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| Status |
Public on Jan 01, 2024 |
| Title |
BM_2_ScRNAseq |
| Sample type |
SRA |
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| Source name |
Bone marrow
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| Organism |
Mus musculus |
| Characteristics |
tissue: Bone marrow
strain: C57BL/6J
Sex: Female
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| Extracted molecule |
total RNA |
| Extraction protocol |
Bone marrow, lymph node and peripheral blood cells isolated from C57BL/6J female mice were stained with Live/Dead dye and lymphocytes were isolated using a BDFACSAria™ IIISorter. Cells were manually counted by Trypan blue and AO-PI after each centrifugation and resuspension.
By using Chromium Next GEM Single Cell 5' Kit v2 (10x Genomics, 1000263) and Chromium Next GEM Chip K Single Cell Kit (10x Genomics, 1000287), we performed single cell TCR/BCR-seq and 5’ gene expression profiling. The cell suspension was loaded onto the Chromium single cell controller (10x Genomics) to generate single-cell gel beads in the emulsion according to the manufacturer’s protocol. Captured cells were lysed and the released RNA were barcoded through reverse transcription in individual GEMs. Cell-barcoded 5’ gene expression libraries and V(D)J enriched TCR/BCR libraries were sequenced on an Illumina NovaSeq6000 system.
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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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| Data processing |
Sequencing reads from gene expression and V(D)J libraries were aligned to mm10 mouse reference genome using cellranger 7.0.0 with “multi” mode. The generated count matrices and V(D)J contig annotations were used for downstream analysis performed with Seurat(v4.1.1) and Scirpy(v0.11.2). All samples were aggregated into a single SeuratObject. Cells with gene number (<300 & >97.5% quantile) or high mitochondrial transcript ratio (>25%), and genes expressed in less than 3 cells were excluded. After removing unwanted cells from the dataset, all samples were combined with function "merge". Next, we employed a global-scaling normalization method "LogNormalize" to normalize the feature expression measurements (UMI counts) for each cell by the total expression, then data integration was performed by canonical correlation analysis according to shared sources of variation across multiple datasets using SelectIntegrationFeatures, FindIntegrationAnchors and IntegrateData functions. Highly variable genes (top 3000) were extracted to perform the principal component analysis (PCA) and top 30 of significant principle components were used for cluster analysis. Clusters were visualized using the Uniform Manifold Approximation and Projection (UMAP). Marker genes for each cluster and subgroup were identified by contrasting gene expression of cells from certain cluster or subgroup to that of others using the Seurat FindMarkers function.
Assembly: mm10
Supplementary files format and content: Matrix table with raw gene counts
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| Submission date |
Dec 07, 2023 |
| Last update date |
Jan 01, 2024 |
| Contact name |
yifan zhang |
| E-mail(s) |
23110700099@m.fudan.edu.cn
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| Organization name |
fudan university
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| Street address |
no
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| City |
shanghai |
| ZIP/Postal code |
201508 |
| Country |
China |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE249618 |
A biphenotypic lymphocyte subset displays both T- and B-cell functionalities |
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| Relations |
| BioSample |
SAMN38718430 |
| SRA |
SRX22819442 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM7951842_BM_2_ScRNAseq_barcodes.tsv.gz |
30.6 Kb |
(ftp)(http) |
TSV |
| GSM7951842_BM_2_ScRNAseq_features.tsv.gz |
284.1 Kb |
(ftp)(http) |
TSV |
| GSM7951842_BM_2_ScRNAseq_matrix.mtx.gz |
30.5 Mb |
(ftp)(http) |
MTX |
SRA Run Selector |
| Raw data are available in SRA |
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