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| Status |
Public on Feb 17, 2022 |
| Title |
COV154 |
| Sample type |
SRA |
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| Source name |
Peripheral blood
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| Organism |
Homo sapiens |
| Characteristics |
disease state: COVID-19
tissue: Peripheral blood
cell type: peripheral blood mono-nuclear cells
age: 39
gender: male
disease symptom: asymptomatic
disease severity: asymptomatic
disease duration: short term
patient comorbidity: Yes
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| Extracted molecule |
total RNA |
| Extraction protocol |
Retrieving the PBMC-containing cryo-tubes from the -196℃ liquid nitrogen storage tank and placing them in a 37℃ water bath for rapid thawing. PBMCs were mixed with 10 mL washing medium (90% DMEM+10% FBS) in a 15-mL polypropylene tube and centrifuged at 500g for 20 min. The supernatant was then aspirated (repeat twice). The cell pellets were resuspended with 500 μl× PBS (0.04% BSA) in the sterile RNase-free vacutainer tubes and added with 5 ml 1× red blood cell lysis buffer (MACS 130-094-183, 10×) and incubated at room temperature for 10 min to lyse remaining red blood cells. After incubation, the suspension was centrifuged at 500g for 20 min at room temperature. The suspension was resuspended in 100 μl Dead Cell Removal MicroBeads (MACS 130-090-101) and remove dead cells using Miltenyi ® Dead Cell Removal Kit (MACS 130-090-101). Then the suspension was resuspended in 1× PBS (0.04% BSA) and centrifuged at 300 g for 3 min at 4 °C (repeat twice). The cell pellet was resuspended in 50 μl of 1× PBS (0.04% BSA). The overall cell viability was confirmed by trypan blue exclusion, which needed to be above 85%, single cell suspensions were counted using a Countess II Automated Cell Counter and concentration adjusted to 700-1200 cells/μl.
RNA libraries were prepared for sequencing using standard Illumina protocols
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
Illumina bcl2fastq software used for for basecalling.
we further reduced the dimensionality of all 207,718 cells by Seurat and used t-Distributed Stochastic Neighbor Embedding (t-SNE) to project the cells into 2D space. The steps included:1.Using the LogNormalize method of the "Normalization" function of the Seurat software to calculated the expression value of genes; 2.PCA (Principal component analysis) analysis was performed using the normalized expression value, Within all the PCs, the top 10 PCs were used to do clustering and t-SNE analysis; 3.To find clusters, selecting weighted Shared Nearest Neighbor (SNN) graph-based clustering method. Marker genes for each cluster were identified with the "bimod"(Likelihood-ratio test)with default parameters via the FindAllMarkers function in Seurat. This selects markers genes which were expressed in more than 10% of the cells in a cluster and average log (Fold Change) of greater than 0.26. To further avoid interference of putative multiplets (where more than one cell may have loaded into a given well on an array), cells in defined cluster had high expression of more than one cell type canonical marker gene (Figure 1, Supplementary Figure 1 ) so that were considered low quality were filtered out. Finally, 119,799 cells were kept in this experiment. Next, the nine cell types were integrated for further subclustering. After integration, genes were scaled to unit variance. Scaling, principal component analysis and clustering were performed as described above.
using "bimod" with default parameters in Seurat. DEGs were filtered using a minimum log2 (fold change) of 0.26, a P value < 0.05 and detection in > 10% of cells in at least one group. To further understand the associations and function of the DEGs, we performed a GO annotation analysis and a KEGG analysis. DEGs with a log2 mean expression difference ≥ 0.26 enriched in GO or KEGG pathways were considered as candidate biomarkers or pathway for the pathogenesis.
Genome_build: GRCh38_v96
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| Submission date |
Jan 19, 2021 |
| Last update date |
Feb 17, 2022 |
| Contact name |
chengsheng zhang |
| E-mail(s) |
cszhang99@126.com
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| Organization name |
First Affiliated Hospital of Xi 'an Jiaotong University
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| Department |
precision medicine center
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| Street address |
277 West Yanta Road, Xi'an, Shaanxi, P.R.China
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| City |
Xian |
| State/province |
Shaanxi |
| ZIP/Postal code |
710061 |
| Country |
China |
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| Platform ID |
GPL24676 |
| Series (1) |
| GSE165080 |
Identification of distinct immune cell subsets associated with various clinical presentations, disease severity and viral persistence of SARS-CoV-2 infection |
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| Relations |
| BioSample |
SAMN17379573 |
| SRA |
SRX9895202 |
| 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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