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Sample GSM5975317 Query DataSets for GSM5975317
Status Public on Apr 29, 2022
Title Microglia_KO1
Sample type SRA
 
Source name FACS sorted quiescent microglia
Organism Mus musculus
Characteristics tissue: microglia
genotype: PRMT1-KO
treatment: Cuprizone 0.2% diet
Treatment protocol Cuprizone 0.2% diet was given to 5-6weeks old mice for 5 weeks
Growth protocol Microglia were FACs purified using CD11b and CD45 markers
Extracted molecule total RNA
Extraction protocol scRNA libraries were generated using the GemCode Single- Cell Instrument (10x Genomics, Pleasanton, CA, USA) and Single Cell 3’ Library & Gel Bead Kit v2 and Chip Kit (P/N 120236 P/N 120237 10x Genomics). The sequencing ready libraries were purified with SPRIselect, quality controlled for sized distribution and yield (LabChip GX Perkin Elmer), and quantified using qPCR (KAPA Biosystems Library Quantification Kit for Illumina platforms P/N KK4824) as previously described(Couturier et al., 2020). Libraries were subsequently shipped and sequenced using Illumina NovaSeq6000 at IGM Genomics Center, UCSD, San Diego, CA.
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NovaSeq 6000
 
Data processing Cell barcodes and UMI (unique molecular identifiers) barcodes were demultiplexed and paired-end reads were first aligned to the mouse genome (mm10) using the Cell Ranger software v3.1.0
Pre-processing was then carried out with the Seurat v3.2.0 R package (Butler et al., 2018). Genes detected in less than 3 cells as well as cells containing less than 200 genes detected were removed.
Cells were further filtered out for each sample based on the distribution of genes detected as well as the percentage of mitochondrial counts to balance the number of cells per sample to ~4000, and the raw count matrices of all samples were merged. Read counts for each cell were then normalized by the cell total, multiplied by 10000 and natural-log transformed.
The expression of the 2000 genes with highest cell-to-cell variation was standardized and the heterogeneity associated with mitochondrial contamination was regressed out. Principal component analysis was performed on the scaled data and the top 10 principal components were used to construct a K-nearest neighbor cell graph. Clustering of cells was carried out through the Louvain algorithm with the granularity parameter set to 0.4 and visualized with the Uniform Manifold Approximation and Projection (UMAP) (Becht et al., 2019) dimensional reduction technique using the Scanpy v1.5.2 python module (Wolf et al., 2018).
Cluster biomarkers were identified using the Wilcoxon Rank Sum test. Cell trajectories across pseudotime were analyzed by the Monocle v2.16.0 R package (Trapnell et al., 2014). Cell progress was defined by differentially expressed genes based on the clusters identified by Seurat. The dimensionality of the data was reduced through the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm to two dimensions and the cells were ordered along the trajectory according to pseudotime. Genes with branch-dependent expression were identified through the branched expression analysis modeling (BEAM) test. RNA velocity analysis was performed by the scVelo v0.2.2 python module (Bergen et al., 2020). Spliced and unspliced mRNAs were first distinguished through the velocyto v0.17.17 python module (La Manno et al., 2018). Velocities representing the direction and speed of cell motion were then computed and projected onto the UMAP embedding.
Assembly: mm10
Supplementary files format and content: mtx
 
Submission date Mar 28, 2022
Last update date Apr 29, 2022
Contact name Stephane Richard
Organization name McGill University
Street address 3755 Côte Ste-Catherine Road
City Montreal
ZIP/Postal code H3T 1E2
Country Canada
 
Platform ID GPL24247
Series (1)
GSE199574 scRNAseq from WT and PRMT1-KO microglia
Relations
BioSample SAMN27022676
SRA SRX14636946

Supplementary file Size Download File type/resource
GSM5975317_KO_1matrix.mtx.gz 82.5 Mb (ftp)(http) MTX
GSM5975317_barcodes.tsv.gz 51.9 Kb (ftp)(http) TSV
GSM5975317_features.tsv.gz 284.1 Kb (ftp)(http) TSV
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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