Spatiotemporal resolution of transcriptomics at subcellular resolution

Abstract

The present disclosure provides methods for profiling spatiotemporal gene expression, including methods for profiling spatiotemporal gene expression in vivo in a subject.The present disclosure also provides methods for profiling the role of post-transcriptional modification in spatiotemporal gene expression, methods for studying the role of spatiotemporal gene expression in the development or progression of disease or disorder, methods for screening agents that can regulate spatiotemporal gene expression, methods for diagnosing disease or disorder in a subject, and methods for treating disease or disorder in a subject.Oligonucleotide probes useful in the methods described herein are also provided by the present disclosure.The present disclosure also provides kits that include the oligonucleotide probes disclosed herein.A system for profiling spatiotemporal gene expression is also provided by the present disclosure.

Description

[Technical Field]

[0001] Related applications This application claims priority to U.S. Provisional Application USSN 63 / 185,511, filed on 7 May 2021, and U.S. Provisional Application USSN 63 / 314,873, filed on 28 February 2022, under 35 U.S.C. § 119(e); each of these is incorporated herein by reference. [Background technology]

[0002] Background of the Invention The regulated flow of gene expression forms some of the most fundamental processes of life and influences the onset and progression of many diseases and disorders. These highly controlled processes include transcription, RNA processing, translation, and the degradation of messenger RNA (mRNA) and proteins. The development of spatial transcriptomics methods is bringing about a rapid paradigm shift towards single-cell sequencing techniques by preserving genetic information in a spatial context, enabling direct visualization of cell organization and tissue structure. However, current spatial transcriptomics methods only detect mRNA as a static image of the transcriptome, obscuring its highly dynamic nature. Furthermore, most current methods focus at the pancellular level, determining heterogeneous cell types and remapping them to tissues, while ignoring the rich information in the intracellular environment. Therefore, methods that link spatial transcriptomics to the temporal dimension are needed to study gene expression in a spatial context over time and to understand the relationship between spatiotemporal gene expression and cell development, as well as the onset and progression of various diseases and disorders. [Overview of the Initiative]

[0003] Summary of the Invention This disclosure describes a method for profiling spatiotemporal gene expression in one or more cells (including, for example, cells present in a tissue). In one aspect, a method referred to herein as “TEMPOmap” (temporally resolved in situ sequencing and mapping) is described. TEMPOmap can be used to track the dynamics of gene expression (i.e., the transcriptome) by degrading newly transcribed RNA at subcellular resolution and incorporating temporal resolution into spatial transcriptome workflows. This method provides image-based single-cell descriptions at the subcellular level and can be used to study intracellular activities such as epitranscriptome processing, mRNA trafficking, local translation, and dynamic parameters of RNA translation. TEMPOmap can also be used to study intact tissue and to understand and identify the causes of the onset and progression of various diseases and disorders associated with changes in gene expression. The methods described herein provide invaluable tools for facilitating the understanding of RNA, proteins, and their interactions, and for visualizing how genomic information is processed temporally and spatially. Any of these methods can be performed in vivo, as further described herein.

[0004] Therefore, in one aspect, this disclosure provides a method for profiling spatiotemporal gene expression in cells, comprising the following steps: a) Incubate cells for time t1 in the presence of a pool of nucleoside analogs to metabolically label the nucleic acids synthesized by the cells, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting metabolically labeled nucleic acids with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more concatenated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix.

[0005] In some embodiments, steps (a) to (h) are performed one or more times. In some embodiments, steps (a) to (h) are repeated at least once using different times t2 during the incubation of step (a). In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally repeated during a fourth time t4, optionally repeated during a fifth time t5, optionally repeated during a sixth time t6, optionally repeated during a seventh time t7, optionally repeated during an eighth time t8, optionally repeated during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0006] In some embodiments, any method disclosed herein is useful for the diagnosis and / or treatment of diseases or disorders. In some embodiments, any method disclosed herein is useful for studying the dynamic parameters of RNA translation. In some embodiments, any method disclosed herein is useful for studying post-transcriptional RNA modifications. In some embodiments, any method disclosed herein is useful for studying spatiotemporal gene expression at various stages of the cell cycle and cell replication.

[0007] In another aspect, this disclosure provides methods for profiling the role of post-transcriptional modifications in spatiotemporal gene expression. In some embodiments, the spatiotemporal gene expression profiling methods described herein may be carried out in cells comprising knockdown of genes involved in the post-transcriptional modification of one or more nucleic acids of interest (e.g., one or more RNA transcripts). The spatiotemporal expression of various nucleic acids of interest in the knockdown cells can then be compared to the spatiotemporal expression of the same nucleic acids of interest in wild-type cells. Any changes in the expression of the nucleic acids of interest compared to their expression in wild-type cells may indicate that post-transcriptional modifications are involved in regulating the spatiotemporal expression of the nucleic acids of interest.

[0008] In another aspect, this disclosure provides methods for studying the role of spatiotemporal gene expression in the onset or progression of disease or disorder. For example, the methods for profiling spatiotemporal gene expression described herein may be performed in cells from diseased tissue (e.g., diseased tissue taken from a subject). The spatiotemporal expression of various target nucleic acids in cells from diseased tissue can then be compared with the spatiotemporal expression of the same target nucleic acid in cells from non-disease tissue. Any changes in the expression of the target nucleic acid compared to its expression in non-disease cells may indicate that the spatiotemporal expression of the target nucleic acid may be involved in the onset or progression of disease or disorder.

[0009] In another aspect, this disclosure provides a method for screening agents capable of modulating the spatiotemporal gene expression of a nucleic acid of interest or a group of nucleic acids of interest. For example, the spatiotemporal gene expression profiling method described herein may be performed in cells (e.g., normal or diseased cells) in the presence of one or more candidate agents. The spatiotemporal expression of various nucleic acids of interest in the cells can then be compared to the spatiotemporal expression of the same nucleic acid of interest in cells not exposed to one or more candidate agents. Any change in the expression of the nucleic acid of interest (one or more) compared to the expression in cells not exposed to the candidate agent(s) may indicate that the spatiotemporal expression of the nucleic acid of interest (one or more) is modulated by the candidate agent(s).

[0010] In another aspect, this disclosure provides a method for diagnosing disease or disorder in a subject. For example, the spatiotemporal gene expression profiling method described herein can be performed on cells from a sample taken from a subject (e.g., a subject suspected of having or at risk of having disease or disorder). The spatiotemporal expression of various target nucleic acids in the cells can then be compared to the spatiotemporal expression of the same target nucleic acid in cells from a non-disease tissue sample. Any change in the expression of the target nucleic acid compared to its expression in non-disease cells may indicate that the subject has disease or disorder.

[0011] In another aspect, this disclosure provides methods for treating a disease or disorder in a subject. For example, the spatiotemporal gene expression profiling method described herein can be performed on cells from a sample taken from a subject (e.g., a subject suspected of having a disease or disorder, or at risk of having a disease or disorder). The spatiotemporal expression of various target nucleic acids in the cells can then be compared to the spatiotemporal expression of the same target nucleic acid in cells from a non-disease tissue sample. If any changes are observed in the expression of the target nucleic acid compared to the expression in non-disease cells, treatment for the disease or disorder can then be applied to the subject.

[0012] In another aspect, this disclosure provides a method for profiling spatiotemporal gene expression in a subject in vivo, comprising the following steps: a) A pool of nucleoside analogs is administered in vivo to a subject for time t1 to metabolically label nucleic acids synthesized by one or more cells of the subject, wherein each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) To collect a tissue sample from the subject; c) Contacting the metabolically labeled nucleic acid in the collected tissue sample with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; d) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where; i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; e) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; f) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; g) Embedding one or more linked amplicons into a polymer matrix; h) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and i) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix.

[0013] In another aspect, the present disclosure provides a plurality of oligonucleotide probes, including a first oligonucleotide probe, a second oligonucleotide probe, and a third oligonucleotide probe, wherein i) The first oligonucleotide probe comprises a reactive chemical moiety; ii) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the nucleic acid of interest; and iii) The third oligonucleotide probe comprises a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe, and a second barcode sequence. Here, the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe.

[0014] In some embodiments, the disclosure provides an oligonucleotide probe comprising the structure: 5'-[reactive chemical portion]-[polyA linker sequence]-[portion complementary to a third oligonucleotide probe]-[polymerization blocker]-3', where -[ comprises an optional nucleotide linker. In some embodiments, the disclosure provides an oligonucleotide probe comprising the structure: 5'-[portion complementary to the nucleic acid of interest]-[barcode sequence]-3', where -[ comprises an optional nucleotide linker. In some embodiments, the disclosure provides an oligonucleotide probe comprising the structure: 5'-[first portion complementary to a first oligonucleotide probe]-[first barcode sequence]-[portion complementary to the nucleic acid of interest]-[second barcode sequence]-[second portion complementary to a first oligonucleotide probe]-3', where -[ comprises an optional nucleotide linker.

[0015] In another aspect, this disclosure provides a kit comprising one or more oligonucleotide probes described herein.

[0016] In another aspect, the present disclosure provides a system for profiling spatiotemporal gene expression in cells. In some embodiments, the system comprises: a) cells; b) a pool of nucleoside analogs, where each nucleoside analog in the pool comprises a reactive chemical moiety (e.g., a bioorthogonal functional group such as a click chemistry handle); c) a first oligonucleotide probe, where the first oligonucleotide probe comprises a chemical moiety that reacts with the reactive chemical moiety of the nucleoside analog; and d) one or more pairs of oligonucleotide probes, comprising a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe contains a barcode sequence and a portion complementary to the nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe, and a second barcode sequence. Here, the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe.

[0017] It should be understood that the concepts described above, and the additional concepts described below, can be formed in any suitable combination; for this disclosure is not limited thereto. Furthermore, other advantages and novel features of this disclosure will become apparent when considered in conjunction with the accompanying drawings, from the following detailed description in various non-limiting aspects. [Brief explanation of the drawing]

[0018] Simple description of the drawing The following drawings form part of this specification and are included to further demonstrate certain aspects of the disclosure, and the disclosure can be better understood by referring to one or more of these drawings in combination with the detailed description of the particular aspects presented herein.

[0019] [Figure 1] Figure 1 provides a schematic diagram of time-resolved in situ sequencing and mapping (TEMPOmap) for investigating gene regulatory mechanisms in cells and tissues at subcellular resolution. TEMPOmap integrates temporal resolution and spatial transcriptomics to create a 4D map of RNA. This method maps RNA trajectories in 3D space over tunable timeframes, enabling a deeper understanding of gene regulation in various biological and physiological processes.

[0020] [Figure 2A-1]Figures 2A–2E illustrate the principle of TEMPOmap and the use of nascent RNA labeling chemistry for spatiotemporally resolved (or spatiotemporally resolved) transcriptomics. Figure 2A provides a schematic diagram outlining TEMPOmap. After preparing 5-ethinyluridine (5-EU) labeled cells, a custom 3-part probe is conjugated or hybridized to the cellular mRNA, resulting in enzymatic replication of each padlock sequence to a cDNA amplicon. The amplicons are immobilized in situ on a hydrogel mesh via functionalized acrylic groups to generate a DNA-gel hybrid (wavy line). The 5-base barcode of each amplicon is read by 5 rounds of SEDAL sequencing. Thus, quantification of the multiplexed RNA reveals gene expression at its location within the nascent cell. [Figure 2A-2] Figure 2A provides a schematic diagram illustrating the TEMPOmap. After preparing 5-ethinyluridine (5-EU) labeled cells, a custom 3-part probe is conjugated or hybridized to the cellular mRNA, resulting in enzymatic replication of each padlock sequence to a cDNA amplicon. The amplicons are immobilized in situ on a hydrogel mesh via a functionalized acrylic group to generate a DNA-gel hybrid (wavy line). The 5-base barcode of each amplicon is read by 5 rounds of SEDAL sequencing. Thus, quantification of the multiplexed RNA reveals gene expression at nascent intracellular locations. [Figure 2B] Figure 2B shows the reconstruction of the spatiotemporal trajectory of RNA by integrating different time points. [Figure 2C] Figure 2C provides a schematic diagram of the 3-part DNA probe design. The DNA sprint probe is conjugated to the labeled RNA in a non-targeting manner, and pairing of the sprint probe and padlock probe is required to circularize the padlock. Second pairing of the primer probe and padlock probe amplifies the target-specific signal. [Figure 2D]Figure 2D shows that the presence of all three probes is necessary for signal amplification. mRNA_I represents ACTB, and mRNA_II represents GAPDH. All four images show ACTB (light gray) mRNA and HeLa cell nuclei (dark gray). When EU-treated cells are compared to untreated cells, the signal-to-noise ratio is 30. [Figure 2E] Figure 2E shows the design of the pulse chase experiment (left) and a series of fluorescence images from the experiment (right), illustrating the translocation of ACTB mRNA after washing following 1 hour of EU treatment at different time intervals.

[0021] [Figure 3] Figure 3 provides a schematic diagram of the TEMPOmap 3-part probe. The sprint probe is divided into a poly-A segment and a sprint padlock annealing sequence (nucleotides highlighted in the box on the sprint probe). The sprint probe terminates with an inverted T (as labeled at the 3' end of the probe) to prevent amplification initiation. The padlock probe contains: a sprint padlock annealing sequence complementary to the region on the sprint probe (nucleotides complementary to the sprint probe, highlighted in the box on the padlock probe) and a junction, two regions of the same barcode (labeled "barcode sequence"), a 20nt hybridization region targeting mRNA (nucleotides complementary to mRNA, highlighted in the box on the padlock probe), and a primer padlock annealing sequence (nucleotides complementary to the primer probe, highlighted in the box on the padlock probe). The primer probe contains: a 20nt hybridization region targeting the mRNA region adjacent to the padlock probe (highlighted in the box on the primer probe, a nucleotide complementary to the mRNA); and a primer-padlock annealing sequence complementary to the region on the padlock probe (highlighted in the box on the primer, a nucleotide complementary to the padlock).

[0022] [Figure 4A] Figures 4A–4B show STARmap analysis of knockdown of seven N6-methyladenosine (m6A) writers or readers by siRNA transfection. Figure 4A provides a clustered heatmap of gene expression when each cell was knocked down with one siRNA compared to wild-type cells. [Figure 4B] Figure 4B shows histograms of the number of readings per cell (left) and the number of genes (right).

[0023] [Figure 5] Figure 5 shows the data processing pipeline. This processing pipeline was originally designed for STARmap and illustrates a typical computational workflow for extracting reads from raw image data.

[0024] [Figure 6A] Figures 6A-6B provide schematic diagrams of time-resolved STARmaps at sub-hour and sub-cellular resolutions. Figure 6A illustrates the principle of STARmap. After cell or tissue fixation, DNA probes that hybridize to intracellular mRNA within the cell are enzymatically replicated as cDNA amplicons. Each pair of DNA probes contains a barcode (labeled on the probe) that codes for the gene's identity, which is read out as a fluorescent color through in situ sequencing. [Figure 6B]Figure 6B shows a time-resolved STARmap. Transcription, nuclear export, and degradation rates are measured on a transcriptome scale. Ethinyluridine (EU) is used to label newly transcribed RNA with short pulses, and the sample is fixed after varying durations. The labeled RNA is modified in situ via click chemistry using polymerizable moieties, then copolymerized with acrylamide and embedded in a hydrogel network (wavy lines), after which unlabeled RNA is removed. The spatiotemporal trajectory of RNA within the cell is reconstructed by integrating the STARmap results at multiple time points.

[0025] [Figure 7] Figure 7 provides an additional schematic diagram illustrating the workflow of the TEMPOmap method. Functionalized cDNA amplicons are covalently bonded to a polyacrylamide matrix to enable tissue removal and processing of biomolecules.

[0026] [Figure 8A] Figures 8A–8B illustrate the targeting of hACTB in pulse-chase experiments. Figure 8A provides raw fluorescence images of 5-EU labeled human HeLa cells. HeLa cells were labeled for 2 hours (pulse), then cultured for various times without 5-EU (chase: 0, 2, 4, or 6 hours), followed by fixation and in situ sequencing quantification. Spatial localization of newly transcribed hACTB RNA is shown in light gray, and spatial localization in the cell nucleus is shown in dark gray. [Figure 8B] Figure 8B shows the quantification of the ratio of fluorescence intensities of hACTB RNA versus cell nucleus (DAPI staining) under different conditions.

[0027] [Figure 9A]Figures 9A–9B show the time-course targeting of four m6A-related RNAs in HeLa cells. Figure 9A provides a raw fluorescence image of 5-EU labeled human HeLa cells. HeLa cells were labeled for 12 hours, fixed immediately after labeling, and then sequenced in situ. Each of the four channels indicates the localization of four human RNAs. Cells in the negative control were cultured without 5-EU labeling. [Figure 9B] Figure 9B provides raw fluorescence images of 1-hour labeled HeLa cells, followed by cell cultures at various time intervals (chase: 0–6 hours) without 5-EU before fixation. Each channel represents spatial information for one type of RNA. The legend is shown in Figure 9A.

[0028] [Figure 10A] Figures 10A–10D show schematic diagrams and validations of TEMPOmap. Figure 10A provides an overview of the TEMPOmap workflow: in situ nascent RNA sequencing at multiple time points followed by spatiotemporal RNA analysis. [Figure 10B] Figure 10B provides a schematic diagram of the TEMPOmap experimental workflow, illustrating the procedures for preparing the TEMPOmap amplicon library and in situ SEDAL sequencing. [Figure 10C] Figure 10C illustrates the principle of 3-part DNA probe design. The generation of the amplicon requires the presence of a sprint probe, a circular padlock probe, and a primer probe. [Figure 10D] Figure 10D (left) provides a schematic diagram of the negative control experiment in Figure 10C and representative fluorescent cell images, illustrating the requirements for a 3-part probe for signal amplification. mRNA_I represents ACTB and mRNA_II represents GAPDH. All four images show ACTB (light gray) mRNA in HeLa cells (DAPI is dark gray). Right: Quantification of cell images, showing the average amplicon reading per cell (five images containing approximately 300 cells were measured under each condition). ****p<1e-04. Scale bar: 10 μm.

[0029] [Figure 11A-B] Figures 11A–11E show the spatiotemporal partitioning of single cells and intracellular transcriptomes. Figure 11A shows the design of a TEMPOmap pulse chase experiment. Figure 11B shows the number of reads (amplicons) per cell at each pulse chase time point, normalized by STARmap probe-targeted gene expression. [Figure 11C] Figure 11C shows a magnified view of a representative single cell with period 1 at each time point in the 3D fluorescence image of TEMPOmap during processing. Z-stack range: 10 μm. [Figure 11D] Figure 11D shows the assignment of intracellular regions (nucleus, central, and peripheral) of a representative cell (bottom), and a box plot summarizing the percentage of readings in each intracellular region of all cells at each time point (top). ****P<0.001 (n=1000~2000). [Figure 11E] Figure 11E shows RNA measurements from TEMPOmap single cells (top row) or nucleocytoplasm (middle row), visualized by Potential of Heat-diffusion for Affinity-based Trajectory Embedding (PHATE), color-coded by pulse chase time (I, III) or cell cycle marker gene expression (II, IV). Black arrows, inferred by the RNA degradation vector field, primarily indicate the direction of transitions in chase time progression. Representative raw images of G2 / M phase cells separated on the PHATE coordinate system are shown in the bottom row. Scale bar: 15 μm.

[0030] [Figure 12A-B] Figures 12A–12G show quantitative estimations of intracellular RNA dynamics throughout the cell cycle. Figure 12A shows a dynamic model for estimating RNA dynamics parameters. For each gene, RNA synthesis (α) and total cell degradation constant (β) were estimated using single-cell RNA concentration. Nuclear export constant (λ), nuclear degradation constant (βn), and cytoplasmic (βc) were estimated using intracellular RNA concentration. Figure 12B shows a dynamic model for estimating cytoplasmic translocation (γ) using DR-based analysis. [Figure 12C] Figure 12C shows the mathematical model of the RNA lifecycle and the assumptions about the dynamics used for estimation (bottom right). Figure 12C also shows histograms of the six parameters for all genes that passed QC, and scatter plots and linear fitting curves (bottom left) showing pairwise correlation analysis (Pearson correlation) between parameters and R values. Pairs of parameters showing correlation are highlighted with asterisks (R>0.1). The intensity of the dots indicates local density. [Figure 12D-E] Figure 12D provides a heatmap showing pairwise correlation matrices of six parameters estimated using single cells from three phases of the cell cycle (G1, G1 / S, G2 / M). Shading according to the provided legend indicates Pearson correlation values. Areas enclosed by rectangles show the correlation of each parameter across the cell cycle. Figure 12E provides a UMAP representation (left) and a heatmap (right) showing gene clustering using all 18 estimated parameters across the cell cycle. Shading according to the provided legend in the heatmap represents normalized Z-score values ​​for each parameter. [Figure 12F-G] Figure 12F shows gene pathway enrichment analysis in each cluster of Figure 12E using DAVID. Figure 12G provides visualization of four dynamic clusters of representative cells across pulse chase time points. Scale bar: 10 μm.

[0031] [Figure 13A-B]Figures 13A–13G show differential RNA dynamics based on gene function and post-transcriptional features. Figure 13A provides a heatmap showing pairwise correlations of all genes by single-cell RNA covariance when all time points are combined, with shading indicating Pearson correlation values. The four dynamic clusters from Figure 12E are shaded on the right, indicating the cluster to which each gene belongs. Groups 1 and 2 are highlighted as highly correlated gene modules. Figure 13B shows enlarged views of Group 1 (top) and Group 2 (bottom), showing the correlation of RNA covariances of each gene module across individual time points. Complete heatmaps for individual time points are shown in Figure 19A. [Figure 13C-D] Figure 13C shows the results of gene pathway enrichment analysis in groups 1 and 2. Figure 13D provides box plots showing the distribution of RNA synthesis (α, left) and total cell degradation constant (β, right) in groups 1 and 2. [Figure 13E] Figure 13E provides a box plot showing the distribution of six parameters estimated for DNA-binding genes, RNA-binding genes, and cell-cell junction-related genes. [Figure 13F] Figure 13F provides a heatmap showing the parameter correlation matrices of DNA binding, RNA binding, and intercellular binding-related genes across the cell cycle. Shading indicates Pearson correlation values. Areas enclosed by rectangles show the correlations of each parameter across the cell cycle. [Figure 13G] Figure 13G shows a box plot comparing six parameters estimated for m6A and non-m6A RNA. **p<0.05, ***p<0.01, ****p<0.001. The y-axis range was selected for the 25th–75th percentile values ​​in Figures 13E and 13G.

