Background
Single-cell omics approaches have revolutionized the field of molecular and cellular biology by endowing us with the ability to capture cellular heterogeneity. Although these approaches can help identify biological process-associated cell-states, as well as cell-type-specific molecular patterns, they involve a cell dissociation step which causes the loss of spatial information.
Delineating the spatial context of a cell-state or cell-type is essential for fully dissecting its role in health and disease. Therefore, a series of spatial omics technologies are now being developed.
In 2026, I expect my PhD project to make substantial use of spatial transcriptomics datasets to elucidate the cell-type- and region-specific molecular alterations associated with stress in the brains of psychiatric patients. Therefore, I will need to improve my understanding of the data generation and analysis methods.
Undoubtedly, one of the best ways to deepen one’s knowledge is to write about the topic of interest as much as one can. With that in mind, I have decided to regularly post about spatial transcriptomic technologies and data analysis methods. I am starting this journey with a poster briefly showing examples of sequencing-based spatial transcriptomic (sST) approaches that adopt various spatial indexing strategies. My future blog posts will explore data analysis workflows step by step.
Poster on sequencing-based spatial transcriptomic technologies
As the original poster is quite large (~3100x4500 pixels), it had to be downsized. If you have trouble viewing its contents, I have left a link to it in the next section, using which you can view and/or download the poster in full resolution.
Link to the poster
Click here to view and download the poster in full resolution.
Further readings
Benchmarking study
sST platforms/technologies
- Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
- Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2
- Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays
- High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue