RESUMO
Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed1-6. However, missing from these measurements is the ability to routinely and easily spatially localize these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are tagged with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as an input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 µm spatial resolution and delivered whole-transcriptome data that are indistinguishable in quality from ordinary single-nucleus RNA-sequencing data. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualized receptor-ligand interactions driving B cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to almost any single-cell measurement technology. As a proof of principle, we performed multiomic measurements of open chromatin, RNA and T cell receptor (TCR) sequences in the same cells from metastatic melanoma, identifying transcription factor motifs driving cancer cell state transitions in spatially distinct microenvironments. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.
Assuntos
Código de Barras de DNA Taxonômico , Genômica , Animais , Humanos , Camundongos , Encéfalo/citologia , Encéfalo/metabolismo , Cromatina/genética , Cromatina/metabolismo , Código de Barras de DNA Taxonômico/métodos , Epigênese Genética , Perfilação da Expressão Gênica , Genômica/métodos , Melanoma/genética , Melanoma/patologia , Tonsila Palatina/citologia , Tonsila Palatina/metabolismo , Receptores de Antígenos de Linfócitos T/genética , RNA/genética , Análise de Célula Única/métodos , Transcriptoma/genética , Microambiente Tumoral , Hipocampo/citologia , Hipocampo/metabolismo , Análise da Expressão Gênica de Célula Única , Especificidade de Órgãos , Ligantes , Elementos de Resposta/genética , Fatores de Transcrição/metabolismoRESUMO
Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are 'tagged' with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.