[0032] [Figure 14A-B]Figures 14A–14E show the TEMPOmap experimental design and optimization. Figure 14A shows the use of CuAAC-mediated click chemistry for conjugation of azide-modified sprints and EU-labeled nascent transcripts. Figure 14B shows a comparison of TEMPOmap's 2-probe and 3-probe designs. Left: schematic diagram of the probe design. Center: representative fluorescence images of cells treated with sense-targeted and antisense-targeted padlocks and primers. Right: quantification of fluorescence in cell images (n=150–200 for each measurement). [Figure 14C] Figure 14C shows the DNA sequences of the TEMPOmap 3 probe system. [Figure 14D] Figure 14D shows a proof-of-concept pulse-chase experiment (top) followed by raw cell images (bottom), illustrating the migration of ACTB mRNA when chased at different time intervals after 1 hour of EU treatment. Cell nuclei (dark gray), amplicons (light gray). Scale bar: 10 μm. [Figure 14E] Figure 14E shows the simultaneous mapping and sequencing of nascent RNA using TEMPOmap and total RNA using STARmap in the experimental workflow. Amplicon readings using TEMPOmap were normalized to RNA readings using STARmap.

[0033] [Figure 15A] Figures 15A to 15D illustrate the data processing and analysis of TEMPOmap. Figure 15A shows the data analysis pipeline for TEMPOmap. [Figure 15B-C] Figure 15B provides a schematic diagram of read assignments within intracellular compartments. Figure 15C provides histograms showing detected reads (DNA amplicons) per cell (left) and genes per cell (right). [Figure 15D]Figure 15D provides a schematic diagram of intracellular segmentation in the cytoplasm based on distance ratio (DR). Two values ​​for each amplicon were calculated in 3D: d1, the shortest distance to the nuclear membrane; d2, the shortest distance to the cell membrane. The "intermediate" region is defined as the area between DR=0 and 10. The "peripheral" region is defined as DR>10.

[0034] [Figure 16A] Figures 16A–16D show intracellular RNA analysis and cell cycle phase identification. Figure 16A shows the nuclear-to-cytoplasmic ratio of amplicon reads for 991 genes at a 6-hour chase time. Genes are ranked from top to bottom according to their ratio. [Figure 16B-C] Figure 16B shows cell cycle identification (G1, G1 / S, G2 / M) by cell cycle gene markers measured via TEMPOmap-labeled RNA expression. Cells were visualized by PCA and shaded according to cell cycle phase (top left). Variations in raw counts of all cell cycle gene markers (bottom left) and four representative markers (right) were predicted by pseudo-time analysis. Figure 16C provides a comparison of cell cycle identification using 1-hour labeled reads and total reads with a scEU-seq dataset, showing no significant difference. The numbers in each box indicate the number of cells. [Figure 16D] Figure 16D shows the results of cell clustering based on PHATE embedding in the nucleocytoplasmic matrix. Cluster 1 incorporates M-phase cells as determined by visual inspection of the raw images.

[0035] [Figure 17A-B] Figures 17A–17H show estimations of RNA dynamics parameters. Figure 17A shows the correlation between cell volume (in voxel units) and single-cell readings, illustrating the effect of cell volume on transcript count. Figure 17B provides a schematic diagram showing different concentrations of a single RNA species in the nucleus and cytoplasm. [Figure 17C]Figure 17C shows a mathematical model for estimating RNA dynamics parameters (α, β, βn, λ, βc) and a detailed workflow of the calculation and fitting procedures. Note: X(t) = single-cell RNA concentration; N(t) = nuclear RNA concentration; C(t) = cytoplasmic RNA concentration; p (nuclear processing constant) = βn + λ. For clarity, assume βn = βn and βc = βc. [Figure 17D-E] Figure 17D shows the change in the natural logarithm of X(t) over time for genes with R2 ~ 1 (left) and R2 ~ 0.5 (right). Estimated β and p were filtered with a threshold of R2 > 0.5 as a quality control. Figure 17E shows the distribution of single-cell mean DR values ​​for all 991 genes over chase time points from 0 to 6 hours. [Figure 17F] Figure 17F provides a histogram of the estimated γ (cytoplasmic translocation) values ​​for all genes. The dashed line separates genes with γ>0 from those with γ<0, indicating the opposite direction of observed translocation. [Figure 17G] Figure 17G shows on the left that 12 genes with γ<0 (R2>0.5) are strongly enriched in extracellular exosomes and transmembrane proteins (9 / 12). In the center of Figure 17G, the DR values ​​over time for representative genes are shown. [Figure 17H] Figure 17H ​​provides a schematic diagram showing the observed inward direction of RNA translocation for genes with γ<0.

[0036] [Figure 18A-B] Figures 18A–18K show RNA dynamics parameters across cell cycle stages. Figures 18A–18F provide an example of pairwise correlation in Figure 12D and show a scatter plot of the relationship between G1 and G2 / M. The correlation coefficients, from left to right, are α (R=0.99), β (R=0.77), βn (R=0.70), λ (R=0.65), βc (R=0.36), and γ (R=0.07). R represents the Pearson correlation value. [Figure 18C-D]Figures 18A–18F provide an example of pairwise correlation in Figure 12D, showing a scatter plot of the relationship between G1 and G2 / M. The correlation coefficients, from left to right, are α (R=0.99), β (R=0.77), βn (R=0.70), λ (R=0.65), βc (R=0.36), and γ (R=0.07). R represents the Pearson correlation value. [Figure 18E-F] Figures 18A–18F provide an example of pairwise correlation in Figure 12D, showing a scatter plot of the relationship between G1 and G2 / M. The correlation coefficients, from left to right, are α (R=0.99), β (R=0.77), βn (R=0.70), λ (R=0.65), βc (R=0.36), and γ (R=0.07). R represents the Pearson correlation value. [Figure 18G-H] Figures 18G–18H show that RNA synthesis (α) and degradation (β) were estimated from the publicly available scEU-seq datasets (Figure 18H) of single-cell RNA expression (Figure 18G) and each cell cycle phase (G1, G1 / S, G2 / M). [Figure 18I] Figure 18I provides density plots showing the distribution of each of the six parameters (from left to right: α, β, βn, λ, βc, γ) estimated for each cell cycle state. The first five parameters were estimated from RNA concentration, and γ was estimated from the DR value, but overall changes across the three states were not shown. [Figure 18J-K] Figure 18J provides a violin plot showing the distribution of βn, λ, and βc in G2 and M phase cells. M phase cells were identified in Figure 16D; G2 phase cells were the remainder of G2 / M cells. Figure 18K provides a box plot showing the intracellular distribution of RNA readouts over time in each dynamic cluster.

[0037] [Figure 19A]Figures 19A–19H show the changes in RNA dynamics under gene function and post-transcriptional modification status. Figure 19A provides a heatmap showing a matrix of pairwise correlation coefficients from single-cell variations in TEMPOmap-measured gene expression at chase times 0, 2, 4, and 6 hours (left to right). The order of genes along each matrix is ​​the same and was determined by a hierarchical clustering tree of matrices combining the four time points (Figure 13A). The sidebars of each matrix show annotations for shading gene clusters from Figure 12E. [Figure 19B-D] Figure 19B provides a pie chart illustrating the major molecular functions of 991 genes analyzed by gene ontology. Figure 19C provides a pie chart illustrating m6A-RNA methylation in the gene pool. Figure 19D provides a pie chart illustrating the relationship with YTHDC1 in the gene pool. [Figure 19E] Figure 19E provides a box plot comparing six parameters estimated for m6A and non-m6A RNA across three cell cycle phases. **p<0.05, ***p<0.01. The Y-axis range was selected for values ​​between the 25th and 75th percentiles. [Figure 19F] Figure 19F shows the expression of YTHDC1 in control cells and siYTHDC1 cells, normalized by the expression of six other STARmap target genes (METTL3 / 14, YTHDC2, YTHDF1-3). [Figure 19G] Figure 19G shows the cumulative distribution of the log2 multiple change in the nuclear-to-cytoplasmic expression ratio after YTHDC1 knockdown at chase time points 0–6 hours (from left to right). [Figure 19H-1] Figure 19H shows the cumulative distribution of log2 factor changes for the six parameters after knockdown of YTHDC1. [Figure 19H-2] Figure 19H shows the cumulative distribution of log2 factor changes for the six parameters after knockdown of YTHDC1.

[0038] [Figure 20A]Figures 20A-20B illustrate the principle of TEMPOmap in vivo. They show the nascent RNA labeling chemistry in tissue sections for spatiotemporal decomposition transcriptomics of metabolically labeled living animals. Figure 20A shows the in vivo TEMPOmap workflow. Tissues were collected from mice injected with EU (1 mg EU) and controls injected with PBS and fixed for 2 hours post-administration. The tissues were sectioned and chemically processed using the TEMPOmap workflow to prepare a DNA amplicon library. The DNA amplicons were then sequenced in situ by a series of fluorescence imaging scans. [Figure 20B] Figure 20B (left): Cardiac sections of EU-injected mice show strong enrichment of amplicon signals compared to controls injected with PBS, demonstrating a high signal-to-noise ratio of TEMPOmap in vivo. Figure 20B (right): Representative fluorescence image of a cardiac section showing the nascent transcriptional signals of four genes (Myh6, Flt1, Dach1, Lamc1) in a 2-hour EU-labeled window in mouse hearts, and the minimal background signal in the hearts of PBS-injected mice. [Modes for carrying out the invention]

[0039] definition Unless otherwise defined, all technical and scientific terms used herein have the meanings generally understood by those skilled in the art in the field to which this invention pertains. The following references provide to those skilled in the art general definitions of many of the terms used herein: Singleton et al., Dictionary of Microbiology and Molecular Biology (2nd ed. 1994); The Cambridge Dictionary of Science and Technology (Walker ed., 1988); The Glossary of Genetics, 5th Ed., R. Rieger et al. (eds.), Springer Verlag (1991); and Hale & Marham, The Harper Collins Dictionary of Biology (1991). Where used herein, the following terms have the meanings attributed to them unless otherwise specified.

[0040] The terms “administer,” “dosing,” and “administer” refer to the transfer, absorption, ingestion, injection, inhalation, or other means of introducing a treatment or therapeutic agent, or a composition of such a treatment or therapeutic agent, into or onto a subject.

[0041] As used herein, the term “amplicon” refers to a nucleic acid (e.g., DNA or RNA) that is the product of an amplification reaction (i.e., the production of one or more copies of a gene fragment or target sequence) or replication reaction. Amplicons can be artificially formed, for example, by PCR or other polymerization reactions. The term “concatenated amplicons” refers to multiple amplicons that are joined together to form a single nucleic acid molecule. Concatenated amplicons can be formed, for example, by rolling circle amplification (RCA), in which a cyclic oligonucleotide is amplified to produce multiple linear copies of the oligonucleotide as a single nucleic acid molecule containing the concatenated multiple amplicons.

[0042] The term "angiogenesis" refers to the physiological process by which new blood vessels are formed from existing ones. Angiogenesis is distinct from vascularization, which is the de novo formation of endothelial cells from mesodermal cell precursors. The first blood vessels in a developing embryo are formed by vascularization, after which angiogenesis accounts for most vascular growth during normal or abnormal development. Angiogenesis is a crucial process not only in growth and development but also in wound healing and granulation tissue formation. However, angiogenesis is also a fundamental step in the transition of tumors from a benign to a malignant state, leading to the use of angiogenesis inhibitors in cancer treatment. Angiogenesis can be chemically stimulated by angiogenic proteins such as growth factors (e.g., VEGF). "Pathological angiogenesis" refers to abnormal (e.g., excessive or insufficient) angiogenesis that leads to and / or is associated with disease.

[0043] An “antibody” refers to a glycoprotein belonging to the immunoglobulin superfamily. The terms antibody and immunoglobulin are used interchangeably. With a few exceptions, mammalian antibodies are typically made up of a basic structural unit having two large heavy chains and two small light chains, each with two large heavy chains. There are several different types of antibody heavy chains, and there are also several different types of antibodies, which are grouped into different isotypes based on which heavy chains they possess. In mammals, five different antibody isotypes (IgG, IgA, IgE, IgD, and IgM) are known, each playing a different role and helping to guide an appropriate immune response to each of the different types of foreign substances encountered. As used herein, the term “antibody” also encompasses antibody fragments and nanobodies, as well as antibody variants. The term “antibody variant” is sometimes used to encompass antibody fragments. In some embodiments, an antibody or antibody variant is administered as a treatment for a disease or disorder (e.g., related to changes in the spatiotemporal gene expression profile in cells isolated from a subject).

[0044] "Anticancer drugs" encompass biotherapeutic anticancer agents and chemotherapeutic agents. Exemplary biotherapeutic anticancer agents include, but are not limited to, interferons, cytokines (e.g., tumor necrosis factor, interferon-alpha, interferon-gamma), vaccines, hematopoietic growth factors, monoclonal serum therapies, immunostimulants and / or immunomodulators (e.g., IL-1, 2, 4, 6, or 12), immune cell growth factors (e.g., GM-CSF), and antibodies (e.g., HERCEPTIN (trastuzumab), T-DM1, AVASTIN (bevacizumab), ERBITUX (cetuximab), VECTIBIX (panitumumab), RITUXAN (rituximab), BEXXAR (tositumomab)). Exemplary chemotherapeutic agents include, but are not limited to, anti-estrogens (e.g., tamoxifen, raloxifene, and megestrol), LHRH agonists (e.g., gosculin and leuprolide), anti-androgens (e.g., flutamide and bicalutamide), photodynamic therapy (e.g., berthorfin (BPD-MA), phthalocyanines, photosensitizer Pc4, and demethoxyhypocrelin A (2BA-2-DMHA)), nitrogen mustards (e.g., cyclophosphamide, ifosfamide, trophosfamide, chlorambucil, estramustine, and melphalan), nitrosoureas (e.g., carmustine (BCNU) and lomustine (CCNU)), alkyl sulfonates (e.g., busulfan and treosulfan), and triazenes (e.g., dacarbazine). , temozolomide), platinum-containing compounds (e.g., cisplatin, carboplatin, oxaliplatin), vinca alkaloids (e.g., vincristine, vinblastine, vindesine, and vinorelbine), taxoids (e.g., paclitaxel or paclitaxel equivalents, e.g., nanoparticle albumin-conjugated paclitaxel (ABRAXANE), docosahexaenoic acid-conjugated paclitaxel (DHA-paclitaxel, taxoplexin), polyglutamate-conjugated paclitaxel (PG-paclitaxel, paclitaxel polygrumex, CT-2103, XYOTAX), tumor-activating prodrugs (TAP) ANG1005 (Angiopep-2 conjugated to three molecules of paclitaxel), paclitaxel-EC-1 (paclitaxel conjugated to erbB2-recognizing peptide EC-1),and glucose-conjugated paclitaxel (e.g., 2'-paclitaxel methyl 2'-glucopyranosyl succinate; docetaxel, taxol), epipodophilins (e.g., etoposide, etoposide phosphate, teniposide, topotecan, 9-aminocamptothecin, camptoirinotecan, irinotecan, cristinator, mitomycin C), antimetabolites, DHFR inhibitors (e.g., methotrexate, dichloromethotrexate, trimer) Trexate, edatrecel), IMP dehydrogenase inhibitors (e.g., mycophenolic acid, thiazophrine, ribavirin, and EICAR), ribonucleotide reductase inhibitors (e.g., hydroxyurea and deferoxamine), uracil analogs (e.g., 5-fluorouracil (5-FU), floxuridine, doxifluridine, latitrexed, tegafururacil, capecitabine), cytosine analogs (e.g., cytarabine (ara) C), cytosine arabinoside, and fludarabine), purine analogs (e.g., mercaptopurine and thioguanine), vitamin D3 analogs (e.g., EB 1089, CB 1093, and KH 1060), isoprenylation inhibitors (e.g., lovastatin), dopaminergic neurotoxins (e.g., 1-methyl-4-phenylpyridinium ion), cell cycle inhibitors (e.g., staurosporine), actinomycin (e.g., actinomycin D, dactinomycin), bleomycin (e.g., bleomycin A2, bleomycin B2, peplomycin), anthracyclines (e.g., daunorubicin, doxorubicin, pegylated liposomal doxorubicin, idarubicin, epirubicin, pirarubicin, zorubicin, mitoxantrone), MDR inhibitors (e.g., verapamil), Ca2+ ATPase inhibitors (e.g., thapsigardin), imatinib, thalidomide, lenalidomide, tyrosine kinase inhibitors (e.g., axitinib (AG013736), bosutinib (SKI-606), cediranib (RECENTIN®, AZD2171), dasatinib (SPRYCEL®, BMS-354825), erlotinib (TARCEVA®), gefitinib (IRESSA®), imatinib (Gleevec®, CGP57148B, STI-571), lapatinib (TYKERB®, TYVERB®),Restaulutinib (CEP-701), Neratinib (HKI-272), Nilotinib (TASIGNA®), Semaxinib (SU5416), Sunitinib (SU11248), Toceranib (PALLADIA®), Vandetanib (ZACTIMA®, ZD6474), Batalanib (PTK787, PTK / ZK), Trastuzumab (HERCEPTIN®), Bevacizumab (AVASTIN®), Rituximab Simab (RITUXAN®), Cetuximab (ERBITUX®), Panitumumab (VECTIBIX®), Ranibizumab (Lucentis®), Nilotinib (TASIGNA®), Sorafenib (NEXAVAR®), Everolimus (AFINITOR®), Alemtuzumab (CAMPATH®), Gemtuzumab Ozogamicin (MYLOTARG®), Temsirolimus (TORISEL®) ), ENMD-2076, PCI-32765, AC220, dovitinib lactate (TKI258, CHIR-258), BIBW2992 (TOVOK(trademark)), SGX523, PF-04217903, PF-02341066, PF-299804, BMS-777607, ABT-869, MP470, BIBF1120 (VARGATEF(registered trademark)), AP24534, JNJ-26483327, MGCD265, DCC-2036, BMS-690154, CEP-11981, cibo Zanib (AV-951), OSI-930, MM-121, XL-184, XL-647, and / or XL228), proteasome inhibitors (e.g., bortezomib (VELCADE)), mTOR inhibitors (e.g., rapamycin, temsirolimus (CCI-779), everolimus (RAD-001), ridafololimus, AP23573 (Ariad), AZD8055 (AstraZeneca), BEZ235 (Novartis), BGT226 (Norvartis), XL765 (Sanofi Aventis), PF-4691502 (Pfizer), GDC0980 (Genentech), SF1126 (Semafoe), and OSI-027 (OSI)), oblimersen,Gemcitabine, carminomycin, leucovorin, pemetrexed, cyclophosphamide, dacarbazine, procarbidine, prednisolone, dexamethasone, campatesin, plicamycin, asparaginase, aminopterin, metopterin, porphyromycin, melphalan, leulosidine, leulosin, chlorambucil, trabectedin, procarbazine, discodermorid, carminomycin, aminopterin, and hexamethylmelamine.

[0045] An "autoimmune disease" refers to a disease resulting from an inappropriate immune response of the body to substances and tissues that are normally present in the body. In other words, the immune system mistakenly identifies a part of the body as a pathogen and attacks its own cells. This may be limited to a specific organ (e.g., autoimmune thyroiditis) or may involve specific tissues in different locations (e.g., Goodpasture disease, which can affect the basement membranes of both the lungs and kidneys). Treatment for autoimmune diseases typically involves immunosuppression, such as using drugs to reduce the immune response. Exemplary autoimmune diseases include, but are not limited to, glomerulonephritis, Goodpasture syndrome, necrotizing vasculitis, lymphadenitis, polyarteritis nodosa, systemic lupus erythematosus, rheumatoid arthritis, psoriatic arthritis, systemic lupus erythematosus, psoriasis, ulcerative colitis, systemic sclerosis, dermatomyositis / polymyositis, antiphospholipid syndrome, scleroderma, pemphigus vulgaris, ANCA-associated vasculitis (e.g., Wegener's granulomatosis, microscopic polyangiitis), uveitis, Sjögren's syndrome, Crohn's disease, Reiter's syndrome, ankylosing spondylitis, Lyme disease, Guillain-Barré syndrome, Hashimoto's thyroiditis, and cardiomyopathy.

[0046] As used herein, the term “biochorthogonal functional group” refers to a functional group that can be used in chemical reactions within a biological system (e.g., inside a cell) without interfering with any of the natural biochemical processes within the biological system. Biochorthogonal functional groups include, for example, click chemistry handles. As used herein, the term “click chemistry handle” refers to a reactant or reactant group that can participate in a click chemistry reaction. Exemplary click chemistry handles are shown in U.S. Patent Publication 20130266512, incorporated herein by reference. For example, strained alkynes such as cyclooctyne are click chemistry handles because they can participate in strain-enhanced cycloaddition. Generally, a click chemistry reaction requires at least two molecules containing click chemistry handles that can react with each other. Such a pair of click chemistry handles that react with each other is sometimes referred to herein as a partner click chemistry handle. For example, azides are a partner click chemistry handle with alkynes. Exemplary click chemistry handles include, but are not limited to, alkenes, dienes, tetrazines, transcyclooctenes, alkynes, azides, nitrones, and tetrazoles. For two molecules to be conjugated by click chemistry, the click chemistry handles of the molecules must be reactive with each other; for example, the reactive part of one click chemistry handle must be able to react with the reactive part of the second click chemistry handle to form at least one covalent bond. Such reactive pairs of click chemistry handles are well known to those skilled in the art.

