Why Spatially Resolved Transcriptomics Matters

The adage “Location! Location! Location!” is just as relevant in biology as it is in real estate. This concept is crucial in developmental biology, where all cells in the human body contain the same DNA but give rise to specialized cells forming distinct tissues and organs as an organism develops. This differentiation is driven by carefully controlled gene expression gradients that activate the right developmental pathways at the right times. Even after development, a cell’s location influences its phenotype, state, and function due to the signals it receives from surrounding cells, which can be through direct cell-cell interactions, soluble messengers, or therapeutic molecules.

Understanding the precise interactions and environments of cells is crucial for deciphering the biological mechanisms underlying human development and disease. Disruptions in these carefully coordinated cellular interactions can lead to devastating diseases. Therefore, it is essential to study cellular biology within its natural context, which is where spatially resolved transcriptomics comes into play.

The Emergence of Spatially Resolved Transcriptomics

The quest to assess cellular biology in its natural context is not new. Techniques such as radioactive in situ hybridization, which visualized ribosomal RNA in 1969 and globulin transcripts in 1973, were early methods that laid the groundwork for current spatial transcriptomics techniques. These early methods, although innovative, were limited in the number of targets they could capture and their resolution.

Technological advancements in the 1990s and early 2000s led to the development of numerous new spatial transcriptomics methodologies. Initially, these techniques were primarily used in academic institutions where they were developed. However, the commercialization of these methods has made spatially resolved transcriptomics more accessible to researchers across various fields, from developmental biology to cancer research, neuroscience, and plant biology. The increasing number of publications in this area highlights the vast potential for new biological insights.

Read more about some of our favorite spatial biology discoveries:

• Spatial transcriptomics publications you’ll want to read (Read here)
• Spatial transcriptomics publications you’ll want to read: 2022 edition (Read here)

Techniques for Spatial Gene Expression Profiling

10x Genomics has introduced spatial transcriptomics techniques, which are divided into sequencing-based and imaging-based methods.

Sequencing-Based Spatial Transcriptomics

In sequencing-based spatial methods, mRNA is captured from tissue samples and then sequenced ex vivo. The spatial location of the mRNA targets is determined through techniques such as the Visium Spatial platform. In this method, tissue sections are mounted on slides containing barcoded spots. For fresh frozen (FF) tissue assays, polyadenylated mRNA is captured, while for formalin-fixed paraffin-embedded (FFPE) tissue assays, ligated probe pairs are used for target identification.

Spatial barcodes are incorporated during the generation of cDNA libraries (for FF assays) or probe extension (for FFPE assays), preserving spatial information. The barcoded libraries are then analyzed by next-generation sequencing and mapped back to specific spots on the capture area.

Overview of Visium Spatial workflow.

Imaging-Based Spatial Transcriptomics

Imaging-based methods, also known as microscopy-based methods, involve imaging mRNAs in situ. These methods can be further subdivided into in situ hybridization–based and in situ sequencing–based techniques. An example of an imaging-based methodology is the Xenium In Situ platform, which uses circularizable padlock probes containing regions that hybridize to the target mRNA and a gene-specific barcode sequence. After successful target recognition and amplification through rolling circle amplification (RCA), detection is achieved through successive rounds of fluorescent probe hybridization, imaging, and probe removal. This process generates an optical signature specific to each gene, creating a spatial map of transcripts across the tissue section.

Overview of Xenium In Situ workflow.

Choosing the Right Method

When deciding between RNA sequencing–based and imaging-based spatial methods, researchers should consider the experimental aims of their research. Sequencing-based methods, like Visium Spatial, are recommended for hypothesis generation due to their ability to provide unbiased whole transcriptome analysis, covering tens of thousands of genes without requiring prior knowledge of the biology being studied.

In contrast, imaging-based methods, like Xenium In Situ, are ideal for hypothesis testing as they profile hundreds to thousands of genes at high resolution, specificity, and sensitivity. This targeted approach is suitable for detailed examination of specific targets identified by other methods, such as single-cell sequencing or unbiased spatial transcriptomics. However, imaging-based profiling can also uncover new biological insights, demonstrating its utility in generating new hypotheses.

Expanding Research with Spatial Biology

The adoption of spatial biology is opening new avenues for basic and clinical research, enhancing our understanding of development and disease. Researchers can explore the possibilities of these technologies through resources like the Visium Discovery Hub or by interactively exploring Xenium datasets from human breast or mouse brain tissue. By leveraging these advanced spatial transcriptomics techniques, scientists can gain deeper insights into the complex interactions and environments that drive cellular function and dysfunction, ultimately paving the way for new therapeutic approaches and a better understanding of biological processes.

References:

1. Marx V. Method of the Year: spatially resolved transcriptomics. Nat Methods. 18: 9–14 (2021). doi: 10.1038/s41592-020-01033-y
2. Williams CG, et al. An introduction to spatial transcriptomics for biomedical research. Genome Med. 14: 68 (2022). doi: 10.1186/s13073-022-01075-1
3. Asp M, Bergenstråhle J & Lundeberg J. Spatially resolved transcriptomes—next generation tools for tissue exploration. Bioessays. 42: e1900221 (2020). doi: 10.1002/bies.201900221
4. Moses L & Pachter L. Museum of spatial transcriptomics. Nat Methods. 19: 534–546 (2022). doi: 10.1038/s41592-022-01409-2
5. Method of the Year 2020: spatially resolved transcriptomics. Nat Methods. 18: 1 (2021). doi: 10.1038/s41592-020-01042-x
6. Stahl PL, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 353: 78–82 (2016). doi: 10.1126/science.aaf2403
7. Zhuang X. Spatially resolved single-cell genomics and transcriptomics by imaging. Nat Methods. 18: 18–22 (2021). doi: 10.1038/s41592-020-01037-8

Source: Spatially resolved transcriptomics: An introductory overview of spatial gene expression profiling methods