Integrated spatial multiomics

Abstract

Provided herein are methods, compositions, systems, kits and uses for integrated, simultaneous spatial multiomic analyses of tissues and samples including chromatin accessibility epigenomic analysis, RNA expression transcriptomic analysis, cell cluster and cell lineage analysis, transcription factor motif analysis, extrachromosomal DNA analysis and mitochondrial DNA analysis.

Description

[0001] Client docket no. S24-450

[0002] Attorney docket no. STDU2-44064.601

[0003] INTEGRATED SPATIAL MULTIOMICS

[0004] PRIORITY STATEMENT

[0005] This application claims priority to and the benefit of U.S. Provisional Application No. 63 / 734,424, filed December 16, 2024, the entire contents of which are incorporated herein by reference for all purposes.

[0006] FEDERAL FUNDING

[0007] This invention was made with Government support under contracts CA222736, HG007735, and 1HG012660. The Government has certain rights in the invention.

[0008] SEQUENCE LISTING

[0009] The text of the computer readable sequence listing filed herewith, titled “STDU2-44064- 601_SQL.xml”, created December 15, 2025, having a file size of 40,353 bytes, is hereby incorporated by reference in its entirety.

[0010] FIELD

[0011] Provided herein are methods, compositions, systems, kits and uses for integrated, simultaneous spatial multiomic analyses of tissues and samples including chromatin accessibility epigenomic analysis, RNA expression transcriptomic analysis, cell cluster and cell lineage analysis, transcription factor motif analysis, extrachromosomal DNA analysis and mitochondrial DNA analysis.

[0012] BACKGROUND

[0013] Spatial epigenomics and multiomics provide fine-grained resolution into cell state but widespread use is limited by the requirement for bespoke slides and capture chemistries for each data modality.

[0014] SUMMARY

[0015] Provided herein are methods, compositions, systems, kits and uses for integrated, simultaneous spatial multiomic analyses of tissues and samples including chromatin accessibility Client docket no. S24-450

[0016] Attorney docket no. STDU2-44064.601 epigenomic analysis, RNA expression transcriptomic analysis, cell cluster and cell lineage analysis, transcription factor motif analysis, extrachromosomal DNA analysis and mitochondrial DNA analysis.

[0017] In some embodiments, the present invention provides a composition, comprising a polyadenosine (poly-A)-tailed transposome, comprising: a Tn5 transposase; a poly-A adaptor sequence; a mosaic end transposase recognition sequence (ME); and a transposase-based second read adaptor sequence. In some embodiments, the second read adaptor sequence is a Nextera read 2 sequence (Nextera R2).

[0018] In some embodiments, the present invention provides a method comprising: providing a poly-adenosine (poly-A)-tailed transposome, comprising: a Tn5 transposase; a poly-A adaptor sequence; a mosaic end transposase recognition sequence (ME); and a transposase-based second read adaptor sequence; fixing a tissue of interest on a surface; staining the tissue to produce a stained tissue; imaging the stained tissue; permeabilizing the imaged tissue in a first permeabilizing reaction; fragmenting DNA and / or RNA in the permeabilized tissue and tagging the DNA and / or RNA with the poly-A adaptor sequences in a transposition reaction; permeabilizing the tissue in a second permeabilizing reaction; transferring the permeabilized tissue from the surface to a second surface comprising one or more capture sequences wherein the capture sequences comprise one or more of a barcode (BC), a unique molecular identifier (UMI) and a polyT-sequence; generating a sequencing library; generating a spatial RNA expression sequencing (RNA-seq) library; amplifying the sequencing library and the RNA-seq library; sequencing the amplified sequencing library and the RNA-seq library with nextgeneration sequencing to generate next generation sequencing data; and analyzing the next generation sequencing data for one or more of cell cluster analysis, cell lineage analysis, chromatin accessibility analysis, RNA expression analysis, spatial mapping analysis, extrachromosomal DNA (ecDNA) analysis, ecDNA copy number analysis, mitochondrial DNA analysis, and transcription factor motif analysis.

[0019] In some embodiments, the second read adaptor sequence is a Nextera read 2 sequence (Nextera R2). In some embodiments, fixing the tissue of interest on a surface comprises fixing the tissue with 1% formaldehyde on a glass slide. In some embodiments, permeabilizing the imaged tissue in a first permeabilizing reaction comprises use of one or more of phospholipase Client docket no. S24-450

[0020] Attorney docket no. STDU2-44064.601

[0021] A2 (PLA2), digitonin, Tween-20, or NP-40. In some embodiments, permeabilizing the tissue in a second permeabilizing reaction comprises use of 5X saponin. In some embodiments, second surface is a glass slide. In some embodiments, the glass slide is a poly-T slide. In some embodiments, the poly-T slide is in 1% SDS. In some embodiments, the poly-T slide is a CytAssist poly-T slide. In some embodiments, transferring the permeabilized tissue from the first surface to the second surface comprises use of an instrument configured to transfer genespecific transcriptomic probes from the first surface to the second surface for spatial profiling across one or more tissue sections. In some embodiments, the instrument is a VISIUM CytAssist instrument.

[0022] In some embodiments, generating the sequencing library comprises ligation with a ligase, extension, tissue digestion, amplification, clean up and / or purification of the sequencing library. In some embodiments, the sequencing library is an ATAC-seq library. In some embodiments, the ligase is a T7 ligase. In some embodiments, the extension is NEBnext extension. In some embodiments, the tissue digestion is proteinase K digestion. In some embodiments, the amplification is polymerase chain reaction (PCR) amplification. In some embodiments, generating the spatial RNA expression sequencing (RNA-seq) library comprises reverse transcription with template switching, tissue digestion, second strand synthesis, and / or cDNA library preparation. In some embodiments, tissue digestion is proteinase K digestion. In some embodiments, amplifying the sequencing library and the RNA-seq library comprises polymerase chain reaction (PCR) amplifying with one or more bar coded primers. In some embodiments, the amplification is simultaneous amplification. In some embodiments, sequencing the amplified sequencing library and the RNA-seq library with next- generation sequencing to generate next generation sequencing data is simultaneous sequencing. In some embodiments, analyzing the next generation sequencing data for one or more of cell cluster analysis, cell lineage analysis, chromatin accessibility analysis, RNA expression analysis, spatial mapping analysis, extrachromosomal DNA (ecDNA) analysis, ecDNA copy number analysis, mitochondrial DNA analysis, and transcription factor motif analysis is simultaneous analyzing.

[0023] In some embodiments, the present invention provides a kit, comprising a poly-adenosine (poly-A)-tailed transposome, comprising; a Tn5 transposase; a poly-A adaptor sequence; a mosaic end transposase recognition sequence (ME); and a transposase-based second read adaptor sequence; and instructions for use of the kit comprising the poly-adenosine (poly-A)-tailed Client docket no. S24-450

[0024] Attorney docket no. STDU2-44064.601 transposome. In some embodiments, the second read adaptor sequence is a Nextera read 2 sequence (Nextera R2).

[0025] In some embodiments, the present invention provides use of a poly-adenosine (poly-A)- tailed transposome, comprising: a Tn5 transposase; a poly-A adaptor sequence; a mosaic end transposase recognition sequence (ME); and a transposase-based second read adaptor sequence. In some embodiments, the second read adaptor sequence is a Nextera read 2 sequence (Nextera R2).