[0047] The term "cancer" refers to a class of diseases characterized by the development of abnormal cells that have the ability to grow uncontrollably and invade and destroy normal body tissues. See, for example, Stedman's Medical Dictionary, 25th ed.; Hensyl ed.; Williams & Wilkins: Philadelphia, 1990. Examples of cancer include, but are not limited to, the following: acoustic neuroma; adenocarcinoma; adrenal cancer; anal cancer; angiosarcoma (e.g., lymphangiosarcoma, intralymphatic sarcoma, angiosarcoma); appendiceal cancer; benign monoclonal gammaglobulinopathy; biliary tract cancer (e.g., bile duct cancer); bladder cancer; breast cancer (e.g., adenocarcinoma of the breast, papillary carcinoma of the breast, breast cancer, medullary carcinoma of the breast); brain cancer (e.g., meningioma, glioblastoma, glioma (e.g., astrocytoma, oligodendroglioma), medulloblastoma); bronchial cancer; carcinoid tumor; cervical cancer (e.g., cervical adenocarcinoma); choriocarcinoma; chordoma; craniopharyngioma; colorectal cancer (e.g., colon cancer, rectal cancer, colorectal adenocarcinoma); connective tissue cancer; epithelial carcinoma; ependymoma; endosarcoma (e.g., Kaposi's sarcoma, multiple idiopathic hemorrhagic sarcoma); endometrial cancer (e.g., uterine cancer) , uterine sarcoma; esophageal cancer (e.g., esophageal adenocarcinoma, Barrett's adenocarcinoma); Ewing's sarcoma; eye cancer (e.g., intraocular melanoma, retinoblastoma); familial eosinophilia; gallbladder cancer; stomach cancer (e.g., gastric adenocarcinoma); gastrointestinal stromal tumor (GIST); germ cell cancer; head and neck cancer (e.g., head and neck squamous cell carcinoma, oral cancer (e.g., oral squamous cell carcinoma), pharyngeal cancer (e.g., laryngeal cancer, pharyngeal cancer, nasopharyngeal cancer, oropharyngeal cancer)); hematopoietic cancer (e.g., leukemia such as acute lymphoblastic leukemia (ALL) (e.g., B-cell ALL, T-cell ALL), acute myeloid leukemia (AML) (e.g., B-cell AML, T-cell AML), chronic myeloid leukemia (CML) (e.g., B-cell CML, T-cell CML), and chronic lymphocytic leukemia (CLL) (e.g., B-cell CLL, T-cell CLL));Lymphomas, such as Hodgkin lymphoma (HL) (e.g., B-cell HL, T-cell HL) and non-Hodgkin lymphoma (NHL) (e.g., B-cell NHL), diffuse large cell lymphoma (DLCL) (e.g., diffuse large B-cell lymphoma), follicular lymphoma, chronic lymphocytic leukemia / small lymphocytic lymphoma (CLL / SLL), mantle cell lymphoma (MCL), marginal zone B-cell lymphoma (e.g., intramucosal lymphoid tissue (MALT) lymphoma, nodal marginal zone B-cell lymphoma, splenic marginal zone B-cell lymphoma), primary mediastinal B-cell lymphoma, Burkitt lymphoma, lymphoplasmacytic lymphoma Parkinson's disease (i.e., Waldenström macroglobulinemia), hairy cell leukemia (HCL), immunoblastic large cell lymphoma, precursor B lymphoblastic lymphoma and primary central nervous system (CNS) lymphoma; and T-cell NHL, e.g., precursor T lymphoblastic lymphoma / leukemia, peripheral T-cell lymphoma (PTCL) (e.g., cutaneous T-cell lymphoma (CTCL) (e.g., mycosis fungoides, Sézary syndrome), angioimmunoblastic T-cell lymphoma, extranodal natural killer T-cell lymphoma, intestinal disease type T-cell lymphoma, subcutaneous panniculitis-like T-cell lymphoma, and anaplastic large cell lymphoma). ; A mixture of one or more leukemias / lymphomas, such as those listed above; and multiple myeloma (MM); heavy chain diseases (e.g., alpha chain disease, gamma chain disease, microchain disease); hemangioblastoma; hypopharyngeal cancer; inflammatory myofibroblastic neoplasm; immunocellular amyloidosis; kidney cancer (e.g., nephroblastoma, also known as Wilms' tumor, renal cell carcinoma); liver cancer (e.g., hepatocellular carcinoma (HCC), malignant liver cancer); lung cancer (e.g., bronchogenic carcinoma, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), adenocarcinoma of the lung); leiomyosarcoma (LMS); mastocytosis (e.g., systemic mastocytosis); muscle cancer; myelodysplastic syndrome (MDS) ); mesothelioma; myeloproliferative disorders (MPD) (e.g., polycythemia vera (PV), essential thrombocytosis (ET), myelogenesis of unknown origin (AMM), also known as myelofibrosis (MF), chronic idiopathic myelofibrosis, chronic myeloid leukemia (CML), chronic neutrophilic leukemia (CNL), eosinophilic syndrome (HES)); neuroblastoma; neurofibroma (e.g., neurofibromatosis type 1 or 2, schwannoma); neuroendocrine carcinoma (e.g., gastrointestinal and pancreatic neuroendocrine neoplasm (GEP-NET), carcinoid tumor); osteosarcoma (e.g., bone cancer); ovarian cancer (e.g., cystadenocarcinoma, ovarian embryonic carcinoma, ovarian adenocarcinoma); papillary adenocarcinoma;Pancreatic cancer (e.g., adenocarcinoma of the pancreas, intraductal papillary mucinous neoplasm (IPMN), islet cell tumor); penile cancer (e.g., Paget's disease of the penis and scrotum); pinealoma; primitive neuroectodermal tumor (PNT); plasmacytoma; paraneoplastic neurological syndromes; neoplasm in situ; prostate cancer (e.g., adenocarcinoma of the prostate); rectal cancer; rhabdomyosarcoma; salivary gland cancer; skin cancer (e.g., squamous cell carcinoma (SCC), keratoacanthoma (KA), melanoma, basal cell carcinoma (BCC)). )); small intestine cancer (e.g., appendiceal cancer); soft tissue sarcoma (e.g., malignant fibrous histiocytoma (MFH), liposarcoma, malignant peripheral nerve sheath tumor (MPNST), chondrosarcoma, fibrosarcoma, myosarcoma); sebaceous gland carcinoma; small intestine cancer; sweat gland cancer; synovial mammary gland; testicular cancer (e.g., seminomasm, testicular fetal carcinoma); thyroid cancer (e.g., papillary thyroid carcinoma, papillary thyroid carcinoma (PTC), medullary thyroid carcinoma); urethral cancer; vaginal cancer; vulvar cancer (e.g., Paget's disease of the vulva).

[0048] As used herein, “cells” may exist in a population of cells (e.g., tissue, organ, or organoid). In some embodiments, the cell population consists of multiple cell types. Cells used in the methods of this disclosure may exist within an organism, within a single cell type derived from an organism, or within a mixture of cell types. These include naturally occurring cells and cell populations, genetically engineered cell lines, and cells derived from transgenic animals. Substantially any cell type and size may be adapted to the methods and systems described herein. Suitable cells include bacterial cells, fungal cells, plant cells, and animal cells. In some embodiments, the cells are mammalian cells (e.g., complex cell populations such as naturally occurring tissues). In some embodiments, the cells are of human origin. In some embodiments, the cells are collected from an object (e.g., a human) through a medical procedure such as a biopsy. Alternatively, the cells may be a cultured population (e.g., a culture derived from a complex population, or a culture derived from a single cell type in which the cells have differentiated into multiple lineages).

[0049] The cell types intended for use in the methods of this disclosure include, but are not limited to, stem cells and progenitor cells (e.g., embryonic stem cells, hematopoietic stem cells, mesenchymal stem cells, neural crest cells, etc.), endothelial cells, muscle cells, cardiomyocytes, smooth muscle cells and skeletal muscle cells, mesenchymal cells, epithelial cells, hematopoietic cells, lymphocytes such as T cells (e.g., Th1 T cells, Th2 T cells, Th0 T cells, cytotoxic T cells), and B cells (e.g., pre-B cells), monocytes, dendritic cells, neutrophils, macrophages, natural killer cells, mast cells, adipocytes, immune cells, neurons, hepatocytes, and cells associated with specific organs (e.g., thymus, endocrine glands, pancreas, brain, neurons, glia, astrocytes, dendritic cells, and genetically modified cells thereof). The cells may also be different types of transformed or neoplastic cells (e.g., cancers of different cellular origins, lymphomas of different cell types, etc.), or any type of cancerous cell (e.g., derived from any of the cancers disclosed herein). Cells of different origins (e.g., ectoderm, mesoderm, and endoderm) are also intended for use in the methods of this disclosure.

[0050] As used herein, the term “gene” refers to a nucleic acid fragment that expresses a protein and includes regulatory sequences preceding (5' non-coding) and following (3' non-coding) a coding sequence. “Natural gene” refers to a gene found in nature that possesses its own regulatory sequences.

[0051] As used herein, “gene expression” refers to the process by which information from a gene is used to synthesize gene products. Gene products include proteins and RNA transcripts (e.g., messenger RNA, transfer RNA, or nuclear small RNA). Gene expression includes transcription and translation. Transcription is the process by which a segment of DNA is transcribed into RNA by RNA polymerase. Translation is the process by which RNA is translated into peptides or proteins by ribosomes. As used herein, “genetic information” refers to one or more genes and / or one or more RNA transcripts (e.g., any number of genes and / or RNA transcripts).

[0052] The term "genetic disorder" refers to a disease caused by one or more abnormalities in the genome of a person, such as a disease present from birth. Genetic disorders are hereditary and can be inherited from the genes of both parents. Genetic disorders can also be caused by mutations or changes in the DNA and / or RNA of a person. In such cases, the genetic disorder is hereditary if it originates in the germline. Exemplary genetic disorders include, but are not limited to, Earlskog-Scott syndrome, Arse syndrome, achondroplasia, acroplasia, poisoning, adrenoleukodystrophy, albinism, Abrefaron-macrostomia syndrome, Alagille syndrome, alkaptonuria, alpha-1 antitrypsin deficiency, Alport syndrome, Alzheimer's disease, asthma, autoimmune polyglandular syndrome, androgen insensitivity syndrome, Angelman syndrome, ataxia, telangiectatic ataxia, and Roam's arteriosclerosis, attention deficit hyperactivity disorder (ADHD), autism, baldness, Batten disease, Beckwith-Wiedemann syndrome, Best's disease, bipolar disorder, brachydactyly, breast cancer, Burkitt lymphoma, chronic myeloid leukemia, Charcot-Marie-Tooth disease, Crohn's disease, cleft lip, Cockayne syndrome, Coffin-Lowry syndrome, colon cancer, congenital adrenal hyperplasia, Cornelia de Lange syndrome, Costello syndrome, Cowden syndrome, craniofacial dysplasia, Crigler-Nadjar syndrome, Creutzfeldt-Jakob disease, cystic fibrosis, hearing loss, depression, diabetes mellitus, twisting dysplasia, Digeorge syndrome, Down syndrome, dyslexia, Duchenne muscular dystrophy, Dubowitz syndrome, ectodermal dysplasia, Ellis-vanCreveld syndrome, Ehlers-Danlos, epidermolysis bullosa, epilepsy, essential tremor, familial hypercholesterolemia, familial Mediterranean fever, fragile X syndrome, Friedreich's ataxia, Gaucher disease, glaucoma, glucose-galactose malabsorption, glutaricuria, cerebral gynecomastia, Goldberg-Sprinzen syndrome (velocopal-cardiac-facial syndrome), Gorin syndrome, Hailey-Hailey disease, hemiplegia, Mochromatosis, hemophilia, hereditary sensorimotor neuropathy (HMSN), hereditary nonpolyposis colorectal cancer (HNPCC), Huntington's disease, immunodeficiency with high IgM levels, juvenile diabetes, Klinefelter syndrome, Kabuki syndrome, Leigh disease, long QT syndrome, lung cancer, malignant melanoma, bipolar disorder, Marfan syndrome, Menkes syndrome, miscarriage, mucopolysaccharidosis, multiple endocrine neoplasia, multiple sclerosis, muscular dystrophy, amyotrophic lateral sclerosis, myotonic Dystrophy, neurofibromatosis, Niemann-Pick disease, Noonan syndrome, obesity, ovarian cancer, pancreatic cancer, Parkinson's disease, paroxysmal nocturnal hemoglobinuria, Pendred syndrome, spinal and bulbar muscular atrophy, phenylketonuria (PKU), polycystic kidney disease, Prader-Willi syndrome, primary biliary cirrhosis, prostate cancer, REAR syndrome, Lifsum disease, retinitis pigmentosa, retinoblastoma, Rett syndrome, Sanfilippo syndrome, schizophrenia, severe combined immunodeficiency All conditions, sickle cell anemia, spina bifida, spinal muscular atrophy, spinocerebellar atrophy, sudden death syndrome in adults, Tangier disease, Tay-Sachs disease, thrombocytopenia syndrome with radial agenesis, Townes-Brocks syndrome, tuberous sclerosis, Turner syndrome, Usher syndrome, von Hippel-Lindau syndrome, Waardenburg syndrome, Weaver syndrome, Werner syndrome, Williams syndrome, Wilson's disease, xeroderma pigmentosum, and Zellweger syndrome.

[0053] "Blood disorders" include diseases affecting hematopoietic cells or hematopoietic tissue. Blood disorders include diseases related to abnormal hematological content and / or function. Examples of blood disorders include: diseases resulting from bone marrow irradiation or chemotherapy for cancer; pernicious anemia, hemorrhagic anemia, hemolytic anemia, aplastic anemia, sickle cell anemia, sideroblastic anemia; anemia associated with chronic infections such as malaria, trypanosomiasis, HTV, hepatitis viruses or other viruses; myeloid anemia due to bone marrow deficiency; renal failure due to anemia; anemia; polycythemia; infectious mononucleosis (EVI); acute nonlymphocytic leukemia (ANLL); acute myeloid leukemia (AML); acute promyelocytic leukemia (APL); acute Myelomonocytic leukemia (AMMoL), polycythemia vera, lymphoma, acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia, Wilms' tumor, Ewing's sarcoma, retinoblastoma, hemophilia, disorders associated with an increased risk of thrombosis, herpes, thalassemia, antibody-mediated disorders such as transfusion reactions and erythroblastosis, mechanical trauma to red blood cells such as microangiogenic hemolytic anemia, thrombotic thrombocytopenic purpura, and disseminated intravascular coagulation, parasitic infections such as malaria parasites, chemical injuries such as lead poisoning, and hypersplenicity.

[0054] The terms “inflammatory disease” and “inflammatory condition” are used interchangeably herein and refer to diseases or conditions caused by, resulting from, or causing inflammation. Inflammatory diseases and conditions include diseases, disorders, or conditions characterized by signs of pain (pain, production of harmful substances and nerve irritation), fever (heat (calor), due to vasodilation), redness (redness, due to vasodilation and increased blood flow), swelling (tumor, due to excessive inflow or restricted outflow of fluid), and / or loss of function (loss of function (functio laesa), partial or complete, temporary or permanent). Inflammation can take many forms, but is not limited to: acute, adhesive, atrophic, catarrhal, chronic, cirrhotic, diffuse, disseminated, exudative, fibrous, fibrotic, focal, granulomatous, hyperplastic, hypertrophic, stromal, metastatic, necrotic, occlusive, parenchymal, plastic, proliferative, proliferous, pseudomembranous, purulent, sclerosing, serous fibrinous, serous, simple, specific, subacute, suppurative, toxic, traumatic, and / or ulcerative. The term “inflammatory disease” may also refer to a dysregulated inflammatory response that causes an excessive reaction by macrophages, granulocytes, and / or T lymphocytes, resulting in abnormal tissue damage and / or cell death. An inflammatory disease is either an acute or chronic inflammatory condition and can be caused by infectious or non-infectious factors.Inflammatory diseases include, but are not limited to, the following: atherosclerosis, arteriosclerosis, autoimmune disorders, multiple sclerosis, systemic lupus erythematosus, polymyalgia rheumatica (PMR), gouty arthritis, osteoarthritis, tendinitis, bursitis, psoriasis, cystic fibrosis, osteoarthritis, rheumatoid arthritis, inflammatory arthritis, Sjögren's syndrome, giant cell arteritis, progressive systemic sclerosis (scleroderma), ankylosing spondylitis, polymyositis, dermatomyositis, pemphigus, bullous pemphigoid, diabetes mellitus (e.g., type 1), myasthenia gravis, and Hashimoto's thyroid gland. Inflammation, Graves' disease, Goodpasture's disease, mixed connective tissue disease, sclerosing cholangitis, inflammatory bowel disease, Crohn's disease, ulcerative colitis, pernicious anemia, inflammatory skin disease, usual interstitial pneumonia (UIP), asbestosis, silicosis, bronchiectasis, beryllium poisoning, talctopulmonary embolism, pneumoconiosis, sarcoidosis, exfoliative interstitial pneumonia, lymphocytic interstitial pneumonia, giant cell interstitial pneumonia, cellular interstitial pneumonia, exogenous allergic alveolitis, Wegener's granulomatosis and related vasculitis (temporal arteritis and polyarteritis nodosa), inflammatory skin disease, Hepatitis, delayed-type hypersensitivity reactions (e.g., ivy dermatitis), pneumonia, airway inflammation, adult respiratory distress syndrome (ARDS), encephalitis, immediate-type hypersensitivity reactions, asthma, hay fever, allergies, acute anaphylaxis, rheumatic fever, glomerulonephritis, pyelonephritis, cellulitis, cystitis, chronic cholecystitis, ischemia (ischemic injury), reperfusion injury, allograft rejection, host-versus-graft rejection, appendicitis, arteritis, blepharitis, bronchiolitis, bronchitis, cervicitis, cholangitis, chorioamnionitis, conjunctivitis, dacryodenitis, dermatomyositis, endocarditis, endometritis, enteritis, small bowel ligation Enteritis, epicondylitis, epididymitis, fasciitis, connective tissue inflammation, gastritis, gastroenteritis, gingivitis, ileitis, iritis, pharyngitis, myelitis, myocarditis, nephritis, omphalitis, oophoritis, orchitis, osteitis, otitis, pancreatitis, parotitis, pericarditis, pharyngitis, pleurisy, phlebitis, pneumonia, proctitis, prostatitis, rhinitis, salpingitis, sinusitis, stomatitis, synovitis, orchitis, tonsillitis, urethritis, cystitis, uveitis, vaginitis, vasculitis, vulvitis, vulvovaginitis, vasculitis, chronic bronchitis, osteomyelitis, optic neuritis, temporal arteritis, transverse myelitis, necrotizing fasciitis, and necrotizing enterocolitis. Inflammatory diseases of the eye include, but are not limited to, postoperative inflammation.

[0055] Additional exemplary inflammatory conditions include, but are not limited to, inflammation related to: acne, anemia (e.g., aplastic anemia, hemolytic autoimmune anemia), asthma, arteritis (e.g., polyarteritis, temporal arteritis, polyarteritis nodosa, Takayasu's arteritis), arthritis (e.g., crystalline arthritis, osteoarthritis, psoriatic arthritis, gouty arthritis, reactive arthritis, rheumatoid arthritis, Reiter's arthritis), ankylosing spondylitis, amyloseosis, amyotrophic lateral sclerosis, autoimmune diseases, allergies or allergic reactions, atherosclerosis, and bronchitis. , bursitis, chronic prostatitis, conjunctivitis, Chagas disease, chronic obstructive pulmonary disease, dermatomyositis, diverticulitis, diabetes (e.g., type 1 diabetes, type 2 diabetes), skin conditions (e.g., psoriasis, eczema, burns, dermatitis, pruritus), endometriosis, Guillain-Barré syndrome, infections, ischemic heart disease, Kawasaki disease, glomerulonephritis, gingivitis, hypersensitivity, headache (e.g., migraine, tension headache), intestinal obstruction (e.g., postoperative intestinal obstruction, intestinal obstruction in sepsis), idiopathic thrombocytopenic purpura, interstitial cystitis (bladder pain syndrome), gastrointestinal disorders (e.g., peptic ulcer, regional enteritis, diverticulitis, gastrointestinal bleeding, phosphatiditis Acidophilic gastrointestinal disorders (e.g., eosinophilic esophagitis, eosinophilic gastritis, eosinophilic gastroenteritis, eosinophilic colitis), gastritis, diarrhea, age-related reflux disease (GORD, or its synonym GERD), inflammatory bowel disease (IBD) (e.g., Crohn's disease, ulcerative colitis, collagen colitis, lymphocytic colitis, ischemic colitis, flow-shifting colitis, Behçet's syndrome, uncertain colitis) and inflammatory bowel syndrome (IBS)), lupus, multiple sclerosis, focal scleroderma, myasthenia gravis, myocardial ischemia, nephrotic syndrome, pemphigus vulgaris, pernicious anemia, peptic ulcer, polymyositis Inflammation, primary biliary cirrhosis, neuroinflammation associated with brain damage (e.g., Parkinson's disease, Huntington's disease, and Alzheimer's disease), prostatitis, chronic inflammation associated with cranial radiation injury, pelvic inflammatory disease, reperfusion injury, focal colitis, rheumatic fever, systemic lupus erythematosus, scleroderma, scierodoma, sarcoidosis, spondyloarthritis, Sjögren's syndrome, thyroiditis, transplant rejection, tendinitis, trauma or injury (e.g., frostbite, chemical irritants, toxins, scarring, burns, physical injury), vasculitis, vitiligo, and Wegener's granulomatosis. In some embodiments, inflammatory disorders are selected from arthritis (e.g., rheumatoid arthritis), inflammatory bowel disease, inflammatory bowel syndrome, asthma, psoriasis, endometriosis, interstitial cystitis, and prostatitis.In some embodiments, an inflammatory state is an acute inflammatory state (e.g., inflammation caused by infection). In other embodiments, an inflammatory state is a chronic inflammatory state (e.g., conditions caused by asthma, arthritis, and inflammatory bowel disease).

