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Sample GSM5387649 Query DataSets for GSM5387649
Status Public on Jun 17, 2021
Title Quant-Seq Day 9 Brownjohn-iMicroglia LPS Rep 01
Sample type SRA
 
Source name Day 9 Brownjohn-iMicroglia
Organism Homo sapiens
Characteristics cell type: Brownjohn-iMicroglia
treatment: Day 9 LPS
Treatment protocol For QuantSeq, treatment with PBS (control) or 100 ng/ml 24h LPS treatment on Day 8 iTF-Microglia or Brownjohn-iMicroglia
Growth protocol For CROP-seq, inducible CRISPRi-iTF-iPSCs were infected with the pooled sgRNA library at <0.15 MOI and then selected for lentiviral integration. For both QuantSeq and CROP-seq, iTF-iPSCs were differentiated into iTF-microglia and cultured with the addition of TMP with the following conditions: iTF-iPSCs were grown in StemFlex until reaching at least 50% confluency and were grown for at least 24h without ROCK inhibitor. They were dissociated with Accutase and centrifuged and pelleted cells were resuspended in Day 0 differentiation medium containing the following: Essential 8™ Basal Medium (Gibco; Cat. No. A15169-01) as a base, 10nM ROCK inhibitor, and 2 mg/ml Doxycycline (Clontech; Cat. No. 631311). iTF-iPSCs were counted and seeded onto double coated plates (Poly-D-Lysine-precoated Bio plates (Corning, assorted Cat. No.) + Matrigel coating) with the following seeding densities: 10,000 cells/well for 96-well plate, 0.1 Mio/well for 12-well plate, 0.15 Mio/well for 6-well plate, 2 Mio/dish for 10-cm dish, and 8 Mio/dish for 15-cm dish. On day 2, media was replaced with Day 2 differentiation media containing Advanced DMEM/F12 Medium (Gibco; Cat. No. 12634-010) as a base medium containing the following: 1X Antibiotic-Antimycotic (Anti-Anti) (Gibco; Cat. No. 15240-062), 1X GlutaMAX™ (Gibco; Cat. No. 35050-061), 2 mg/ml doxycycline, 100 ng/ml Human IL34 (Peprotech; Cat. No. 200-34) and 10 ng/ml Human GM-CSF (Peprotech; Cat. No. 300-03). On day 4 and day 6, the medium was replaced with iTF-Microglia medium, containing Advanced DMEM/F12 as a base medium and the following: 1X Anti-Anti, 1X GlutaMAX, 2 mg/ml doxycycline, 100 ng/ml Human IL-34 and 10 ng/ml Human GM-CSF, 50 ng/ml Human M-CSF (Peprotech; Cat. No. 300-25) and 50 ng/ml Human TGFB1 (Peprotech; Cat. No. 100-21C).
Extracted molecule total RNA
Extraction protocol For QuantSeq, cell culture medium was aspirated, cells were washed once with DPBS, and RNA lysis buffer was added directly to wells containing either Day 0 iTF-iPSCs, Day 9 iTF-Microglia or Brownjohn-iMG +/- 100 ng/ml 24h LPS treatment, or Day 15 iTF-Microglia. Biological triplicates for each condition (approximately 0.15 Mio cells each) were pelleted, snap frozen, and stored at -80°C. RNA was extracted using the Quick-RNA Miniprep Kit (Zymo; Cat. No. R1055). For CROP-seq, Day 8 iTF-Microglia were washed 3X with DPBS, dissociated with TrypLE, and resuspended in nuclease-free water before loading onto four wells of the 10x Chromium Controller (10x Genomics, v3.1) according to the manufacturer’s protocol, with 35,000 cells recovered per sample as the target. 
For QuantSeq, libraries were prepared from total RNA (473 ng per sample) using the QuantSeq 3‘ mRNA-Seq Library Prep Kit for Illumina (FWD) (Lexogen; Cat. No. 015UG009V0252) following the manufacturer’s instructions. Library amplification was performed with 14 total PCR cycles. mRNA-seq library concentrations (mean of 1.13 ± 0.66 ng/uL) were measured with the Qubit dsDNA HS Assay Kit (Invitrogen; Cat. No. Q32851) on a Qubit 2.0 Fluorometer. Library fragment-length distributions (mean of 287 ± 28 bp) were quantified with High Sensitivity D5000 Reagents (Agilent Technologies; Cat. No. 5067-5593) on the 4200 TapeStation System. The libraries were sequenced on an Illumina NextSeq 2000 instrument with single-end reads. For CROP-seq, sample preparation was performed using the Chromium Next GEM Single Cell 3′ Reagent Kits version 3.1 (10x Genomics, cat. no. PN-1000121) according to the manufacturer’s protocol, reserving 10-30 ng full-length cDNA to facilitate sgRNA assignment by amplifying sgRNA-containing transcripts using hemi-nested PCR reactions adapted from a previously published approach (Hill et al., 2018; Tian et al., 2019). cDNA fragment analysis was performed using the 4200 TapeStation System and sgRNA enrichment libraries were separately indexed and sequenced as spike-ins alongside the whole-transcriptome scRNA-seq libraries using a NovaSeq 6000 using the following configuration: Read 1: 28; i7 index: 8; i5 index: 0; Read 2: 91. 
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model NextSeq 2000
 
