Spatial transcriptomics is an advanced gene expression analysis method that preserves information about the original location of transcripts within the tissue section under investigation. In contrast to conventional RNA-seq, in which RNA is isolated from homogenised material, spatial transcriptomics integrates gene expression data with a histological image of the sample. This makes it possible to determine which genes are active in individual tissue regions, identify areas with distinct molecular profiles, and analyse relationships between tissue architecture and the biological processes occurring within it. The method can be applied to both animal and plant tissues. It is particularly valuable in studies where the spatial organisation of cells and tissue structures is essential for accurate interpretation of the results.
Applications of spatial transcriptomics
Spatial transcriptomics is used, among other applications, for:
The method is particularly valuable in oncology, immunology, neurobiology, developmental biology, regenerative research and the analysis of complex plant and animal tissues.
Spatial transcriptomics workflow
Technical specifications of spatial transcriptomics
The final data output can be adjusted to the tissue type, the area occupied by the sample, transcriptome complexity and the project objective.
Requirements for animal samples
- The material should be collected from a live or recently euthanised organism and secured as quickly as possible. Before embedding, remove excess connective and adipose tissue, blood and other elements that are not part of the analysis.
- Gently rinse the sample surface with chilled, RNase-free PBS buffer or physiological saline, then carefully dry it.
- For tumour samples, the tumour tissue should be properly separated from adjacent tissue. Larger fragments should be trimmed to dimensions corresponding to the capture-area surface.
- We recommend preparing at least two OCT blocks for each sample:
- one for quality control, selection of the appropriate section, permeabilisation optimisation and the actual experiment,
- the second as backup material.
- For most animal tissues, rapid freezing on dry ice is appropriate. For small biopsies, brain, oedematous tissues and materials prone to ice-crystal formation, freezing in isopentane cooled with liquid nitrogen may be recommended.
- If immediate embedding is not possible, the tissue may be temporarily stored at 4°C in an appropriate buffer or tissue-preservation solution. This storage period should be as short as possible because it may affect RNA integrity.
Requirements for plant samples
- Fresh plant material should be collected using clean, RNase-free tools, preferably cooled to approximately 4°C. Remove soil, growth medium and other contaminants from the sample surface.
- The tissue may be gently rinsed with ultrapure water, then elements not subject to analysis should be removed. During preparation, preserve the proper structure and orientation of the selected fragment.
- Because plant tissues differ in structure, the embedding method should be adapted to the material type.
- Tissues containing spaces or cavities, such as young buds, flower buds, seeds, stems and some roots, may require vacuum infiltration with diluted OCT before freezing.
- Tissues without larger spaces, such as leaves, lateral roots, root tips or callus, may be embedded directly in OCT and rapidly frozen on dry ice.
- When sufficient material is available, we recommend preparing three to five blocks for each sample. This is particularly important for thin, delicate or difficult-to-orient plant structures. Additional blocks may be needed for:
- RNA quality control,
- tissue-structure assessment,
- selection of the appropriate sectioning level,
- permeabilisation optimisation,
- the actual experiment.
Sample embedding in OCT
The tissue should be completely surrounded by OCT and positioned according to the planned cutting direction. Incorrect sample orientation, air bubbles or folding may make section preparation more difficult and reduce the surface available for analysis.
If several small fragments are embedded in one block, they should:
- be located in the same plane,
- be positioned close to one another without overlapping,
- collectively cover approximately 25% or more of the capture area,
- be positioned away from the edges and bottom of the mould.
Storage and transport
OCT-embedded blocks should be properly labelled, protected with aluminium foil or airtight packaging and stored at -80°C or in liquid nitrogen. Transport should take place on dry ice, without allowing the samples to thaw. Even brief thawing may impair tissue morphology and RNA quality.
Section quality control
Before the actual experiment, tissue morphology and RNA integrity are assessed. Morphological assessment confirms that:
- the appropriate tissue region is present in the section,
- the tissue structure has been preserved,
- the sample has no substantial cracks, folds or creases,
- there are no large air bubbles,
- no significant freezing artefacts are visible.
For animal tissues, H&E staining is usually used, while toluidine-blue staining may be used for plant tissues. RNA isolated from representative sections is assessed with an Agilent 2100 Bioanalyzer or an equivalent system. An RIN value of at least 6 is recommended for further project execution.
Spatial transcriptomics bioinformatics analysis
Standard bioinformatics analysis includes:
- quality control and assessment of sequencing data,
- mapping reads to the reference genome,
- identification and quantification of genes at individual spatial positions,
- assessment of tissue coverage,
- determination of the number of genes detected at individual positions,
- integration of sequencing results with the histological image,
- visualisation of spatial gene expression profiles,
- clustering of positions based on their expression profiles,
- identification of genes characteristic of individual clusters,
- analysis of genes differentiating clusters and tissue regions,
- functional gene annotation,
- functional enrichment analysis,
- integration of data from multiple samples,
- joint clustering of spatial data,
- analysis of differences between experimental groups.
The analysis scope can be extended to include additional custom analyses, integration with single-cell RNA-seq data and visualisations tailored to the project objective and the characteristics of the material under study.