[0026] In some embodiments, the present invention provides a system, comprising: a polyadenosine (poly-A)-tailed transposome, comprising: a Tn5 transposase; a poly-A adaptor sequence; a mosaic end transposase recognition sequence (ME); and a transposase-based second read adaptor sequence; a surface comprising one or more capture sequences wherein the capture sequences comprise one or more of a barcode (BC), a unique molecular identifier (UMI) and a polyT-sequence; and an instrument configured to transfer gene-specific transcriptomic probes to the surface for spatial profiling across one or more tissue sections. In some embodiments, the second read adaptor sequence is a Nextera read 2 sequence (Nextera R2). In some embodiments, the surface is a glass slide. In some embodiments, the glass slide is a poly-T slide. In some embodiments, the poly-T slide is a CytAssist poly-T slide. In some embodiments, the instrument is a VISIUM CytAssist instrument. In some embodiments, the system comprises one or more of a glass slide configured for tissue fixation, an immunofluorescent stain, a fluorescent imaging instrument, a permeabilizing reagent, a transposition reaction vessel, a ligase, an extension reagent, proteinase K, a sequencing library, a spatial RNA expression sequencing (RNA-seq) library, one or more PCR amplification bar code oligonucleotide primers, an instrument configured for PCR amplification, and / or an instrument configured for next generation sequencing. In some embodiments, the sequencing library is an ATAC-seq sequencing library.

[0027] DESCRIPTION OF THE FIGURES

[0028] Fig. 1 shows that SPACE-seq supports simultaneous spatial profiling of accessible chromatin and gene expression using standard whole transcriptome reagents, a) Schematic illustration of the SPACE-seq method, b) Eosin-stained image of the mouse brain section obtained using the Visium CytAssist instrument, c) Spatial Assay for transposase-accessible chromatin with sequencing (ATAC-seq) clusters visualized in their spatial context (top) and after Client docket no. S24-450

[0029] Attorney docket no. STDU2-44064.601 dimensionality reduction (bottom), d) Selected marker genes visualized in their spatial context and quantified using GeneScore (spatial ATAC-seq; top), Gene Expression (spatial RNA-seq; center), or RNA in situ hybridization, e) Genome coverage tracks from spatial ATAC-seq and expression levels from spatial RNAseq for select marker genes divided by cluster, f) Correlation analysis between spatial RNA-seq GeneExpression and spatial ATAC-seq GeneScore for genes significant in at least one pairwise comparison between clusters (p < 0.05 and Ilog2 F.C.I > 1 in either GeneScore or GeneExpression; n=8,384 genes), g) Heatmap displaying differential genes that are significant in at least one pairwise comparison between clusters quantified using GeneScore (p < 0.05 and Ilog2 F.C.I > 1; spatial ATAC-seq). Key marker genes are highlighted.

[0030] Fig. 2 shows optimization of a transposome of the present invention with polyA adaptors, barcode (BC) ligation, and permeabilization conditions for SPACE-seq. a) Conceptual diagram illustrating the use of a polyA-tailed transposome to enable spatial epigenomics using slides designed for polyA capture chemistry. (UMI refers to unique molecular identifiers) b) transcription start site (TSS) enrichment for bulk ATACseq samples performed using a commercially available Tn5 transposase (“Tn5”) vs. a Tn5 of the present invention using standard adaptors (left), T7 ligase and variable-length polyA adaptors (center), and T4 ligase and variable-length polyA adaptors (right), c) Peak matrix correlation, percent mitochondrial reads, and TSS enrichment quantification for experiments with variable lengths of polyA adaptors and ligation conditions, d) TSS enrichment of bulk ATAC-seq for mouse brain samples using conventional adaptors with varying duration of phospholipase A2 (PLA2) exposure (min), e) Peak matrix correlation, percent mitochondrial reads, and TSS enrichment quantification for PLA2 permeabilization optimization.

[0031] Fig. 3 shows development of SPACE-seq using commercially available spatial transcriptomics reagents. A) Fluorescent image, number of fragments per spot, and TSS enrichment for spatial ATAC-seq using the 10X Visium vl slide and 1.875 uL Tn5. B) Fluorescent image, number of fragments per spot, and number of UMIs of transcripts for SPACE-seq using the 10X Visium slide, c) using the 10X Visium v2 slide without using the Visium CytAssist instrument, or d) using the 10X Visium v2 slide with the Visium CytAssist instrument. b)-d) were performed using 3.75 uL Tn5.

[0032] Fig 4. Shows a schematic of the SPACE-seq method. 1) Tissues are fixed onto glass slides. 2) Tissue imaging is performed after immunofluorescence (IF) staining. 3) Tissues are Client docket no. S24-450

[0033] Attorney docket no. STDU2-44064.601 partially permeabilized by phospholipase A2, digitonin, Tween- 20 and NP-40. 4) Tissues undergo transposition using a transposome of the present invention to generate polyA-tailed ATAC-seq fragments. 5) A 5X saponin solution is applied to further permeabilize the tissues. 6) The Visium CytAssist instrument supports efficient capture of ATAC-seq fragments and mRNAs. 7) Spatial barcodes are added to ATAC-seq fragments and cDNAs for subsequent library preparation.

[0034] Fig. 5 shows a characterization of SPACE-seq performance on mouse brain, (a) Image of the tumor section obtained using the Visium CytAssist instrument, b) TSS enrichment (left) and percentage of mitochondrial chromosome reads (right) per spot using spatial ATAC-seq. c) Number of genes detected per spot using spatial RNA-seq. d) Spatial RNA-seq clusters shown after dimensionality reduction (left) and in their spatial distribution (right), e) Heatmaps displaying differential items significant in at least one pairwise comparison between clusters for gene expression (left), chromatin accessibility (center) and transcription factor (TF) motifs (right). Key marker genes are highlighted.

[0035] Fig. 6 shows spatial distributions of marker gene expression and accessibility in the mouse brain. a)-d) Selected marker genes visualized in their spatial context and quantified using GeneScore (spatial ATAC-seq; top) or Gene Expression (spatial RNA-seq; bottom).

[0036] Fig. 7 shows the spatial architecture and clonal landscape of an archival human glioblastoma sample, a) Illustration and clinical characteristics of the human glioblastoma sample, b) Eosin-stained image of the tumor section obtained using the Visium CytAssist instrument, c) TSS enrichment and number of fragments per spot using spatial ATAC-seq. d) Spatial distribution of each integrated cluster, e) Selected marker genes visualized in their spatial context and quantified using GeneScore (spatial ATAC-seq). f) Heatmaps displaying all differential items significant in at least one pairwise comparison between clusters for gene expression (left), chromatin accessibility (center), and transcription factor (TF) motifs (right). Key marker genes are highlighted, g) Comparison between cluster 1 (Cl) and C2-4 for gene expression (left), chromatin accessibility (center), and TF motifs (right), h) Selected TF motif deviations visualized in their spatial context, i) Spatial distribution of a mitochondrial DNA variant 199T>C. j) Quantification of the enrichment of each high-confidence mitochondria DNA mutation in each cluster. Client docket no. S24-450

[0037] Attorney docket no. STDU2-44064.601

[0038] Fig 8. Shows a characterization of SPACE-seq performance on a human glioblastoma sample, a) Number of fragments (left), TSS enrichment per spot for spatial ATAC-seq (center), and number of UMIs (right) for spatial RNA-seq per spot, b) Spatial ATAC-seq (left) or spatial RNA-seq (right) clusters shown in their spatial context (left), c) Integrated clusters after dimensionality reduction.

[0039] Fig. 9 shows spatial distributions of marker gene expression and accessibility in a human glioblastoma sample. a)-d) Selected marker genes visualized in their spatial context and quantified using GeneScore (spatial ATAC-seq; top) or Gene Expression (spatial RNA-seq; bottom).

[0040] Fig. 10 shows that SPACE-seq detects EGFR extrachromosomal DNA (ecDNA) in a human glioblastoma sample, a) Spatial ATAC-seq genome coverage across all chromosomes, chromosome 7, the EGFR-amplified ecDNA, and EGFR exon 7 (in order top to bottom). In the EGFR exon 7 view, individual reads are shown in addition to genome coverage, b) Estimated EGFR ecDNA copy number per spot using spatial ATAC-seq. c) EGFR gene expression (left), gene score from spatial ATAC-seq (center) and copy number (right) visualized for each cluster, d) Spatial distribution of EGFR gene expression.

[0041] Fig. 11 shows SPACE-seq spatial localization of somatic mitochondrial DNA clones, a) Percentage of mitochondrial reads (right) per spot using spatial ATAC-seq. b) Per-spot mitochondrial genotyping using spatial ATAC-seq. c) Identification of high-confidence variants from high strand concordance, d) Spatial distribution of mitochondrial DNA variants (see also Fig. 7i). e) Heatmap showing variant heteroplasmy levels in individual spots for 7 mitochondrial variants.

