Spatial Technologies

Approximate time: XY minutes

Learning Objectives

• Describe the differences between sequencing and imaging-based technologies
• Understanding advantages and disadvantages of different technologies

https://www.nature.com/articles/s41581-024-00841-1 https://www.sciencedirect.com/science/article/pii/S1044532325000302

Overview of Spatial Technologies

Over the years, transcriptomics technologies have evolved rapids from bulk sequencing all the way to the current spatial transcriptomics methods.

Bo Xia Lab representing evolution of sequencing technologies as Legos.

Bulk Sequencing

Single Cell Sequencing

Spatial Transcriptomics

Spatial transcriptomics tend to be categorized in two broad categories:

• Sequencing-based technologies
• Imaging-based technologies

Each of these methods process the tissue slide in different ways that will be explored more in the upcoming sections. The most important thing to note is that the ultimate output will be the same for each of these technologies:

• A TIFF image file which contains pixels that are associated with coordinates
• Gene counts matrix that maps expression levels to each of the pixels within the TIFF image

This field is ever-changing with new technologies appearing everyday. Here we will summarize the most used technologies as of January 2026.

Sequencing-based Technologies

Sequencing-based methods focus on capturing the full transcriptome of the cells in the dataset. To accomplish this, the tissue is “binned” into different spots which are then sequenced to measure expression levels. In some times, the spot can sometime be comprised of multiple cells (not single-cell level). As the technology has evolved, the bins sizes have become ever smaller, allowing for near single-cell levels.

In essence, these methods allow you apply a grid to the tissue and quanitify thousands of genes according to each square on the grid. Some popular technologies that belong to this category include:

TODO: table of: method, capture size, resolution, H&E, tissue preseveration, year released https://www.nature.com/articles/s41581-024-00841-1/tables/1

• Visium
• Visium HD
• Stereo-seq
• Slide-seq

Advantages

Analyses that make use of many genes at once (functional analysis, RNA velocity, etc.) can be done on these datasets as you are sequencing the entire transcriptome instead a gene panel.

Can be run on non-model organisms with more ease.

Disadvantage

High resolution experiments (Visium HD) can be very expensive Cells are not

Imaging-based Technologies

These methods utilize floresence to quantify gene expression on a tissue slide. Specifically utilizing fluoresence in situ hybridization (FISH) to measure expression of a select panel of genes (selected by the researcher) using a probes. Therefore we are able to evaluate the expression for each individual cell after segmentation.

• seqFISH
• MERFISH
• Xenium

Advantages

As imaging the slide is the foremost part of the method, you are able to annotate subregions of the tissue on a more granular level.

Disadvantages

As this is a probe-based method, there must be known probes for each gene of interest. This can be particularly challenging for non-model organisms and limits the scale of expression for each cell.

Segmentation methods are still up in the air and it can be challenging to define the boundaries of each cell. Some of these methods include

Overall Comparison of Methods

Sequencing-based	Imaging-based
Transcriptome-wide sequencing	Probe-based sequencing from a panel of genes
Spots/bins resolution depends on bin size (not always single-cell)	Single-cell resolution
More accessible to non-model organisms	Can be challenging to find probes for non-model organisms