library construction visium spatial gene expression slide  (10X Genomics)

Journal: Molecular Therapy Advances

Article Title: Single-cell and spatial transcriptomic analyses of gene therapy-associated retinal inflammation in non-human primates

doi: 10.1016/j.omta.2026.201726

Figure Lengend Snippet: Robust expression of human RPE65 and RPGR transgenes in AAV-treated NHP retinas (A and D) Immunostaining of retina sections from AAV2-CAG- hRPE65 (NHP1) and AAV8-GRK1- hRPGRco (NHP2) treated areas detect both native NHP and transgene-derived human RPE65 and RPGR proteins, respectively. Control sections were taken from outside the treated blebs. GCL, ganglion cell layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer; PL, photoreceptor layer; RPE, retinal pigmented epithelium; CH, choroid. Scale bars, 20 μm. (B and E) Spatial transcriptomic maps of native versus human RPE65 (NHP1) and RPGR (NHP2) gene expression within retina sections. Red spots represent the locations of cell clusters expressing the gene of interest overlayed on the H&E-staining image. Scale bars, 0.5 mm. (C and F) scRNA-seq reveals the levels of transgene expression by each retinal cell type. Circle size represents the proportion of cells that express the transgene within each population, while color intensity represents the mean expression level per cell. AC, amacrine cells; BPC, bipolar cells; HC, horizontal cells; MG, Müller glia.

Article Snippet: Spatial gene expression library was finally constructed and sequenced with Illumina NovaSeq X Plus by Novogene.

Techniques: Expressing, Immunostaining, Derivative Assay, Control, Gene Expression, Staining

Journal: Molecular Therapy Advances

Article Title: Single-cell and spatial transcriptomic analyses of gene therapy-associated retinal inflammation in non-human primates

doi: 10.1016/j.omta.2026.201726

Figure Lengend Snippet: Distribution of mononuclear phagocytes after AAV gene therapy in NHPs (A and C) Spatial transcriptomic mapping of monocytic phagocytes (including microglia) over treated versus untreated retinal sections from NHP1 (A) and NHP2 (C). Red spots represent cells expressing the marker genes P2RY12 and HEXB . Scale bars, 0.5 mm. (B and D) Immunostaining for IBA1 demonstrates amoeboid-shaped monocytic phagocytes, consistent with activation. Scale bars, 20 μm.

Article Snippet: Spatial gene expression library was finally constructed and sequenced with Illumina NovaSeq X Plus by Novogene.

Techniques: Expressing, Marker, Immunostaining, Activation Assay

Journal: Cell Reports Methods

Article Title: Comprehensive noise reduction in single-cell data with the RECODE platform

doi: 10.1016/j.crmeth.2025.101178

Figure Lengend Snippet: Illustration of RECODE’s denoising efficacy on spatial transcriptomics data (A) Annotated cell-type spatial distribution within a mouse embryo at embryonic day 16.5 defined in Chen et al. (B) Side-by-side visualization of spatial gene expression patterns and Welch’s t values for selected cell-type-specific markers in the mouse embryo, contrasting raw data with RECODE-processed data. (C) Gene expression maps before and after RECODE processing across multiple cell types and spatial transcriptomics platforms: mouse brain (10× Visium), mouse embryo (10× Visium HD), human pancreatic ductal adenocarcinoma (10× Xenium), and human skin (10× Xenium Prime). Gene names are shown in parentheses.

Article Snippet: Mouse embryo, Visium HD , 10x Genomics , Visium HD Spatial Gene Expression Library, Mouse Embryo (FFPE).

Techniques: Gene Expression

Journal: bioRxiv

Article Title: Spatial programming of fibroblasts promotes resolution of tissue inflammation through immune cell exclusion

doi: 10.1101/2024.09.20.614064

Figure Lengend Snippet: a) Schematic overview of multi-modal study design, including patient cohort, sample collection and processing for spatial transcriptomics (ST; 10x Genomics Visium) and multiplex immunofluorescence (IF; Leica Cell DIVE). b) Representative spatial plot showing a section of annotated spots from ST of synovial tissue with matched H&E stain. c) UMAP representation of ST spots, annotated based on gene expression. d) Dotplot of key marker genes and GO terms that define spatial tissue niches. e) Spatial plot of deconvoluted spots in synovial tissue following BayesSpace analysis. f) Heatmap showing presence of cell types in tisue niches following BayesSpace analysis based on scRNA-seq reference datasets (Zhang et al., 2019; Wei et al., 2020). g) Representative spatial plot (I) and matched H&E-stained synovial tissue (II) with spatial plots showing expression of gene modules that define tissue niches (III). h) Representative multiplex IF image of synovial tissue showing markers that define tissue architecture. Scale bar: 100 µm. i) Matched representative tissue image following computational cell segmentation showing cell centroids and annotation of ST-defined tissue niches. j) Comparison of marker gene expression between niches in IF and ST data. k) Representative multiplex IF images showing key markers of each niche as well as PDPN, CD68 and CD31 to mark major tissue landmarks. Plasma cell niche imaged using PhenoImager™ HT (Akoya Biosciences); all other niches imaged using Cell DIVE (Leica). Scale bars: 100 µm.

Article Snippet: Permeabilisation of the synovial tissue samples was performed for a total of 12 minutes at 37 °C, and libraries were constructed using the Visium Spatial Gene Expression Library Construction Kit (PN-1000186 and PN-1000190, 10x Genomics), according to manufacturers’ instructions.

Techniques: Multiplex Assay, Immunofluorescence, Staining, Expressing, Marker, Comparison