[0042] DEFINITIONS

[0043] Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase “in some embodiments” as used herein does not necessarily refer to the same embodiment, though it may. Thus, as described below, various embodiments of the invention may be readily combined, without departing from the scope or spirit of the invention.

[0044] In addition, as used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and / or” unless the context clearly dictates otherwise. The term “based on” is not Client docket no. S24-450

[0045] Attorney docket no. STDU2-44064.601 exclusive and allows for being based on additional factors not described unless the context clearly dictates otherwise. In addition, throughout the specification, the meaning of “a,” “an,” and “the” include plural references. The meaning of “in” includes “in” and “on.”

[0046] The term “one or more,” as used herein, refers to a number higher than one. For example, the term “one or more” encompasses any of the following: two or more, three or more, four or more, five or more, six or more, seven or more, eight or more, nine or more, ten or more, eleven or more, twelve or more, thirteen or more, fourteen or more, fifteen or more, twenty or more, fifty or more, 100 or more, or an even greater number.

[0047] As used herein, a “nucleic acid” or “nucleic acid molecule” generally refers to any ribonucleic acid or deoxyribonucleic acid, which may be unmodified or modified DNA or RNA. “Nucleic acids” include, without limitation, single- and double- stranded nucleic acids. As used herein, the term “nucleic acid” also includes DNA as described above that contains one or more modified bases. Thus, DNA with a backbone modified for stability or for other reasons is a “nucleic acid.” The term “nucleic acid” as it is used herein embraces such chemically, enzymatically, or metabolically modified forms of nucleic acids, as well as the chemical forms of DNA characteristic of viruses and cells, including for example, simple and complex cells.

[0048] The terms “oligonucleotide” or “polynucleotide” or “nucleotide” or “nucleic acid” refer to a molecule having two or more deoxyribonucleotides or ribonucleotides, preferably more than 3, and usually more than 10. The exact size will depend on many factors, which in turn depends on the ultimate function or use of the oligonucleotide. The oligonucleotide may be generated in any manner, including chemical synthesis, DNA replication, reverse transcription, or a combination thereof. Typical deoxyribonucleotides for DNA are thymine, adenine, cytosine, and guanine. Typical ribonucleotides for RNA are uracil, adenine, cytosine, and guanine.

[0049] As used herein, the terms “locus” or “region” of a nucleic acid refer to a subregion of a nucleic acid, e.g., a gene on a chromosome, a single nucleotide, etc.

[0050] The term “gene” refers to a nucleic acid (e.g., DNA or RNA) sequence that comprises coding sequences necessary for the production of an RNA, or of a polypeptide or its precursor. A functional polypeptide can be encoded by a full-length coding sequence or by any portion of the coding sequence as long as the desired activity or functional properties (e.g., enzymatic activity, ligand binding, signal transduction, etc.) of the polypeptide are retained. The term “portion” when used in reference to a gene refers to fragments of that gene. The fragments may range in Client docket no. S24-450

[0051] Attorney docket no. STDU2-44064.601 size from a few nucleotides to the entire gene sequence minus one nucleotide. Thus, “a nucleotide comprising at least a portion of a “gene” may comprise fragments of the gene or the entire gene.

[0052] The term “gene” also encompasses the coding regions of a structural gene and includes sequences located adjacent to the coding region on both the 5' and 3' ends, e.g., for a distance of about 1 kb on either end, such that the gene corresponds to the length of the full-length mRNA (e.g., comprising coding, regulatory, structural, and other sequences). The sequences that are located 5' of the coding region and that are present on the mRNA are referred to as 5' nontranslated or untranslated sequences. The sequences that are located 3' or downstream of the coding region and that are present on the mRNA are referred to as 3' non-translated or 3' untranslated sequences. The term “gene” encompasses both cDNA and genomic forms of a gene. In some organisms (e.g., eukaryotes), a genomic form or clone of a gene contains the coding region interrupted with non-coding sequences termed “introns” or “intervening regions” or “intervening sequences.” Introns are segments of a gene that are transcribed into nuclear RNA (hnRNA); introns may contain regulatory elements such as enhancers. Introns are removed or “spliced out” from the nuclear or primary transcript; introns therefore are absent in the messenger RNA (mRNA) transcript. The mRNA functions during translation to specify the sequence or order of amino acids in a nascent polypeptide.

[0053] The term “purified” refers to molecules, either nucleic acid or amino acid sequences that are removed from their natural environment, isolated, or separated. An “isolated nucleic acid sequence” may therefore be a purified nucleic acid sequence. “Substantially purified” molecules are at least 60% free, preferably at least 75% free, and more preferably at least 90% free from other components with which they are naturally associated. As used herein, the terms “purified” or “to purify” also refer to the removal of contaminants from a sample. The removal of contaminating proteins results in an increase in the percent of polypeptide or nucleic acid of interest in the sample. In another example, recombinant polypeptides are expressed in plant, bacterial, yeast, or mammalian host cells and the polypeptides are purified by the removal of host cell proteins; the percent of recombinant polypeptides is thereby increased in the sample.

[0054] As used herein, the term “kit” refers to any delivery system for delivering materials. In the context of reaction assays, such delivery systems include systems that allow for the storage, transport, or delivery of reaction reagents (e.g., primers, enzymes, etc. in the appropriate Client docket no. S24-450

[0055] Attorney docket no. STDU2-44064.601 containers) and / or supporting materials (e.g., buffers, written instructions for performing the assay etc.) from one location to another. In some embodiments, the kit comprises one or more oligonucleotides selected from Table 1. comprising one or more of SEQ ID NOs. 1-43. In some embodiments, the oligonucleotide is a Tn5 oligonucleotide, a PCR amplification bar code primer, a DNA extension primer, an ATAC-seq primer, a sequencing primer, a read 1 sequencing primer, a read 2 sequencing primer, an RNA-seq primer and / or an indexed primer.

[0056] Table 1. SPatial assay for Accessible chromatin, Cell lineages, and gene Expression with sequencing (SPACE-seq) oligonucleotides Client docket no. S24-450

[0057] Attorney docket no. STDU2-44064.601 Client docket no. S24-450

[0058] Attorney docket no. STDU2-44064.601

[0059] For example, kits include one or more enclosures (e.g., boxes) containing the relevant reaction reagents and / or supporting materials. As used herein, the term “fragmented kit” refers to delivery systems comprising two or more separate containers that each contain a sub-portion of the total kit components. The containers may be delivered to the intended recipient together or separately. For example, a first container may contain an enzyme for use in an assay, while a second container contains a primer. The term “fragmented kit” is intended to encompass kits containing Analyte specific reagents (ASR’s) regulated under the Federal Food, Drug, and Cosmetic Act, but are not limited thereto. Indeed, any delivery system comprising two or more separate containers that each contains a sub-portion of the total kit components are included in the term “fragmented kit.” In contrast, a “combined kit” refers to a delivery system containing all of the components of a reaction assay in a single container (e.g., in a single box housing each of the desired components). The term “kit” includes both fragmented and combined kits.

[0060] As used herein, the term “information” refers to any collection of facts or data. In reference to information stored or processed using a computer system(s), including but not limited to internets, the term refers to any data stored in any format (e.g., analog, digital, optical, Client docket no. S24-450 Attorney docket no. STDU2-44064.601 etc.). As used herein, the term “information related to a subject” refers to facts or data pertaining to a subject (e.g., a human, plant, or animal).

