Identification and Localization of Cell Types in the Mouse Olfactory Bulb Using Slide-SeqV2.

Spatial transcriptomics maps RNA molecules to the location in a tissue where they are expressed. Here we document the use of Slide-SeqV2 to visualize gene expression in the mouse olfactory bulb (OB). This approach relies on spatially identified beads to locate and quantify individual transcripts. The expression profiles associated with the beads are used to identify and localize individual cell types in an unbiased manner. We demonstrate the various cell types and subtypes with distinct spatial locations in the olfactory bulb that are identified using Slide-SeqV2.

Principles of Spatial Transcriptomics Analysis: A Practical Walk-Through in Kidney Tissue.

Spatial transcriptomic technologies capture genome-wide readouts across biological tissue space. Moreover, recent advances in this technology, including Slide-seqV2, have achieved spatial transcriptomic data collection at a near-single cell resolution. To-date, a repertoire of computational tools has been developed to discern cell type classes given the transcriptomic profiles of tissue coordinates. Upon applying these tools, we can explore the spatial patterns of distinct cell types and characterize how genes are spatially expressed within different cell type contexts. The kidney is one organ whose function relies upon spatially defined structures consisting of distinct cellular makeup. Thus, the application of Slide-seqV2 to kidney tissue has enabled us to elucidate spatially characteristic cellular and genetic profiles at a scale that remains largely unexplored. Here, we review spatial transcriptomic technologies, as well as computational approaches for cell type mapping and spatial cell type and transcriptomic characterizations. We take kidney tissue as an example to demonstrate how the technologies are applied, while considering the nuances of this architecturally complex tissue.