[0056] The term "liver disease" or "hepatic disease" refers to damage to or disease of the liver. Non-exclusive examples of liver disease include: intrahepatic cholestasis (e.g., Alagille syndrome, biliary cirrhosis), fatty liver (e.g., alcoholic fatty liver, Reye's syndrome), hepatic vein thrombosis, hepatolenticular degeneration (i.e., Wilson's disease), hepatomegaly, liver abscess (e.g., amoebic liver abscess), cirrhosis (e.g., alcoholic cirrhosis, biliary cirrhosis, experimental cirrhosis), alcoholic liver disease (e.g., fatty liver, hepatitis, cirrhosis), parasitic liver disease (e.g., hepatic echinococcosis, phylloxacin, amoebic liver abscess), jaundice (e.g., hemolytic jaundice, hepatocellular jaundice, cholestatic jaundice), and cholestasis. Portal hypertension, hepatomegaly, ascites, hepatitis (e.g., alcoholic hepatitis, animal hepatitis, chronic hepatitis (e.g., autoimmune hepatitis, hepatitis B, hepatitis C, hepatitis D, drug-induced chronic hepatitis), toxic hepatitis, viral human hepatitis (e.g., hepatitis A, hepatitis B, hepatitis C, hepatitis D, hepatitis E), granulomatous hepatitis, secondary biliary cirrhosis, hepatic encephalopathy, varices, primary biliary cirrhosis, primary sclerosing cholangitis, hepatocellular adenoma, hemangioma, gallstones, liver failure (e.g., hepatic encephalopathy, acute liver failure), angiomyolipoma, calcified liver metastases, cystic liver metastases, fibrolamellar hepatocellular carcinoma Hepatocarcinoma), hepatic adenoma, liver cancer, hepatic cyst (e.g., simple cyst, multiple cystic liver disease, hepatic cystadenoma, common bile duct cyst), mesenchymal tumor (e.g., mesenchymal hamartoma, infantile hemangioendothelioma, hemangioma, hepatic purpura, lipoma, inflammatory pseudotumor), epithelial tumor (e.g., bile duct hamartoma, bile duct adenoma), focal nodular hyperplasia, nodular regenerative hyperplasia, hepatoblastoma, hepatocellular carcinoma, cholangiocarcinoma, cystadenocarcinoma, hemangiomas, angiosarcoma, Kaposi's sarcoma, hemangioendothelioma, fetal sarcoma, fibrosarcoma, leiomyosarcoma, rhabdomyosarcoma, carcinosarcoma, teratoma, carcinoid, squamous cell carcinoma, primary lymphoma, hepatic purpura, hepatic myeloid porphyria (erythrohepatic Porphyria, hepatic porphyria (e.g., acute intermittent porphyria, late-onset cutaneous porphyria), and Zellweger syndrome.

[0057] The terms "lung disease" or "pulmonary disease" refer to diseases of the lungs. Examples of lung diseases include, but are not limited to, bronchiectasis, bronchitis, bronchopulmonary dysplasia, interstitial lung disease, occupational lung disease, emphysema, cystic fibrosis, acute respiratory distress syndrome (ARDS), severe acute respiratory syndrome (SARS), asthma (e.g., intermittent asthma, mild persistent asthma, moderate persistent asthma, severe persistent asthma), chronic bronchitis, chronic obstructive pulmonary disease (COPD), emphysema, interstitial lung disease, sarcoidosis, asbestosis, aspergilloma, aspergillosis, pneumonia (e.g., lobar pneumonia, polylobar pneumonia, bronchopneumonia, interstitial pneumonia), pulmonary fibrosis, pulmonary tuberculosis, rheumatic lung disease, pulmonary embolism, and lung cancer (e.g., non-small cell lung cancer (e.g., adenocarcinoma, squamous cell lung cancer, large cell lung cancer), small cell lung cancer).

[0058] The term “neurological disorder” refers to any disorder of the nervous system, including disorders involving the central nervous system (brain, brainstem, and cerebellum), the peripheral nervous system (including cranial nerves), and the autonomic nervous system (some of which are present in both the central and peripheral nervous systems). Neurodegenerative disorders refer to a type of neurological disorder characterized by the loss of nerve cells, and include, but are not limited to, Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, tauopathies (including frontotemporal dementia), and Huntington’s disease. Examples of neurological disorders include, but are not limited to, headaches, stupor and coma, dementia, seizures, sleep disorders, trauma, infections, neoplasms, neuro-ophthalmology, motor disorders, demyelinating diseases, spinal cord disorders, and disorders of the peripheral nerves, muscles, and neuromuscular junctions. Addiction and mental disorders include, but are not limited to, bipolar disorder and schizophrenia, which are also included in the definition of neurological disorders. Further examples of neurological disorders include: acquired epileptic aphasia; acute disseminated encephalomyelitis; adrenoleukodystrophy; corpus callosum agenesis; agnosia; Aicardi syndrome; Alexander disease; Alpers disease; alternating hemiplegia; Alzheimer's disease; amyotrophic lateral sclerosis; anencephaly; Angelman syndrome; hemangioma; oxygen deficiency; aphasia; apraxia; arachnoid cyst; arachnoiditis; Arnold-Chiari malformation; arteriovenous malformation; Asperger's syndrome; telangiectasia ataxia; attention deficit hyperactivity disorder; autism; autonomic dysfunction; back pain; Baten's disease; Behçet's disease; Bell's palsy; benign essential blepharospasm; benign focal muscular atrophy; benign intracranial hypertension; Binswanger's disease; blepharospasm; Bloch-Sulzberger syndrome Syndromes; brachial plexus injury; brain abscess; brain injury; brain tumors (including glioblastoma multiforme); spinal tumors; Brown-Séquard syndrome; Canavan disease; carpal tunnel syndrome (CTS); burning pain; central pain syndrome; central pontine myelin disintegration; cranial disorders; cerebral aneurysm; cerebral arteriosclerosis; cerebral atrophy; cerebral gigantism; cerebral palsy; Charcot-Marie-Tooth disease; chemotherapy-induced neuropathy and neuropathic pain; Chiari malformation; chorea; chronic inflammatory demyelinating polyneuropathy (CIDP); chronic pain; chronic regional pain syndrome; Coffin-Lowry syndrome; coma including persistent vegetative state; congenital facial palsy; corticobasal degeneration; cranial arteritis; craniosynostosis; Creutzfeldt-Jakob disease; cumulative traumatic injury; Cushing's syndrome;Cytomegalic inclusion body disease (CIBD); cytomegalovirus infection; dancing eyes-dancing feet syndrome; Dandy-Walker syndrome; Dawson's disease; de ​​Morsier syndrome; Dégerine Krampke palsy; dementia; dermatomyositis; diabetic neuropathy; diffuse sclerosis; autonomic dysfunction; dysgraphia; dyslexia; dystonia; early infantile epileptic encephalopathy; empty cellulitis syndrome; encephalitis; brain herniation; trigeminal nerve hemangioma; epilepsy; Erb's palsy; essential tremor; Fabry disease; Fahl's syndrome; syncope; familial spastic paralysis; febrile seizures; Fisher syndrome; Friedreich's ataxia; frontotemporal dementia and other "ta Wopathies; Gaucher disease; Gerstmann syndrome; Giant cell arteritis; Giant cell inclusion body disease; Spheroid cell leukodystrophy; Guillain-Barré syndrome; HTLV-1 associated myelopathy; Hallerforden-Spats disease; Head trauma; Headache; Hemifacial spasm; Hereditary spastic paraplegia; Hereditary polyneurotic ataxia; Herpes zoster; Shingles; Hirayama syndrome; HIV-related dementia and neurological disorders (see also neurological symptoms of AIDS); Holoprosencephaly; Huntington's disease and other polyglutamine recurrent disorders; Hydroencephalopathy; Hydrocephalus; Cortisol excess; Hypoxia; Immune-mediated Encephalomyelitis; Inclusion body myositis; Incontinentia pigmenti; Infantile phytanoic acid storage; Infantile Refsum disease; Infantile seizures; Inflammatory myopathy; Intracranial cysts; Increased intracranial pressure; Joubert syndrome; Kahns-Sayre syndrome; Kennedy disease; Kinsborne syndrome; Klippel-Feyle syndrome; Krabbe disease; Kugelberg-Welander disease; Kuru disease; Lafora disease; Lambert-Eaton myasthenic syndrome; Landau-Kleffner syndrome; Lateral medullary (Wallenberg) syndrome; Learning disability; Leigh disease; Lennox-Gastaut syndrome; Lesch-Nyhan syndrome; White matter Dystrophy; Lewy body dementia; Lissencephaly; Locked-in syndrome; Lou Gehrig's disease (also known as motor neuron disease or amyotrophic lateral sclerosis); Lumbar disc disease; Lyme disease - neurological sequelae; Machado-Joseph disease; Cerencephalopathy; Megaencephalopathy; Melkerson-Rosenthal syndrome; Meniere's disease; Meningitis; Menkes disease; Metachromatic leukodystrophy; Microcephaly; Migraine; Miller-Fischer syndrome; Ministroke; Mitochondrial myopathy; Moebius syndrome; Monomeric muscular atrophy; Motor neuron disease; Moyamoya disease; Mucopolysaccharidosis;Multiple infarct dementia; multifocal motor neuropathy; multiple sclerosis and other demyelinating diseases; multiple system atrophy with orthostatic hypotension; muscular dystrophy; myasthenia gravis; diffuse sclerosis of the spinal cord with fragmentation; myoclonic encephalopathy in infants; myoclonus; myopathy; congenital myotonia; narcolepsy; neurofibromatosis; neuroleptic malignant syndrome; neurological symptoms of AIDS; neurological sequelae of lupus; neuromyotonia; neuronal ceroid lipofuscinosis; neuronal migration disorders; Niemann-Pick disease; O'Sullivan-McLeod syndrome; occipital neuralgia; occult spinal dysraphism Sequence; Ohtahara syndrome; olivopontocerebellar atrophy; opsoclonus-myoclonus; optic neuritis; orthostatic hypotension; overuse syndrome; paresthesia; Parkinson's disease; myotonic dysplasia; paraneoplastic disorders; seizures; Parry-Romberg syndrome; Perizeus-Merzbacher disease; periodic paralysis; peripheral neuropathy; painful neuropathy and neuropathic pain; persistent vegetative state; pervasive developmental disorder; photic sneeze reflex; phytanic acid storage; Pick's disease; nerve compression; pituitary tumor; polymyositis; porencephaly; postpolio syndrome Group; Postherpetic neuralgia (PHN); Post-infectious encephalomyelitis; Orthostatic hypotension; Prader-Willi syndrome; Primary lateral sclerosis; Prion disease; Progressive hemifacial atrophy; Progressive multifocal leukoencephalopathy; Progressive sclerosing polydystrophy; Progressive supranuclear palsy; Pseudotumor brain; Ramsay Hunt syndrome (Type I and Type II); Rasmussen encephalitis; Reflex sympathetic dystrophy syndrome; Refsum disease; Repetitive movement disorder; Repetitive stress injury; Restless legs syndrome; Retrovirus-associated myelopathy; Rett syndrome; Reye's syndrome; Chorea (Saint Vitus Dance; Sandhoff's disease; Schilder's disease; Schizoencephalopathy; Septooptic neurodysplasia; Shaken baby syndrome; Herpes zoster; Shy-Drager syndrome; Sjögren's syndrome; Sleep apnea; Soto's syndrome; Spasticity; Spina bifida; Spinal cord injury; Spinal cord tumor; Spinal muscular atrophy; Stiff person syndrome; Stroke; Sturge-Weber syndrome; Subacute sclerosing panencephalitis; Subarachnoid hemorrhage; Subcortical arteriosclerotic encephalopathy; Sydenham's chorea; Syncope; Syringomyelia; Tardive dyskinesia; Tay-Sachs disease; Temporal arteritis; Tethered spinal cord syndrome; Thomsen's disease; Thoracic outlet syndrome; Tic; Todd's paralysis; Tourette's syndrome; Transient ischemic attack;Infectious spongiform encephalopathy; transverse myelitis; traumatic brain injury; tremor; trigeminal neuralgia; tropical spastic paraparesis; tuberous sclerosis; vascular dementia (multiple infarct dementia); vasculitis including temporal arteritis; von Hippel-Lindau disease (VHL); Wallenberg syndrome; Werdnig-Hoffmann disease; West syndrome; whiplash; Williams syndrome; Wilson's disease; and Zellweger syndrome.

[0059] Neurodegenerative diseases are a type of neurological disorder characterized by the loss of nerve cells, and include, but are not limited to, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, tauopathy (including frontotemporal dementia), and Huntington's disease. In some aspects, Alzheimer's disease is a neurodegenerative disease. The cause of Alzheimer's disease is largely unknown, but is often thought to involve a genetic basis. The disease is characterized by the loss of neurons and synapses in the cerebral cortex, resulting in atrophy of the affected areas. Biochemically, Alzheimer's disease is characterized as a protein misfolding disorder caused by the accumulation of abnormally folded amyloid-beta and tau proteins in the brain. Symptoms of Alzheimer's disease include, but are not limited to, difficulty recalling recent events, language problems, disorientation, mood swings, decreased motivation, self-neglect, and behavioral problems. Ultimately, physical function is gradually lost, and Alzheimer's disease eventually leads to death. Treatment currently focuses on addressing cognitive problems caused by the disease (e.g., with acetylcholinesterase inhibitors or NMDA receptor antagonists), psychosocial interventions (e.g., behavior-oriented or cognitive-oriented approaches), and general care. Currently, there are no treatments that can completely halt or reverse the progression of the disease.

[0060] "Proliferative disorders" refer to diseases resulting from abnormal growth or expansion due to the proliferation of cells (Walker, Cambridge Dictionary of Biology; Cambridge University Press: Cambridge, UK, 1990). Proliferative disorders may be associated with: 1) pathological proliferation of cells that are normally quiescent; 2) pathological migration of cells from their normal location (e.g., metastasis of neoplastic cells); 3) pathological expression of proteolytic enzymes such as matrix metalloproteinases (e.g., collagenase, gelatinase, elastase); or 4) pathological angiogenesis, such as in proliferative retinopathy and tumor metastasis. Exemplary proliferative disorders include cancer (i.e., "malignant neoplasms"), benign neoplasms, angiogenesis, inflammatory diseases, and autoimmune diseases.

[0061] The terms “polynucleotide,” “nucleotide sequence,” “nucleic acid,” “nucleic acid molecule,” “nucleic acid sequence,” and “oligonucleotide” refer to a series of nucleotide bases (also called “nucleotides”) in DNA and RNA, and mean any chain of two or more nucleotides. Polynucleotides can be chimeric mixtures or derivatives or modified versions thereof, and can be single-stranded or double-stranded. Oligonucleotides can be modified with base moieties, sugar moieties, or phosphate backbone to improve, for example, molecular stability, their hybridization parameters, etc. In some embodiments, nucleic acids are metabolically labeled nucleic acids. “Metabolic labeled nucleic acid” as used herein refers to nucleic acids in which one or more non-natural nucleoside analogs, such as 5-ethynyluridine, are incorporated into their oligonucleotide chain during transcription.

[0062] As used herein, the term “post-transcriptional modification” refers to the chemical modification or alteration of RNA (e.g., RNA primary transcript) after transcription. Post-transcriptional modifications are common in eukaryotic cells (e.g., human cells) and are often important for the generation of mature, functional RNA molecules and / or for the translocation of RNA molecules from the nucleus to various locations within the cell that perform various functions. Post-transcriptional modifications also play an important role in the conversion of mRNA transcripts into mature mRNA that can be translated into proteins. Post-transcriptional modifications include, but are not limited to, modifications involved in 5' processing of RNA transcripts (e.g., 5' capping of mRNA with 7-methylguanosine), 3' processing of RNA transcripts (e.g., cleavage or polyadenylation of the 3' end of RNA transcripts), intron splicing (i.e., removal of non-coding regions (introns) from premRNA), and histone mRNA processing. Specific post-transcriptional modifications include, but are not limited to, modifications involving 7-methylguanosine (m 7 G), N 6 -Methyladenosine (m 6 A) This includes poly(A) tailing, intron splicing, and histone mRNA processing.

[0063] A “protein,” “peptide,” or “polypeptide” is a polymer of amino acid residues linked together by peptide bonds. The term can refer to proteins, polypeptides, and peptides of any size, structure, or function. Typically, a protein is at least three amino acids long. A protein can refer to an individual protein or a collection of proteins. The proteins of this invention preferably contain only natural amino acids; however, non-natural amino acids (i.e., compounds that do not exist naturally but can be incorporated into polypeptide chains) and / or amino acid analogs known in the art may be used as alternatives. Furthermore, one or more amino acids in a protein may be modified, for example, by adding carbohydrate groups, hydroxyl groups, phosphate groups, farnesyl groups, isofarnesyl groups, fatty acid groups, chemicals such as linkers for conjugation or functionalization, or other modifications. A protein may be a single molecule or a multimolecular complex. A protein may be a fragment of a naturally occurring protein or peptide. A protein may be natural, recombinant, synthetic, or any combination thereof.

[0064] An "RNA transcript" is a product resulting from the transcription of a DNA sequence catalyzed by RNA polymerase. When an RNA transcript is a complementary copy of a DNA sequence, it is called a primary transcript, or if it is an RNA sequence derived from the post-transcriptional processing of a primary transcript, it is called mature RNA. "Messenger RNA (mRNA)" refers to RNA that does not contain introns and can be translated into polypeptides by cells. "cRNA" refers to complementary RNA transcribed from a recombinant cDNA template. "cDNA" refers to DNA that is complementary to the mRNA template and derived from the mRNA template. "Nasal RNA" refers to RNA that is actively transcribed by cells, and RNA that has recently been transcribed by cells but has not yet undergone any kind of post-transcriptional modification.

[0065] The terms “sample” or “biological sample” refer to any sample containing tissue samples (e.g., tissue sections, surgical biopsies, and needle biopsies of tissue); cell samples (e.g., cytological smears (Pap or blood smears, etc.) or cell samples obtained by microdissection); or cell fractions, fragments, or organelles (e.g., those obtained by lysing cells and separating their components by centrifugation, etc.). Other examples of biological samples include blood, serum, urine, semen, feces, cerebrospinal fluid, interstitial fluid, mucus, tears, sweat, pus, biopsy tissue (e.g., obtained by surgical biopsy or needle biopsy), nipple aspirate, milk, vaginal fluid, saliva, swabs (e.g., oral swabs), or any material containing biomolecules derived from the first biological sample. In some embodiments, the biological sample is a surgical biopsy taken from a subject, e.g., a biopsy of any tissue as described herein. In one aspect, the biological sample is a tumor biopsy (for example, from a subject diagnosed with cancer, suspected of having cancer, or believed to have cancer).

[0066] The “subjects” to which the administration is intended refers to humans (i.e., males or females of any age group, e.g., pediatric subjects (e.g., infants, children, or adolescents) or adult subjects (e.g., young adults, middle-aged adults, or elderly adults)) or non-human animals. In some embodiments, non-human animals are mammals (e.g., primates (e.g., cynomolgus monkeys or rhesus monkeys)) or mice. The term “patient” refers to a subject who requires treatment for a disease. In some embodiments, the subject is human. In some embodiments, the patient is human. A human can be male or female at any stage of development. Subjects or patients who “require” treatment for a disease or disorder include, but are not limited to, those exhibiting any risk factors or symptoms of the disease or disorder. In some embodiments, the subject is a non-human laboratory animal (e.g., mouse, rat, dog, or pig).

[0067] The “therapeutic dose” of a treatment or therapeutic agent is the amount sufficient to provide a therapeutic benefit in the treatment of a condition, or to delay or minimize one or more symptoms associated with the condition. The therapeutic dose of a treatment or therapeutic agent means the amount of the treatment that produces a therapeutic effect in the treatment of a condition, either alone or in combination with other treatments. The term “therapeutic dose” may encompass amounts that improve the overall treatment, reduce or avoid the cause of a symptom, sign, or condition, and / or enhance the therapeutic effect of another therapeutic agent.

[0068] As used herein, “tissue” refers to a group of cells and their extracellular matrix from the same origin. Together, the cells perform specific functions. Multiple tissue types combine to form organs. The cells may be of different cell types. In some embodiments, tissue is epithelial tissue. Epithelial tissue is formed by cells that cover the surface of organs (e.g., the surface of the skin, the airways, soft organs, the reproductive tract, and the inner lining of the digestive tract). Epithelial tissue performs protective functions and is also involved in secretion, excretion, and absorption. Examples of epithelial tissue include, but are not limited to, simple squamous epithelium, stratified squamous epithelium, simple cuboidal epithelium, transitional epithelium, pseudostratified epithelium, columnar epithelium, and glandular epithelium. In some embodiments, tissue is connective tissue. Connective tissue is fibrous tissue composed of cells separated by abiotic material (e.g., extracellular matrix). Connective tissue gives shape to organs and holds them in place. Connective tissue includes fibrous connective tissue, skeletal connective tissue, and fluid connective tissue. Examples of connective tissue include, but are not limited to, blood, bone, tendons, ligaments, fat, and areolae. In some aspects, tissue is muscular tissue. Muscular tissue is active contractile tissue formed from muscle cells. Muscular tissue functions to generate force and cause movement. Muscular tissue includes smooth muscle (e.g., found in the inner layers of organs), skeletal muscle (e.g., typically attached to bones), and cardiac muscle (e.g., found in the heart, which contracts to pump blood throughout the organism). In some aspects, tissue is nervous tissue. Nervous tissue includes cells that comprise the central and peripheral nervous systems. Nervous tissue forms the brain, spinal cord, cranial nerves, and spinal nerves (e.g., motor neurons). In some aspects, tissue is brain tissue. In some aspects, tissue is placental tissue. In some aspects, tissue is cardiac tissue.