[0061] As used herein, the terms “sample,” “test sample,” and “biological sample” refer to a sample containing or suspected of containing a target of the present disclosure. The sample may be derived from any suitable source. In some cases, the sample may comprise a liquid, fluent particulate solid, or fluid suspension of solid particles. In some cases, the sample may be processed prior to the analysis described herein. For example, the sample may be separated or purified from its source prior to analysis. In a particular example, the source is a mammalian (e.g., human) bodily substance (e.g., bodily fluid, blood such as whole blood, buffy coat, serum, plasma, one or more other bodily fluids, a dried blood spots, a biopsy or the like). The sample may be a liquid sample or a liquid extract of a solid sample. In some embodiments, the source of the sample may be an organ or tissue, such as a biopsy sample and / or an endoscopic brushing sample (e.g., endoscopic esophageal brushing sample), which may be solubilized by tissue disintegration / cell lysis. Samples can be obtained by any number of methodologies. Cell free or substantially cell free samples can be obtained by subjecting the sample to various techniques including but are not limited to, centrifugation and filtration. In some embodiments, one or more nucleic acids and / or proteins are isolated from a sample e.g., a tissue sample, a blood sample, a plasma sample, a serum sample, a whole blood sample, a buffy coat sample, an organ biopsy sample, and / or a tumor sample.

[0062] As used herein, the term “second read adaptor sequence” refers to a specific DNA sequence attached to the end of a DNA fragment generated by library preparation using a transposase enzyme to simultaneously fragment DNA and to attach adaptors including, for example, second read adaptor sequences during tagmentation. In some embodiments, a second read adaptor binds to a sequencing primer. In some embodiments, a second read adaptor sequence supports paired-end sequencing on a sequencing platform. In some embodiments, a second read adaptor sequence is, for example, a Nextera Read 2 sequence. In some embodiments, library preparation comprises use, for example, of an Illumina Nextera library preparation kit. In some embodiments, paired-end sequencing is performed, for example, on an Illumina platform using an Illumina flow cell.

[0063] DETAILED DESCRIPTION OF THE DISCLOSURE Client docket no. S24-450

[0064] Attorney docket no. STDU2-44064.601

[0065] Provided herein are methods, compositions, systems, kits and uses for integrated, simultaneous spatial multiomic analyses of tissues and samples including chromatin accessibility epigenomic analysis, RNA expression transcriptomic analysis, cell cluster and cell lineage analysis, transcription factor motif analysis, extrachromosomal DNA analysis and mitochondrial DNA analysis.

[0066] The spatial organization of cells within tissues is fundamental to their function in health and may go awry in disease. To understand the spatial organization of complex tissues, technologies have been developed to examine spatial arrangement at the proteomic, transcriptomic, and epigenomic levels1-4. While these approaches provide valuable data in diverse biological contexts, methods that simultaneously capture multiple types of data (z.e., “multiomics” methods) are needed because they capture multiple aspects of cell state5-10. However, spatial multiomics methods are limited by the need for custom-made instrumentation and reagents. To provide readily accessible spatial multiomics with improved cost and resolution of spatial transcriptomics, in some embodiments the present invention provides a unified molecular method configured to capture multiple spatial modalities using, for example, a commercially available spatial transcriptomics platform. In some embodiments, the present invention provides a SPatial assay for Accessible chromatin, Cell lineages, and gene Expression with sequencing (SPACE-seq). In some embodiments, the SPACE-seq protocol is applied to spatial transcriptomics platforms using polyA capture chemistry such as, for example, 10X Genomics (Visium; Visum HD), open-ST (Novaseq flowcell) and complete genomics (Stereo- seq). In some embodiments, SPACE-seq simultaneously captures ATAC-seq fragments and mRNAs using, for example, Visium slides with a 1-10 cell (55um) level of resolution. In some embodiments, the present invention provides an unbiased, high-throughput spatial platform and method that interrogates chromatin accessibility, somatic mitochondrial mutations, and gene expression using a commercially available platform including, for example, the 10X Genomics Visium CytAssist platform (Fig. 1). The Cytassist instrument is a configured to support Visium workflow by facilitating the transfer of transcriptomic probes from standard glass slides to Visium slides, facilitating whole transcriptomic spatial profiling insights across an entire tissue section. A Visium slide is configured to measure total mRNA in an intact tissue section and to map locations where gene activity is occurring. The capture area comprises -5,000 gene expression spots, each spot with primers that include: (1) a partial read 1 sequencing primer, for Client docket no. S24-450

[0067] Attorney docket no. STDU2-44064.601 example, an Illumina TruSeq Read 1 primer; (2) a spatial barcode wherein all primers in a specific spot share the same spatial barcode wherein said spatial barcode is, for example, 5-30 nucleotides (nt) in length, 10-20 nt in length, 12-18 nt in length, or 16 nt in length; (3) a unique molecular identifier (UMI) wherein in said UMI is, for example, 5-30 nt in length, 10-20 nt in length, 12-18 nt in length, or 12 nt in length; and (4) a poly(dT) sequence that captures polyadenylated mRNA for cDNA synthesis wherein said poly(dT) sequence is, for example, 10-50 nt in length, 20-40 nt in length, or 30 nt in length.

[0068] In some embodiments, SPACE-seq supports cell-type clustering in tissue samples including, for example, complex tissue sources such as the brain, and complex tumor tissue sources such as ecDNA-containing glioblastoma samples. In some embodiments, SPACE-seq identifies enriched transcription factor (TF) motifs, mitochondrial variants and copy number variations. In some embodiments, a SPACE-seq assay of the present invention is configured for transposase-accessible chromatin using sequencing (ATAC-seq) compatible with polyA capture chemistry in a solid-phase spatial transcriptomics workflow, such that a single unified chemistry may be used to interrogate spatial epigenomic and transcriptomic profiles of complex tissues and tumors.

[0069] In some embodiments, ATAC-seq comprises use of a hyperactive Tn5 transposase enzyme (“Tn5”) to simultaneously fragment DNA and insert custom adaptor sequences at the cut sites that serve as PCR handles for amplification11 12. In some embodiments, Tn5 transposase is loaded with adaptor sequences of a user’s preference and design. In some embodiments, loading Tn5 with adaptors comprising a 3’ polyadenine (polyA) overhang generates polyA-tailed chromatin fragments. In some embodiments, the chromatin fragments are captured using spatial transcriptomic reagents that bind polyA sequences (Fig. 2a). In some embodiments, the present invention provides a polyA-loaded transposome, ligation conditions for attachment of spatial barcode chromatin fragments, and tissue permeabilization reagents and conditions for Tn5 access to nuclear DNA without loss of tissue integrity together with release of chromatin fragments for capture by a spatial slide.

[0070] In some embodiments, SPACE-seq provides simultaneous capture of spatial ATAC-seq, RNA-seq, and mitochondrial DNA mutations using a whole transcriptome spatial platform. In some embodiments, the present invention provides an unbiased resolution of multiple features of Client docket no. S24-450

[0071] Attorney docket no. STDU2-44064.601 cell state with a unified molecular strategy compatible with polyA capture chemistry in spatial transcriptomics. In some embodiments, the method is integrated with spatial protein markers and / or spatial DNA methylation profiling. In some embodiments, a polyA-loaded transposome of the present invention is integrated with CUT&TAG epigenomic profiling. (Kaya-Okur, H. S. et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat Common 10, 1930 (2019). In some embodiments, SPACE-seq provides integrated multiomics and clonal dynamics of complex tissues with high-order spatial precision.

[0072] EXPERIMENTAL METHODS

[0073] Collection of murine tissue samples

[0074] Mouse experiments were conducted under Stanford’s approved animal protocol APLAC- 14046. Wild-type C57BL / 6 mice at eight weeks old were purchased from Jackson Laboratories and were then euthanized by cervical dislocation. The mouse brain tissues were harvested, snap- frozen in optimal cutting temperature (OCT) compound (Tissue- Tek, 4583) blocks in a dry ice- isopentane bath, kept on dry ice before sectioning and stored at -80°C.

[0075] Collection of tumor samples from patients with glioblastoma

[0076] LGA / Lamplified glioblastomas were retrospectively identified in the Stanford University pathology database as approved by the Stanford University institutional review board (protocol 69198). Corresponding frozen glioblastoma tissue was obtained from the Stanford Cancer Institute Tissue Bank. The glioblastoma sample was then embedded in an OCT compound block in a dry-ice-isopentane bath, kept on dry ice before sectioning, and stored at -80°C.

