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62 protocols using chromium single cell 3 reagent kit v2

1

Single-cell transcriptomics of colon samples

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PBL or colon single-cell suspensions from each patient were pooled with equivalent number of live cells and resuspended at 1–2.5 × 103 cells/µl in 0.04%BSA/PBS, with the addition of 10 µM Y-27632 (MedChem Express) for colon samples. Samples from unique individuals were pooled, and samples from the proximal (Right,R) or distal (Left,L) colon of the same individual were placed in separate pools, so each sample could later be uniquely identified using demuxlet21 (link). For the primary biopsy UC and VDZ analysis, the two pools were loaded into four wells each of a Chromium Single Cell 3′ v2 Reagent Kit (10X Genomics), with a total of 8 wells (Supplementary Table 2). 1 × 106 cells of both single-cell colon suspension pools were stained with a custom TotalSeq-A panel, (BioLegend) (Supplementary Table 3) according to the manufacturer’s instructions and loaded into two wells. For all experiments, 60,000 cells were loaded per well and processed for single-cell encapsulation and cDNA library generation using the Chromium Single Cell 3′ v2 Reagent Kits (10X Genomics). TotalSeq-A library generation was performed according to manufacturer’s instructions (BioLegend). Libraries were sequenced on an Illumina NovaSeq6000 to obtain 25,000 reads per cell for the gene expression libraries and 10,000 reads per cell for the TotalSeq libraries.
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2

Single-cell RNA-Seq of mouse and human neural cells

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Mouse Cluster#C cells were FACS-sorted using the flow cytometry panel shown in Figure S10A. Human hNeP were FACS-sorted by using the flow cytometry panel shown in Figure 5A. Single cell RNA-Sequencing was performed using Chromium™ Single Cell 3’ v2 Reagent Kits (10x Genomics) following the manufacturer’s protocol(Zheng et al., 2017 (link)). Briefly, after sort collection, cells were resuspended in PBS at concentration ranging between 400 to 600 cells per µl. Between 5,000 to 10,000 cells were loaded for gel bead-in-emulsion generation and barcoding. To increase barcode diversity, samples were split in 2 technical replicates for all downstream steps: Reverse transcription, cDNA amplification, fragmentation and library preparation. Final libraries with size ranging between 200 to 1000 bp were size-selected using Ampure XP beads (Beckman Coulter). Quality and quantity of samples was controlled at multiple steps during the procedure by running small fraction (< 5%) of sample on BioAnalyzer (high sensitivity DNA chip, Agilent). Libraries were sequenced on HiSeq2500 platform to obtain 26 (read1) x 100 (read2) paired-end reads.
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Single-cell RNA-seq of Tumor-Infiltrating Immune Cells

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For the discovery cohort scRNA-seq, live CD3-CD19/20-CD56- SSC-A dim CD16 dim (to exclude neutrophils) cells were sorted from a melanoma involved draining LN on a BD FACSAria Fusion. For the discovery cohort the same sorting strategy was applied to melanoma, kidney and head and Neck primary tumors. After sorting, cells were pelleted and resuspended at 1x10e3 cells/ul in 0.04%BSA/PBA and loaded onto the Chromium Controller (10X Genomics). Samples were processed for single-cell encapsulation and cDNA library generation using the Chromium Single Cell 3’ v2 Reagent Kits (10X Genomics). The library was subsequently sequenced on an Illumina HiSeq 4000 (Illumina). All samples were sequenced at 25,000 reads per cell.
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4

Single-cell RNA-seq protocol for WCBM and Image-seq

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WCBM and Image-seq samples were counted in a hemocytometer and encapsulated for a maximum output of 8,000 cells into emulsion droplets using the Chromium Controller (10x Genomics). scRNA sequencing libraries were subsequently prepared using Chromium Single Cell 3 v2 Reagent kits (10x Genomics). Reverse transcription and library preparations were done on a Biorad T100 Thermo Cycler (Biorad). cDNA libraries and final libraries were quantified on an Agilent BioAnalyzer (Agilent Technologies) using a High Sensitivity DNA kit (Agilent Technologies). Libraries were diluted to 4 nM and pooled before sequencing on the NextSeq 500 Sequencing system (Illumina). Pools were sequenced with 75 cycle run kits (26 bp Read1, 8 bp Index1 and 55 bp Read2) to a saturation level of ~70–80%.
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5

