determine clusters. Dimensionality reduction was performed using PCA and the first ten principle compoments were used to generate clusters by K-means algorithm and graph-based algorithm, respectively.
The other clustering method is Seurat 3.0(R package). Cells whose gene number was less than 200, or gene number ranked in the top 1%, or mitochondrial gene ratio was more than 25% were regarded as abnormal and filtered out. Dimensionality reduction was performed using PCA, and visualization was realized by TSNE and UMAP.
GO enrichment, KEGG enrichment, Reactome enrichment and Disease enrichment (human only) of cluster markers were performed using KOBAS software with Benjamini-Hochberg multiple testing adjustment, using top 20 markers gene of cluster. The results were visualized using R package
Protein-protein interaction was obtained from STRING database with combine_score >=400. For each cluster, the interaction of top 20 marker genes was extracted from the database and the results were visualized using Cytoscape software, respectively.
Transcription Factors were predicted within 2000 bp upstream and 500 bp downstream of TSS for top 20 marker genes of each cluster using TFBSTools and JASPAR database. The gene and TF network for each cluster was visualized using Cytoscape software.
Genome_build: mm10
Supplementary_files_format_and_content: Matrix table with raw gene counts for every gene and every sample
|
| |
|
| Submission date |
Sep 08, 2020 |
| Last update date |
Mar 28, 2021 |
| Contact name |
Zhaohui Tong |
| E-mail(s) |
tongzhaohuicy@sina.com
|
| Phone |
13910930309
|
| Organization name |
Beijing Chaoyang Hospital
|
| Department |
Department of Respiratory and Critical Care Medicine
|
| Lab |
Beijing Institute of Respiratory Medicine
|
| Street address |
NO. 8, Gong Ti South Road
|
| City |
Beijing |
| State/province |
Beijing |
| ZIP/Postal code |
100020 |
| Country |
China |
| |
|
| Platform ID |
GPL24247 |
| Series (1) |
| GSE157627 |
The dynamic immune cell landscape in the lungs of Pneumocystis infected mice |
|
| Relations |
| BioSample |
SAMN16078905 |
| SRA |
SRX9090592 |
