Single-cell RNA sequencing enables the study of gene expression on a single-cell level. In addition to identifying the cell types present in a sample, it is possible to analyze their unique patterns of gene expression. This makes single-cell RNA sequencing a powerful tool for studying cellular heterogeneity in floating cells, such as peripheral blood mononuclear cells (PBMCs), as well as in complex tissues like liver or intestinal tissue. Moreover, it helps identify the developmental stages of tumors and characterize the tumor microenvironment, facilitating adjustments in therapy and prognosis.
Cell type identification and annotation are accomplished by identifying cell-type-specific marker genes, such as CD3D for T-cells, for the analysis of peripheral mononuclear blood cells. Regarding complex tissues like brain tissue, this becomes more challenging, as cell type identification doesn’t rely solely on gene expression, but also on the localization of the cell within the organ. Moreover, elucidation of metabolic and signaling pathways remains challenging, as it lacks the spatial information necessary to understand direct cell-cell interactions. This becomes particularly relevant in the exploration of tumor heterogeneity, specifically in relation to the localization of immunosuppressive immune cells within the tumor microenvironment.
That is when spatial transcriptomics (Workflow in Figure 1) comes into play, combining gene expression information with tissue morphology.
Starting from solid frozen or FFPE (formalin-fixed, paraffin-embedded) tissue samples (1), ultrathin tissue slices are prepared on microscopic glass slides (2), followed by histological or immunofluorescence staining to visualize the spatial tissue morphology (3).
For transcription analysis, the target RNA on the slides is ligated to specimen-specific oligonucleotide probes (a set of probe pairs for each target gene) (4). Unbound probes are removed, followed by RNA digestion. The remaining probes are then released from the tissue and transferred to a Visium CytAssist Spatial Gene Expression Slide (4a). Each so-called capture area of this slide contains approximately 5,000 barcoded spots (STS SD) or 11 million barcoded squares (STS HD). This barcode is part of oligonucleotides bound to the capture area and encodes the spatial information (4b). The transferred probes bind to the stationary oligonucleotides and are extended. After extension, the probes are released and used for library preparation (5), followed by Illumina short-read sequencing (6). Finally, gene expressions are linked to the position on the slide and superimposed with the histological or immunofluorescence image, resulting in a gene expression map with maximal resolution at the single-cell level (7).
Figure 1 | Spatial transcriptomics workflow. 1) FFPE tissue block 2) tissue slices on a glass slide 3) HE-stained tissue 4) probe ligation, 4a+b) and transfer to the capture area of the Visium CytAssist Spatial Gene Expression Slide, 5) probe hybridization, extension, and release, 6) short-read sequencing, and 7) overlay of the histological image with transcriptional information.
We will be happy to support you in deciding whether one of our bulk RNA sequencing approaches (Coding Transcriptome Sequencing or Whole Transcriptome Sequencing), Single-Cell RNA Sequencing, Spatial Transcriptome Sequencing SD, or Spatial Transcriptome Sequencing HD is most suitable for your research project.