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Photo-sensitive oligonucleotides combined with topologically imposed light gradients enable spatially-resolved single-cell transcriptomics and epigenomics

ABSTRACT: The organization of cells within a tissue plays a critical role in tuning cellular function. Several methods have been recently developed to capture the transcriptome of single cells while retaining positional information. However, these genome-wide sequencing methods typically do not have the spatial resolution of individual cells and are limited to quantifying positional information within an arranged lattice, thereby failing to capture regions of nonoverlapping tissue. Further, these methods are generally limited to profiling fixed cells with reduced mRNA capture efficiency compared to standard scRNA-seq. In addition, existing methods lack modularity and cross-platform compatibility, thereby limiting most of these techniques from jointly profiling the genome-wide epigenetic state of cells. To overcome these limitations, we present scSTAMP-seq (single-cell Spatial Transcriptomic And Multiomic Profiling), an approach that employs cholesterol-tagged photolabile oligonucleotides that incorporate into cell membranes, enabling us to “stamp” the position of each cell using patterned light prior to tissue dissociation and single-cell sequencing. Applied to live cells, scSTAMP-seq efficiently captures spatially resolved single-cell transcriptomes and at a high resolution for all cells within a field of view. Furthermore, we showcase the dynamic spatial resolution provided by light gradients, enabling us to accurately map the position of individual cells. Finally, we show that scSTAMP-seq is modular and can be seamlessly integrated with various downstream single-cell sequencing technologies. We demonstrate this by performing scRNA-seq using plate- and droplet-based methods, and by performing joint epigenome and transcriptome sequencing from the same cell while preserving positional information. Collectively, these results demonstrate that scSTAMP-seq is a sensitive and high-throughput technology for mapping single-cell transcriptomes and epigenomes at the spatial resolution of individual cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE237524 | GEO | 2025/12/04

REPOSITORIES: GEO

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Project description:To glean an appreciation of the holistic genetic activity in the gastrulating mouse embryo, we performed a genome-wide spatial transcriptome analysis (Stereo-seq), using a low-cell number sequencing protocol on laser microdissected samples of epiblast cells with retained positional address. The 3D transcriptome reveals that (i) the epiblast is partitioned into transcription domains corresponding to regions of epiblast where cells are endowed specifically with ectoderm and mesendoderm potency, (ii) novel lineage markers are identified as genes expressed in epiblast domains populated by cells displaying different lineage fates, (iii) functionally related gene regulatory circuitry and signaling pathways are acting in concert in the transcriptional domains, and (iv) the spatial information provides reference zipcodes for mapping the prospective address of cell samples from different embryos and stem cell lines. The quantified expression data can also be visualized as â3D digitized whole mount in situ hybridizationâ of all the expressed transcripts in the epiblast. (i) By using laser-microdissection, we carried out transcriptome profiling on embryo sections at a high resolution of ~20 cells per sample with the spatial information preserved. We then constructed a comprehensive spatial transcriptome map in the mid-gastrulation embryo that is visualized in a 3D embryonic model based on the sequencing data. Embryo position (A/L/P/R) and section (1-11) descriptors: A stands for laser capture microdissected samples from the anterior epiblast of the embryo; P for posterior; L for the left lateral epiblast of the embryo; R for the right lateral. The section is collected from distal to proximal, and the section 1 to 11 is the cryosection order, covering the whole embryonic part of a late mid-streak embryo. Section 1 is the most distal section and 11 is the most proximal section. (ii) Additional samples are RNA-seq data of 70 single cells from E7.0 mouse embryo. These 70 samples were randomly picked from the anterior or posterior embryonic half.

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Photo-sensitive oligonucleotides combined with topologically imposed light gradients enable spatially-resolved single-cell transcriptomics and epigenomics

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