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| Status |
Public on Jun 13, 2024 |
| Title |
HTO library of 5 GFP negative mice |
| Sample type |
SRA |
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| Source name |
Stromal vascular fraction (SVF) from Epididymal white adipose tissue in female p21-Cre/+; +/+ mice
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| Organism |
Mus musculus |
| Characteristics |
tissue: Stromal vascular fraction (SVF) from Epididymal white adipose tissue in female p21-Cre/+; +/+ mice
stain: C57BL/6
Sex: female
age: 25-30 month
treatment: SVF cells were sorted on a BD FACSAria Fusion cell sorter (BD Biosciences) for viable GFPhigh (GFP_pos) and non-GFPhigh (GFP_neg) cell populations.
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| Extracted molecule |
polyA RNA |
| Extraction protocol |
SVF cells were isolated from 5 25-30 months old female P mice. Cells from each donor were labelled with cell hashing antibodies (TotalSeq-A anti-mouse Hashtag, BioLegend) according to the manufacturer’s protocol. Cells were then washed, and resuspended in 0.04% BSA/PBS. Labelled cells from each donor were pooled at equal proportions, then immediately sorted on a BD FACSAria Fusion cell sorter (BD Biosciences) for viable GFPhigh and non-GFPhigh cell populations. Cells from wildtype mice were used as GFP background for gating and sorting. Cell viability was assessed on a Countess II automated cell counter (Thermo Fisher Scientific). Up to 12,000 cells were loaded onto one lane of a 10X Chromium X. Single cell capture, barcoding and library preparation were performed using the 10X Chromium platform version 3.1 chemistry according to the manufacturer’s protocol (CG000388). cDNA and libraries were checked for quality on Agilent 4200 TapeStation (Agilent Technologies, Santa Clara, CA) and Qubit Fluorometer (Thermo Fisher Scientific), quantified by KAPA qPCR. Library was sequenced on an Illumina NovaSeq 6000 S4 v1.5 200 cycle flow cell lane, targeting 6,000 barcoded cells with an average sequencing depth of 50,000 reads per cell.
10X Chromium platform version 3.1 chemistry according to the manufacturer’s protocol (CG000388)
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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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| Description |
10x Genomics
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| Data processing |
Illumina base call files for all libraries were converted to FASTQs using bcl2fastq v2.20.0.422 and FASTQ files associated with the gene expression libraries were aligned to the GRCm38 reference assembly with vM23 annotations from GENCODE (10x Genomics mm10 reference 2020-A) using the version 6.1.2 Cell Ranger multi pipeline (10x Genomics). The FASTQ files associated with the hashtag libraries were processed with the CITE-seq-Count v1.4.5 which populates a cell-barcode by hashtag matrix file which produces a cell-by-hashtag digital count matrix for each hashtag library. De-multiplexing was also done using the Cell Ranger multi pipeline with the MULTIseqDemux algorithm. Downstream analysis was performed using the Seurat R toolkit (version 4.2.0)26. Cells were further excluded from downstream analysis if they did not meet the following criteria: (1) more than 300 genes detected per cell; (2) less than 20% mitochondrial transcripts; (3) less than 1% hemoglobin transcripts. After quality control filtering, 11,530 and 11,699 cells remained in the GFPhigh and non-GFPhigh groups, respectively. The gene expression matrices were normalized by the total UMI counts in each cell, multiplied by 10,000, log-transformed, and the top 2,000 most variable genes were selected using the variance stabilizing transformation method. The two groups were then integrated using the standard workflow in Seurat toolkit, which resulted in an integrated gene expression matrix. Using the integrated matrix, the mean expression of each gene in the cells was scaled to 0, and a linear dimensional reduction (principal component analysis, PCA) was performed on the scaled data. To cluster the cells, the first 40 PCs were used to construct a K-nearest neighbor (KNN) graph. The clusters were identified through the Louvain algorithm on the KNN graph. The resolution parameter was set as 0.2, which resulted in 16 cell clusters comprising 10 different cell types. The single cells were visualized in a 2D UMAP embedding that was computed from the KNN graph. To define the cell clusters, marker genes, which (1) detected at a minimum of 25% of cells in the cluster and (2) the mean expression in the cluster compared to all other cells is higher than 0.25 (log scale), were generated by the FindAllMarkers function using Wilcoxon Rank Sum test under the ‘‘RNA’’ assay.
Assembly: mm10
Supplementary files format and content: Seurat rds file
Supplementary files format and content: GFP_pos_neg_fat_All.rds
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| Submission date |
Jun 12, 2024 |
| Last update date |
Jun 13, 2024 |
| Contact name |
William F Flynn |
| Organization name |
The Jackson Laboratory
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| Street address |
10 Discovery Drive
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| City |
Farmington |
| State/province |
CT |
| ZIP/Postal code |
06032 |
| Country |
USA |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE269660 |
Repeated intermittent clearance of p21-highly-expressing cells extends lifespan and confers sustained benefits to health and physical function |
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| Relations |
| BioSample |
SAMN41803475 |
| SRA |
SRX24888713 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8324306_HTO_GFP_fat_neg_barcodes.tsv.gz |
192.5 Kb |
(ftp)(http) |
TSV |
| GSM8324306_HTO_GFP_fat_neg_features.tsv.gz |
118 b |
(ftp)(http) |
TSV |
| GSM8324306_HTO_GFP_fat_neg_matrix.mtx.gz |
600.4 Kb |
(ftp)(http) |
MTX |
SRA Run Selector |
| Raw data are available in SRA |
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