Spatial profiling of chromatin accessibility in mouse and human tissues

Abstract

Cellular function in tissue is dependent on the local environment, requiring new methods for spatial mapping of biomolecules and cells in the tissue context1. The emergence of spatial transcriptomics has enabled genome-scale gene expression mapping2–5, but the ability to capture spatial epigenetic information of tissue at the cellular level and genome scale is lacking. Here we describe a method for spatially resolved chromatin accessibility profiling of tissue sections using next-generation sequencing (spatial-ATAC-seq) by combining in situ Tn5 transposition chemistry6 and microfluidic deterministic barcoding5. Profiling mouse embryos using spatial-ATAC-seq delineated tissue-region-specific epigenetic landscapes and identified gene regulators involved in the development of the central nervous system. Mapping the accessible genome in the mouse and human brain revealed the intricate arealization of brain regions. Applying spatial-ATAC-seq to tonsil tissue resolved the spatially distinct organization of immune cell types and states in lymphoid follicles and extrafollicular zones. This technology progresses spatial biology by enabling spatially resolved chromatin accessibility profiling to improve our understanding of cell identity, cell state and cell fate decision in relation to epigenetic underpinnings in development and disease.

Spatial Transcriptomics Using Multiplexed Deterministic Barcoding in Tissue

“…Furthermore, barcoding strategies with microfluidic channels can be combined with a multitude of modalities, including DNA-barcoded antibodies (Liu et al, 2022), chromatin accessibility (Deng et al, 2022b), and epigenomic readouts (Deng et al, 2022a). To increase adaptability, xDbit libraries can be sequenced using standard next generation sequencing platforms.…”

“…Deterministic barcoding in tissue (DBiT-seq) is a cost-effective and openly accessible platform to scale ST (Liu et al, 2020). DBiT-seq uses microfluidic channels to barcode tissue sections using DNA oligonucleotides and allows the integration of multi-omics information, including antibodies (Liu et al, 2022), epigenomics (Deng et al, 2022a), and chromatin accessibility readouts (Deng et al, 2022b).…”

Smoother: A Unified and Modular Framework for Incorporating Structural Dependency in Spatial Omics Data

“…We define spatial deconvolution as the problem of inferring cell-type abundances at each location from the observed omics data, with or without cell-type reference information from external data. The task is especially relevant for spatial techniques with limited resolution, including 10x Visium, spatial-CUT&Tag 4 and spatial-ATAC-seq 5 , where each profiled location represents a mixture of cells potentially from multiple cell types. The design of deconvolution model is usually determined by the generative model of the observations Y G × S .…”

“…This harmonious architecture regulates a diverse variety of biological processes, including embryonic development, neuronal plasticity, and the tumor microenvironment. Recent advances in spatially resolved omics technologies provide unique opportunities to study the spatial patterns of gene and epigenetic activities and the dynamics of biological systems at the cellular and tissue level [1][2][3][4][5] . While existing non-spatial omics analysis methods can be applied to spatial data, the neglect of positional information makes them incapable of overcoming limitations such as low spatial resolution and structured technical noise 6 , let alone inferring biologically meaningful spatial organization.…”

Epigenomic tomography for probing spatially-defined molecular state in the brain

“…During such profiling, the spatial context is often the key information for understanding the tissue-level biology ranging from microenvironment effects to cytoarchitectural functions and organization. Various spatially sensitive approaches have been developed over recent years to probe transcriptomics(Chen et al, 2015; Eng et al, 2019; Lee et al, 2014; Liu et al, 2020; Lubeck et al, 2014; Rodriques et al, 2019; Wang et al, 2018), epigenomics(Deng et al, 2022a; Deng et al, 2022b), genomics(Zhao et al, 2022), and multi-omics(Liu et al ., 2020; Zhao et al ., 2022) with resolution up to single cells. These single-cell spatial genomic techniques provide useful insights into the myriad cell types involved and their spatial organization in the tissue.…”