[0077] Bulk ATAC-seq

[0078] 50,000 viable cells were pelleted by centrifugation at 500 x g for 5 minutes at 4 °C using a fixed-angle centrifuge. The supernatant was aspirated without disturbing the cell pellet, first by removing the bulk down to 100 pl with a 1,000 pl pipette, followed by removing the remaining 100 pl with a 200 pl pipette. The cell pellet was then resuspended in 50 pl of cold ATAC Resuspension Buffer (RSB) containing 0.1% NP-40, 0.1% Tween-20, 0.01% digitonin, and lx RNase A. The mixture was gently pipetted up and down three times and incubated on ice for 3 minutes. Client docket no. S24-450

[0079] Attorney docket no. STDU2-44064.601

[0080] Following incubation, 1 ml of cold ATAC RSB supplemented with 0.1% Tween-20 and lx RNase A (but without NP-40 or digitonin) was added to wash out the lysis buffer. The tube was inverted three times to mix the contents. The nuclei were then pelleted by centrifugation at 500 x g for 10 minutes at 4 °C. The supernatant was carefully removed using the two-step pipetting method to avoid disturbing the nuclei pellet. The nuclei pellet was resuspended in 50 p.1 of transposition mixture by gentle pipetting up and down six times. The transposition mix consisted of 25 pl of 2x TD buffer (20 mM Tris-HCl, 10 mM MgCE, 20% dimethylformamide), 2.5 pl of transposome assembly, 16.5 pl of PBS, 0.5 pl of 1% digitonin, 0.5 pl of 10% Tween-20, 0.5 pl of lOOxRNase A, and 4.5 pl of nuclease-free water. The transposition reaction was incubated at 37 °C for 30 minutes in a thermomixer.

[0081] For the primary amplification of transposed fragments, the transposed nuclei were resuspended in 50 pl of T7 ligation mix, which included 25 pl of 2x StickTogether Buffer, 2 pl of 25 pM SP-ATAC-Readl primer, 2 pl of T7 ligase, and 21 pl of nuclease-free water. The mixture was incubated overnight at 25 °C. The reaction was then cleaned up using the Qiagen MinElute PCR Purification Kit (catalog number D4014). The DNA was eluted in 21 pl of elution buffer and stored at -20 °C until amplification. Typically, this elution yields approximately 20 pl of product, all of which was used in the subsequent PCR amplification. The bulk ATAC-seq library preparation was then prepared following OMNIATAC-seq protocol12.

[0082] Tn5 transposome assembly

[0083] The assembly of Tn5 transpsome was performed as previously described (Chen X et al. ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing. Nat Methods. 2016 Dec;13(12):1013-1020). Initially, oligonucleotides (Tn5Me, Tn5MErev-15PA, Tn5MEB, Tn5MErev) were prepared at a concentration of 100 pM by resuspension in water. Equal volumes of Tn5ME / Tn5MErev-15PA and Tn5ME-B / Tn5MErev were mixed separately in 200 pl PCR tubes to achieve a concentration of 50 pM each. The mixtures underwent denaturation at 95 °C for 5 minutes on a thermocycler and were then slowly cooled by turning off the thermocycler.

[0084] Subsequently, equal volumes of Tn5ME / Tn5MErev-15PA and Tn5ME-B / Tn5MErev were combined to achieve a concentration of 25 pM each. To make a stock of transposase adaptor, glycerol and oligo mixtures were then mixed in equal amounts to yield a concentration Client docket no. S24-450

[0085] Attorney docket no. STDU2-44064.601 of 12.5 pM each. For each Visium reaction, Tn5 transposase assembly was as following: 7.5 ul transposase adaptors, 3.75 ul ddH2O and 3.75 ul Tn5 transposase (Diagenode, C01070010). The resulting solution was gently mixed and left at room temperature for 30 minutes to facilitate the annealing of oligos to Tn5.

[0086] SPACE-seq

[0087] Cryosections were prepared at a thickness of 10 pm using a cryostat (Epredia HM525 NX), placed onto glass slides, and kept on dry ice. A thermocycler adaptor (10X Genomics) was pre-equilibrated at 37 °C on a thermomixer, and tissue slides were incubated on the adaptor for 1 minute.

[0088] 10X Genomics Visium cassettes were assembled onto tissue slides. Each well was filled with 150 pl of 1% formaldehyde in Dulbecco's Phosphate-Buffered Saline (DPBS) and incubated at room temperature for 10 minutes to fix the tissue. To quench the fixation, 150 pl of IM Tris- HC1 was added to each well and incubated for 5 minutes. Next, the solution was aspirated, and 100 ul of DPBS was added, along with 1 U / ul RNase inhibitor (DPBS-I). After aspirating DPBS- I solution, 100 ul of blocking solution (2% bovine serum albumin [BSA], 0.01% Tween-20, lU / ul RNase inhibitor in DPBS) was applied to each well and incubated for 15 minutes at 4 °C. The blocking solution was then removed, and 100 ul of staining solution comprising 0.5 ul DAPI and 0.5 ul wheat germ agglutinin (WGA) antibody was added to each well and incubated at 4 °C for 15 minutes. Each well was then washed once with 200ul of DPBS-I. For imaging, 85% Glycerol in DBPS-I was added to slides, and coverslips were applied. After imaging, coverslips were removed by immersing slides in DPBS solution within a 50 ml tube, and tissues were rehydrated with DPBS.

[0089] Following rehydration, 100 pl of DPBS-I was added to each well. Subsequently, 100 pl of 0.1 U / pl porcine phospholipase A2 (pPLA2) with lU / pl RNase inhibitor was applied, and the slides were gently shaken at 300 rpm for 6 minutes. The slides were washed with DPBS-I and then treated with 100 pl of RSB buffer containing 0.1% NP40, 0.1% Tween-20, 0.01% Digitonin, and lU / pl RNase inhibitor for 10 minutes at room temperature, and 100 pl of RSB-TI (with 0.1% Tween-20 and lU / pl RNase inhibitor) was then added to each well for 5 minutes.

[0090] After aspiration, 100 pl of transposition mix containing 50 pl 2x TD buffer, 15 pl transposome assembly, 33 pl DPBS, 1 pl 1% digitonin, 1 pl 10% Tween-20, and 2.5 pl RNase Client docket no. S24-450

[0091] Attorney docket no. STDU2-44064.601 inhibitor was added to each well. The slides were then incubated at 37 °C for 60 minutes with gentle shaking at 300 rpm. To halt the transposition reaction, 10 pl of 500 mM EDTA was added to each well, and the slides were incubated at 37 °C for an additional 10 minutes. Each well was then washed with DPBS-I and added with 100 pl of a 5X saponin solution (50 pl 10X saponin, 47.5 pl DPBS, and 2.5 pl RNase inhibitors) and was incubated at 4 °C for 10 minutes.

[0092] After an additional washing step with DPBS-I, 150 pl of 10% Eosin was applied to the slides for a 1-minute incubation at room temperature to stain the tissues. The slides were washed once with DPBS-I and, when completely dehydrated, placed on the tissue slide stage of the Cytassist machine. A permeabilizing mixture was prepared containing 50 pl of RNase buffer (PN-2000551, 10X Genomics), 7.5 pl of ddH2O, 7.5 pl of 10% SDS and 10 pl of tissue removal enzyme (PN-300387, 10X Genomics). The Visium Cytassist slide was placed on the Visium slide stage and 25 ul of the permeabilizing mixture was added to each spacer well on the Visium cytassist slide. The lid of the Cytassist machine was closed and then the assembly was incubated at 37 °C for 30 minutes.

[0093] Following a DPBS-I wash, 100 pl of T7 ligation mixture (50 pl of 2X sticktogether buffer, 5 pl of T7 ligase, 2.5 pl of RNase inhibitor and 42.5 pl of ddH2O) was applied to each well and incubated at 25 °C for 2 hours. After ligation, each well was aspirated and 75 pl of reverse transcription mixture (10X Genomics) was added. The slides were incubated at 53 °C for 45 minutes. The solution was then removed, and 150 pl of IX NEBNext polymerase mixture was added; the slides were incubated at 72 °C for 15 minutes.

