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| Status |
Public on Jan 24, 2024 |
| Title |
dpi7_contra_3 |
| Sample type |
SRA |
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| Source name |
cortex, contralateral
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| Organism |
Mus musculus |
| Characteristics |
tissue: cortex, contralateral
disease state: stroke
cell type: microglia
genotype: Spp1-CreER: R26-Tdtomato
development stage: P13
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| Treatment protocol |
Brains were homogenized in ice-cold HBSS supplemented with 15mM HEPES and 0.5% glucose by 5 gentle strokes in a 7 mL glass Dounce homogenizer. Myelin debris were removed by density gradient separation; pellet was resuspended in 40% Percoll and centrifuged in 800G for 20 min at 4°C. Isolated microglia were labeled with a combination of conjugated antibodies, and Flow-sorted for subsequent library construction.
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| Extracted molecule |
total RNA |
| Extraction protocol |
For bulk RNA-Seq, 2,000 freshly sorted microglia were lysed in 10μL TCL buffer (QIAGEN) supplemented with 1% 2-mercaptoethanol. For single cell RNA-Seq, cell hashing was performed by incubating the single cell suspensions with antibody cocktails containing FACS antibodies and TotalSeq antibody (Biolegend) at 1:100 final dilution for each antibody, followed by incubation for 30min on ice. Next, cells were washed and CD45+CD11b+CX3CR1+ were sorted for single cell capturing and library preparations. Briefly, 70,000 cells pooled from 10 biological samples (with 1-8 mice pooled per sample) were partitioned into nanoliter Gel-bead-inEmulsions (GEMs) droplets using the Chromium Single Cell 3′ V3.1 Kits (10x Genomics). For ATAC-Seq, 15,000 to 20,000 freshly sorted microglia per sample were lysed for 4 min on ice in 50μl lysis buffer. The nuclei were then collected and incubated with Tn5 transposase and tagmentation buffer at 37°C for 20 min, followed by DAN purification using Tagment DNA extract beads. For single cell RNA-Seq, cell hashing was performed by incubating the single cell suspensions with antibody cocktails containing FACS antibodies and TotalSeq antibody (Biolegend) at 1:100 final dilution for each antibody, followed by incubation for 30min on ice. Next, cells were washed and CD45+CD11b+CX3CR1+ were sorted for single cell capturing and library preparations. Briefly, 70,000 cells pooled from 10 biological samples (with 1-8 mice pooled per sample) were partitioned into nanoliter Gel-bead-inEmulsions (GEMs) droplets using the Chromium Single Cell 3′ V3.1 Kits (10x Genomics). In brief, 15,000 to 20,000 freshly sorted microglia per sample were lysed for 4 min on ice in 50μl lysis buffer. The nuclei were then collected and incubated with Tn5 transposase and tagmentation buffer at 37°C for 20 min, followed by DAN purification using Tagment DNA extract beads.
For bulk RNA-Seq, full-length RNA-seq libraries were prepared following a modified SMART-Seq2 protocol. The cDNA libraries were generated using the TruePrep RNA Library Prep Kit for Illumina and pair-end sequenced (150 bp × 2) with Novaseq 6000 (Illumina).Single cell gene expression libraries and feature barcoding libraries were generated as recommended by the 10x Genomics Chromium Single Cell 30 Reagent Kits User Guide with appropriate modifications to the PCR cycles based on the calculated cDNA concentration. Libraries were pair-end (150bp x2) sequenced on a NovaSeq 6000 system (Illumina). ATAC-Seq libraries were prepared with Chromatin Profile Kit (Novoprotein; N248) following the manufacturer’s instructions. The complete DNA elute was then amplified for 13 PCR cycles with indexed primers. Following DNA clean-up with Ampure XP beads, the libraries were analyzed with Bioanalyzer for quality control, and subsequently pair-end sequenced (150 bp x 2) with a Novaseq6000 system (Illumina).
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
dpi7.raw_tpm.csv
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| Data processing |
For bulk RNA-Seq, FASTQ files were trimmed using cutadapt (v2.10) with ‘-q 30’ and aligned to the mouse genome/transcriptome (GENCODE GRCm38 vM25, mm10) using STAR (v2.7.5c) with ‘twopassModeBasic’. The expression abundances were estimated (expected counts and TPM values) using RSEM (v1.3.3). COMBAT was used to correct for batch effects. The count matrix was processed with the edgeR package (v3.32.0) in R to calculate DEGs with the default parameters. Principal component analysis (PCA) was run on the centered expression matrix of the top 2000 variable genes. Gene set enrichment analyses (Broad, GSEA 4.2.3 build 10) and TopGO (v2.40.0) were used for pathway analysis with graphical rendering using clusterProfiler (v3.16.1). Heatmaps were plotted with Complexheatmap (v2.6.2).
For single cell RNA-Seq, Reads processing, alignment to the mm10 transcriptome and unique molecular identifier(UMI) counting/collapsing were performed using Cellranger toolkit (v7.0.0, 10x Genomics) with ‘—include-introns false’. Main downstream analysis like ‘Demultiplexing with hashtag oligos (HTOs)’, clustering and filtering were run with Seurat (v4.1.1) in R(v4.1.3)/Rstudio.
For ATAC-Seq, Cutadapt(v2.10) trimmed reads were aligned to mouse genome (ENCODE, GRCh38 GCA_000001405.15) with bowtie2(v2.2.5) “-I10 -X2000 --very-sensitive-local --no-mixed --no-discordant”. For advanced filtering, samtools(v1.10), bedtools(v2.29.2) and picard(v2.23.8) MarkDuplicates were used to remove bad-quality, blacklist-region reads and duplicates as mentioned in kundajelab pipeline(github.com/kundajelab/atac_dnase_pipelines). Then the clean bam files were used to generate normalized bigwig files with deeptools(v3.5.0) “bamCoverage -e250 -bs100 --normalizedUsing RPKM”. And Genome-wide signal correlation of each two samples were processed and plotted using ‘multiBigwigSummary bins -bs 5000’ and ‘plotCorrelation’.
Assembly: mm10
Supplementary files format and content: csv file includes raw tpm for each sample (bulk RNA-Seq)
Supplementary files format and content: CellRanger output matrix files and HTO setting csv file packaged in format .zip (single cell RNA-Seq)
Supplementary files format and content: Final Seurat Object in format .rds (single cell RNA-Seq)
Supplementary files format and content: Final nodup, clean and normalized genomic signal in format .bigwig (ATAC-Seq)
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| Submission date |
Nov 09, 2023 |
| Last update date |
Jan 24, 2024 |
| Contact name |
DANYANG HE |
| E-mail(s) |
hedanyang@westlake.edu.cn
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| Organization name |
Westlake Univeristy
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| Department |
School of Life Sciences
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| Lab |
Laboratory of Neuroimmunology
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| Street address |
600 Dunyu Road Sandun Town
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| City |
Hangzhou |
| State/province |
Zhejiang |
| ZIP/Postal code |
310024 |
| Country |
China |
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| Platform ID |
GPL24247 |
| Series (2) |
| GSE247391 |
Fate-mapping via Spp1-expression history revealed innate immune memory of microglia imprinted by neonatal injury [Spp1Tdt] |
| GSE247394 |
Fate-mapping via Spp1-expression history revealed innate immune memory of microglia imprinted by neonatal injury |
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| Relations |
| BioSample |
SAMN38180996 |
| SRA |
SRX22456492 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
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