Technology information

Description
Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 mum. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency ~50% that of single-cell RNA-seq data (~10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts.

Comment
Slide‐seqV2, an high‐resolution spatial sequencing technology, can reach the ∼50% RNA capture efficiency of scRNA‐seq and successfully characterise the spatiotemporal developing trajectory of mouse neocortex. [PMID: 35040595]

Keywords
Transcriptome, Genetics, Single-Cell Analysis, Messenger, Sequence Analysis

Targets
mRNAs

Spatial resolution
Cellular