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Spatial biology is a rapidly advancing field that maps the location, organization, and interactions of molecules, cells, and tissues within their native environments1,2,3. Unlike bulk or conventional single-cell methods that require tissue dissociation and result in loss of positional information, spatial approaches preserve the physical coordinates of analytes or cells/nuclei, enabling direct investigation of how tissue architecture influences cellular identity, intercellular communication, and biological function4,5,6,7. While spatial transcriptomics and spatial proteomics are currently the most widely adopted modalities, the field is rapidly expanding toward spatial multi-omic profiling3,8,9. Co-profiling gene expression and epigenomic states within the same tissue is especially powerful, as it directly links transcriptional output to regulatory mechanisms—such as chromatin accessibility and histone modifications—that govern gene activity and are known to vary across spatial domains10,11,12. Thus, integrated spatial epigenome and transcriptome analysis will provide critical insights into how regulatory programs shape cellular identity and tissue organization.
Several spatial multiomic strategies have been developed to enable simultaneous epigenomic and transcriptomic profiling. Deterministic barcoding in tissue sequencing (DBiT-seq) employs microfluidic channels to deliver spatial barcodes directly or indirectly, via stamping with gel slabs, to tissue sections, allowing for the spatial annotation of analytes. This approach facilitates spatially resolved co-profiling of epigenomic and transcriptomic features12,13,14,15. The Slide-tag method, commercialized as the Takara Trekker platform, directly introduces spatial barcodes into intact tissue prior to dissociation, allowing spatially indexed nuclei to be processed using standard single-cell workflows and computationally projected back to their original tissue coordinates16. In contrast, the spatial assay for accessible chromatin, cell lineages, and gene expression with sequencing (SPACE-seq) employs a target-out strategy in which poly(A)-tailed epigenetic targets and mRNAs are captured on a poly-dT capturing sequence in spatial transcriptomics tiles17.
Cleavage under targets & tagmentation (CUT&Tag) is a powerful tool for mapping interactions between DNA and histone or non-histone proteins from extremely low input samples18. CUT&Tag relies on Tn5 transposase-mediated chromatin fragmentation and DNA tagging (tagmentation), employing antibody-guided, protein A-conjugated Tn5 for locus-specific cleavage and molecular tagging. While the conventional CUT&Tag assay involves multiple incubation and wash steps, a simplified and streamlined CUT&Tag workflow was utilized to enhance CUT&Tag efficiency in downstream single-cell multiome applications19.

Figure 1: Workflow and quality control overview of the spatial Trekker–CUT&Tag multiome assay. (A) Schematic diagram of the spatial Trekker–CUT&Tag multiome workflow. A coronal section of fresh-frozen mouse brain tissue is mounted onto a Trekker spatial tile and subjected to spatial barcoding. Following tissue lysis, nuclei are isolated and assessed for yield and quality. Approximately 50,000 nuclei are used for H3K27ac CUT&Tag, and tagmented nuclei are subjected to single-cell barcoding by using 10x Genomics Chromium Multiome gel beads after counting. Single-cell barcoded DNA is pre-amplified and divided into two fractions. The indexed CUT&Tag library is generated directly by index PCR. For gene expression and spatial barcode libraries, pre-amplified DNA is further amplified and size-selected. Fragments corresponding to typical cDNA sizes are used for gene expression library preparation, while shorter DNA fragments are used to generate the spatial barcode library. Libraries are sequenced and mapped following 10x Genomics and Curio Trekker guidelines. The expected experimental timeline is indicated on the left. (B) Key quality control (QC) checkpoints and critical considerations throughout the workflow. Nuclei QC includes assessment of yield, intactness, aggregation, and debris content. Pre-sequencing QC includes evaluation of DNA size distributions and primer dimer contamination for all libraries. CUT&Tag library specificity is assessed by quantitative PCR (qPCR), measuring enrichment of target genomic regions over background. Please click here to view a larger version of this figure.
This study presents a spatial Trekker CUT&Tag multiome assay that simultaneously profiles histone H3K27ac modification associated with active cis-regulatory elements and gene expression in fresh-frozen tissue sections. This protocol provides step-by-step procedures for Takara Trekker spatial barcoding, tissue dissociation and nuclei isolation, nuclei counting and quality control, low-input CUT&Tag profiling of the H3K27ac modification, capture of molecular targets on 10x Genomics single-cell Multiome gel beads, and library preparation. The workflow was demonstrated using a coronal section of mouse brain tissue. Unlike the standard 10x Genomics Multiome workflow, in which chromatin accessibility is measured by assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), this protocol substitutes CUT&Tag-derived DNA fragments for ATAC fragments, enabling direct interrogation of histone modification landscapes at single-cell resolution. To link Trekker spatial barcodes with 10x Genomics single-cell barcodes, poly(A)-tailed spatial barcodes and mRNA transcripts are captured by the poly-dT sequences of the Multiome gel beads, while CUT&Tag DNA fragments are captured by the spacer sequences. This dual-capture strategy enables simultaneous recovery of epigenomic, transcriptomic, and spatial information from the same single nuclei. To our knowledge, this is the first spatial multiomic workflow that directly integrates barcode-in Trekker spatial annotation with a single-cell multiome assay to co-profile a histone mark’s genome-wide distribution and the transcriptome. The resulting spatially resolved multiome landscapes, integrating H3K27ac occupancy and gene expression data, enable projection of single-cell profiles back to their original tissue coordinates and provide a direct link between epigenomic regulatory mechanisms and transcriptional programs in relation to the intact tissue architecture.