Embryo-scale, single-cell spatial transcriptomics

Abstract

Spatial patterns of gene expression manifest at scales ranging from local (e.g., cell-cell interactions) to global (e.g., body axis patterning). However, current spatial transcriptomics methods either average local contexts or are restricted to limited fields of view. Here, we introduce sci-Space, which retains single-cell resolution while resolving spatial heterogeneity at larger scales. Applying sci-Space to developing mouse embryos, we captured approximate spatial coordinates and whole transcriptomes of about 120,000 nuclei. We identify thousands of genes exhibiting anatomically patterned expression, leverage spatial information to annotate cellular subtypes, show that cell types vary substantially in their extent of spatial patterning, and reveal correlations between pseudotime and the migratory patterns of differentiating neurons. Looking forward, we anticipate that sci-Space will facilitate the construction of spatially resolved single-cell atlases of mammalian development.

Single‐cell omics: Overview, analysis, and application in biomedical science

“…51 Spatial transcriptomics enables the visualisation of the mRNA distribution in tissue sections. Existing spatial transcriptomics methods can be roughly divided into (1) fluorescent in situ hybridization methods (e.g., RNAscope, 52 MERFISH 53 , seq-FISH 54 and (2) methods based on scRNA-seq (e.g., Slideseq, 55 sci-Space 56 ). Fluorescence-based methods rely on direct labelling of tissue sections with fluorescent probes [52][53][54] whereas scRNA-seq methods apply oligonucleotide or beadbased spatial barcoding.…”

“…Fluorescence-based methods rely on direct labelling of tissue sections with fluorescent probes [52][53][54] whereas scRNA-seq methods apply oligonucleotide or beadbased spatial barcoding. 55,56 Spatial transcriptomics at single-cell resolution is a rapidly developing field which provides a unique opportunity to dissect the tissue architecture together with underlying cellular interactions and thus offering a better understanding of morphologically complex tissues. 57 A commercially available Visium HD solution from 10x Genomics for single-cell spatial transcriptomics is planned to be released in the first half of 2022.…”

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

“…Several remarkable methodologies have been recently developed that allow spatially resolved transcriptomic profiling of tissue sections. They can be divided in three main classes based on their detection method: physical segmentation using microdissection coupled to sequencing (Nichterwitz et al, 2016;Peng et al, 2019), pre-designed probes for either single-molecule hybridization (Eng et al, 2019;Zhuang, 2021) or amplification and in situ decoding (Alon et al, 2021;Lee et al, 2014;Wang et al, 2018), and barcoded probes (Cho et al, 2021a;Rodriques et al, 2019;Srivatsan et al, 2021;Stahl et al, 2016;Vickovic et al, 2019;Yao et al, 2020). These techniques all have specific advantages and disadvantages in resolution and applicability but share a major caveat in the limited field of view.…”

“…These techniques all have specific advantages and disadvantages in resolution and applicability but share a major caveat in the limited field of view. Although small parts of developing mouse tissues (Di Bella et al, 2021;Stickels et al, 2021) or even whole mouse embryos (Peng et al, 2019;Srivatsan et al, 2021;Yao et al, 2020) have been analyzed using these approaches, no available technology can profile samples of the size of whole mouse embryos in mid-or late-stage gestation with high definition. This poses a tremendous challenge for systematically studying the differentiation continuum that happens across different areas of the same tissue and for comparing different tissues simultaneously.…”

“…These methodological parameters are all fundamental for reliably profiling the transcriptomic heterogeneity of complex tissues and organisms such as mammalian embryos. Whole mouse embryo-scale spatially resolved transcriptomes have been reported recently(Liu et al, 2020;Srivatsan et al, 2021) but they contained low density of detected signals and were restricted to only one stage of organogenesis. The sparsity of gene detection in those studies makes it difficult to analyze gene expression gradients across the developing tissues and, thus, it is hard to recapitulate fine anatomical structures.…”