Introducing ‘sci-Space,’ A New Method For Embryo-scale, Single-cell Spatial Transcriptomics (Biology)

Researchers introduce “sci-Space,” a new approach to spatial transcriptomics that can retain single-cell resolution and spatial heterogeneity at scales much larger than previous methods.

They used their approach to build single-cell atlases of whole sections of mouse embryos at 14 days of development.

Single-cell RNA sequencing methods have led to great advances in understanding how organisms and complex tissues develop. Although cells’ spatial organization is central to normal development, homeostasis, and pathophysiology, many single-cell RNA sequencing methods lose valuable contextual spatial information.

Those that preserve spatial context between cells can be limited to a specific set of genes and/or a small tissue area. To overcome these challenges, Sanjay Srivatsan and colleagues developed sci-Space, a spatial transcriptomic approach that retains single-cell resolution while also resolving spatial context of cells at larger scales.

Srivatsan et al.‘s approach uses a grid of barcoded oligos – short, single strands of synthetic DNA – that can be transferred from a slide to nuclei of an overlaid frozen tissue section. According to the authors, sci-Space allows for both the spatial origin and transcriptome for thousands of cells per slide to be obtained.

To demonstrate their new technique, Srivatsan et al. applied sci-Space to developing mouse embryos. By capturing spatial coordinates and whole transcriptomes of nearly 120,000 cells, the authors assembled a spatially resolved single-cell atlas of whole day 14 mouse embryo sections and revealed spatially expressed genes across a variety of cell types, including differentiating neurons.


Reference: Sanjay R. Srivatsan, Mary C. Regier, Eliza Barkan, Jennifer M. Franks, Jonathan S. Packer, Parker Grosjean, Madeleine Duran, Sarah Saxton, Jon J Ladd, Malte Spielmann, Carlos Lois, Paul D. Lampe, Jay Shendure, Kelly R. Stevens, Cole Trapnell, “Embryo-scale, single-cell spatial transcriptomics”, Science  02 Jul 2021: Vol. 373, Issue 6550, pp. 111-117 DOI: 10.1126/science.abb9536


Provided by AAAS

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