Data processing QuantSeq: Alignment and mapping were performed using Salmon version 1.4.0 (Patro et al., 2017), with the --noLengthCorrection flag and either the human reference genome GRCh38 (Gencode, release 37), or a custom GRCh38 reference genome containing the references for each 3TF transgene integrated in iTF-iPSCs, to obtain transcript abundance counts. CROP-Seq: Alignment and gene expression quantification was performed on scRNAseq libraries and sgRNA-enriched libraries using Cell Ranger (version 5.0.1, 10X Genomics) with default parameters and reference genome GRCh38-3.0.0. Cellranger aggr was used to aggregate counts belonging to the same sample across different GEM wells. The resulting gene vs. cell barcode matrix contained 58,302 cells which had on average 41,827 reads per cell, and a median of 3,346 genes per cell.
QuantSeq: Tximport version 1.18.0 (Soneson et al., 2015) was used to obtain gene-level count estimates. Genes with zero counts across all samples were removed from the analysis. CROP-seq: sgRNA unique molecular identifier (UMI) counts for each cell barcode were obtained using a previously described mapping workflow (Hill et al., 2018). To facilitate sgRNA identity assignment, a combination of demuxEM (Gaublomme et al., 2019) and a z-score cut-off method we previously described (Tian et al., 2019) were used such that only cells with a single sgRNA as determined by both methods were carried forward in the analysis.
QuantSeq: For differential gene expression analysis of LPS-treated vs. PBS-treated iTF-Microglia samples, DESeq2 version 1.30.1 (Love et al., 2014) was used to calculate the log-fold-change and p-values and perform shrinkage of log-fold-change for downstream visualization using ggplot2 version 3.3.3. CROP-seq: The raw gene vs. barcode matrix outputted by Cell Ranger was converted into a SingleCellExperiment (SCE) object using the read10xCounts function from the DropletUtils package version 1.10.3 (Lun et al., 2019) in R (v 4.0.3). sgRNA assignments were appended to the SCE metadata and filtered to only include cells with a single sgRNA, resulting in 28,905 cells. The SCE was converted into a Seurat object using Seurat::as.Seurat version 4.0.1 (Hao et al., 2020).
CROP-Seq: The data was normalized and highly variable genes were identified using Seurat::SCTransform (Hafemeister and Satija, 2019). For initial data exploration, principal-component analysis was performed using Seurat::RunPCA to determine the number of principal components to retain. UMAP dimensional reduction using Seurat::RunUMAP and clustering using Seurat::FindNeighbors and Seurat::FindClusters were performed on the retained principal components with resolution = 0.7.
CROP-Seq: To determine the differentially expressed genes between UMAP clusters, Seurat::FindAllMarkers was used.
Genome_build: GRCh38
Supplementary_files_format_and_content: The processed data files for CROP-seq are hdf5 formatted matrices of UMI counts, with rows as genes and columns as cell barcodes, obtained from running cellranger count.
 
Submission date Jun 16, 2021
Last update date Jun 17, 2021
Contact name Martin Kampmann
E-mail(s) martin.kampmann@ucsf.edu
Organization name UCSF
Lab Martin Kampmann
Street address 675 Nelson Rising Ln
City San Francisco
State/province CA
ZIP/Postal code 94158
Country USA
 
Platform ID GPL30173
Series (1)
GSE178317 A CRISPRi/a platform in iPSC-derived microglia uncovers regulators of disease states
Relations
BioSample SAMN19729561
SRA SRX11157674

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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