[0094] To reverse cross-link the tissues, each well was treated with 200 pl of a solution containing 50mM Tris-HCl, ImM EDTA, 1% SDS, 200 mM NaCl, and 0.8 pg / ml Proteinase K. The slides were incubated at 58 °C for 1 hour. After washing with DPBS and elution buffer, the ATAC-seq fragments were eluted by treating the wells with 35 pl of 0.08 N NaOH for 10 minutes. The eluted ATAC-seq fragments were neutralized with 5 pl of IM Tris-HCl, and transferred to PCR tubes. Each well was then washed with DPBS and elution buffer.

[0095] For second strand synthesis (SSS), an SSS solution (10X Genomics) was added to each well, and incubated at 65 °C for 15 minutes. Following this, the slides were washed with EB buffer, and the cDNA was eluted with 35 pl of 0.08 N NaOH, and neutralized with 5 pl of IM Tris-HCl. Client docket no. S24-450

[0096] Attorney docket no. STDU2-44064.601

[0097] Library preparation and sequencing

[0098] Spatially barcoded single- stranded cDNA fragments (GEX) were then prepared following the 10X Genomics Gene Expression protocol, starting with step 4 cDNA amplification and Visium Spatial Gene Expression Library Construction. The spatial barcoded ATAC fragments were amplified using Truseq partial read 1 and Nextera partial read 2 (Nextera R2) with NEBNext master mix. The amplified products were purified using 0.9X SPRI beads and the primer dimers (-130 bp) were removed by gel extraction using E-gel EX 2% agarose. The gel- extracted products were then amplified using i7 and i5 indexed primer using NEBNext master mix. The final indexed libraries were cleaned up using 0.8X SPRI beads. The average size of libraries was measured by high sensitivity D5000 ScreenTape (Agilent, 5067-5592) using tapestation and the concentration of libraries was measured by NEBNext library quantification kit for Illumina (NEB, E7630L). Pooled libraries were sequenced on Illumina Nextseq 550 instrument. 29 bases were sequenced for readl, 10 bases for i7 and i5 index and 123 bases for read2.

[0099] Spatial RNA-seq analysis

[0100] Spatial RNA files were processed using the spaceranger count pipeline from 10X Genomics version 2.1.1. With use of the Visium Cytassist slide but not a probe set, the spaceranger count pipeline was modified to process files using polyA-capture settings used for Visium VI slides, but with the spatial barcodes and coordinates of a Visium Cytassist slide. The spaceranger count settings for a Visium V 1 slide were used, with the brightfield image and parameter “-unknown- slide visium- 1”. The spaceranger was then redirected to use the spatial barcodes of the Visium Cytassist slide instead of the Visium VI spatial barcodes by deleting the 3 files (“visium-vl_coordinates.txt,” “visium-vl.gal”, and “visium-vl.txt”), and renaming the corresponding “visium-v4” files to take their place. The files are located and modified within the spaceranger installation under “spaceranger-2.1.1 / lib / python / cellranger / barcodes”. Mouse samples were analyzed using the “refdata-gex-mml0-2020-A” reference genome from 10X (Pleasanton, CA), and human samples were analyzed using “refdata-gex-GRCh38-2020-A”.

[0101] After initial mapping, barcode correction, and quality control was performed by spaceranger, the 10X filtered counts matrix was loaded into Seurat v5 for downstream analysis. Normalization, dimensionality reduction, and clustering were performed in Seurat. For Client docket no. S24-450 Attorney docket no. STDU2-44064.601 consistency with spatial ATAC-seq analysis, after initial quality control using Seurat, gene expression data was loaded into an ArchR GeneExpression matrix, and dimensionality reduction, clustering, and imputation were performed using ArchR. Barcodes were retained for analysis. No additional filtering was performed based on mitochondrial reads, nCounts, or nFeatures. Visualizations were created in R using the package ggplot2.

[0102] Spatial ATAC-seq analysis

[0103] To assure consistency between the RNA and ATAC barcode and UMI correction workflows and spatial mapping, spatial ATAC data was processed using spaceranger with identical settings as described above for spatial RNA data. A table was created from the 10X spaceranger bam file mapping each read name to the associated cell barcode and UMI found in the CB and UB bam tags. In parallel, spatial ATAC files were processed using a conventional ATAC-seq pipeline. Because readl was used to capture the UMI and cell barcode, only read2 was used for ATAC-seq analysis. Reads were trimmed to a maximum length of 75bp and adaptor sequences were removed using 'fastp'. Hisat2 was used to align fastq files to the mmlO or hg38 reference genome using parameters no-spliced-alignment- very-sensitive -X 2000”. The CB and UB tags were added to the hisat2 ATAC-seq alignments using the read name table created from spaceranger as well as a custom python script utilizing the “simplesam” package. Duplicates were removed from the bam file using the “dedup” utility from the “umi_tools” package based on both the cell barcode and umi tags. Finally, a synthetic paired end fragments file was created from the single end alignments for compatibility with ArchR. ArchR was used for downstream spatial ATAC-seq analysis. The “createArrowFiles” step was modified for spatial ATAC-seq by using the permissive parameters “minFragSize=-l”, “maxFragSize=10**10”, “minFrags=100”, and “minTSS=l” to retain nearly all barcodes for downstream analysis. A “tileSize” of 5kb was used for the ArchR TileMatrix. After creation of Arrow files, data pre-processing, dimensionality reduction, clustering, and imputation were performed in ArchR. Barcode spatial positions were loaded into the ArchR metadata to facilitate visualization. As described above for the spatial RNA data, visualizations were created in R using ggplot2. ecDNA copy number estimation Client docket no. S24-450

[0104] Attorney docket no. STDU2-44064.601

[0105] Copy numbers of genomic regions were computed based on background ATAC-seq signals as previously described and validated16. Read counts were determined in large intervals across the genome using a sliding window of 3 megabases moving in 1 -megabase increments across the reference genome. Genomic regions with known mapping artifacts were filtered out using the ENCODE hg38 blacklist. For each interval, insertions per base pair were calculated and compared to 200 of its nearest neighbors with matched GC nucleotide content. Mean log2(fold change) was computed for each interval. Based on a diploid genome, copy numbers were calculated using the formula CN = 2 * [2Alog2(FC)], where CN denotes copy number and FC denotes mean fold change compared to neighboring intervals. To query the copy numbers of a gene, all genomic intervals were obtained that overlapped with the annotated gene sequence and computed the mean copy number of those intervals.

[0106] Analysis of mitochondrial DNA mutations from spatial ATAC-seq data

[0107] To identify somatic mitochondrial DNA (mtDNA) variants from spatial ATACseq data, the spatial ATAC-seq pipeline described above was repeated using a reference genome where nuclear regions of hg38 that mtDNA may erroneously align to are removed to enable uniform mapping of reads across the mitochondrial genome18. The quality-filtered and deduplicated bam file was then passed to mgatk in tenx mode for variant calling18. High confidence variants were determined based on variants that had a strand correlation of at least 0.25. Variant heteroplasmy for each variant for each cell were loaded into the original ArchR project metadata for visualization and analysis.

