Spatial transcriptomics is usually divided into two categories: imaging-based and sequencing-based. Imaging techniques use in vivo detection probes to target the gene of interest, so it has high specificity and can reach a sub-cellular resolution, but it takes a lot of effort to optimise panels and requires prior knowledge. Whereas sequencing technologies capture whole transcriptome regions at high throughput but typically suffer from low resolution and sensitivities.
Yuan Jiang, Head of STOmics at Complete Genomics, explored how Stereo-seq can tackle these issues by providing high-resolution spatial transcriptomics. The three key advantages of Stero-seq are that it is high throughput, species agnostic, and provides single-cell resolution.
Stereo-seq functions by using a sequencing chip, with millions of billions of capturing spots patterned onto a single chip. These spots are coded with hundreds or thousands of individual capturing probes that carry a CID barcode. The barcode provides certain information that helps map transcripts to their original physical locations within cells.
Next, Jiang explained that she adopts two strategies to capture the RNA. The first strategy is the typical run-of-the-mill method that uses a Poly-A-based way to capture total RNA in an unbiased and species-agnostic manner. The second approach uses an in-house algorithm to map the transcripts back to their original location and create a 3D map.
Jiang elaborated on the latter approach by explaining that it supports various staining methods that help scientists get more accurate region-specific transcriptional data. Insights from the staining alongside RNA profiling offer information on the co-localisation of proteins with microgenes. The in-house visualisation tool is compatible with third-party cell-segmentation methods.
Moving on, Jiang gave some real-world examples of Stereo-seq in action. The first example looked at the world’s first 3D single-cell atlas of Macaque cortex. This was created by using hundreds of sequencing chips to map the Macaque cortex. Based on the 261 cell types identified, Jiang created the most comprehensive Macaque cortical taxonomy. Now, the research is building on this in an attempt to map the human brain in a similar way, which could help improve neurological understanding.
Other case studies examined axolotl brain regeneration by leveraging glial cell reprogramming and liver cancer mechanisms. Jiang wrapped up her presentation by introducing the Omni kit. This product uses a random design to capture total RNA, including non-coding RNA and is compatible with FFPE samples.
