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| Status |
Public on Jun 17, 2024 |
| Title |
KPC_3975, Early Vehicle, snRNAseq |
| Sample type |
SRA |
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| Source name |
Pancreatic ductal adenocarcinoma
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| Organism |
Mus musculus |
| Characteristics |
tissue: Pancreatic ductal adenocarcinoma
Sex: Male
time point_(days): 3
genotype: KrasG12D/+; Trp53R172H/+; p48-Cre
treatment: Vehicle
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| Extracted molecule |
total RNA |
| Extraction protocol |
Samples were prepared as previously described (Hwang et al. Nature genetics 2022, PMID: 35902743). Briefly, ST stock solution was prepared in nuclease-free water with a final concentration of 146 mM NaCl (Thermo Fisher Scientific, Cat. #AM9759), 20 mM Tricine (VWR, Cat #. E170-100G), 1mM CaCl2 (VWR, Cat. # 97062-820) and 21 mM MgCl2 (Sigma-Aldrich, Cat. # M1028). 2mL of NST nuclei isolation solution was prepared for each sample by adding 0.2% Nonidet P40 Substitute (Thermo Fisher Scientific, Cat. #AAJ19628AP), 0.01% bovine serum albumin (New England Biolabs, Cat. # B9000S), 0.15 mM of spermine (Sigma-Aldrich, Cat. # S3256-1G), 0.5 mM spermidine (Sigma-Aldrich, Cat. # S2626-1G), and 1:40 Protector RNase Inhibitor (Roche, Cat. # 3335399001) to ST stock. For each specimen, 3 ml working ST buffer was made by adding 1:100 Protector RNase Inhibitor to ST stock. Nuclei resuspension solution (NRS) was prepared by adding 1% BSA (Miltenyi, Cat. # 130- 091-376) and 1:40 Protector RNase inhibitor to PBS (Gibco, Cat. # 10010023). Snap-frozen tumor chunks were placed in microcentrifuge tubes with 1mL NST and manually minced with fine straight tungsten carbide scissors (Fine Science Tools; Cat. # 15514-12) for 8 min. Nuclei suspension was then passed over a 30-micron cell strainer (Miltenyi Biotec; Cat. # 130-098-458) into a 15 mL conical tube (ThermoFisher Scientific; Cat. # 339651). Microcentrifuge tubes and strainers were washed with an additional 1mL NST, then nuclei suspensions were diluted with 3mL ST buffer. Following this, suspensions were centrifuged for 5 min at 500g, 4 °C with slow brake. Following inspection of the pellet, the supernatant was removed, and the pellet was resuspended in 150-200 μL of NRS and then passed through a FACS tube filter (Falcon; Cat. #352235). Nuclei were then quantified using a disposable hemocytometer (inCYTO; Cat. # 82030-472) in brightfield and then diluted or concentrated in NRS, as described in section 1.1 of the 10x 3’ v3.1 Single Cell Gene Expression protocol (https://www.10xgenomics.com/support/single-cell-gene-expression/documentation/steps/library-prep/chromium-single-cell-3-reagent-kits-user-guide-v-3-1-chemistry).
Single-cell gene expression libraries were generated using the above-mentioned 10x protocol (https://www.10xgenomics.com/support/single-cell-gene-expression/documentation/steps/library-prep/chromium-single-cell-3-reagent-kits-user-guide-v-3-1-chemistry), up to 12 samples were pooled per flow-cell and then sequenced on a NovaSeq S2 (Illumina) with the following paired-end read configuration: read 1: 28 nt; read 2: 90 nt; i7 index read: 10 nt; i5 index read: 10 nt
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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 |
BCL files were converted to FASTQ using Illumina’s BCL Convert Tool. CellRanger (version 7.0.1) was used to demultiplex the FASTQ reads, and align them to the mm10 mouse transcriptome (mm10_premrna-1.2.0). We then used CellBender remove background (version 0.2.0) Terra workflow (snapshot 11) to remove ambient RNA and other technical artifacts from the count matrices. We used a false positive rate of 0.01 along with a number of epochs ranging between 150 and 200 and a learning rate comprised between 5e-5 and 1e-4. We set the parameters “expected cells” based on the estimated number of cells from the CellRanger output. For downstream analyses, we used CellBender’s output file (out_filtered.h5). Next, we filtered the combined gene expression matrix to only include high-quality nuclei using the following criteria: total genes in ]400-6,000[, total counts in ]1,000-35,000[, percent mitochondrial counts < 5%, percent ribosomal counts < 5%, cellular complexity (log10 Genes per UMI) > 0.8. We identified doublets at a per-sample basis using the quality control filtering steps previously mentioned in combination with DoubletFinder (version 2.0.3) and removed them from each gene*nuclei expression matrices. We additionally removed genes that were not detected in at least 100 nuclei across the entire dataset.
Assembly: mm10
Supplementary files format and content: R Data Serialization (rds)
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| Submission date |
Jun 07, 2024 |
| Last update date |
Jun 17, 2024 |
| Contact name |
Julien Dilly |
| E-mail(s) |
julien_dilly@dfci.harvard.edu
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| Phone |
6174167457
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| Organization name |
Dana-Farber Cancer Institute
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| Department |
Medical Oncology
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| Lab |
Aguirre
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| Street address |
450 Brookline avenue
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02215 |
| Country |
USA |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE269313 |
Mechanisms of resistance to oncogenic KRAS inhibition in pancreatic cancer |
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| Relations |
| BioSample |
SAMN41736701 |
| SRA |
SRX24833755 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8312897_KPC_3975_processed_snRNAseq.rds.gz |
94.5 Mb |
(ftp)(http) |
RDS |
SRA Run Selector |
| Raw data are available in SRA |
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