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Sample GSM5609422

Query DataSets for GSM5609422

Status

Public on Sep 08, 2022

Title

Spleen mito+

Sample type

SRA

Source name

House mouse

Organism

Mus musculus

Characteristics

cells: mito-dendra2+ Spleen cells

Treatment protocol

No treatment

Growth protocol

The F4/80+CD106+CD169+ macrophages were isolated from mito-Dendra2 mice and intravenously injected into wildtype mice after PHZ treatment. 5 days later, early erythroblasts (Ter119+Cd44+) were isolated from BM and spleen and separated into mito- and mito+ by flow cytometry based on the presence of mito-Dendra2 signal.

Extracted molecule

total RNA

Extraction protocol

Cells were washed, and processed using the 10x Genomics Chromium controller and Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 following manufacturer's instructions.
The library was prepared using 10xGenomics's Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 and dual index kit following manufacturer's instructions. Illumina P5 and P7 sequences and sample index sequences are added during the Sample Index PCR. The final library fragments contain the P5, P7, Read 1 and Read 2 sequences used in Illumina bridge amplification and sequencing. Additionally, each fragment contains the 10x Barcode, UMI and cDNA insert sequence used in data analysis. Sequencing was done by DNBseq platform at BGI Genomics.
Single cell RNA-Seq (3'GEM)

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

DNBSEQ-G400

Data processing

Raw reads were aligned to the pre-build mm10 reference genome using cellranger count v6.0.0 (10X Genomics) with default settings.
The molecule information file from mito- and mito+ samples were combined using cell ranger aggr with --normalize=none --nosecondary options.
Cells were removed if the number of UMIs was less than 500, the number of genes detected was less than 100, or ≥ 10% of reads were mapped to mitochondrial genes.
Read counts were normalized for each sample using the Seurat SCTransform function.
The variation due to mitochondrial RNA ratio and cell cycle phase scores were regressed out.
The normalized data from mito- and mito+ samples were integrated based on the 3,000 most highly variable genes using the Seurat integration procedure.
Top 40 principal components were used for Uniform manifold approximation and projection (UMAP) followed by cell clustering.
Marker genes for each cluster was identified using the Seurat FindConservedMarkers function.
Clusters were annotated by comparing the marker genes to known cell type markers from literatures.
Early erythroblast cells were used to identify differential exressed genes between mito- and mito+ samples using the Seurat FindAllMarkers function.
Genome_build: mm10
Supplementary_files_format_and_content: HDF5 file continaing a feature barcode matrix of early erythroblasts. This file can be loaded into R using Seurat.
Supplementary_files_format_and_content: TSV file containig the result of differential gene expression alaysis

Submission date

Oct 04, 2021

Last update date

Sep 08, 2022

Contact name

Rui Yokomori

Organization name

Cancer Science Institute of Singapore, National University of Singapore

Lab

Takaomi Sanda Lab

Street address

14 Medical Drive