[0108] EXAMPLE 1 - Integration of transposome, ligation conditions and tissue permeabilization

[0109] To integrate 1) a polyA-loaded transposome, 2) ligation conditions for attachment of spatial barcode chromatin fragments, and 3) tissue permeabilization reagents and conditions for Tn5 access to nuclear DNA without loss of tissue integrity together with release of chromatin fragments for capture by a spatial slide, the 3 parameters were systematically tested using bulk ATAC-seq (Fig. 2b-e). 15 base pair (bp) polyA adaptors provided higher enrichment at the transcription start site (TSS), and T7 DNA ligase yielded consistently superior data quality compared to T4 DNA ligase (Fig. 2b). Combining 15 bp polyA adaptors with T7 DNA ligase yielded ATAC-seq data highly correlated with results from the conventional ATAC-seq protocol Client docket no. S24-450

[0110] Attorney docket no. STDU2-44064.601 using a Tn5 transposome with traditional adaptors (Fig. 2c). To enhance Tn5 access to nuclear DNA, the use of phospholipase A2 (PLA2) was tested to disrupt phospholipids in the cell membrane to facilitate entry of the Tn5 transposome into the nucleus. Introduction of PLA2 improved the quality of bulk ATAC-seq data obtained from mouse brain samples (Fig. 2d-e). Accordingly, in some embodiments use of 15 bp polyA adaptors, T7 DNA ligase, and PLA2 are integrated in SPACE-seq.

[0111] EXAMPLE 2 - PolyA-tailed ATAC fragments and polyadenylated mRNAs capture

[0112] To test whether polyA-tailed ATAC fragments and polyadenylated mRNAs are effectively captured using standard spatial transcriptomics reagents, spatially barcoded Visium slides from 10X Genomics were selected due to widespread availability and use (Fig. 3). Using mouse brain tissue sections, increasing the amount of Tn5 transposome was found to be critical for enhancing fragment yield (Fig. 3a-b). The Visium vl workflow was compared with the Visium v2 CytAssist-enabled workflow with incorporated mRNA capture. The Visium v2 CytAssist-enabled SPACE-seq workflow resulted in a significantly larger number of ATAC-seq fragments, while maintaining comparable RNA unique molecular identifiers (UMIs) per spot (Fig. 3b-d). The Visium v2 CytAssist-enabled SPACE-seq workflow was selected for further characterization (Fig. la, Fig. 4).

[0113] EXAMPLE 3 - Mouse brain spatial ATAC-seq and RNA-seq libraries

[0114] 3810 spots under tissue were identified in the mouse brain dataset for quality control on the spatial ATAC-seq and spatial RNA-seq libraries (Fig. lb, 5a-c). Unbiased dimensionality reduction and clustering of the spots demonstrated that both spatial ATAC and spatial RNA modalities independently recapitulated the known organization of the mouse brain. Specifically, cluster Cl corresponded to the cerebral cortex, cluster C2 to the hippocampus, cluster C4 to cerebral nuclei (CNU), and cluster C5 to the thalamus. (Fig. 1c, Fig. 5d). This was further confirmed by visualizing both ATAC and RNA data for known marker genes such as Mef2c, Neurod6 and Nlngl, alongside reference in situ hybridization data from the Allen Brain Atlas (Fig. Id-e, Fig. 5e, Fig. 6). High concordance of the spatial RNA gene expression and spatial ATAC gene accessibility across clusters was observed and regulatory elements that control expression of the marker genes identified (Fig. If-g, Fig. 5e). Client docket no. S24-450

[0115] Attorney docket no. STDU2-44064.601

[0116] EXAMPLE 4 - SPACE-seq applied to a human glioblastoma sample

[0117] SPACE-seq was applied to an archived human glioblastoma sample (Fig. 7a-b). Despite the storage for > 2 years, high-quality data was obtained for both spatial ATAC-seq and spatial RNA-seq (Fig.7c, Fig. 8a). Dimensionality reduction and clustering were performed independently for each modality (Fig. 8b), and the results integrated to obtain unified cluster assignments incorporating both the ATAC and RNA data, thereby identifying four distinct clusters (Fig. 7d, Fig. 8c). Cluster Cl was the most distinct cluster and was marked by a mesenchymal-like hypoxia signature, including upregulation of genes such as VEG FA. NDRG1, a J ADM, consistent with prior literature (Fig. 7e, Fig. 9a)13. Cluster C2 exhibited signatures of malignant mesenchymal-like cells characterized by genes like CLU, and CD44, as well as macrophage markers CD 14 and C1QA (Fig. 9b). Cluster C2 also showed the highest expression and accessibility for EGFR, which was amplified on extrachromosomal DNA (ecDNA) in this sample (Fig. 7e, Fig. 10a). Cluster C3 displayed malignant oligodendrocyte progenitor-like cell (OPC) signatures, with genes such as BCAN, OLIG2, and TTYH1. and astrocyte-like characteristics marked by BCAN and S100B (Fig. 7e, Fig. 9c). Cluster C4 exhibited features of malignant neural progenitor-like cells (NPC), expressing genes like DCX and RUNX1T1, and showed enrichment of chromatin and transcriptional regulators such as NFIA, NFIB, and PLCG2 (Fig. 7e, Fig. 9d). These findings align with previously published transcriptomic cellular phenotypes within glioblastomal13-15. Spatial epigenomic data identified regulatory elements and transcription factors that underlie observed transcriptional phenotypes, such as HIF1A, a key responder to hypoxia, and activator protein 1 (AP-1) complex components, such as JUN and FOS family members in Cl, CTCF in C2, OL1G2 / 3 in C3, and NFIA / B in C4 (Fig. 9f-h).

[0118] EXAMPLE 5 - ATAC-seq of the extrachromosomal amplified region of 7pll

[0119] Single cell ATAC-seq data are sensitive to many features of tumor biology including ecDNA heterogeneity and somatic evolution16-18. To determine whether spatial ATAC-seq data of the present invention serve parallel purposes, the spatial ATAC-seq signal from the extra- chromosomally amplified region on chromosome 7pl 1 was examined (Fig. 10a). This region was observed to exhibit high amplification, with a putative driver mutation within the EGFR gene (EGFR p.F254I; Fig. 10a). The mutation in the extracellular domain of EGFR, has been Client docket no. S24-450

[0120] Attorney docket no. STDU2-44064.601 reported in other glioblastoma patients19. The ecDNA copy number was estimated across the tumor with the EGFR ecDNA copy number enriched in cluster C2 (Fig. 10b). Both gene accessibility and gene expression of EGFR were highest in cluster C2 and downregulated in hypoxic areas in cluster Cl (Fig. 7e, Fig. lOb-d), indicating that the tumor microenvironment plays an important role in oncogene expression influenced by ecDNA copy number. Accordingly, SPACE-seq discloses features of tumor biology including ecDNA copy number and identification of putative driver mutations not achievable with conventional spatial transcriptomics.

[0121] EXAMPLE 6 - SPACE-seq reads map to the mitochondrial genome and are sensitive to clonal dynamics

[0122] Mitochondrial DNA (mtDNA) is present at up to 1000 copies per cell with a mutation rate 100-fold greater than nuclear DNA thereby providing a powerful recorder of somatic cell lineages in adult humans17,20. To test whether spatial ATAC-seq reads of the present invention mapping to the mitochondrial genome are sensitive to clonal dynamics within the tumor17 18-20-21the mgatk tool was used to identify variants (Fig. I la). Twelve high-confidence somatic mitochondrial mutations with differing levels of heteroplasmy (z.e., allele frequency) were observed. The variants were prevalent throughout the glioblastoma tissue (Fig. 7i, Fig. l lb-e). Seven of the 12 variants showed higher heteroplasmy levels in cluster C3 and lower levels in cluster C4, while clusters Cl and C2 exhibited similar heteroplasmy levels. (Fig. 7i-j, Fig. l id). Lineage analysis indicated that NPC cluster C4 harboring the minor alleles may represent the initial clone of cells. In contrast, the clone of cells containing the major allele of the variants, that is enriched in OPC cluster C3 differentiated later. Although clusters Cl and C2 had distinct transcriptional and epigenetic profiles, they shared a close clonal relationship with intermediate heteroplasmy levels, indicating that the clusters may have initially differentiated from NPC-like lineages into mesenchymal-like lineages, with cluster Cl subsequently becoming hypoxic. This is consistent with findings that show a bidirectional cell-fate shift influenced by the tumor microenvironment14. These data indicate that somatic mitochondrial mutations identified by SPACE-seq are sensitive to clonal dynamic trajectories during tumor evolution.

[0123] REFERNCES Client docket no. S24-450

[0124] Attorney docket no. STDU2-44064.601

[0125] 1. Goltsev. Y. et al. Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging. Cell 174, 968-981 e915 (2018).

