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Status |
Public on Jul 13, 2020 |
Title |
KC pancreas tuft cell 17 |
Sample type |
SRA |
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Source name |
KrasG12D;Ptf1aCre/+ (KC) mouse
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Organism |
Mus musculus |
Characteristics |
strain: Mixed tissue: Pancreas cell type: tuft cell age: 8-10 month
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Extracted molecule |
polyA RNA |
Extraction protocol |
Pancreatic tuft cells were isolated from 3, 8-10 month old KC PanIN-bearing. The pancreas was quickly dissected, minced in 5 ml of DMEM with FBS and allowed to incubate for 2 min. Supernatant and fat were removed and pancreatic tissue was then incubated in 10 ml DMEM supplemented with 1 mg/ml collagenase I (Sigma), 1 mg/ml soybean trypsin inhibitor (Gibco), 1-1.5 mg/ml hyaluronidase (depending on tumor burden, Sigma), and 250 ml of DNAse I, shaking gently at 37°C for a maximum of 30 min. Digestion was monitored and tissue was further digested mechanically by pipetting. Digested tissue was passed through a 100 mm filter, washed with FACS buffer (PBS, 1 mM EDTA, 0.5% BSA), and incubated with ACK lysing buffer (Gibco) to remove red blood cells before staining for FACS. Single cell suspensions were incubated on ice with mouse Fc receptor block (BD Biosciences, 1:200) followed by antigen-specific antibodies in FACS buffer. DAPI (molecular probes, 1:1000) and Annexin V (Biolegend, Pacific Blue conjugate at 1:200) were used to exclude dead and dying cells. Cells were labeled with Cd45 (Alexa Fluor 488), EpCAM (Alexa Fluor 647), and Siglec F (PE) (Biolegend, 1:200). Fluorescence Minus One (FMO) staining controls were included for gating populations of interest. Siglecf+;EpCAM+;Cd45- Cells were FACS purified at the Salk Institute’s Flow Cytometry core facility on a BD Biosciences Influx cell sorter (100-µm size nozzle, 1 x PBS sheath buffer with sheath pressure set to 20 PSI). Cells were sorted in 1-drop Single Cell sort mode for counting accuracy; these were deposited directly into lysis buffer composed of DNase/RNase-free water, Triton X-100, and Ribolock (Thermo Fischer) in a 96 well plate. 10x Genomics scRNA-seq was conducted on immune cells and fibroblasts collected by FACS from caerulein-treated KC and KPouC pancreata. Pancreata were digested and prepared as previously described for tuft cell isolation. Each sample was prepared by flow sorting live immune cells (EpCAM-neg;Cd45+) and non-immune stromal cells (EpCAM-neg;Cd45-neg); PI was used to exclude dead cells. Immune and non-immune stroma from each independent sample were mixed at a 7:3 ratio, respectively, prior to loading on the microfluidic chip with barcoded beads according to 10X Chromium Next GEM Single Cell 3’ (v3.1, Catalog # 1000128, 10x Genomics Inc). SmartSeq2 libraries were constructed as previously described (Picelli et al., 2014) 10x Genomics: Cell lysis, first strand cDNA synthesis and amplification were carried out according to 10X v3.1 protocol, with cDNA amplification set for 11 cycles. Following sample indexing and bead-based library purification, cDNA fragments distribution and concentration were measured using TapeStation (Agilent Biosystems) and Qubit (ThermoFisher).The libraries were pooled in equal mole ratio and sequenced in two illumine NextSeq 550 PE-75 high-output runs.
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 2500 |
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Description |
Tuft_cell_17
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Data processing |
Smartseq2: Reads were aligned to the mm10 mouse genome using STAR version 2.5.3a (73). Mapping was carried out using default parameters, filtering non-canonical introns and allowing up to 10 mismatches per read and only keeping uniquely mapped reads. Raw transcript Samrtseq2: counts were obtained using HTSeq version 0.9.1 (74). The union of all detected genes was compiled into a single expression table (156 cells and 27,998 genes) Smartseq2: Cells with less than 500 unique genes and genes expressed in fewer than 3 cells were filtered using the Seurat R package. Genes were log-normalized in Seurat. 10x Genomics: fastq files were processed using cellranger 3.1.0 and mm10 reference.The raw sequencing data from each mice was first processed separately in Cell Ranger v3.1.0 using refdata-mm10-3.0.0 and default parameters (10x Genomics). Each dataset captured similar number of cells (~4500 cells/mice) with similar sequencing depth (median ~20k reads/cell). The cellranger filtered gene-by-cell count matrices were loaded to the R package Seurat (v3.1.4) and combined into a single merged matrix. Low-quality cells were further filtered based on the percent of mitochondria gene reads, number of UMI, and number of genes detected (subset = percent.mt <7 & nCount_RNA < 25000 & nFeature_RNA >350)). After removing the low-quality cells, we applied a global-scaling normalization method “LogNormalize” that normalizes the gene expression measurement for each cell by the total expression, mulplies this by a scaling factor of 23,000. The normalized data is further linear transformed by ScaleData() function prior to dimension reduction. Principal components analysis (PCA) was performed on the scaled data by only using the most variable 2000 genes (identified using the default “vst” method). Batch effect between mice were examine in PCA space and no obvious batch effect was observed. Genome_build: mm10 Supplementary_files_format_and_content: raw read counts per gene per cell
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Submission date |
Jul 12, 2020 |
Last update date |
Jul 13, 2020 |
Contact name |
Zhibo Ma |
E-mail(s) |
[email protected]
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Organization name |
Salk Institute for Biological Studies
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Street address |
10010 N Torrey Pines Rd
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City |
La Jolla |
State/province |
California |
ZIP/Postal code |
92037 |
Country |
USA |
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Platform ID |
GPL17021 |
Series (2) |
GSE154259 |
Tuft cells restrain pancreatic tumorigenesis through paracrine eicosanoid signaling [single-cell RNA-seq] |
GSE154260 |
Tuft cells restrain pancreatic tumorigenesis through paracrine eicosanoid signaling |
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Relations |
BioSample |
SAMN15512106 |
SRA |
SRX8713173 |
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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