10X Chromium scRNA-Seq Library Preparation

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The scRNA-Seq libraries were generated using the 10X Genomics Chromium Controller Instrument and Chromium Single Cell 3' V2 Reagent Kits (10X Genomics, Pleasanton, USA).
Briefly, cells nuclei were concentrated to 1000 nuclei/μL and approximately 15000 nuclei were loaded into each channel to generate single-cell Gel Bead-In-Emulsions (GEMs), which results into expected mRNA barcoding of 9000 single nucleus for each sample. After the RT step, GEMs were broken and barcoded-cDNA was purified and amplified. The amplified barcoded cDNA was fragmented, A-tailed, ligated with adaptors and index PCR amplified.
The final libraries were quantified using the Qubit High Sensitivity DNA assay (Thermo Fisher Scientific, USA) and the size distribution of the libraries were determined using a High Sensitivity DNA chip on a Bioanalyzer 2200 (Agilent, USA). All libraries were sequenced by HiSeq Xten (Illumina, USA) on a 150 bp paired-end run.
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6

Single-cell RNA-seq: 10xGenomics Workflow

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Cells were collected by trypsinization and processed according to the 10xGenomics scRNA-seq sample preparation protocol (Chromium Single Cell 3’ v2 Reagent Kit, 10xGenomics). 2,000 cells were targeted for each sample.
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7

Chromium Single-Cell 3' RNA-seq Protocol

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Enriched (Ficoll-Paque PREMIUM, GE Healthcare) mononuclear cells were used for Chromium single-cell 3′ RNA-seq. The gel beads in emulsion generation, cDNA amplification, and library preparation were performed according to the manufacturer’s instructions using Chromium Single Cell 3′ v2 Reagent Kit (10X Genomics) aiming for a 4000– to 6000–target cell capture per sample. The sample libraries were sequenced in Illumina HiSeq 2500 using Rapid mode aiming for sequencing depth of 50,000 reads per cell. The Cell Ranger v1.3 mkfastq and count analysis pipelines (10X Genomics) were used to demultiplex and convert Chromium single-cell 3′ RNA-seq barcode and read data to FASTQ files and to generate align reads and gene-cell matrices. The gene-barcode matrices were analyzed using the ScType scRNA-seq processing pipeline (31 ) with the Louvain cell clustering as implemented in Seurat v3.1.0 (32 (link)). Cells with either a low (below 100 to 200) or unexpectedly high number (3000 to 4000, depending on the sample) of detected genes, or cells with more than 8 to 10% of mitochondrial UMI (unique molecular modifier) counts, were classified as low-quality or uninteresting cells and were excluded from the analysis.
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8

Single-cell RNA-seq of tumor tissues

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Blood, tumors, and lungs were isolated from test groups and tumor-naïve animals. Tissues were dissociated into single cell suspension as described above. Staining for CD45 was performed as for PBMC FACS analysis. Samples were pooled across 3 animals per group, and CD45+ populations were FACS-sorted into PBS with 2% RNase-free BSA (Ambion). Then, the cells were processed according to the 10xGenomics sample preparation protocol (Chromium Single Cell 3’ v2 Reagent Kit, 10xGenomics). Two thousand cells were targeted for each sample.
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9

Single-nucleus RNA Sequencing of GTEx Samples

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Tissue samples were selected from among a subset of GTEx project samples that were flash frozen and banked. Nuclei from each sample were extracted using the EZ, CST, NST, and TST protocols described in (26 (link)). Libraries for snRNA-seq were generated using the Chromium Single Cell 3′ v2 Reagent Kit (10x Genomics), and sequencing was performed with Illumina HiSeq X (96 samples) or NextSeq (three samples), according to the manufacturer’s protocols. The resulting snRNA-seq data were aligned and quantified using CellRanger v2.1.0 (10x Genomics), ambient RNA correction was performed using CellBender (30 (link)), and low-quality nuclei were filtered out using standard criteria (28 ). The resulting snRNA-seq expression profiles were integrated across samples using a total correlation variational autoencoder (28 ). Detailed descriptions of all computational analyses are provided in (28 ).
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10

Single-cell RNA-Seq of Mixed Muscle and Adipose Cells

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The extracted primary muscle cells and adipocytes were sequentially subjected to preliminary quality inspection. Cell concentration and viability were determined using a Countstar BioMed Professional Immune Cell Counter (Life Science, Shanghai, China). Two single-cell suspensions of muscles containing cells and adipocytes were mixed. The volumes of liquid with similar concentrations were mixed in a ratio of 1:3 for the liquid and upper-layer cells. The mixed cell suspension was then adjusted to the ideal concentration of 1000/μL. The Chromium Single Cell Controller (10× Genomics, San Francisco, CA) was used to analyze 3000 recovered cells. The RNA from the barcoded cells was subsequently reverse-transcribed, and sequencing libraries were constructed with reagents from a Chromium Single Cell 3′ v2 Reagent Kit (10× Genomics) in accordance with the instructions provided by the manufacturer. Sequencing was performed with Illumina HiSeq 4000 as instructed by the manufacturer (CapitalBio Technology, Beijing, China). The sequencing length consisted of two parts: (i) 26 bp Read1, including a 16 bp barcode and a 10 bp UMI, and (ii) 98 bp Read2, which was the sample RNA sequence.
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