Spatial Omics
Bring omics data into the spatial dimension and reconstruct molecular expression and tissue architecture in situ.
10x Xenium In Situ
10x Xenium in-situ spatial transcriptomics is a technology based on tissue in-situ hybridization, cyclic imaging, and high-precision image analysis that detects RNA molecules from a preset gene panel while preserving tissue morphology and cell position. Conventional transcriptome sequencing reveals expression changes but loses spatial position; single-cell sequencing reveals heterogeneity but typically requires tissue dissociation, destroying original architecture. Xenium combines molecular detection, cell segmentation, and tissue imaging to observe spatial expression of key genes at subcellular to single-cell scale.
Principle Introduction
Xenium uses specific probes to identify target RNA in tissue sections. After in-situ probe binding, enzymatic amplification, barcode decoding, and multi-round fluorescence imaging assign each RNA molecule to tissue coordinates. Concurrent DAPI, morphology, or immunofluorescence imaging aids nuclear and cellular segmentation. Transcript coordinates are integrated with cell segmentation to yield per-cell expression matrices and spatial positions. Versus sequencing-based spatial transcriptomics, Xenium favors high-resolution in-situ detection of known targets; versus RNA-FISH, it detects more genes with automated large-area analysis.
Literature
Published in Nature Communications, 'Multimodal spatial transcriptomic characterization of mouse kidney injury and repair' used 10x Xenium with Visium and snRNA-seq to map cellular dynamics and microenvironment remodeling from acute injury to chronic repair after renal IRI at single-cell resolution. A 300-gene kidney panel profiled >1M cells across time points; Xenium identified 20 cell states (S1/S2/S3, Inj-PT, FR-PT) and 9 cellular neighborhoods (CN), with repair-phase CN7 (FR-PT, fibroblasts, immune) linked to fibrosis. Spatial ligand-receptor inference and immunofluorescence showed FR-PT interacted with fibroblasts/macrophages via PDGF and ICAM1-ITGβ2, with RUNX2 as a key upstream regulator.
Experiment Flow
Project evaluation
confirm species, sample type, preservation, aim and gene panel design.
Sample QC
evaluate section integrity, morphology, RNA status and background risk.
Probe hybridization & amplification
hybridize probes, wash, ligate and amplify the signal on the section.
Cyclic fluorescence imaging
read barcodes by cyclic imaging and obtain transcript coordinates.
Image processing & cell segmentation
segment cells from images and models to assign transcripts per cell.
Bioinformatics
generate matrix, clustering, markers and spatial maps for interpretation.
Deliverables
Expression matrix
cell-level gene matrix, spatial coordinates, transcript coordinates, detection stats.
QC
cell count, transcript count, genes per cell, background, tissue coverage.
Basic analysis
clustering, cell-type annotation, marker screening, dimensionality reduction, spatial maps.
Spatial analysis
in-situ target expression, cellular neighborhoods, cell interaction, regional differences.
Report
workflow, QC, key figures, methods, interpretation, visualizations.
FAQ
Not required, but existing data helps design panels and annotation.
Usually yes, but assess fixation, storage, RNA degradation, morphology.