[0126] 2. Rodriques, S. G. et al. Slide-seq: A scalable technology for measuring genomewide expression at high spatial resolution. Science 363, 1463-1467 (2019).

[0127] 3. Llorens-Bobadilla, E. et al. Solid-phase capture and profiling of open chromatin by spatial ATAC. Nat Biotechnol (2023).

[0128] 4. Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-pattemed arrays. Cell 185, 1777-1792 el721 (2022).

[0129] 5. Vickovic, S. et al. SM-Omics is an automated platform for high-throughput spatial multi- omics. Nat Commttn 13, 795 (2022).

[0130] 6. Zhao, T. et al. Spatial genomics enables multi-modal study of clonal heterogeneity in tissues. Nature 601, 85-91 (2022).

[0131] 7. Deng, Y. et al. Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level. Science 375, 681-686 (2022).

[0132] 8. Ben-Chetrit, N. et al. Integration of whole transcriptome spatial profiling with protein markers. Nat Biotechnol (2023).

[0133] 9. Zhang, D. et al. Spatial epigenome-transcriptome co-profiling of mammalian tissues. Nature 616, 113-122 (2023).

[0134] 10. Russell, A. J. C. et al. Slide-tags enables single-nucleus barcoding for multimodal spatial genomics. Nature 625, 101-109 (2024).

[0135] 11. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods 10. 1213-1218 (2013).

[0136] 12. Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat Methods 14, 959-962 (2017).

[0137] 13. Greenwald, A. C. et al. Integrative spatial analysis reveals a multi-layered organization of glioblastoma. Cell 187, 2485-2501 e2426 (2024).

[0138] 14. Ravi, V. M. et al. Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma. Cancer Cell 40, 639-655 e613 (2022).

[0139] 15. Wang, L. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell- intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534-1552 (2022). Client docket no. S24-450

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[0141] 16. Hung, K. L. et al. ecDNA hubs drive cooperative intermolecular oncogene expression. Nature 600, 731-736 (2021).

[0142] 17. Ludwig, L. S. et al. Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics. Cell 176, 1325-1339 el322 (2019).

[0143] 18. Lareau, C. A. et al. Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling. Nat Biotechnol 39, 451-461 (2021).

[0144] 19. Higa, N. et al. Distribution and favorable prognostic implication of genomic EGFR alterations in IDH-wildtype glioblastoma. Cancer Med 12, 49-60 (2023).

[0145] 20. Xu, J. el al. Single-cell lineage tracing by endogenous mutations enriched in transposase accessible mitochondrial DNA. Elife 8 (2019).

[0146] 21. Weng, C. et al. Deciphering cell states and genealogies of human haematopoiesis. Nature 627, 389-398 (2024).

[0147] 22. Kaya-Okur, H. S. et al. CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat Commun 10, 1930 (2019).

[0148] All publications mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described method and system of the disclosure will be apparent to those skilled in the art without departing from the scope and spirit of the disclosure. Although the disclosure has been described in connection with specific embodiments, it should be understood that the disclosure as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the disclosure that are obvious to those skilled relevant fields are intended to be within the scope of the following claims.

Claims

1. Client docket no. S24-450Attorney docket no. STDU2-44064.601CLAIMS1. A composition, comprising a poly-adenosine (poly-A)-tailed transposome, comprising: a) a Tn5 transposase; b) a poly-A adaptor sequence; c) a mosaic end transposase recognition sequence (ME); and d) a transposase-based second read adaptor sequence.

2. A method comprising: a) providing a poly-adenosine (poly-A)-tailed transposome, comprising:1) a Tn5 transposase;2) a poly-A adaptor sequence;3) a mosaic end transposase recognition sequence (ME); and4) a transposase-based second read adaptor sequence; b) fixing a tissue of interest on a surface; c) staining said tissue to produce a stained tissue; d) imaging said stained tissue; e) permeabilizing said imaged tissue in a first permeabilizing reaction; f) fragmenting DNA and / or RNA in said permeabilized tissue and tagging saidDNA and / or RNA with said poly-A adaptor sequences in a transposition reaction; g) permeabilizing said tissue in a second permeabilizing reaction; h) transferring said permeabilized tissue from said surface to a second surface comprising one or more capture sequences wherein said capture sequences comprise one or more of a barcode (BC), a unique molecular identifier (UMI) and a polyT-sequence; i) generating a sequencing library; j) generating a spatial RNA expression sequencing (RNA-seq) library; k) amplifying said sequencing library and said RNA-seq library; l) sequencing said amplified sequencing library and said RNA-seq library with nextgeneration sequencing to generate next generation sequencing data; and m) analyzing said next generation sequencing data for one or more of cell cluster analysis, cell lineage analysis, chromatin accessibility analysis, RNA expression analysis,Client docket no. S24-450Attorney docket no. STDU2-44064.601 spatial mapping analysis, extrachromosomal DNA (ecDNA) analysis, ecDNA copy number analysis, mitochondrial DNA analysis, and transcription factor motif analysis.

3. The method of claim 2, wherein said second surface is a glass slide.

4. The method of claim 3, wherein said glass slide is a poly-T slide.

5. The method of claim 2, wherein said transferring said permeabilized tissue from said first surface to said second surface comprises use of a instrument configured to transfer gene-specific transcriptomic probes from said first surface to said second surface for spatial profiling across one or more tissue sections.

6. The method of claim 2, wherein said generating said sequencing library comprises ligation with a ligase, extension, tissue digestion, amplification, clean up and purification of said sequencing library.

7. The method of claim 6, wherein said sequencing library is an ATAC-seq library.

8. The method of claim 6, wherein said amplification is polymerase chain reaction (PCR) amplification.

9. The method of claim 2, wherein said generating said spatial RNA expression sequencing (RNA-seq) library comprises reverse transcription with template switching, tissue digestion, second strand synthesis, and cDNA library preparation.

10. The method of claim 2, wherein said amplifying said sequencing library and said RNA- seq library comprises polymerase chain reaction (PCR) amplifying with one or more bar coded primers.

11. A kit, comprising : a) a poly-adenosine (poly-A)-tailed transposome, comprising:Client docket no. S24-450Attorney docket no. STDU2-44064.6011) a Tn5 transposase;2) a poly-A adaptor sequence;3) a mosaic end transposase recognition sequence (ME); and4) a transposase-based second read adaptor sequence; and b) instructions for use of said kit comprising said poly-adenosine (poly-A)-tailed transposome.

12. Use of a poly-adenosine (poly-A)-tailed transposome, comprising: a) a Tn5 transposase; b) a poly-A adaptor sequence; c) a mosaic end transposase recognition sequence (ME); and d) a transposase-based second read adaptor sequence.

13. A system, comprising: a) a poly-adenosine (poly-A)-tailed transposome, comprising:1) a Tn5 transposase;2) a poly-A adaptor sequence;3) a mosaic end transposase recognition sequence (ME); and4) a transposase-based second read adaptor sequence; b) a surface comprising one or more capture sequences wherein said capture sequences comprise one or more of a barcode (BC), a unique molecular identifier (UMI) and a polyT-sequence; and c) an instrument configured to transfer gene-specific transcriptomic probes to said surface for spatial profiling across one or more tissue sections.

14. The system of claim 13. wherein said surface is a glass slide.

15. The system of claim 14, wherein said glass slide is a poly-T slide.

16. The system of claim 13, comprising one or more of a glass slide configured for tissue fixation, an immunofluorescent stain, a fluorescent imaging instrument, a permeabilizingClient docket no. S24-450Attorney docket no. STDU2-44064.601 reagent, a transposition reaction vessel, a ligase, an extension reagent, proteinase K, a sequencing library, a spatial RNA expression sequencing (RNA-seq) library, one or more PCR amplification bar code oligonucleotide primers, an instrument configured for PCR amplification, and / or an instrument configured for next generation sequencing.

17. The system of claim 16, wherein said sequencing library is an ATAC-seq sequencing library.

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