chromium gem x scrna seq 3 v4 workflow  (10X Genomics)

Journal: bioRxiv

Article Title: Systematic mapping of emergent transcriptional states in interacting single-cell dyads by Cell-Cell-seq

doi: 10.64898/2026.02.05.704136

Figure Lengend Snippet: ( A ) Workflow schematic for the granzyme B secretion assay. PC3-A2-PAP tumor cells are first adhered inside gelatin-coated Nanovial cavities pre-functionalized with anti-granzyme B capture antibodies, T cells are added to establish defined contact for a controlled incubation interval (Δt), and secreted granzyme B bound locally is revealed with a fluorescent detection antibody. (B) Representative flow cytometry gates: identification of all Nanovials (FSC/SSC), enrichment of PC3-loaded Nanovials (GFP+), and detection of PC3-T cell dyads (T-cell marker, APC-Cy7). Right, bright-field/fluorescence microscopic image showing sorted Nanovials containing PC3-A2-PAP cells (green) paired with T cells (magenta). Scale bar, 50 µm. ( C ) Flow cytometry histograms of captured granzyme B signal across conditions: (i) no capture antibody (control for setting the signal threshold), (ii) PC3+TCR156-WT (weak TCR), (iii) PC3+TCR156-45 (potent TCR), (iv) pMHC-coated Nanovials+TCR156-45 (artificial antigen presentation), and (v) PMA/ionomycin activation (positive control). Percentages of events with granzyme B above the signal threshold (yellow region) are shown.

Article Snippet: To link defined cell-cell interactions with transcriptional state, we introduced sorted Nanovials containing tumor–T cell dyads into a droplet microfluidics scRNA-seq workflow (10x Genomics Chromium GEM-X).

Techniques: Incubation, Flow Cytometry, Marker, Fluorescence, Control, Immunopeptidomics, Activation Assay, Positive Control

Journal: Nature Communications

Article Title: Lifting regenerative barriers promotes epithelial cell fate plasticity supporting lineage conversion

doi: 10.1038/s41467-025-66446-9

Figure Lengend Snippet: A Overview of the scRNA-seq workflow (10x Genomics). Viable epithelial oe OE and oe SKIN cells from organotypic cultures were sorted for tdTomato+ and EGFP+ at days 3 and 10 (D3, D10). tdTomato+ samples were spiked with ~5% EGFP+ epidermal-derived s SKIN cells as in vitro skin reference. Minimum of 3 libraries per sample and time point (x10 Chromium). B UMAP representing 19 cell clusters (Louvain, 0–18). C Representative 3D-rendered images of tdTomato oe SKIN and s SKIN grown on EGFP dermis ex vivo as heterotypic cultures. D Cluster 18 contains s SKIN reference control cells (EGFP+). UMAP showing enriched Egfp gene expression. E UMAP showing Sox2 expression. Zoomed-in inset (dotted lines) shows negligible expression in EGFP s SKIN, C18. Colour bar indicates log2-transformed normalised expression levels. F Representative 3D-rendered images reveal SOX2 expression remains as a distinctive marker distinguishing oe SKIN (left) and s SKIN (right). G Annotated cell-type distribution across UMAP space. H UMAP showing transcription patterns by sample type ( oeOE/oeSKIN-D3, oeOE-D10 and oeSKIN-D10 ), and s SKIN C18. I Differentially expressed genes (DEGs) in basal cells shows similarity between D3 and oeSKIN-D10 compared to oeOE-D10 . J Violin plots showing tissue regeneration and maturation gene expression (genes enriched in D3 and oeSKIN-D10 shaded in pink). Log2-transformed normalised expression data. Dashed lines represent mean values. K UMAPs of selected DEGs upregulated in D3 + oeSKIN -D10 (pink) or oeOE -D10 (cyan). Colour bars indicate log2-transformed normalised expression levels. L , M Violin plots of oesophageal ( L ) and skin ( M ) enriched genes reveal identity differences between oe OE-D10 and oe SKIN-D10 . ( N ) UMAPs of classical epidermal (top), and hair follicle-related (bottom) genes enriched in cluster 18 (reference) and 8 (transitioning). Colour bars indicate log2-transformed normalised expression levels. Insets show zoomed cells in C8/C18. O , P UMAPs after integration with in vivo oesophageal scRNA-seq dataset (McGinn et al., 2021). Colour bars indicate log-transformed normalised expression. Scale bars . 20 µm. Mouse lines . Constitutive H2B-EGFP were used as source of tail dermis, and nTnG of oesophageal tissue. Panels A and C created in BioRender. Alcolea, M. (2025) https://BioRender.com/huzygrn See also Supplementary Figs. –M and . Source data are provided as a Source Data file.

