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Status |
Public on Nov 26, 2023 |
Title |
51V_0916 |
Sample type |
SRA |
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Source name |
colon tumor
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Organism |
Mus musculus |
Characteristics |
tissue: colon tumor cell line: CT26 cell type: CD45+ cells, CD45+ CD3+ T cells and CD45- BFP+ tumor cells
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Treatment protocol |
Cells from 9 (Cyp51-KO) and 12 (sg-Ctrl) tumors were stained with antibodies for surface proteins at 4℃ for 30 min and sorted into bulk CD45+ cells, CD45+ CD3+ T cells and CD45- BFP+ tumor cells with MA900 Multi-Application Cell Sorter (SONY). Sorted cell subsets were combined at a ratio of 50 % bulk CD45+ cells, 40 % CD45+ CD3+ T cells and 10 % tumor cells.
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Growth protocol |
Cyp51-KO or sg-Ctrl CT26 tumors were harvested at day 26 post orthotopic injection in BALB/c mice. Single cell suspensions of tumor tissues were prepared as described above.
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Extracted molecule |
total RNA |
Extraction protocol |
For the quality check and counting of single cell suspension, the cell survival rate is generally above 90%. The cells that have passed the test are washed and resuspended to prepare a suitable cell concentration of 700~1200 cells/μl. Then the cells were loaded ~18,000 cells/chip position using the 10× Chromium Next GEM Single Cell 5’ Kit v2. The system is operated on the machine. GEMs (Gel Bead in Emulsion) were constructed for single cell separation according to the number of cells to be harvested.
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Library strategy |
RNA-Seq |
Library source |
transcriptomic single cell |
Library selection |
cDNA |
Instrument model |
Illumina NovaSeq 6000 |
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Data processing |
The output gene expression matrices were analyzed by R software (v4.2.0) with the Seurat package (version 4.2.0). All samples were merged into one Seurat object using the merge function in Seurat. Low quality cells with < 200 or >7000 genes detected, < 500 or >100,000 UMI counts detected or > 5% mitochondrial UMI counts detected were removed. Dimension reduction and unsupervised clustering were performed according to the standard workflow in Seurat. SCTransform function was applied to normalize and find highly variable genes (HVGs) within the single-cell gene expression data. Mitochondrial genes, dissociation-induced genes and HLA genes were removed from HVGs for downstream analyses. Then, the effect of the percentage of mitochondrial gene counts was regressed out by using SCTransform function with parameter “vars.to.regress = ‘percent.mt’ ”. A principal component analysis (PCA) matrix was calculated to reduce noise by using RunPCA with default parameters. After PCA analysis, we use Findneighbors and FindClusters (by Louvain algorithm) function provided by Seurat. Then UMAP and graph-based clustering were performed on the object for visualization and cell clustering by RunUMAP function. The main immune cell types were annotated based on the expression pattern of DEGs and the well-known cellular markers from the literature. In the first-round of unsupervised clustering of all cells, we found 5 spread small clusters (less than 10 cells) of WT group which might be caused by sequencing noise. Therefore, we removed these clusters for downstream analysis. Assembly: Cell Ranger (version 7.0) was applied to filter low quality reads, align reads to mouse reference genome (GRCm38), assign cell barcodes, and generate the UMI matrices. Supplementary files format and content: The output gene expression matrices were analyzed by R software (v4.2.0) with the Seurat package (version 4.2.0). All samples were merged into one Seurat object using the merge function in Seurat. Low quality cells with < 200 or >7000 genes detected, < 500 or >100,000 UMI counts detected or > 5% mitochondrial UMI counts detected were removed.
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Submission date |
Nov 24, 2023 |
Last update date |
Nov 26, 2023 |
Contact name |
Haochen Yang |
E-mail(s) |
yanghaochen2021@sibcb.ac.cn
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Organization name |
Shanghai Institute of Biochemistry and Cell Biology
|
Lab |
Chenqi Xu Lab
|
Street address |
320 Yue-yang Road
|
City |
Shanghai |
State/province |
Shanghai |
ZIP/Postal code |
200031 |
Country |
China |
|
|
Platform ID |
GPL24247 |
Series (1) |
GSE248570 |
Shaping immune landscape of colorectal cancer by cholesterol metabolites [BALB/c] |
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Relations |
BioSample |
SAMN38412729 |
SRA |
SRX22635970 |