[0069] The terms “treatment,” “to treat,” and “to treat” mean to reverse, alleviate, delay the onset of, or inhibit the progression of a disease described herein. In some embodiments, treatment may be administered after the onset or observation of one or more signs or symptoms of the disease (e.g., prophylactically (as may be further described herein) or based on suspicion or risk of the disease). In other embodiments, treatment may be administered when there are no signs or symptoms of the disease. For example, treatment may be administered to a susceptible subject before the onset of symptoms (e.g., considering a history of symptoms in the subject or a family member of the subject). Treatment may also be continued after the resolution of symptoms, for example, to delay or prevent recurrence. In some embodiments, treatment may be administered after observing changes in the spatiotemporal gene expression of one or more nucleic acids of interest in cells or tissues compared to healthy cells or tissues, using the methods disclosed herein.

[0070] As used herein, the terms “tumor” and “neoplasm” refer to an abnormal mass of tissue whose growth exceeds and is inconsistent with that of normal tissue. Tumors are “benign” or “malignant” depending on the following characteristics: degree of cellular differentiation (including morphology and function), growth rate, local invasion, and metastasis. “Benign neoplasms” are generally well-differentiated, grow more slowly than malignant neoplasms, and remain localized at the site of origin. Furthermore, benign neoplasms do not have the ability to infiltrate, invade, or metastasize to distant sites. Exemplary benign neoplasms include, but are not limited to, lipomas, chondromes, adenomas, acrochordon, senile angioma, seborrheic keratosis, lentigo, and sebaceous hyperplasia. In some cases, certain “benign” tumors may later develop into malignant neoplasms, which may be due to additional genetic alterations in a subpopulation of neoplastic cells in the tumor; these tumors are called “pre-malignant neoplasms.” An exemplary pre-malignant neoplasm is a teratoma. In contrast, “malignant neoplasms” are generally poorly differentiated (anaplastic) and have characteristic rapid growth with progressive invasion, infiltration, and destruction of surrounding tissue. Furthermore, malignant neoplasms generally have the ability to metastasize to distant sites. The terms “metastasis,” “metastatic,” or “metastatic” refer to the spread or migration of cancer cells from a primary tumor or original tumor to another organ or tissue, and are typically distinguishable by the presence of a “secondary tumor” or “secondary cell mass” of the histological type of the primary tumor or original tumor, rather than the histological type of the organ or tissue in which the secondary (metastatic) tumor is located. For example, prostate cancer that has migrated to the bone is called metastatic prostate cancer, which includes cancerous prostate cancer cells that grow within the bone tissue.

[0071] Detailed description of a specific aspect The aspects described herein are not limited to any particular embodiment, system, composition, method, or configuration, and are therefore naturally subject to change. The terms used herein are intended solely to describe a particular aspect and are not intended to limit it unless otherwise defined herein.

[0072] This disclosure provides methods for profiling spatiotemporal gene expression, including methods for profiling spatiotemporal gene expression in vivo in a subject. This disclosure also provides methods for profiling the role of post-transcriptional modifications in spatiotemporal gene expression, methods for studying the role of spatiotemporal gene expression in the onset or progression of disease or disorder, methods for identifying gene expression-modulating agents, methods for diagnosing disease or disorder in a subject, and methods for treating disease or disorder in a subject. Oligonucleotide probes useful in the methods and systems disclosed herein are also provided. This disclosure also provides kits containing the oligonucleotide probes disclosed herein. Systems for profiling spatiotemporal gene expression are also provided.

[0073] Methods for profiling spatiotemporal gene expression In one aspect, the present disclosure provides a method for profiling spatiotemporal gene expression in cells (see, for example, Figure 1). In the method disclosed herein, cells can be metabolically labeled by incubation in the presence of a pool of nucleoside analogs, where each nucleoside analog contains a reactive chemical moiety (e.g., any reactive bioorthogonal functional group, e.g., a click chemistry handle, as further described herein) for a certain period of time (referred herein to as "t1"). The metabolically labeled nucleic acid can then be contacted with a first oligonucleotide probe containing a reactive chemical moiety (e.g., any bioorthogonal functional group that can react with the reactive chemical moiety of a nucleoside analog incorporated into a cell transcript). The reactive chemical moiety of the nucleoside analog and the first oligonucleotide probe react with each other, causing the first oligonucleotide probe to bind to a metabolically labeled transcript produced by the cell. The metabolically labeled nucleic acid can then be contacted with one or more pairs of oligonucleotide probes, as further described herein, and used to amplify the transcript produced by the cell to generate one or more ligated amplicons. The one or more ligated amplicons can then be embedded in a polymer matrix and sequenced to determine the identity of the transcript (e.g., through SEDAL sequencing (sequencing with error reduction by dynamic annealing and ligation), as further described herein) and their positions within the polymer matrix. The positions of the transcripts can be used to identify individual cells, intracellular locations, and organelles. This method can then be repeated one or more times, incubating the cells and nucleoside analogs at different times (i.e., t2, t3, t4, etc.) to determine how the expression of one or more nucleic acids changes over time.

[0074] In some embodiments, the present disclosure provides a method for profiling spatiotemporal gene expression in cells, comprising the following steps: a) Incubate cells for time t1 in the presence of a pool of nucleoside analogs to metabolically label the nucleic acids synthesized by the cells, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix.

[0075] In some embodiments, steps (a) to (h) are performed one or more times. Repeating steps (a) to (h), and incubating the pool of cells and nucleoside analogs together for various times in step (a), allows for the observation of the expression of the desired metabolically labeled nucleic acid, or multiple desired metabolically labeled nucleic acids, over time, making it possible to profile the spatiotemporal expression of the desired labeled nucleic acid. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed. There is no limit to the number of times steps (a) to (h) can be repeated. There is also no limit to the time spent incubating the pool of cells and nucleoside analogs together in step (a). In some embodiments, the incubation in step (a) is carried out for a few minutes (e.g., about 1 minute, about 2 minutes, about 5 minutes, about 10 minutes, about 20 minutes, about 30 minutes, about 40 minutes, about 50 minutes, or about 60 minutes). In some embodiments, the incubation in step (a) is carried out for a period of several hours (e.g., approximately 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 11 hours, 12 hours, 13 hours, 14 hours, 15 hours, 16 hours, 17 hours, 18 hours, 19 hours, 20 hours, 21 hours, 22 hours, 23 hours, or 24 hours). In some embodiments, the incubation in step (a) is carried out for more than 24 hours. In some embodiments, the incubation in step (a) is carried out for a period of several days (e.g., approximately 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, 7 days, or longer than 7 days).

[0076] The use of any type of cell in the methods disclosed herein is contemplated by this disclosure (e.g., any cell type as defined herein). In some embodiments, the cells are mammalian cells. In some embodiments, the cells are human cells. In some embodiments, the cells are cancer cells. This disclosure also contemplates performing the methods described herein on multiple cells simultaneously. In some embodiments, spatiotemporal gene expression is profiled simultaneously on more than 10 cells, more than 20 cells, more than 50 cells, more than 100 cells, more than 200 cells, more than 300 cells, more than 400 cells, more than 500 cells, or more than 1000 cells. In some embodiments, the method is performed on multiple cells of the same cell type. In some embodiments, the method is performed on multiple cells including cells of different cell types (e.g., stem cells, progenitor cells, nerve cells, astrocytes, dendritic cells, endothelial cells, microglia, oligodendrocytes, muscle cells, cardiomyocytes, mesenchymal cells, epithelial cells, immune cells, hepatocytes, smooth muscle cells and skeletal muscle cells, hematopoietic cells, lymphocytes, monocytes, neutrophils, macrophages, natural killer cells, mast cells, adipocytes, neurons, etc.). In some embodiments, the cells are HeLa cells. In some embodiments, the cells (one or more) are permeabilized cells (e.g., the cells are permeabilized before the step of contacting a population of first oligonucleotide probes). In some embodiments, the cells (one or more) are located within intact tissue (e.g., any of the tissue types described herein, e.g., epithelial tissue, connective tissue, muscle tissue, and nerve tissue). In some embodiments, the tissue is in vivo prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes (i.e., the tissue is in vivo during the step of incubating cells in the presence of a pool of nucleoside analogs). In some embodiments, one or more cells within the tissue are incubated in vivo in the presence of a pool of nucleoside analogs, and the tissue is then harvested prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes.Tissue collection may involve taking an entire organ from the subject (e.g., a non-human laboratory animal) or it may involve a tissue biopsy. In some embodiments, the tissue is found in non-human laboratory animals (e.g., mice, rats, dogs, pigs, or non-human primates (e.g., monkeys, apes, etc.)). In some embodiments, the tissue is plant tissue.

[0077] In some embodiments, any method described herein can be carried out in vivo. Therefore, in some embodiments, this disclosure provides a method comprising the following steps for profiling spatiotemporal gene expression in a subject: a) A pool of nucleoside analogs is administered in vivo to a subject for time t1 to metabolically label nucleic acids synthesized by one or more cells of the subject, wherein each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) To collect a tissue sample from the subject; c) Contacting the metabolically labeled nucleic acid in the collected tissue sample with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; d) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where; i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; e) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; f) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; g) Embedding one or more linked amplicons into a polymer matrix; h) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and i) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix.

[0078] In some embodiments, the collected tissue is epithelial tissue, connective tissue, muscle tissue, or nerve tissue. In some embodiments, the collected tissue is cardiac tissue. In some embodiments, the subject is a non-human experimental animal (e.g., mouse, rat, dog, pig, or non-human primate). The nucleoside analog may be administered to the subject by any suitable means, e.g., injection. In some embodiments, the nucleoside analog is administered by retro-orbital administration. In some embodiments, collecting a tissue sample from the subject includes performing a tissue biopsy. In some embodiments, collecting a tissue sample from the subject includes collecting one or more whole organs from the subject.

[0079] The use of labeled cells (i.e., metabolically labeled cells) in the methods described herein is also contemplated by this disclosure. In some embodiments, cells are labeled with a nucleoside analog. In some embodiments, the nucleoside analog is an analog of adenosine, guanosine, thymidine, cytidine, uridine, and / or inosine. In some embodiments, the nucleoside analog is 3'-azido-3'-deoxythymidine, C8-alkyne-deoxyuridine, (2'S)-2'-deoxy-2'-fluoro-5-ethynyluridine, or 5-ethynyl-2'-deoxycytidine. In some embodiments, the metabolically labeled nucleic acid is a 5-ethynyluridine-labeled nucleic acid. In some embodiments, multiple cells are profiled simultaneously using the methods described herein.

[0080] The methods described herein may be used to profile spatiotemporal gene expression for one target metabolically labeled nucleic acid at a time, or for multiple target metabolically labeled nucleic acids simultaneously. In some embodiments, spatiotemporal gene expression is profiled simultaneously for up to 100, up to 200, up to 500, up to 1000, up to 2000, up to 3000, or more than 3000 target metabolically labeled nucleic acids. In some embodiments, spatiotemporal gene expression is profiled simultaneously for up to 1000 target metabolically labeled nucleic acids. The target metabolically labeled nucleic acid may be a transcript expressed from the genomic DNA of a cell. In some embodiments, the target metabolically labeled nucleic acid is nascent RNA, messenger RNA (mRNA), transfer RNA (tRNA), or ribosomal RNA (rRNA). In some embodiments, the target metabolically labeled nucleic acid is nascent RNA (i.e., RNA newly produced by a cell, or RNA newly produced by a cell but not yet subjected to any kind of post-transcriptional modification). In one embodiment, the target metabolically labeled nucleic acid is mRNA.

[0081] Nucleoside analogs having various reactive chemical moieties are intended for use in the methods described herein. The reactive chemical moiety of the nucleoside analog may be any reactive bioorthogonal functional group (e.g., any click chemistry handle described herein). Those skilled in the art will readily understand that other bioorthogonal functional groups not disclosed herein are suitable for use in the methods disclosed herein, and that the bioorthogonal functional groups described herein may be substituted with any other known in the art. See, for example, U.S. Patent Publication 20130266512 and Thirumurugan, P. et al. Click Chemistry for Drug Development and Diverse Chemical-Biology Applications. Chem. Rev. 2013, 113(7), 4905-4979. In some embodiments, the reactive chemical moiety of the nucleoside analog includes azides, alkynes, nitrones, alkenes, tetrazines, or tetrazoles. In some embodiments, the reactive chemical moiety of the nucleoside analog includes alkynes. In some embodiments, the nucleoside analog is 3'-azido-3'-deoxythymidine, C8-alkyne-deoxyuridine, (2'S)-2'-deoxy-2'-fluoro-5-ethynyluridine, or 5-ethynyl-2'-deoxycytidine. In some embodiments, the nucleoside analog is 5-ethynyluridine. In some embodiments, the nucleoside analog is located at the 5' end of the oligonucleotide probe. In some embodiments, the nucleoside analog is located at the 3' end of the oligonucleotide probe.

[0082] The methods described herein involve the use of a first oligonucleotide probe (also referred to herein as a “sprint probe”) comprising a reactive chemical moiety. The reactive chemical moiety of the first oligonucleotide probe must be reactive with the reactive chemical moiety of a nucleoside analog used to metabolically label cells, such that upon contact with the cell, the first oligonucleotide probe conjugates with a metabolically labeled transcript present in the cell. The reactive chemical moiety of the first oligonucleotide probe may be any bioorthogonal functional group described herein or known in the art. In some embodiments, the chemical moiety of the first oligonucleotide probe comprises an azide, alkyne, nitrone, alkene, tetrazine, or tetrazole. In some embodiments, the chemical moiety of the first oligonucleotide probe comprises an azide. In some embodiments, the reaction between the chemical moiety of the nucleoside analog and the chemical moiety of the first oligonucleotide probe comprises a click chemistry reaction (e.g., a copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) reaction).

[0083] The first oligonucleotide probe may also include various other components. In some embodiments, the first oligonucleotide probe further includes a polymerization blocker. The polymerization blocker may be any portion that can prevent the use of the first oligonucleotide probe as a primer in amplification in step (e) of the method described herein. In some embodiments, the polymerization blocker is located at the 3' end of the first oligonucleotide probe. The polymerization blocker may be any chemical portion that prevents, for example, a polymerase from using the first oligonucleotide probe as a primer for polymerization. In some embodiments, the polymerization blocker is a nucleic acid residue containing a blocked 3' hydroxyl group (e.g., containing an oxygen-protecting group on the 3' hydroxyl group). In some embodiments, the polymerization blocker contains hydrogen instead of the 3' hydroxyl group. In some embodiments, the polymerization blocker contains any chemical portion instead of the 3' hydroxyl group, which prevents the addition of further nucleotides. In some embodiments, the polymerization blocker contains an inverted nucleic acid residue. In some embodiments, the polymerization blocker is an inverted adenosine, thymine, cytosine, guanosine, or uridine residue. In one embodiment, the polymerization blocker is an inverted thymine residue. In several embodiments, the first oligonucleotide probe further comprises a polyadenosine (poly-A) linker sequence. In several embodiments, the poly-A linker sequence is about 2 to about 100, about 10 to about 90, about 30 to about 70, or about 40 to about 60 nucleotides long. In one embodiment, the poly-A linker sequence is about 50 nucleotides long.

[0084] In some embodiments, the first oligonucleotide probe is about 30, 35, 40, 45, 50, 55, 60, 65, 70, or about 75 nucleotides long. In some embodiments, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is about 3–20, 4–19, 5–18, 6–17, 7–16, 8–15, 9–14, 10–13, or about 11–12 nucleotides long. In some embodiments, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is about 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or about 20 nucleotides long. In one embodiment, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is approximately 12 nucleotides long. In some embodiments, the first oligonucleotide probe has the following structure: 5'-[Reactive chemical part]-[PolyA linker sequence]-[Part complementary to the third oligonucleotide probe]-[Polymerization blocker]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0085] The methods disclosed herein also include the use of second and third oligonucleotide probes provided as a pair of oligonucleotide probes. The second oligonucleotide probe (also referred herein as the “primer” probe) comprises a barcode sequence consisting of a specific sequence of nucleotides. In some embodiments, the barcode sequence of the second oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the barcode sequence of the second oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is greater than about 10 nucleotides long, greater than about 15 nucleotides long, or greater than about 20 nucleotides long. In one embodiment, the barcode sequence of the second oligonucleotide probe is 5 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is about 10 to 30, about 11 to 29, about 12 to 28, about 13 to 27, about 14 to 26, about 15 to 25, about 16 to 24, about 17 to 23, about 18 to 22, or about 19 to 21 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the target metabolically labeled nucleic acid is approximately 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the target nucleic acid is 20 nucleotides long. In some embodiments, the second oligonucleotide probe is approximately 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40 nucleotides long. In some embodiments, the second oligonucleotide probe is 32 nucleotides long. In some embodiments, the second oligonucleotide probe has the following structure: 5'-[Part complementary to the target metabolically labeled nucleic acid]-[Barcode sequence]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0086] A third oligonucleotide probe (also referred to herein as a “padlock” probe) used in the method described herein comprises a first barcode sequence and a second barcode sequence, each consisting of a specific sequence of nucleotides. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is longer than about 10 nucleotides, longer than about 15 nucleotides, or longer than about 20 nucleotides. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 5 nucleotides long. In some embodiments, the second barcode sequence of the third oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the second barcode sequence of the third oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is longer than about 10 nucleotides, longer than about 15 nucleotides, or longer than about 20 nucleotides. In one embodiment, the second barcode sequence of the third oligonucleotide probe is approximately 5 nucleotides long. The third oligonucleotide probe also includes a portion complementary to the first oligonucleotide probe. In some embodiments, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is approximately 3–20, approximately 4–19, approximately 5–18, approximately 6–17, approximately 7–16, approximately 8–15, approximately 9–14, approximately 10–13, or approximately 11–12 nucleotides long. In some embodiments, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is approximately 3, approximately 4, approximately 5, approximately 6, approximately 7, approximately 8, approximately 9, approximately 10, approximately 11, approximately 12, approximately 13, approximately 14, approximately 15, approximately 16, approximately 17, approximately 18, approximately 19, or approximately 20 nucleotides long. In some embodiments, a portion of a third oligonucleotide probe complementary to the first oligonucleotide probe is split between the 5' and 3' ends of the third oligonucleotide probe.In some embodiments, the portion of the third oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is approximately 10–30, 11–29, 12–28, 13–27, 14–26, 15–25, 16–24, 17–23, 18–22, or 19–21 nucleotides long. In some embodiments, the portion of the third oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is approximately 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, or more than 30 nucleotides long. In some embodiments, the third oligonucleotide probe has the following structure: 5'-[First portion complementary to the first oligonucleotide probe]-[First barcode sequence]-[Part complementary to the target metabolically labeled nucleic acid]-[Second barcode sequence]-[Second portion complementary to the first oligonucleotide probe]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0087] In some embodiments, the barcodes of the oligonucleotide probes described herein include gene-specific sequences used to identify the metabolically labeled nucleic acid of interest. The use of barcodes in the oligonucleotide probes described herein is further described, for example, in International Patent Application Publication WO2019 / 199579, published on 17 October 2019, and in Wang et al., Science 2018, 361, 380, both of which are incorporated herein by reference in their entirety.

[0088] In some embodiments, the ligation step cannot be carried out in the absence of a third oligonucleotide probe. In some embodiments, the step of amplifying a cyclic oligonucleotide by rolling circle amplification to produce one or more linked amplicons further includes a step of providing nucleotides modified with reactive chemical groups. In some embodiments, the step of amplifying a cyclic oligonucleotide by rolling circle amplification to produce one or more linked amplicons further includes a step of providing amine-modified nucleotides. During the amplification process, the amine-modified nucleotides are incorporated into the one or more linked amplicons produced. The resulting amplicons are functionalized with a primary amine, which can then be reacted with another suitable chemical moiety (e.g., N-hydroxysuccinimide) to facilitate the step of embedding the amplicons in a polymer matrix. In some embodiments, the step of embedding one or more linked amplicons in a polymer matrix includes reacting the amine-modified nucleotides of one or more linked amplicons with N-hydroxysuccinimide methacrylate, and copolymerizing the one or more linked amplicons with the polymer matrix.

[0089] The use of various polymer matrices is contemplated in this disclosure, and any polymer matrix capable of embedding one or more linked amplicons is suitable for use in the methods described herein. In some embodiments, the polymer matrix is ​​a hydrogel (i.e., a network of hydrophilic crosslinked polymers). In some embodiments, the hydrogel is a polyvinyl alcohol hydrogel, a polyethylene glycol hydrogel, a sodium polyacrylate hydrogel, an acrylic polymer hydrogel, or a polyacrylamide hydrogel. In some embodiments, the hydrogel is a polyacrylamide hydrogel.

[0090] The methods disclosed herein also include the use of a fourth oligonucleotide probe. In some embodiments, the fourth oligonucleotide probe comprises a fluorophore. As described herein, the fourth oligonucleotide probe is complementary to the second barcode sequence of the third oligonucleotide probe. In some embodiments, the second barcode sequence of the third oligonucleotide probe is a gene-specific sequence used to identify the metabolically labeled nucleic acid of interest. In some embodiments, the step of contacting one or more ligated amplicons embedded in a polymer matrix with the fourth oligonucleotide probe is performed to identify the metabolically labeled nucleic acid of interest. This method for identifying the metabolically labeled nucleic acid of interest is known as sequencing with error reduction by dynamic annealing and ligation (SEDAL sequencing), and is described in Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 2018, 36, eaat5691 and International Patent Application Publication WO 2019 / 199579, respectively, which are incorporated herein by reference. In some embodiments, SEDAL sequencing is performed two, three, four, five, or more times to identify one or more target metabolically labeled nucleic acids.

[0091] A fourth oligonucleotide probe used in the methods described herein (for example, as used in SEDAL sequencing) can be read out using any suitable imaging technique known in the art. For example, in embodiments in which the fourth oligonucleotide probe comprises a fluorophore, the fluorophore can be read out using imaging to identify the metabolically labeled nucleic acid of interest. In some embodiments, the imaging step includes fluorescence imaging. In some embodiments, the imaging step includes confocal microscopy. In some embodiments, the imaging step includes epifluorescence microscopy.

