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| Status |
Public on Aug 13, 2020 |
| Title |
Macrophages WT |
| Sample type |
SRA |
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| Source name |
Non-parenchymal liver cells enriched for F4/80 positive macrophages
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| Organism |
Mus musculus |
| Characteristics |
tissue: Liver
cell type: Non-parenchymal liver cells enriched for F4/80 positive macrophages
genotype: Spta wt/wt
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| Treatment protocol |
No treatment
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| Growth protocol |
8-10 week old male mice
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| Extracted molecule |
total RNA |
| Extraction protocol |
The abdominal cavity of a living, deeply anesthetized mouse was opened, and the portal vein was catheterized for in situ liver perfusion and digestion with 50 ml of 0.06 U/ml collagenase B buffered solution (Roche, 11088815001). Once digested, livers were dissected out and the mouse was sacrificed. The digested livers were then mechanically disaggregated in a petri dish on ice and filtered through a 100 μm pore cell strainer. The cell suspensions were centrifuged twice at 60 x g for 2 min at 4°C, and the pellets were discarded. The supernatants were then centrifuged at 300 x g for 5 min at 4°C to obtain a pellet of nonparenchymal liver cells containing liver macrophages. To select for F4/80+ macrophages from liver cell suspensions, Dynabeads Sheep anti-Rat IgG (Invitrogen, 11035), in combination with purified rat anti-mouse F4/80 antibody (BD Pharmingen, 0.5 mg/ml, 565409) ), and a DynaMag™-2 Magnet (Thermo Fisher Scientific, 12321D) were used according to the manufacturer's protocol (Invitrogen). The purity of the separated cells was tested by detecting F4/80 positive cells by FACS.
Nonparenchymal liver cell suspension enriched for F4/80+ macrophages were processed for library preparation according to the 10x Genomics Chromium Single Cell 3’ v3 Reagent Kit instruction guide. Briefly, sample volume was adjusted to a target capture of 10,000 cells and loaded onto the 10x Genomics single-cell-A chip. After droplet generation, samples were subjected to reverse transcriptase and the barcoded cDNA was further amplified for 11 cycles (adjusted for a cell recovery of >6000, as suggested by the 10x Genomic user guide). cDNA quality and concentration were assessed using High-Sensitivity D5000 ScreenTape (Agilent). cDNA strands were then subjected to enzymatic fragmentation, end repair and A-tailing. Adaptors were ligated to the fragmented cDNA, and sample index was added during sample index PCR (set for 13 cycles, as recommended by 10X Genomics user guide to correlate with a cDNA input of 12-150 ng). Library quality and concentration were assessed using High-Sensitivity D5000 ScreenTape (Agilent). Libraries were pooled in equimolar amounts and sequenced using the Illumina NovaSeq 6000 system according to 10X Genomics recommendations: paired-end reads, R1=28 cycles, i7=8 cycles and R2=91 cycles. Sequencing depth was targeted for 50,000 reads per cell in both samples.
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
The Cell Ranger Single-Cell Software Suite was used for cDNA oligopeptide alignment, barcode assignment and UMI counting from fastq data. Cell Ranger Count (version 3.0.1) generated a digital expression matrix for each sample and filtered the cell-containing droplets from empty droplets.
The two filtered digital expression matrices were then merged into one using CellRanger Aggr and then further analyzed using R (v3.6.1) [https://www.R-project.org/].
Supplementary_files_format_and_content: First processed data file are the raw and filtered count matrix obtained after Cell Ranger Count and CellRangerr Agg containing count for every gene in each barcoded cell.
Cell quality control was performed using the scater R package (v1.12.2). Cells with a high mitochondrial gene ratio count were excluded from the data set (1506 out of 18,633 cells were removed). They were determined by the isOutlier function of the scater package, which placed the cut-off at 53% (at 3 median absolute deviation (MAD) above median of all cells).
Normalization was performed using the deconvolute normalization algorithm implemented in the scran R package (v1.12.1), using the computeSumFactors function on cells clustered with quickCluster function from the same package. After normalization, principal component analysis (PCA) was performed using the denoisePCA function of the same package to reduce the number of dimensions representing each cell. Based on the first 10 PCA, a shared nearest neighbor graph was built with the buildSNNGraph function, and the Louvain algorithm was performed to identify cell clusters using the cluster_louvain function implemented in the igraph package (v1.2.4.1).
Supplementary_files_format_and_content: Second processed data file is an .rds file containing single cell experiment object (sce) of the data after quality contorl, normalization, dimensionality reduction and clustering
Genome_build: Ensembl GRCm38.p5 Release 91
Supplementary_files_format_and_content: barcodes.tsv.gz: List of all unique 10 x barcode with sample origin (-1 or -2)
Supplementary_files_format_and_content: features.tsv.gz: Identifier and name of all features
Supplementary_files_format_and_content: matrix.mtx.gz: count expression matrix
Supplementary_files_format_and_content: sce-SPTAmerged-Final.rds: .rds file containing single cell experiment object (sce) of the data after quality contorl, normalization, dimensionality reduction and clustering
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| Submission date |
Feb 13, 2020 |
| Last update date |
Aug 13, 2020 |
| Contact name |
Marc Pfefferle |
| E-mail(s) |
marc.pfefferle@uzh.ch
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| Organization name |
University hospital Zürich (USZ)
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| Street address |
Wagistrasse 12
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| City |
Schlieren |
| State/province |
Schweiz |
| ZIP/Postal code |
8952 |
| Country |
Switzerland |
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| Platform ID |
GPL24247 |
| Series (2) |
| GSE145241 |
Erythrophagocytosis drives anti-inflammatory programming of liver macrophages (Single-cell RNA-seq SPTA mac) |
| GSE145244 |
Erythrophagocytosis drives anti-inflammatory programming of liver macrophages |
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| Relations |
| BioSample |
SAMN14094195 |
| SRA |
SRX7717675 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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