Article Snippet: A Overview of the scRNA-seq workflow (10x Genomics).

Techniques: Derivative Assay, In Vitro, Ex Vivo, Control, Gene Expression, Expressing, Transformation Assay, Marker, In Vivo

Journal: Nature Communications

Article Title: Lifting regenerative barriers promotes epithelial cell fate plasticity supporting lineage conversion

doi: 10.1038/s41467-025-66446-9

Figure Lengend Snippet: A Overview of the scATAC-seq workflow (10x Genomics). Epithelial oe OE, oe SKIN and s SKIN cells nuclei were isolated at day 10, libraries prepared (x10 Chromium) and sequenced. Created in BioRender. Alcolea, M. (2025) https://BioRender.com/p4w9gy0 . B , C Track plots showing chromatin accessibility for skin-related ( B ), and oesophageal-related ( C ) loci across sample types. Peaks with differential accessibility are shaded. D UMAP of C18/C8 cells after re-clustering. Colours show original clusters and sample origin. E Pseudotime trajectory for C18/C8 cells on UMAP. Colour bar denotes pseudotime axis. F Violin plots showing distribution of cells along the pseudotime trajectory for each sample type, split into Oesophageal identity, Transitioning cells (TC; purple shade) and Skin identity. Rug plots show individual cells along the trajectory. G Heatmap of genes defining 4 main expression patterns along pseudotime trajectory. Data expressed as log-transformed normalised expression levels, averaged across all basal cells and scaled to a range [0–100]. H – J Expression of representative genes from Pattern 2 (skin, H ), 4 (oesophageal, I ) and 3 (transitioning, J ). Data presented as auto-scaled, log2-transformed normalised, smoothed (generalised additive model). Shaded grey bands in line plots indicate 95% confidence intervals. K UMAPs of hypoxia-inducible genes (pattern 3) up-regulated in transitioning cells (TC). Left, C8 + C18 UMAP reclustering; right, UMAP including all clusters. Colour bars indicate log2-transformed normalised expression levels. L scATAC-seq pseudotime trajectory on UMAP with rug plot showing pseudotime order of individual cells and coloured by sample origin. M , N Line plots of pseudotime-dependent accessibility for skin and oesophagus related transcription factors ( M ) and HIF1a ( N ) loci with accessibility-driven rug plots, coloured by sample. O 3D confocal side views of CD34, KRT15 and SOX9 in oe HF after HIF1a activator (DMOG) or HIF1a inhibitor (KC7F2) treatment. Vehicle = DMSO. P – R Quantification of CD34+ ( P ), KRT15+ ( Q ) and SOX9+ ( R ) cells per oe HF (% vs DAPI + ). ≥ 1600 cells from ≥ 18 oe HFs quantified; n = 4 mice. Points show individual measurements (greyscale = biological replicate). Data expressed as mean ± SD. Kruskal-Wallis with multiple comparisons. Scale bars 50μm. Fluorescent labels . Blue, DAPI; Yellow, CD34; Greyscale, KRT15; Magenta, SOX9. Mouse lines . Constitutive H2B-EGFP mice were used as source of tail skin. mTmG (scATAC-seq) and C57BL/6 wild-type (HIF1a treatments) mice were the source of oesophageal tissue. Dashed lines delimit hair follicles. See Supplementary Fig. . Source data are provided as a Source Data file.