[0092] In various embodiments, the methods described herein may include a further step of profiling additional molecules other than the nucleic acid of interest. In some embodiments, the methods described herein further include profiling additional molecules within a cell. Such additional molecules may include, but are not limited to, RNA, DNA, proteins, carbohydrates, small molecules, metabolites, and / or lipids.

[0093] In some embodiments, the method described herein further includes determining the cell type of the profiled cell by comparing the spatiotemporal gene expression profile of the cell with reference data including spatiotemporal gene expression profiles of various cell types.

[0094] In some embodiments, the methods described herein further include overexpressing or knocking out one or more genes in a cell to determine whether one or more genes are involved in the spatiotemporal expression of the metabolically labeled nucleic acid of interest.

[0095] Methods for profiling the role of post-transcriptional modifications in spatiotemporal gene expression In another aspect, this disclosure relates to post-transcriptional modifications in spatiotemporal gene expression (e.g., 7-methylguanosine, N 6 -Methyladenosine (m 6 The present invention provides methods for profiling the roles of (A), poly(A) tails, intron splicing, or histone mRNA processing. For example, the spatiotemporal gene expression profiling methods described herein may be carried out in cells that include knockdown of genes involved in the post-transcriptional modification of one or more metabolically labeled nucleic acids of interest (e.g., one or more metabolically labeled RNA transcripts). The spatiotemporal expression of various metabolically labeled nucleic acids of interest in the knockdown cells can then be compared with the spatiotemporal expression of the same metabolically labeled nucleic acids of interest in wild-type cells. Any changes in the expression of the metabolically labeled nucleic acids of interest compared to their expression in wild-type cells may indicate that the post-transcriptional modification is involved in regulating the spatiotemporal expression of the metabolically labeled nucleic acid of interest.

[0096] In some embodiments, a method for profiling the role of post-transcriptional modifications in spatiotemporal gene expression in cells includes the following steps: a) Cells containing knockdown of genes involved in post-transcriptional modification are incubated for t1 time in the presence of a pool of nucleoside analogs to metabolically label nucleic acids synthesized by the cells, where each nucleoside analog in the pool contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix. Here, the change in the expression of the target metabolically labeled nucleic acid compared to its expression in wild-type cells indicates that post-transcriptional modification is involved in regulating the spatiotemporal expression of the target metabolically labeled nucleic acid.

[0097] In some embodiments, multiple cells are analyzed simultaneously using the method described herein. In some embodiments, steps (a) to (h) are performed one or more times. By repeating steps (a) to (h) and incubating the pool of cells and nucleoside analogs together for various times in step (a), the expression of the metabolically labeled nucleic acid of interest, or multiple metabolically labeled nucleic acids of interest, can be observed over time, making it possible to profile the spatiotemporal expression of the labeled nucleic acid of interest. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0098] Profiling of various post-transcriptional modifications can be performed using the methods disclosed herein. Any post-transcriptional modification where a particular gene or set of genes is known or thought to be involved in the introduction can be profiled using the methods of the present disclosure. In some embodiments, the post-translational modification includes 5' processing of the transcript (e.g., introduction of a 5' cap). In some embodiments, the post-transcriptional modification includes 3' processing of the transcript (e.g., polyadenylation of the transcript or cleavage of the 3' end of the transcript). In some embodiments, the post-transcriptional modification includes 7-methylguanosine, N 6 -methyladenosine (m 6 A), poly(A) tail, intron splicing, or histone mRNA processing. In some embodiments, the post-transcriptional modification includes methylation of adenosine. In one embodiment, the post-transcriptional modification is m 6 A.

[0099] Various genes involved in the post-transcriptional modification of nucleic acids can be knocked down and studied using the methods described herein. In some embodiments, the genes involved in the post-transcriptional modification are selected from the group consisting of YTH domain family (YTHDF) 1, YTHDF2, YTHDF3, YTH domain-containing (YTHDC) 1, YTHDC2, methyltransferase-like (METTL) 3, and METTL14. The methods disclosed herein can be used to study the role of genes involved in post-transcriptional modification in the spatio-temporal gene expression of one target metabolically labeled nucleic acid at a time, or in the spatio-temporal gene expression of multiple target metabolically labeled nucleic acids at a time. In some embodiments, the role of post-transcriptional modification in spatio-temporal gene expression is profiled simultaneously for up to 100, up to 200, up to 500, up to 1000, up to 2000, up to 3000, or more than 3000 target metabolically labeled nucleic acids. In one embodiment, the role of post-transcriptional modification in spatio-temporal gene expression is profiled simultaneously for up to 1000 target metabolically labeled nucleic acids.

[0100] In some embodiments, the cells are present in a tissue in vivo prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes (i.e., the tissue is present in vivo during the step of incubating the cells in the presence of a pool of nucleoside analogs). In some embodiments, one or more cells within the tissue are incubated in vivo in a subject in the presence of a pool of nucleoside analogs, and the tissue is subsequently collected from the subject prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes. Tissue collection may involve collecting an entire organ from the subject (e.g., a non-human experimental animal) or may involve a tissue biopsy. In some embodiments, the tissue is present in a non-human experimental animal (e.g., a mouse, rat, dog, pig, or a non-human primate such as an ape or monkey).

[0101] Methods for studying the role of spatiotemporal gene expression in the onset or progression of disease or disability In another aspect, this disclosure provides methods for studying the role of spatiotemporal gene expression in the onset or progression of disease or disorder. For example, the spatiotemporal gene expression profiling methods described herein may be performed in cells from diseased tissue (e.g., diseased tissue taken from a subject). The spatiotemporal expression of various metabolically labeled nucleic acids of interest in cells from diseased tissue can then be compared with the spatiotemporal expression of the same metabolically labeled nucleic acids of interest in cells from non-disease tissue. Any changes in the expression of the metabolically labeled nucleic acids of interest compared to expression in non-disease cells may indicate that the spatiotemporal expression of the metabolically labeled nucleic acids of interest may be involved in the onset or progression of disease or disorder.

[0102] In some embodiments, methods for studying the role of spatiotemporal gene expression in the onset or progression of a disease or disorder include the following steps: a) Incubating cells from diseased tissue for time t1 in the presence of a pool of nucleoside analogs to metabolically label the nucleic acids synthesized by the cells, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix. Here, changes in the expression of the target metabolically labeled nucleic acid compared to its expression in cells from non-disease cells or non-disease tissues suggest that changes in the spatiotemporal expression of the target metabolically labeled nucleic acid may be involved in the onset or progression of disease or disorder.

[0103] In some embodiments, multiple cells are profiled simultaneously using the method described herein. In some embodiments, steps (a) to (h) are performed one or more times. By repeating steps (a) to (h) and incubating the pool of cells and nucleoside analogs together for various times in step (a), the expression of the metabolically labeled nucleic acid of interest, or multiple metabolically labeled nucleic acids of interest, can be observed over time, making it possible to profile the spatiotemporal expression of the labeled nucleic acid of interest. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0104] The role of one or more nucleic acids of interest in any disease or disorder that may be associated with altered gene expression can be studied using the methods described herein, and the methods described herein are not limited to the study of any particular disease or disorder. In some embodiments, the disease or disorder is a genetic disorder, proliferative disorder, inflammatory disorder, autoimmune disorder, liver disorder, spleen disorder, lung disorder, hematological disorder, neurological disorder, gastrointestinal (GI) tract disorder, genitourinary disorder, infectious disease, musculoskeletal disorder, endocrine disorder, metabolic disorder, immune disorder, central nervous system (CNS) disorder, neurological disorder, ophthalmic disorder, or cardiovascular disorder.

[0105] The use of various tissue samples in the methods described herein is also contemplated by this disclosure. When carrying out the methods described herein, any tissue sample (e.g., a sample of any type of tissue listed in the definition) may be used. In some embodiments, the diseased tissue is a tissue sample taken from a subject. In some embodiments, the subject is a non-human experimental animal. In some embodiments, the subject is a mouse, rat, dog, or pig. In some embodiments, the subject is a human (e.g., a patient diagnosed with, suspected to have, or at risk of having, the disease or disorder of study). In some embodiments, the diseased tissue is in vivo prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes (i.e., the tissue is in vivo during the step of incubating cells in the presence of a pool of nucleoside analogs). In some embodiments, one or more cells in the diseased tissue are incubated in vivo in the subject in the presence of a pool of nucleoside analogs, and then the diseased tissue is taken prior to the step of contacting the metabolically labeled nucleic acid with a population of first oligonucleotide probes. Tissue sampling may involve taking an entire organ from the subject (e.g., a non-human laboratory animal) or it may involve a tissue biopsy. In some embodiments, diseased tissue is present in a non-human laboratory animal (e.g., a mouse, rat, dog, pig, or a non-human primate such as an ape or monkey).

[0106] A method for screening drugs that can modulate spatiotemporal gene expression. In another aspect, this disclosure provides a method for screening agents capable of modulating the spatiotemporal gene expression of a target metabolite-labeled nucleic acid or a group of target metabolite-labeled nucleic acids. For example, the spatiotemporal gene expression profiling method described herein may be carried out in cells in the presence of one or more candidate agents. The spatiotemporal expression of various target metabolite-labeled nucleic acids in cells (e.g., normal or diseased cells) can then be compared to the spatiotemporal expression of the same target metabolite-labeled nucleic acid in cells not exposed to one or more candidate agents. Any change in the expression of the target metabolite-labeled nucleic acid(s) compared to the expression in cells not exposed to the candidate agent(s) may indicate that the spatiotemporal expression of the target metabolite-labeled nucleic acid(s) is modulated by the candidate agent(s).

[0107] In some embodiments, a method for screening drugs capable of modulating spatiotemporal gene expression includes the following steps: a) Incubating cells for t1 time in the presence of one or more candidate drugs and a pool of nucleoside analogs to metabolically label nucleic acids synthesized by the cells, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix. Here, the changes in the expression of the target metabolically labeled nucleic acid in the presence of one or more candidate drugs, compared to expression in the absence of one or more candidate drugs, indicate that one or more candidate drugs regulate spatiotemporal gene expression.

[0108] In some embodiments, multiple cells are profiled simultaneously using the method described herein. In some embodiments, steps (a) to (h) are performed one or more times. By repeating steps (a) to (h) and incubating the pool of cells and nucleoside analogs together for various times in step (a), the expression of the metabolically labeled nucleic acid of interest, or multiple metabolically labeled nucleic acids of interest, can be observed over time, making it possible to profile the spatiotemporal expression of the labeled nucleic acid of interest. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0109] In some embodiments, one or more candidate drugs may be provided as a library of candidate drugs (e.g., from a screening collection of small molecules or other candidate therapeutic agents). In some embodiments, the library of candidate drugs may contain several hundred candidate drugs (e.g., about 100, about 200, about 300, about 400, about 500, about 600, about 700, about 800, or about 900). In some embodiments, the screening library contains thousands of candidate drugs (e.g., approximately 1,000, 2,000, 3,000, 5,000, 10,000, 20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000, or more than 100,000). In some embodiments, one candidate drug is screened per cell. In some embodiments, only one candidate drug at a time is screened using the method described herein.

[0110] In some embodiments, one or more candidate drugs are selected from the group consisting of small molecules, proteins, peptides, nucleic acids, lipids, and carbohydrates. In some embodiments, the candidate drug (e.g., small molecule) is an anticancer agent. In some embodiments, the candidate drug (e.g., small molecule) includes a known drug. In some embodiments, the candidate drug (e.g., small molecule) includes an FDA-approved drug. In some embodiments, the small molecule includes a library of compounds. In some embodiments, the protein is an antibody. In some embodiments, the protein is an antibody fragment. In some embodiments, the protein is an antibody variant. In some embodiments, the protein is a receptor. In some embodiments, the protein is a cytokine. In some embodiments, the nucleic acid is mRNA, antisense RNA, miRNA, siRNA, RNA aptamer, dsRNA, short hairpin RNA (shRNA), or antisense oligonucleotide (ASO). Any candidate drug can be screened using the method herein. In particular, any candidate drug that is thought to be able to modulate spatiotemporal gene expression can be screened using the method herein. In some embodiments, the spatiotemporal regulation of the gene expression of a target metabolite-labeled nucleic acid or multiple target metabolite-labeled nucleic acids by one or more candidate agents is associated with reducing, alleviating, or eliminating symptoms of a disease or disorder, or preventing the onset or progression of a disease or disorder. In some embodiments, the diseases or disorders regulated by the candidate agents are genetic disorders, proliferative disorders, inflammatory diseases, autoimmune diseases, liver diseases, spleen diseases, lung diseases, hematological diseases, neurological diseases, gastrointestinal (GI) tract diseases, genitourinary diseases, infections, musculoskeletal diseases, endocrine diseases, metabolic disorders, immune disorders, central nervous system (CNS) disorders, neurological disorders, ophthalmic diseases, or cardiovascular diseases.

[0111] Methods for diagnosing diseases or disorders in subjects In another aspect, this disclosure provides a method for diagnosing disease or disorder in a subject. For example, the spatiotemporal gene expression profiling method described herein can be performed on cells from a sample taken from a subject (e.g., a subject suspected of having or at risk of having a disease or disorder, or a subject who is healthy or considered healthy). The spatiotemporal expression of various metabolically labeled nucleic acids of interest in the cells can then be compared to the spatiotemporal expression of the same metabolically labeled nucleic acids of interest in cells from non-disease cells or non-disease tissue samples (e.g., cells from a healthy individual, or multiple cells from a population of healthy individuals). Any changes in the expression of the metabolically labeled nucleic acids of interest compared to expression in non-disease cells may indicate that the subject has a disease or disorder.

[0112] In some embodiments, a method for diagnosing a disease or disorder in a subject includes the following steps: a) Cells from a sample taken from the subject are incubated for time t1 in the presence of a pool of nucleoside analogs to metabolically label the nucleic acids synthesized by the cells, where the pool of nucleoside analogs includes a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix. Here, changes in the expression of the metabolically labeled nucleic acid of interest, compared to expression in cells from non-disease cells or non-disease tissue samples, indicate that the subject has a disease or disorder.

[0113] In some embodiments, the spatiotemporal expression of a target metabolically labeled nucleic acid in cells from non-disease cells or non-disease tissue samples can be simultaneously profiled as a control experiment. In some embodiments, the spatiotemporal expression profile of the target metabolically labeled nucleic acid in cells from non-disease cells or non-disease tissue samples includes reference data.

[0114] In some embodiments, multiple cells are profiled simultaneously using the method described herein. In some embodiments, steps (a) to (h) are performed one or more times. By repeating steps (a) to (h) and incubating the pool of cells and nucleoside analogs together for various times in step (a), the expression of the metabolically labeled nucleic acid of interest, or multiple metabolically labeled nucleic acids of interest, can be observed over time, making it possible to profile the spatiotemporal expression of the nucleic acid of interest. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0115] The diagnosis of any disease or disorder is attempted by the methods described herein. In some embodiments, the disease or disorder is a genetic disorder, proliferative disorder, inflammatory disorder, autoimmune disorder, liver disorder, spleen disorder, lung disorder, hematological disorder, neurological disorder, gastrointestinal (GI) tract disorder, genitourinary tract disorder, infection, musculoskeletal disorder, endocrine disorder, metabolic disorder, immune disorder, central nervous system (CNS) disorder, neurological disorder, ophthalmic disorder, or cardiovascular disorder. In some embodiments, the disease or disorder is cancer.

[0116] In some embodiments, the subjects are non-human experimental animals (e.g., mice, rats, dogs, pigs, or non-human primates such as apes or monkeys). In some embodiments, the subjects are livestock. In some embodiments, the subjects are humans. In some embodiments, the samples include tissue samples. In some embodiments, the tissue samples are biopsies (e.g., biopsies of bone, bone marrow, mammary gland, gastrointestinal tract, lung, liver, pancreas, prostate, brain, nerve, kidney, endometrium, cervix, lymph nodes, muscle, or skin). In some embodiments, the biopsies are tumor biopsies. Methods for treating diseases or disorders in a subject

[0117] In another aspect, this disclosure provides methods for treating a disease or disorder in a subject. For example, the spatiotemporal gene expression profiling method described herein can be performed on cells from a sample taken from a subject (e.g., a subject suspected of having a disease or disorder, or at risk of having a disease or disorder). The spatiotemporal expression of various metabolically labeled nucleic acids of interest in the cells can then be compared to the spatiotemporal expression of the same metabolically labeled nucleic acids of interest in cells from a non-disease tissue sample. If any changes are observed in the expression of the metabolically labeled nucleic acids of interest compared to the expression in non-disease cells, treatment for the disease or disorder can then be applied to the subject.

[0118] In some embodiments, a method for treating a disease or disorder in a subject includes the following steps: a) Cells from a sample taken from the subject are incubated for time t1 in the presence of a pool of nucleoside analogs to metabolically label the nucleic acids synthesized by the cells, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe in the population of first oligonucleotide probes, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe containing a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix; and i) If spatiotemporal changes in gene expression are observed compared to expression in cells from non-disease cells or non-disease tissue samples, the subject should be treated for the disease or disorder.

[0119] In some embodiments, the spatiotemporal expression of a target metabolically labeled nucleic acid in cells from non-disease cells or non-disease tissue samples can be simultaneously profiled as a control experiment. In some embodiments, the spatiotemporal expression profile of the target metabolically labeled nucleic acid in cells from non-disease cells or non-disease tissue samples includes reference data.

[0120] In some embodiments, multiple cells are analyzed simultaneously using the method described herein. In some embodiments, steps (a) to (h) are performed one or more times. By repeating steps (a) to (h) and incubating the pool of cells and nucleoside analogs together for various times in step (a), the expression of the metabolically labeled nucleic acid of interest, or multiple metabolically labeled nucleic acids of interest, can be observed over time, making it possible to profile the spatiotemporal expression of the nucleic acid of interest. In some embodiments, steps (a) to (h) are repeated at least once at different times t2. In some embodiments, steps (a) to (h) are optionally repeated during a third time t3, optionally during a fourth time t4, optionally during a fifth time t5, optionally during a sixth time t6, optionally during a seventh time t7, optionally during an eighth time t8, optionally during a ninth time t9, and tenth time t 10 This can be repeated as needed.

[0121] Any appropriate treatment for a disease or disorder can be administered to the subject. In some embodiments, the treatment includes administering a therapeutic agent. In some embodiments, the treatment includes surgery. In some embodiments, the treatment includes imaging. In some embodiments, the treatment includes performing further diagnostic methods. In some embodiments, the treatment includes radiotherapy. In some embodiments, the therapeutic agent is a small molecule, protein, peptide, nucleic acid, lipid, or carbohydrate. In some embodiments, the therapeutic agent (e.g., small molecule) is an anti-cancer agent. In some embodiments, the therapeutic agent (e.g., small molecule) includes a known drug. In some embodiments, the therapeutic agent (e.g., small molecule) includes an FDA-approved drug. In some embodiments, the small molecule includes a library of compounds. In some embodiments, the protein is an antibody. In some embodiments, the protein is an antibody fragment. In some embodiments, the protein is an antibody variant. In some embodiments, the protein is a receptor. In some embodiments, the protein is a cytokine. In some embodiments, nucleic acids are mRNA, antisense RNA, miRNA, siRNA, RNA aptamers, double-stranded RNA (dsRNA), short hairpin RNA (shRNA), or antisense oligonucleotides (ASOs). In some embodiments, nucleic acids are DNA.

[0122] Treatment of any disease or disorder is intended by the methods described herein. In some embodiments, the disease or disorder is a genetic disorder, proliferative disorder, inflammatory disorder, autoimmune disorder, liver disorder, spleen disorder, lung disorder, hematological disorder, neurological disorder, gastrointestinal (GI) tract disorder, genitourinary disorder, infection, musculoskeletal disorder, endocrine disorder, metabolic disorder, immune disorder, central nervous system (CNS) disorder, neurological disorder, ophthalmic disorder, or cardiovascular disorder. In some embodiments, the disease or disorder is cancer.

[0123] In some embodiments, the subject is human. In some embodiments, the sample includes a biological sample. In some embodiments, the sample includes a tissue sample. In some embodiments, the tissue sample is a biopsy (e.g., a biopsy of bone, bone marrow, breast, gastrointestinal tract, lung, liver, pancreas, prostate, brain, nerve, kidney, endometrium, cervix, lymph node, muscle, or skin). In some embodiments, the biopsy is a tumor biopsy. In some embodiments, the biopsy is a solid tumor biopsy. Oligonucleotide probes

[0124] This disclosure also provides oligonucleotide probes for use in the methods and systems described herein. In one aspect, this disclosure provides a plurality (i.e., a set) of oligonucleotide probes, including a first oligonucleotide probe (also referred herein as a “sprint” probe), a second oligonucleotide probe (also referred herein as a “primer” probe), and a third oligonucleotide probe (also referred herein as a “padlock” probe), where: i) The first oligonucleotide probe comprises a reactive chemical moiety; ii) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the nucleic acid of interest; and iii) The third oligonucleotide probe comprises a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe, and a second barcode sequence. Here, the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe.

[0125] All oligonucleotide probes described herein may optionally have spacers or linkers of varying nucleotide lengths between each of the enumerated components, or the components of the oligonucleotide probe may be directly bonded to one another. The reactive chemical portion of the first oligonucleotide probe may be any bioorthogonal functional group described herein or known in the art. In some embodiments, the chemical portion of the first oligonucleotide probe comprises an azide, alkyne, nitrone, alkene, tetrazine, or tetrazole. In some embodiments, the chemical portion of the first oligonucleotide probe comprises an azide. The first oligonucleotide probe may also comprise various other components. In some embodiments, the first oligonucleotide probe further comprises a polymerization blocker described herein. In some embodiments, the polymerization blocker is located at the 3' end of the first oligonucleotide probe. The polymerization blocker may be any chemical portion that prevents polymerase from using the first oligonucleotide probe as a primer for polymerization. In some embodiments, the polymerization blocker is a nucleic acid residue containing a blocked 3' hydroxyl group (e.g., containing an oxygen-protecting group on the 3' hydroxyl group). In some embodiments, the polymerization blocker comprises an inverted nucleic acid residue. In some embodiments, the polymerization blocker is an inverted adenosine, thymine, cytosine, guanosine, or uridine residue. In some embodiments, the polymerization blocker is an inverted thymine residue. In some embodiments, the first oligonucleotide probe further comprises a polyadenosine (poly-A) linker sequence. In some embodiments, the poly-A linker sequence is about 2 to about 100, about 10 to about 90, about 30 to about 70, or about 40 to about 60 nucleotides long. In some embodiments, the poly-A linker sequence is about 50 nucleotides long.

