For decades, transcriptomics has provided researchers with a window into gene expression.
However, most approaches require tissue samples to be dissociated, stripping away the spatial information that reveals how cells interact in their native environment.
Spatial transcriptomics is changing that by combining gene expression profiling with spatial resolution, allowing scientists to see not only what genes are expressed but also where in the tissue they are active.
This technology has opened the door to discoveries in developmental biology, neuroscience, oncology, and immunology.
For example, researchers can now study how cancer cells interact with their surrounding microenvironment, identify immune cell infiltration patterns in diseased tissues, or map developmental gradients in embryonic tissues.
The ability to tie molecular signatures to their physical locations provides insights that bulk or single-cell RNA sequencing alone cannot capture.
Different methods of spatial transcriptomics have emerged, ranging from slide-based capture of RNA transcripts to in situ sequencing and hybridization approaches. Each has trade-offs in terms of resolution, throughput, and sensitivity, but all share the goal of linking molecular data to histological context.
This fusion of imaging and sequencing has quickly made spatial transcriptomics one of the most exciting frontiers in genomics.
Designing a spatial transcriptomics study involves unique considerations. Sample preservation and preparation are critical for maintaining tissue architecture.
Researchers must balance the size of the tissue region analyzed with the level of molecular detail needed, and downstream bioinformatics workflows must integrate both sequencing and imaging data.
These complexities require careful planning to ensure meaningful biological interpretation.
As interest grows, more researchers are exploring resources to guide experimental design and interpretation.
Those looking for overviews of current technologies, applications, and workflows can find useful background through references such as spatial transcriptomics, which introduce key concepts and methodologies.
By anchoring gene expression to spatial coordinates, this approach is reshaping how scientists view biology. Instead of studying cells in isolation, spatial transcriptomics allows us to see them as part of dynamic, interacting neighborhoods.
This perspective is revealing new mechanisms of development, disease progression, and tissue organization that were previously hidden, advancing both basic science and translational medicine