Article Snippet: A Overview of the scRNA-seq workflow (10x Genomics).

Techniques: Isolation, Expressing, Transformation Assay

Journal: bioRxiv

Article Title: HIV-SEQ Reveals Global Host Gene Expression Differences Between HIV-Transcribing Cells from Viremic and Suppressed People with HIV

doi: 10.1101/2024.12.17.629023

Figure Lengend Snippet: A. Schematic illustrating the genomic location of HIV-specific capture sequences of HIV-seq. The name and nucleotide position (based off HXB2 annotation) of each of capture sequence are labeled in green. B. Schematic of HIV-seq protocol. PBMCs from PWH are enriched for CD4+ T cells and then labeled with CITE-seq antibodies to enable subsequent surface phenotyping. After cell encapsulation using a 10X Chromium instrument, custom-designed HIV-specific capture sequences described in panel A that have been appended to a non-poly(dT) PCR handle are spiked in with the poly(dT) oligos and incorporated into the 10X Genomics’ Chromium Next GEM Single Cell 5’ workflow. Each ‘Single Cell 5’ Gel Bead’ features an Illumina R1 sequence (‘read 1’ sequencing primer), a 16 nucleotide (nt) 10X Barcode (BC), a 10 nt unique molecular identifier (UMI), and a 13 nt template switch oligo (TSO). Reverse transcription is primed off both poly(dT) as well as the HIV capture sequences (i). Following template switching and transcript extension (ii, iii), barcoded cDNA libraries corresponding to both gene expression (GEX) and antibody-derived tags (ADT, for CITE-seq) are processed through the standard 10X workflow, and then sequenced. Data analysis was performed using the Seurat pipeline, SeqGeq software, and custom scripts.

Article Snippet: The standard 10X Genomics’ 5’ scRNA-seq workflow entails droplet encapsulation of individual cells, followed by capture and reverse transcription of polyadenylated transcripts using poly(dT) oligos.

Techniques: Sequencing, Labeling, Encapsulation, Reverse Transcription, Expressing, Derivative Assay, Software

Journal: Nature

Article Title: Latent human herpesvirus 6 is reactivated in CAR T cells

doi: 10.1038/s41586-023-06704-2

Figure Lengend Snippet: a, Quantification of HHV-6B by qPCR at day 19 for four donors normalized to the cell count. Bars are shown in order of increasing abundance. b, Longitudinal qPCR surveillance of HHV-6B U31 gene copies in CAR T cell culture from two donors. c, Schematic of the single-cell sequencing workflow to detect HHV-6+ cells from the CAR T culture. Two models are presented that would explain HHV-6 reactivation: model 1 (top), in which all cells express HHV-6 transcripts; and model 2 (bottom), in which only a subset of cells express HHV-6B. Both the host and HHV-6B viral RNA can be directly quantified using the 10x Genomics scRNA-seq workflow. d, Summary of HHV-6B expression from an individual donor (98). The top 0.2% of cells contain 99% of the HHV-6B transcript UMIs from this experiment. e, Tabulated summary of scRNA-seq profiling for four CAR T donors, including number of cells profiled, percentage expressing HHV-6, U31 qPCR value and number of shared TCR clones between the HHV-6B+ cells. N/A, not applicable. f, Extended longitudinal sampling of HHV-6B through U31 qPCR. Number at right end of each plot line indicates the fold (×) increase from the first qPCR measurement (day 21) to the final measurement (day 27; black outline) for each donor. g, Schematic and summary of HHV-6B expression in donor 34 after 19 and 25 days, showing evidence of HHV-6B spreading in the culture as depicted in the schematic. h, Correlation analyses of host factor gene expression with HHV-6B RNA abundance in individual cells for donor 34 on day 25. The per-gene correlation statistics are shown in black against a permutation of the HHV-6B expression in grey. Select genes are indicated. i, Pathway enrichment analysis of Molecular Signatures Database Hallmark gene sets for gene set enrichment analysis. A positive normalized enrichment score corresponds to genes that are overexpressed in cells with large amounts of HHV-6B transcript.

