More recently, next-generation sequencing has enabled us to measure the genome, transcriptome, and epigenome at the single-cell level, with resolution and scale previously impossible. However, challenges persist, particularly in understanding diseases and complex biological systems, because cells interact with one another within the tissue environment. The spatial organization of cells within tissues strongly influences their function, underscoring the importance of integrating spatial information into genomic studies. In recent years, significant advancements in high-throughput sequencing technologies, coupled with innovative spatial barcoding and fluorescence microscopy, have paved the way for the development of a suite of spatial transcriptome (ST) technologies to measure gene expression in situ. Current ST techniques have evolved rapidly in sensitivity, multiplexing, and throughput, and ST is emerging as a revolutionary genomic technology that tightly integrates tissue and genomic measurements.
ST measures gene expression in specific locations within tissue samples. In ST, tissue sections or intact samples are spatially barcoded or indexed, correlating gene expression data with precise spatial coordinates. Spatially resolved gene expression data provide critical insights into the spatial heterogeneity of cell types, cell-cell interactions, molecular gradients within tissues, groups of spatially co-varying genes, and gene signatures associated with pathologic features. There are two main types of ST platforms: imaging (iST) and sequencing (sST) modalities. sST methods tag transcripts with oligonucleotide addresses indicating spatial location, typically by placing tissue slices on a barcoded substrate, isolating tagged transcripts for sequencing, and computationally mapping transcript identities to locations. iST methods use variations of fluorescence in situ hybridization (FISH), in which mRNA molecules are tagged with hybridization probes and detected in a combinatorial manner across multiple rounds of staining with fluorescent reporters, imaging, and de-staining. Computational reconstruction then yields maps of transcript identity with single-molecule resolution. iST targets subsets of the transcriptome using predefined gene panels, offering higher spatial resolution and sensitivity than sST. As ST techniques continue to evolve, coupled with rapidly emerging computational and analytic methods, they are poised to become indispensable for dissecting the spatial complexity of biological systems at unprecedented resolution. These platforms show tremendous promise for translational research and diagnostic applications in cancer, neuroscience, and aging, aligning with the strengths of the UTHSA research community.
The GSF provides spatial transcriptomics capabilities through both sequencing-based (sST) and imaging-based (iST) platforms. These include the 10x Genomics Visium HD, implemented via the CytAssist system (supported by CPRIT Core Facility Award RP220662), and the 10x Genomics Xenium Analyzer (supported by the 2025 NIH S10 grant S10OD038331). Visium HD enables whole-transcriptome profiling at single-cell resolution, whereas the Xenium platform offers high-resolution, imaging-based analysis of gene expression directly within tissue sections using targeted gene panels.
The GSF performs spatial transcriptomics analysis through both sST and iST platforms: 10X Genomics Visium HD through the CytAssist system (supported by CPRIT Core Facility Award RP 220662) and 10X Genomics Xenium Analyzer (supported by 2025 NIH S10 grant S10OD038331). Visium HD provides whole-transcriptome analysis at the single-cell scale: https://www.10xgenomics.com/platforms/visium, while Xenium enables high-resolution, imaging-based analysis of gene expression directly within tissue sections using targeted gene panels: https://www.10xgenomics.com/platforms/xenium. Together, Visium HD serves as a discovery tool, while Xenium is ideal for hypothesis validation and focused spatial analysis.