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| Status |
Public on Aug 12, 2023 |
| Title |
22082R-05-06 |
| Sample type |
SRA |
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| Source name |
Cells
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| Organism |
Mus musculus |
| Characteristics |
tissue: Cells
cell line: BV2 Cells
cell type: Microglia
treatment: LPS
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| Treatment protocol |
BV2 cells were treated with either TGF-β (50 ng/mL), IL-10 (50 ng/mL), and LPS (100 ng/mL) for 72 hours
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| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted from BV2 cells and BV2 cell-derived extracellular vesicles using the Qiagen miRNeasy Mini Kit (Cat. No. 217004). 20 µL of EV fraction was resuspended in 700 µL of trizol lysis buffer. BV2 cell pellets were harvested in 700 μL of trizol lysis buffer. Added 140ul of chloroform was added to each sample and shook vigorously. Samples were then centrifuged for 15 min at 12,000 x g at 4°C. After centrifugation, the sample separated into 3 phases: an upper, colorless, aqueous phase containing RNA; a white interphase; and a lower, red, organic phase.
The top aqueous phase was carefully isolated without disturbing the other phases. The top aqueous phase was transferred to a new collection tube and 1.5 volumes of 100% ethanol was added and mixed by pipetting up and down. 700 μL of the sample was added to the provided spin column in collection tubes. Samples were spin at ≥8000 x g for 15 s at room temperature and the flow-through was discarded. This was repeated for the rest of the sample.
Bound RNA was washed 2 times using the included wash solution (Buffer RPE). Finally, a preheated elution solution (RNase-free water) was used to elute the RNA in 40 uL volume for cells and 20 uL for extracellular vesicles.
cDNA Libraries were prepared for small RNAs using the SMARTer smRNA-seq kit. A total of 18 cycles of PCR were carried out to obtain a good yield of cDNA from cells and EVs. Final library quality was verified with Qbit and bioanalyzer. Negative (no RNA) and positive controls provided expected results. Next-generation RNA sequencing was performed using a HiSeq X Illumina 2x150, 40M total reads per sample (20M each direction) at Admera Health.
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| Library strategy |
miRNA-Seq |
| Library source |
transcriptomic |
| Library selection |
size fractionation |
| Instrument model |
HiSeq X Ten |
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| Data processing |
RNA-seq analysis was conducted to identify genes exhibiting differential expression. The counts data provided information on the abundance of reads mapped to the reference genome or the number of fragments assigned to each gene. The primary objective was to identify systematic changes between the conditions of interest, specifically Control vs Treatment. The analysis utilized the Deseq2 package, developed by Michael I. Love, Simon Anders, and Wolfgang Huber (Package Authors). A Deseq2DataSetFromMatrix object was created, and the design parameter was set to ~Treatment, which captured the information on how the traits file was structured. For instance, in the case of n=4 Control vs n=4 LPS, the design matrix reflected these conditions.
To ensure data quality, the raw counts data were aligned to the traits file, following the documentation guidelines. Lowly expressed genes were filtered out based on the criterion of rowSums(counts(dds)) ≥ 30, meaning that only genes with 30 reads in total across all samples (5 X 6 samples = 30) were retained. This step was performed to remove genes with insufficient expression levels. Additionally, if required by the dataset, Ensembl IDs were converted to gene names for ease of downstream analysis. The control condition was designated as the reference for comparison, and genes exhibiting differential expression were identified using the criteria of adjusted p-value < 0.05 and log2 fold change (LFC > 0 for upregulated genes and LFC < 0 for downregulated genes).
It should be noted that in the comparison of Bulk RNA-seq on responder BV2 cells, the LPS samples were contrasted against the control (n = 4), deviating from the general protocol. Principal component analysis (PCA) was employed as an initial analysis step to identify patterns, relationships, and important variables in the high-dimensional dataset.
Assembly: Next generation sequencing
Supplementary files format and content: comma separated file includes raw counts for each sample
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| Submission date |
Aug 07, 2023 |
| Last update date |
Aug 12, 2023 |
| Contact name |
Srikant Rangaraju |
| E-mail(s) |
[email protected]
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| Organization name |
Emory University
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| Department |
Neurology
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| Street address |
615 Michael St
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| City |
Atlanta |
| State/province |
GA |
| ZIP/Postal code |
30322 |
| Country |
USA |
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| Platform ID |
GPL21273 |
| Series (2) |
| GSE240294 |
Identification of state-specific proteomic and transcriptomic signatures of microglia-derived extracellular vesicles [mirna-seq] |
| GSE240295 |
Identification of state-specific proteomic and transcriptomic signatures of microglia-derived extracellular vesicles |
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| Relations |
| BioSample |
SAMN36877072 |
| SRA |
SRX21285552 |
| 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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