[0126] In some embodiments, the first oligonucleotide probe is about 30, 35, 40, 45, 50, 55, 60, 65, 70, or about 75 nucleotides long. In some embodiments, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is about 3–20, 4–19, 5–18, 6–17, 7–16, 8–15, 9–14, 10–13, or about 11–12 nucleotides long. In some embodiments, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is about 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or about 20 nucleotides long. In one embodiment, the portion of the first oligonucleotide probe complementary to the third oligonucleotide probe is approximately 12 nucleotides long. In some embodiments, the first oligonucleotide probe has the following structure: 5'-[Reactive chemical part]-[PolyA linker sequence]-[Part complementary to the third oligonucleotide probe]-[Polymerization blocker]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0127] The plurality of oligonucleotide probes disclosed herein also include second and third oligonucleotide probes. The second oligonucleotide probe comprises a barcode sequence consisting of a specific nucleotide sequence. In some embodiments, the barcode sequence of the second oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the barcode sequence of the second oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is greater than about 10 nucleotides long, greater than about 15 nucleotides long, or greater than about 20 nucleotides long. In one embodiment, the barcode sequence of the second oligonucleotide probe is 5 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is about 10 to 30, about 11 to 29, about 12 to 28, about 13 to 27, about 14 to 26, about 15 to 25, about 16 to 24, about 17 to 23, about 18 to 22, or about 19 to 21 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the target metabolically labeled nucleic acid is approximately 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30 nucleotides long. In some embodiments, the portion of the second oligonucleotide probe complementary to the target nucleic acid is 20 nucleotides long. In some embodiments, the second oligonucleotide probe is approximately 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, or 40 nucleotides long. In some embodiments, the second oligonucleotide probe is 32 nucleotides long. In some embodiments, the second oligonucleotide probe has the following structure: 5'-[Part complementary to the target nucleic acid]-[Barcode sequence]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0128] A third oligonucleotide probe used in the method described herein includes a first barcode sequence and a second barcode sequence, each consisting of a specific sequence of nucleotides. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is longer than about 10 nucleotides, longer than about 15 nucleotides, or longer than about 20 nucleotides. In some embodiments, the first barcode sequence of the third oligonucleotide probe is about 5 nucleotides long. In some embodiments, the second barcode sequence of the third oligonucleotide probe is about 1 to about 10 nucleotides long. In some embodiments, the second barcode sequence of the third oligonucleotide probe is about 5 to about 10 nucleotides long. In some embodiments, the barcode sequence is longer than about 10 nucleotides, longer than about 15 nucleotides, or longer than about 20 nucleotides. In some embodiments, the second barcode sequence of the third oligonucleotide probe is about 5 nucleotides long. The third oligonucleotide probe also includes a portion complementary to the first oligonucleotide probe. In some embodiments, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is split between the 5' and 3' ends of the third oligonucleotide probe. In some embodiments, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is about 3–20, about 4–19, about 5–18, about 6–17, about 7–16, about 8–15, about 9–14, about 10–13, or about 11–12 nucleotides long. In some embodiments, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is about 3, about 4, about 5, about 6, about 7, about 8, about 9, about 10, about 11, about 12, about 13, about 14, about 15, about 16, about 17, about 18, about 19, or about 20 nucleotides long.In one embodiment, the portion of the third oligonucleotide probe complementary to the first oligonucleotide probe is 12 nucleotides long (e.g., 6 nucleotides at the 5' end of the probe and 6 nucleotides at the 3' end of the probe). In some embodiments, the portion of the third oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is about 10–30, about 11–29, about 12–28, about 13–27, about 14–26, about 15–25, about 16–24, about 17–23, about 18–22, or about 19–21 nucleotides. In some embodiments, the portion of the third oligonucleotide probe complementary to the metabolically labeled nucleic acid of interest is approximately 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, or longer than 30 nucleotides. In some embodiments, the third oligonucleotide probe has the following structure: 5'-[First part complementary to the first alkyl group probe]-[First barcode sequence]-[Part complementary to the target nucleic acid]-[Second barcode sequence]-[Second part complementary to the first alkyl group probe]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker).

[0129] In some embodiments, the oligonucleotide probes further include a fourth oligonucleotide probe. In some embodiments, the fourth oligonucleotide probe includes a sequence complementary to the second barcode sequence of the third oligonucleotide probe (i.e., the complementary sequence is the same length as the second barcode sequence of the third oligonucleotide probe as defined herein). In some embodiments, the second barcode sequence of the third oligonucleotide probe is a gene-specific sequence used to identify the nucleic acid of interest (e.g., RNA such as nascent RNA or mRNA). In some embodiments, the fourth oligonucleotide probe includes a fluorophore. In some embodiments, the fluorophore is attached to the 5' end of the fourth oligonucleotide probe. In some embodiments, the fluorophore is attached to the 3' end of the fourth oligonucleotide probe.

[0130] In another aspect, the Disclosure provides an oligonucleotide probe comprising a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion complementary to an additional oligonucleotide probe, and a second barcode sequence. In some embodiments, the first barcode sequence is complementary to a barcode sequence on the additional oligonucleotide probe. In some embodiments, the lengths of the various components of the probe described herein are the same as those of the third oligonucleotide probe described herein.

[0131] In some embodiments, the first barcode sequence of the oligonucleotide probe is approximately 1 to 10 nucleotides long. In some embodiments, the first barcode sequence of the oligonucleotide probe is 5 to 10 nucleotides long. In some embodiments, the barcode sequence is longer than approximately 10 nucleotides, longer than approximately 15 nucleotides, or longer than approximately 20 nucleotides. In one embodiment, the first barcode sequence is 5 nucleotides long. In some embodiments, the second barcode sequence of the oligonucleotide probe is approximately 1 to 10 nucleotides long. In some embodiments, the second barcode sequence of the oligonucleotide probe is 5 to 10 nucleotides long. In some embodiments, the barcode sequence is longer than approximately 10 nucleotides, longer than approximately 15 nucleotides, or longer than approximately 20 nucleotides. In one embodiment, the second barcode sequence is 5 nucleotides long. In some embodiments, a portion of the oligonucleotide probe complementary to an additional oligonucleotide probe is split between the 5' and 3' ends of the oligonucleotide probe. In one embodiment, the oligonucleotide probe has the following structure: 5'-[First part complementary to the first alkyl group probe]-[First barcode sequence]-[Part complementary to the target nucleic acid]-[Second barcode sequence]-[Second part complementary to the first alkyl group probe]-3' This includes, where ]-[ comprises any nucleotide linker. Each example of any nucleotide linker may independently be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 nucleotides long. In some embodiments, ]-[ comprises any non-nucleotide linker (e.g., a chemical linker or a peptide-based linker). kit

[0132] Kits are also encompassed in this disclosure. In one aspect, a kit provided may comprise one or more oligonucleotide probes as described herein. In some embodiments, a kit may further comprise a container (e.g., vials, ampoules, bottles, and / or dispenser packages, or other suitable containers). In some embodiments, a kit comprises either a plurality (i.e., a set) of oligonucleotide probes or a single oligonucleotide probe as described herein. In some embodiments, a kit comprises a plurality of plurality of oligonucleotide probes or a plurality of single oligonucleotide probes as described herein, where each of the plurality of oligonucleotide probes or single oligonucleotide probes is used to profile the spatiotemporal gene expression of a separate metabolically labeled nucleic acid of interest. In some embodiments, a kit comprises more than one, two, three, four, five, ten, twenty, thirty, forty, fifty, 100, 200, 30, forty, fifty, 1000, 200, 500, or more than 1000 of the plurality of oligonucleotide probes or single oligonucleotide probes disclosed herein. In some embodiments, the kit further comprises other reagents for carrying out the methods disclosed herein (e.g., cells; a pool of nucleoside analogs, where each nucleoside analog in the pool of nucleoside analogs comprises a reactive chemical moiety as further described herein; ligases; polymerases; amine-modified nucleotides; and / or reagents for creating polymer matrices (e.g., polyacrylamide matrices)). In some embodiments, the kit is useful for profiling spatiotemporal gene expression in cells. In some embodiments, the kit is useful for profiling the role of post-transcriptional modifications in spatiotemporal gene expression. In some embodiments, the kit is useful for studying the role of spatiotemporal gene expression in the onset or progression of disease or disorder. In some embodiments, the kit is useful for screening drugs that can modulate spatiotemporal gene expression.In some embodiments, the kit is useful for diagnosing a disease or disorder in a subject. In some embodiments, the kit is useful for treating a disease or disorder in a subject. In some embodiments, the kit described herein further includes instructions for use of the kit.

[0133] Spatiotemporal gene expression profiling system This disclosure also provides a system for profiling spatiotemporal gene expression in cells. In some embodiments, the system comprises: a) cells; b) a pool of nucleoside analogs, where each nucleoside analog in the pool comprises a reactive chemical moiety; c) a population of first oligonucleotide probes, where each first oligonucleotide probe in the population comprises a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; and d) one or more pairs of oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe contains a barcode sequence and a portion complementary to the nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion of the first oligonucleotide probe in the group of first oligonucleotide probes complementary to the first oligonucleotide probe, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe.

[0134] In some embodiments, the system further includes a microscope (e.g., a confocal microscope). In some embodiments, the system further includes a computer. In some embodiments, the system further includes a CPU. In some embodiments, the system further includes computer storage and / or memory. In some embodiments, the system further includes a camera. In some embodiments, the system includes software for performing microscopic examination and / or image analysis. In some embodiments, the system further includes a ligase. In some embodiments, the system further includes a polymerase. In some embodiments, the system further includes an amine-modified nucleotide. In some embodiments, the system further includes reagents for creating a polymer matrix (e.g., a polyacrylamide matrix). Cells in the system of this disclosure may be any of the cell types disclosed herein. In some embodiments, the system includes multiple cells. In some embodiments, the cells are of different cell types. In some embodiments, the cells are present in a tissue. In some embodiments, the tissue is a tissue sample provided by or from a subject. In some embodiments, the subject is human.

[0135] example Example 1: Nascent RNA labeling chemistry for spatiotemporal decomposition transcriptomics The importance of understanding how cells regulate their activity and respond to environmental stimuli within their spatial context is increasingly recognized. Indeed, biological tissues are composed of a vast number of spatially confined cells that work in coordination to perform specific functions and control their activity. The position of cells within an organism or tissue influences their differentiation and activity, and similarly, the landscape of heterogeneous cells contributes to the specific development and physiological state of the tissue.

[0136] Rapid advances in the study of cell organization in tissues and multicellular organisms began with the development of transcriptome sequencing techniques, or RNA-seq, which enabled comprehensive detection and quantification of mRNA in pooled cells. Single-cell RNA sequencing (scRNA-seq) facilitated the evaluation of the transcriptome of individual cells, enabling inferences about biological differences between cell types. More recently, spatially degraded transcriptome methods have taken this a step further, investigating the transcriptome of single cells while preserving their intracellular spatial context. Image-based methods such as STARmap demonstrate their advantages by detecting the three-dimensional location of cells through sequential imaging, a crucial element for analyzing tissues, organoids, and organs. Large consortia such as the Human Cell Atlas and the Brain Initiative Cell Census Network are leveraging spatial transcriptomes to create a comprehensive reference “map” of diverse cell types in human tissues as a foundation for understanding life, health, and disease.

[0137] In addition to understanding how tissues are structured by functionalized cell types, the spatial organization of biomolecules within cells is equally, if not more, crucial to understanding cellular function and tissue physiology. Spatial separation of proteins creates a compartmentalized cellular environment, contributing to the effective and orderly function of cells. Such heterogeneous organization of proteins also requires spatial control of mRNA and localized protein translation to ensure fidelity of interactions and thermodynamic efficiency. Known examples of intracellular localization of mRNA in animal cells include those observed in fibroblasts, neurons, oligodendrocytes, muscle cells, and cardiomyocytes, suggesting a recurring theme of asymmetric distribution of RNA in cell biology. Furthermore, strong evidence of asymmetric mRNA distribution and on-site protein synthesis allows for the separation of transcription and translation, demonstrating the critical role of mRNA location in cellular function. Since protein synthesis is often performed multiple times as needed, fine-tuning of mRNA processing in a time-dependent manner, in addition to localization, is prevalent. Notable examples include mRNA transport and trafficking in neuronal and embryonic development. Therefore, it is essential to study not only the overall cellular organization within tissues, but also specific compartmentalized activities within each cell type. Consequently, understanding the spatiotemporal regulation of mRNA, RNA-protein interactions, and protein synthesis at the intracellular level is crucial to revealing how cells differ from one another.

[0138] Nevertheless, most spatial transcriptome strategies still examine at the pancellular level, tracking and identifying single cells, but do not investigate the spatial information of mRNA in the intracellular environment. Even attempts to investigate deeper at the intracellular level, the current state-of-the-art techniques in this field only provide a snapshot of mRNA localization in the steady state of the cell, obscuring the highly regulated balance between transcription and transcript turnover. Because the dynamics of intracellular mRNA location have far-reaching implications, from a fundamental understanding of cell biology to distinguishing between healthy and diseased states, there is an urgent need for time-resolved spatial sequencing methods that track mRNA migration within a single cell from birth to death to accurately profile gene expression over defined time periods.

[0139] One promising approach to capturing RNA dynamics is through metabolic labeling. Transcriptome metabolic sequencing using nucleotide analogs allows for the selective labeling of nascently transcribed RNA. Using 4-thiouridine (4SU), 5-bromouridine (5BrU), 5-ethynyluridine (5-EU), and adenosine analogs, various chemical handles can be incorporated into labeled RNA, which can then be further enriched and isolated from unlabeled transcripts by various means. These approaches enable monitoring of temporal changes in gene expression and characterization of nascent transcript dynamic parameters. Specifically, 5-EU labeled RNA can be captured and classified by click chemistry, demonstrating significant potential for achieving bioorthogonality and a high signal-to-noise ratio in the chemical processing of cells.

[0140] By incorporating metabolic labels into spatial transcriptomics, TEMPOmap( temp orally resolved in situ sequencing and mapTEMPOmap (a method for time-resolved insitu sequencing and mapping) has been developed. TEMPOmap is a novel method for degrading the nascent transcriptomics of a single cell in the time dimension. Therefore, it is possible to create a "4D map" of RNA within one or more cells (Figure 1). This method is based on hydrogel histochemistry, DNA barcoding, and a two-nucleotide sequencing scheme (SEDAL sequencing). It includes metabolic labeling, DNA-RNA proximity ligation, and a three-part DNA probe design, enabling highly efficient and low-background selective capture of nascent transcripts. Because TEMPOmap can provide spatial, temporal, and single-molecule information about RNA on a whole-transcriptome scale, it is possible to visualize the intracellular localization of nascent transcripts. Similar to other spatial transcriptome methods, TEMPOmap can be used to identify heterogeneity within a single cell and map it to structured tissue. Therefore, this method provides a more detailed description of single-cell state and intracellular function by enabling the elucidation of genome-scale mRNA synthesis and degradation rates and the simultaneous observation of spatial migration constraints of these transcripts over tunable periods.

[0141] The initial demonstration of TEMPOmap elucidated the dynamics of the nascent transcripts in HeLa cells and the observed target transcriptome, revealing the common epitranscriptome modification N6-methyladenosine (m 6 This was done by linking it to A). TEMPOmap also makes it possible to study the biochemical basis of neuroscience, as neurons have an elaborate structure that requires mRNA transport and dispersed protein synthesis. Using this method, we can determine how neurons adapt and change in response to environmental stimuli in terms of RNA localization, RNA-protein interactions, and local translation. TEMPOmap is a versatile platform that can be used to understand how gene expression is dynamically handled in many different cell and tissue types and to determine the broad effects of post-transcriptional regulation.

[0142] Design and principle of the TEMPOmap method. To demonstrate selective and efficient capture of nascent RNA, HeLa cells were exposed to the nucleoside analog 5-EU to create chemical handles on labeled transcripts (Figure 2A). Next, azide-modified DNA oligos, or DNA "sprints," were designed and incubated with permeabilized cells, and covalently attached to labeled mRNA via copper(I)-catalyzed azide-alkyne cyclization (CuAAC). This bioorthogonal DNA-RNA conjugation ensures selective modification of nascent transcribed RNA, preventing detection of transcripts lacking alkyne functional groups. Next, a library of primer-padlock pairs targeting the exon region of mRNA was designed. When the primer and padlock hybridized to the target mRNA, the 5' phosphorylated padlock was cyclically linked to the RNA only if the sprint was in close proximity on the same mRNA. Furthermore, to overcome autofluorescence and scattering in most fluorescence in situ hybridization (smFISH) experiments, in situ enzymatic reactions were performed to amplify the padlock sequence as a template. This further reduced nonspecific hybridization of single probes by utilizing primer-padlock pairs targeting the same gene, enabling rolling cycle amplification (RCA) only when the primer and padlock independently hybridized to the same RNA, resulting in cDNA nanoball (amplicon) formation. Thus, using this three-part DNA probe design (sprint, primer, and padlock), time- and sequence-controlled transcript amplification was achieved via a two-step thresholding strategy (Figure 2c).

[0143] During RCA, amine-modified nucleotides were added to the amplification reaction to functionalize the amplicons with amine groups. Next, acrylamide functional groups were chemically added to the amine amplicons using N-hydroxysuccinimide methacrylate (MA-NHS). To preserve the physical location of the endogenous transcript, a DNA hydrogel hybrid was created by crosslinking the acrylamide-modified amplicons with hydrogel monomers during polymerization, immobilizing the amplicons on the hydrogel network. This hybrid constructs a molecular scaffold that allows for the removal of unamplified RNA and DNA probes while retaining the chemically conjugated amplicons. Furthermore, sample stability was significantly improved, enabling subsequent high-resolution imaging. Finally, each padlock had a unique barcode encoded on both sides; one side was used for orthogonal sequence recognition with the respective primers, and the other side was used for sequential base reading and decoding by SEDAL sequencing, achieving highly multiplexed detection of single-cell transcriptomes.

[0144] This method was combined with pulse-chase experiments. RNA encoding approximately 1000 genes was captured after different chase periods and traced for spatiotemporal trajectory reconstruction by integrating their positions at different time points (Figure 2B). This method demonstrated enrichment of metabolically labeled transcripts (Figure 2D) and reliable detection of changes in gene expression over tunable time courses (Figure 2E). Considering the application of a rigorous two-step thresholding principle, this approach further demonstrated that near genome-wide transcriptome readout can be achieved with a high signal-to-noise ratio.

[0145] 3-Part DNA Probe Design. The sequence design for the 3-part DNA probe used in TEMPOmap is shown in Figure 3. The 3-part probe consists of a DNA sprint probe, a primer probe, and a padlock probe. The sprint is divided into two regions: a poly-A linker and a sprint-padlock annealing region. The poly-A linker contains 50 adenosine nucleotides, which provides the sprint with sufficient length to reach the nearby padlock. The sprint-padlock annealing sequence enables hybridization of the sprint and padlock, creating a double-stranded DNA region with a sealable "nick" in the ligation step. The 5' phosphorylated padlock consists of the sprint-padlock annealing region, two regions of the same barcode, a primer-padlock annealing region, a 20nt hybridization sequence targeting the mRNA of interest, and several short linkers. Upon ligation, the padlock becomes circular and serves as a DNA template for in situ enzymatic amplification. The primer contains a gene-specific region that is inversely complementary to the barcode of the matching padlock, a 4-nucleotide sequence also complementary to the padlock, and a 20nt hybridization sequence that targets mRNA. The two 20nt hybridization regions on the primer and padlock are located 1-2 nucleotides adjacent to each other on the mRNA. When the primer and padlock bind, the primer acts as an amplification initiator, amplifying the padlock sequence to generate a cDNA amplicon.

[0146] To validate the enrichment of the labeled probe-targeted gene, a negative control condition was compared to a test condition targeting only human β-actin mRNA (ACTB). As shown in Figure 2D, HeLa cells pulsed at 5-EU for 15 hours and treated according to the TEMPOmap design showed high fluorescence intensity of quantized amplicon signals, most of which were located around the cell periphery. This clear trend of RNA localization reflects the endogenous function and location of the β-actin protein as part of the cytoskeleton and also demonstrates localized translation of the human ACTB gene. In contrast, controls without 5-EU labeling, sprinting, or matching primer-padlock pairs showed little to no signal. The signal-to-noise ratio of the 5-EU labeled signal to the unlabeled signal demonstrated significant enrichment of the labeled nascent transcript.

[0147] Based on the discovery of ACTB mRNA in the periphery of HeLa cells, this method was tested for its ability to capture the dynamics of mRNA nuclear export and migration under different pulse and chase time progressions. Therefore, in HeLa cells, newly synthesized RNA was pulse-labeled with 5-EU for 1 hour, and the cells were washed for various time periods (Figure 1D, left). TEMPOmap was then applied to detect the migration of ACTB transcripts over varying wash times. The images clearly showed the trajectory of nuclear export from the nucleus to the cytoplasm (Figure 1D, right). Thus, it was concluded that this method is indeed capable of capturing and enriching nascent transcripts and detecting the migration and dynamics of these RNAs.

[0148] Example 2: RNA m 6 A-methylation profiling mRNA in higher eukaryotes is extensively modified during gene expression through important post-transcriptional regulation. Among these diversely modified nucleotides, N6-methyladenosine (m 6 A) is the most common internal mark on eukaryotic transcripts. 6 The functions and characteristics of A are gradually being elucidated. 6Recognizing the motif of part A 6 RNA-binding proteins such as those in the "readers" group have been discovered, providing valuable insights into the molecular mechanisms of RNA regulation.