Article Snippet: Both the host and HHV-6B viral RNA can be directly quantified using the 10x Genomics scRNA-seq workflow. d , Summary of HHV-6B expression from an individual donor (98).

Techniques: Cell Counting, Cell Culture, Sequencing, Expressing, Clone Assay, Sampling, Gene Expression

Journal: Nature

Article Title: Latent human herpesvirus 6 is reactivated in CAR T cells

doi: 10.1038/s41586-023-06704-2

Figure Lengend Snippet: (a) Schematic of the experiment where CAR T cells from D98 were profiled using the 10x Genomics Multiome workflow to detect both viral DNA and RNA. (b) Scatter plot of the abundance of viral DNA and RNA at single-cell resolution. Pearson correlation between the log10 abundances is shown. (c) Per-cell viral gene expression signatures. The proportion of viral gene expression belonging to each class (late, early, immediate early) per cell is shown. (d) Same plot as in (c) but colored by the log2 number of viral DNA fragments. The population of cells highly expressing early HHV-6 transcripts show a corresponding high HHV-6 DNA copy number is highlighted by the arrow. (e) Pearson correlation of HHV-6 transcript signatures with their log abundance of DNA fragments per cell. The two-sided p-value for the Pearson correlation test is noted by each bar. (f) Bulk-level RNA and DNA correspondence in the four donors studied in the day 19 allogeneic CAR products.

Article Snippet: Both the host and HHV-6B viral RNA can be directly quantified using the 10x Genomics scRNA-seq workflow. d , Summary of HHV-6B expression from an individual donor (98).

Techniques: Gene Expression, Expressing

Journal: Nature

Article Title: Latent human herpesvirus 6 is reactivated in CAR T cells

doi: 10.1038/s41586-023-06704-2

Figure Lengend Snippet: (a) Schematic of CAR T product reculture experiment. Donor D97, which at day 19 showed a low but detectable level of HHV-6, was selected for reculture for five days. (b) Summary of RT-qPCR at the control and two treatment levels of Foscarnet. Each dot represents a technical replicate over one biological replicate per condition (validated in panel d). HHV-6 was not detected (n.d.) at the 1 mM concentration. Error bars represent the standard error of the mean. Comparison of foscarnet treated to untreated resulted in significantly lower abundance of HHV-6 RNA (p = 0.00026; two-sided ordinary least squares linear model). (c) Schematic of D34 reculture +/− foscarnet at 1 mM. (d) Difference between untreated and treated in the abundance of HHV-6+ cells. Comparing the two 10x Genomics scRNA-seq data channels, foscarnet-treated cells had a lower incidence of HHV-6 positive cells (OR = 6.25; p = 8.3e-122; Fisher’s exact test, two-sided). (e) Reduced dimensionality analysis of treated and untreated D34 cells profiled with scRNA-seq. Host gene expression was used for the analysis, showing overlapping clustering of populations irrespective of treatment status. (f) Differential gene expression analysis comparing foscarnet treated and control CAR T cells. The three most significant differential genes are noted. 0 genes were differentially expressed with a minimum log2 fold-change exceeding 1 (noted by the red).

Article Snippet: Both the host and HHV-6B viral RNA can be directly quantified using the 10x Genomics scRNA-seq workflow. d , Summary of HHV-6B expression from an individual donor (98).

Techniques: In Vitro, Quantitative RT-PCR, Control, Concentration Assay, Comparison, Gene Expression