[0149] m 6 One class of A leaders includes the YTH domain family 1-3 (YTHDF1-3) and YTH domain-containing 1-2 (YTHDC1-2). Despite their common evolutionary relationships and similar RNA substrates, the biological functions of each of these proteins are unique. For example, YTHDF2 regulates the stability of target RNA by attracting it to the cell's RNA decay site; YTHDF1 promotes mRNA translation by recruiting translation factors; YTHDF3 is suggested to function in conjunction with YTHDF1-2 to promote both RNA degradation and translation. In contrast, YTHDC1 promotes nuclear export and mRNA splicing by interacting with splicing factors and nuclear export adapter proteins, while YTHDC2 plays a crucial role during spermatogenesis. 6 Leader A works collaboratively to achieve multi-layer adjustment, m 6 Fine-tune the phenotypic results of A-modified transcripts.

[0150] m 6 The relationship between the regulation of A-modified mRNAs and their spatial location within cells has not been systematically studied. Since RNA function is strongly related to its cellular localization and trafficking, we investigated whether TEMPOmap could provide further insights into the molecular mechanisms of epitranscriptome regulation. For this purpose, we used 1000 m 6 A list of A-processing-related genes was carefully selected, from which targeted primers and padlock probes were designed, and their spatiotemporal dynamics were detected and profiled using TEMPOmap. This approach was used to analyze RNA metastasis in spatiotemporal space. 6This provides an image-based explanation of A methylation processing and reveals the complex network that modulates this post-transcriptional modification.

[0151] The list of 1000 genes includes m 6 The list included RNAs with extremely high or low A abundances, and genes encoding RNAs reliably recognized by YTHDF1-3 and YTHDC1-2. This list also included m 6 The study also includes genes involved in A processing (addition, recognition, removal, etc.). Furthermore, it includes genes that function as intracellular location markers to support RNA localization analysis, and genes that are active during the cell cycle to support cell visualization at different time stages. In addition to the studies of the above genes in wild-type HeLa cells, YTHDF1-3, YTHFC1-2, and m 6 Seven genes were independently knocked down by treating cells with short interfering RNAs (siRNAs) targeting A-writers METTL14 and METTL3; this installs methylation into the RNA. The in situ expression of these 1000 genes was then compared in control and knockdown samples to capture changes in transcription and post-transcriptional in situ profiling. Confirmed by the independent roles of METTL14 / 3, YTHDF1-3, and YTHDC1-2, it was hypothesized that mRNA transport and trafficking should be more or less affected by gene knockdown.

[0152] To validate the efficiency of gene knockdown using these siRNAs, an initial test was performed using STARmap to detect the expression (or lack thereof) of siRNA target genes, and this test was compared to untreated wild-type cells. Each well of cultured cells was initially treated with one type of siRNA, and after the cells grew for two days, all cells were pooled together in one well and grown overnight. The STARmap protocol was then applied to detect the expression of seven genes in single cells using two rounds of in situ sequencing. Eight distinct clusters of HeLa cells were discovered after gene expression analysis; seven clusters represented YTHDF1-3, YTHDC1-2, and METTL14 / 3 knockdown cells, and one cluster was untransfected with siRNA (Figure 4). This method can be extended to profile the gene expression of 1000 genes when treated with the same group of siRNAs.

[0153] After confirming the success of siRNA transfection, knockdown experiments for seven genes (and control siRNA transfection) were repeated in HeLa cells. Six hours after transfection, eight cell populations were pooled together and equally divided into six groups. One group was then labeled with 200 μM 5-EU for approximately 15 hours before fixation. The following day, the remaining five unlabeled cell groups were incubated with 200 μM 5-EU for 1 hour each, and then replaced with fresh medium (containing 200 μM 5-EU) for 0, 1, 2, 4, and 6 hours, respectively. Subsequently, TEMPOmap was performed, and the experiment was scaled to detect 1000 genes. Raw images of SEDAL sequencing were collected.

[0154] After collecting raw images from six cell populations processed with pulse chases of different lengths, the images were first preprocessed using a computational workflow (Figure 5) to extract reads and quantify detected genes. Next, multilayer information within the data was analyzed. TEMPOmap is the first experimental method to enable spatiotemporally decomposed, multiplexed in situ RNA detection.

[0155] The data analysis is divided into two layers: analysis of RNA in undisturbed cells only, and analysis of RNA changes in cells with gene knockdown. In the first layer, RNA migration and half-life changes are examined by comparing the location and quantification of RNA reads at various time points. Pulse chase data are also compared with 15-hour labeled data representing steady-state RNA in the cell. Next, gene enrichment is examined in specific intracellular regions at a given time point, and / or the mobility / immobility of RNA to different intracellular regions. Interesting gene co-localization or co-migration can also be used to analyze the data. Similarly, RNA half-life or degradation rate can be calculated to further investigate the specific relationship between half-life and location. Similarly, it is possible to determine whether migration to a specific intracellular region is related to the length of the half-life, or whether the migration rate itself is related to the half-life. Subsequently, it is analyzed whether a specific group of RNAs sharing similar activity or behavior is enriched with GO term, or whether different "clusters" of RNA have different biochemical roles, and from there m 6 More detailed mechanistic studies of the A processing pathway will be conducted from the perspective of RNA localization.

[0156] In the second layer, the analysis of undisturbed cells from the first layer was combined with the analysis of gene knockdown cells, m 6 Investigate whether either the A writer or reader is involved in RNA intracellular trafficking, localization, and / or stability. It has been well-established that YTHDF1 promotes ribosome occupancy of target mRNA and YTHDF2 affects RNA stability, and these observed causal relationships can likely be partially explained by yet-to-be-discovered spatial and trans-localization of RNA. In addition to looking for changes induced by knockdown of specific genes, m 6 Suppression of any gene along the A processing pathway may also cause universal changes in the spatial transcriptome profile.

[0157] This example is m 6 This study demonstrates the analysis of mRNA levels, half-lives, and translocations of up to 1000 genes related to metabolism. This method can be used to study any biological phenomenon influenced by the spatial context of biomolecules and the morphological context of cells, beyond post-transcriptional modifications.

[0158] Example 3: Visualization of RNA in neurons and intact 3D tissue. TEMPOmap can also be applied to solve important problems in neuroscience. Because neuronal axons and dendrites extend into space up to tens of millimeters away from the cell body, the fact that the proteome in these regions senses stimuli and responds without delay is highly noteworthy. TEMPOmap can be used to visualize neuronal mRNA transport and distal RNA-protein interactions. TEMPOmap can be applied to cultured neurons, and its workflow can be optimized for treating intact tissue. TEMPOmap has enabled the uniform detection of tissue 100 microns thick, equivalent to 10 layers of cells. TEMPOmap can be used on mouse brain slices when treating mice with external stimuli.

[0159] To demonstrate the capabilities of TEMPOmap in neurons, the current experimental workflow can be applied to fixed neuron cultures, and initial tests can be performed to detect only ACTB mRNA. Neurons can be stimulated with KCl, and pulse-chase experiments can be performed after KCl stimulation. TEMPOmap probes targeting the most highly expressed, regulated genes after neuronal stimulation can be used to test the capture of the dynamics of these genes. Genome-wide CRISPR screening can be performed in neurons, and approximately 1000 gene probes targeting mRNA trafficking, RNA-protein interactions, and local translation can be designed to systematically provide image-based studies of the mechanisms of RNA remote transport and translation. Furthermore, epitranscriptome processing at synapses can also be investigated. The use of TEMPOmap can provide greater insight into the relationship between mRNA processing and neuronal activity, such as synapse formation and experience-dependent plasticity.

[0160] Alternatively, since RNA dynamics is also important for tissue physiology, the TEMPOmap experimental workflow can be optimized to realize the possibility of 3D in situ sequencing. Thus, leveraging the advantages of spatial transcriptomics, this method distinguishes and classifies cells from a new dynamic perspective and enables cell mapping to tissues. Individual chemical and enzymatic steps within the workflow can be modified to make them compatible with 3D visualization.

[0161] Example 4: Spatiotemporal resolution of transcriptomics at subcellular resolution Gene expression is dynamically regulated across multiple steps of the RNA lifecycle: transcription, processing, nuclear export, translation, and degradation. Understanding gene regulatory mechanisms in functionally diverse cell types within multicellular organisms requires the measurement of cell type-specific RNA localization and kinetics. Single-cell RNA sequencing (scRNA-seq) techniques have enabled transcriptome measurements at the single-cell level, redefining cell types through transcriptome profiles. Recent developments in spatial transcriptome methods have further enabled the simultaneous counting of cellular transcripts and the tracking of their spatial information in situ for spatially degraded molecular cell typing within the context of tissue structure. 1~11 In parallel, single-cell metabolic labeling experiments revealed that isolating the nascent transcriptome from existing RNA is necessary to identify the RNA metabolic program and immediate regulatory changes in response to external stimuli. 12 .

[0162] However, an integrated method for simultaneously measuring the spatial localization of RNA and the dynamics of RNA biosynthesis, nuclear export, and degradation at the transcriptome scale still does not exist, limiting our ability to understand the dynamic regulatory schemes triggered by development, environment, metabolism, and pathological signals.

[0163] To bridge this technological gap, spatiotemporal-resolved transcriptome methods were developed. Previously, a method for reading and mapping spatially-resolved transcript amplicons (STARmap, Figure 6A) was developed. 1 A system was developed in which chemically functionalized cDNA amplicons were covalently bound to a polyacrylamide matrix, enabling precise tissue removal and biomolecule processing. This example describes the addition of a time dimension to STARmap. mRNA is metabolically labeled with chemically modified polymerizable nucleosides, and the modified transcripts are directly bound to the polymer matrix.

[0164] The current STARmap protocol covalently binds acrylate-modified DNA amplicons to a polyacrylamide hydrogel matrix, but this crosslinking method has been shown to have limited mRNA retention capabilities. In this example, metabolically labeled RNA was directly bound to the hydrogel. This method provides a solution to improve crosslinking efficiency and preferentially binds labeled RNA, which is suitable for pulse-chase experiments for time-course sample analysis. 12 It is compatible with (Figure 6B, t-STARmap). The mRNA is first metabolically labeled with 5-EU, and the labeled transcript is crosslinked with a polyacrylamide hydrogel via a two-step synthesis involving click chemistry. This synthetic scheme consists of high-yield reactions commonly found in bioorthogonal labeling strategies, assisting the modified RNA to bind to the acrylamide gel via acrylate groups at the linker ends. The acrylate groups are involved in the free-radical polymerization of the polyacrylamide matrix and act as links to lock the RNA onto the polyacrylamide hydrogel during polymerization. Since the chemical reaction provides efficient RNA-hydrogel crosslinking, further specified RNA molecules can be visualized by STARmap.

[0165] Next, pulse and chase experiments (Figure 2B) are performed using mammalian cell cultures and animal models. The data is then analyzed to further computationally reconstruct the spatiotemporal trajectories of individual RNAs within the cells. The t-STARmap method can be used to study important biological problems such as changes in cellular state in response to stimuli (cell cycle, neural activity, viral infection, etc.) and cell type-specific gene regulatory programs in functional organelles.

[0166] Example 5: Further use of nascent RNA labeling chemistry for spatiotemporal decomposition transcriptomics This example describes a novel image-based in situ RNA sequencing method that provides a system for detecting and quantifying genetic and metabolic activity in single cells and constructs a platform for understanding the composition and changes in cell type, cellular state, and intercellular interactions in tissues and organs. This technique provides high-throughput, multimodal "omics" information on target cellular activity by offering spatial and temporal resolution for single-cell RNA sequencing.

[0167] In situ RNA hybridization and sequencing methods have been invented and developed, providing tools to reveal genome-wide profiling of gene expression in single cells and to significantly accelerate our ability to understand disease. However, there remains an urgent need to measure and predict RNA synthesis, transport, and turnover in single cells in order to profile gene expression over a specific time frame. The methodology described here is unique in its ability to provide spatial, temporal, and single-molecule information about RNA in a high-throughput manner. Proximity ligation of DNA transcripts is used in conjunction with metabolic labeling, DNA barcoding, and SEDAL sequential sequencing. 1 It is combined with various existing biotechnology tools, such as those mentioned above.

[0168] Readout mapping of spatially resolved transcript amplicons (STARmap) 1A method has been developed that is a reliable in situ transcriptome tool for spatial mapping of gene expression. This example describes an alternative method that not only visualizes the transcriptome of a single cell but also tracks changes in the transcriptome over time. This strategy (Figure 7) is achieved by metabolically labeling mRNA with the chemically modified nucleoside 5-ethynyluridine (5-EU) and ligating the labeled mRNA with an azide-modified DNA primer via copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC). This RNA-primer crosslinking event is then recognized by a padlock probe that hybridizes to the mRNA and amplified by rolling-cycle amplification. The amplified signal is then retained within a hydrogel scaffold. Gene-specific identifiers are encoded in each padlock probe, and the mRNA identity is visualized and decoded by SEDAL sequencing.

[0169] This approach will achieve near genome-wide transcriptome enrichment and selective retention of metabolically labeled transcripts, enabling reliable detection of changes in gene expression over specific timeframes. Targeting of the human β-actin gene (hACTB) in HeLa cells is shown in Figure 8; this demonstrates significant enrichment of the retained transcript compared to 5-EU unlabeled transcripts and the ability to detect the transcript over various timeframes.

[0170] RNA dynamics have been shown to influence RNA processing, translation, and degradation, particularly N6-methyladenosine (m6), a rich epitranscriptome mark. 6 The presence or absence of A) was also quantified. The effect of this RNA modification was studied by detecting the dynamics of four representative RNAs, two of which were m 6 It includes A, but the other two are m 6It does not contain A (Figure 9). It was demonstrated that four genes represented in four colors in the image were detected simultaneously. The image-based measurement of RNA degradation reasonably correlates with the RNA half-life measured previously using next-generation sequencing, and the image clearly shows the tendency of RNA translocation for all four RNAs.

[0171] Example 6: Spatiotemporal resolved single-cell transcriptomics reveals kinetic sculpting of the RNA life cycle The spatiotemporal regulation of the cellular transcriptome is important for directing protein expression to the ultimate execution of cellular functions. The complex intracellular dynamics such as RNA synthesis, decay, nuclear export, and translocation are obscure due to the limitations of existing transcriptomic methods. Methods for time-resolved in situ sequencing and mapping (TEMPOmap) are described herein. This method represents a highly multiplexed three-dimensional in situ mapping technique that reveals intracellular gene expression over time and space in single cells. Using TEMPOmap, important kinetic parameters of thousands of genes were determined throughout the RNA life cycle of human cells, and the multistage kinetic shaping of gene expression in the context of gene function, intracellular organization, and cell cycle progression was revealed. These spatiotemporal resolved transcriptomic measurements deepen the understanding of how regulatory strategies enable precise gene expression in time and space through kinetic sculpting.

[0172] Introduction Cell states and functions are shaped by the spatiotemporally heterogeneous regulation of gene expression. The ability to systematically profile the information of the entire transcriptome resolved at the single-cell level over time and space is important for understanding transcriptional and post-transcriptional gene regulatory mechanisms in cells and tissues. Spatiotemporal resolved transcriptomic methods have enabled the integrated profiling of gene expression from heterogeneous cell types in the context of tissue morphology. 13~19However, these spatial transcriptomics approaches only provide static snapshots of cells and tissues, obscuring the dynamic flow of gene expression. 20 In contrast, the RNA metabolic labeling approach has enabled profiling of the nascent single-cell transcriptome, but it lacks spatial information. 21~25 Furthermore, while imaging living cells allows for direct tracking of RNA trajectories within cells, simultaneously visualizing multiple transcripts remains challenging. 26 Therefore, there is an urgent need for a time-resolved, highly multiplexed spatial mapping method to profile gene expression, which tracks nascent mRNA in situ with subcellular and single-cell resolution from birth to death.

[0173] To provide single-cell analysis of the entire RNA lifecycle system in time and space, TEMPOmap (time-resolved in situ sequencing and mapping) was developed, a method for tracking the spatiotemporal evolution of nascent transcriptomics over time at subcellular resolution (Figure 10A). TEMPOmap integrates time-gated metabolic labeling and selective amplification of the nascent transcriptome with state-of-the-art three-dimensional (3D) in situ RNA sequencing within a hydrogel-cell scaffold at a resolution of 200 nm. 13 By designing precisely controlled pulse-chase labeling experiments, a complete collection of dynamic parameters for thousands of genes throughout their RNA lifecycle, including transcription rate, disintegration within intracellular regions, nuclear export, and cytoplasmic translocation, was traced simultaneously for the first time. In light of these spatiotemporal parameters, the mRNAs of various genes were found to be kinetically classified at different stages of the RNA lifecycle and across different cell cycle phases, ultimately contributing to molecular and cellular function.

[0174] TEMPOmap for spatiotemporal decomposition transcriptomics TEMPOmap begins with metabolic labeling of cells with 5-ethinyluridine (5-EU). 25,27This adds a bioorthogonal chemical handle to the labeled mRNA (Figure 10B). Next, three probe sets (sprint, padlock, and primer) were designed for each gene to selectively generate complementary DNA (cDNA) amplicons derived from metabolically labeled RNA (Figures 10B-10C and 14B-14C): (1) The sprint probe is an azide and chain terminator-modified DNA oligonucleotide that covalently binds to 5-EU labeled mRNA via copper(I)-catalyzed azide-alkyne cyclization (CuAAC, Figure 14A), thus excluding unlabeled RNA from subsequent cDNA amplification; (2) The padlock probe recognizes 20-25 nucleotide (nt) cDNA sequences and mRNA targets with gene barcodes, which can be cyclized when the sprint probe is nearby; (3) The primer probes target adjacent 20-25 nts next to the padlock probe, which function as primers for in situ amplification of the cyclized padlock via rolling cycle amplification (RCA), and standard fluorescence in (4) Form cDNA nanoballs (amplicons) that overcome autofluorescence and scattering in situ hybridization (smFISH); and in combination, only mRNAs to which all three probes bind are amplified in a labeling and sequence-controlled manner via a two-step thresholding strategy for selective detection of the labeled mRNA population (Figure 10C-10D).

[0175] Of note is that the initially designed two-probe set recognizes 5-EU labeled RNA via one gene-targeting padlock probe and one general azide-modified probe, without a chain terminator that plays a dual role as sprint and primer (Figure 14B). However, the two-probe design results in a strong background signal from the amplicon (Figure 14B), suggesting that a single gene-targeting padlock probe achieves less specific gene detection, and that a dual gene-targeting primer and padlock pair in the three-probe design may be ideal in some situations. 13The TEMPOmap protocol was observed to specifically enrich metabolically labeled transcripts (Figure 10D) and reliably detect changes in the intracellular localization of β-actin mRNA (ACTB) over a controllable time course (Figure 14D).

[0176] The in situ-generated cDNA amplicon library was then embedded in a hydrogel matrix for multiple cycles of fluorescence imaging, and the gene-encoding barcode was decoded via SEDAL (Sequencing with Dynamic Annealing and Ligation Error Reduction) (Figures 10B and 14C). 13 This allows for the simultaneous detection of hundreds to thousands of genes. After the sequencing cycle is complete, the amplicon reads are then registered, decoded, and subjected to 3D segmentation for intracellular and single-cell degradation analysis (Figure 11A).

[0177] RNA lifecycle in time and space at single-cell resolution Next, TEMPOmap was applied to profile a focused list of 991 genes (981 coding RNAs, 10 non-coding RNAs) in human HeLa cells. Another 7 genes were profiled using the STARmap probe. 13 This is also included during amplicon preparation, and it hybridizes to both labeled and unlabeled RNA as an internal control for batch correction and data normalization (Figure 14E). Next, pulse chase experiment. 15,28This was performed using a single steady-state criterion with 1 hour (hr) pulse labeling and various chase times (0, 1, 2, 4, and 6 hours), as well as 20 hours of pulse labeling (Figure 11A). Barcodes in all samples were sequenced over 6 rounds of in situ sequencing, and then the cell bodies were segmented by intracellular compartment staining (nucleus and cytoplasm) in the final round to assign the intracellular location of amplicons in 19,856 cells in 3D (Figures 11B–11C). The cytoplasmic space was further divided into a central region ("intermediate") and a peripheral region using a distance ratio (DR)-based method (Figure 11D): each amplicon was measured by the shortest distance to the nuclear membrane (dn) and the cell membrane (dc) in 3D, respectively, and the DR value was calculated as the ratio of dn to dn+dc. Following a 1-hour pulse labeling cycle, a decrease in total RNA reads per cell, a gradual shift in RNA distribution from the nucleus to the cytoplasm, and further allocation from the central to peripheral cytoplasm were observed during the 0-6 hour chase (Figures 11B-11C). Notably, a significant portion (approximately 40%) of the reads retained in the nucleus was still observed after a 6-hour chase. Further examination of the retained RNA molecules revealed that the RNAs with the highest nucleus-to-cytoplasmic read ratio included long non-coding RNAs (NEAT1, MALAT1), which was supported by deep sequencing of RNA from the cell fraction (Figure 15A). 29,30 Notably, mRNAs (KIF13A, LENG8, CCNL2, COL7A) were also found to be retained in the nucleus. This observation supports previous findings regarding widespread nuclear retention of mRNA, which may function as a regulatory buffer against cytoplasmic gene expression noise. 31,32 .

[0178] Next, all cells under a 1-hour pulsed condition were pooled at various chase time points (18,176 cells) for single-cell degradation dynamic trajectory analysis using PHATE and Dynamo (Figure 11E, I). 33,34The results showed a clear trajectory along the progression of chase time, suggesting that the transcriptional states of temporally degraded single cells can be easily distinguished and aligned within the gene expression space. When the same PHATE coordinates were superimposed with the dynamic vector of RNA degradation, the trajectory of single cells along the progression of the RNA lifecycle was further reproduced. 34~36 Next, the question arose as to how the RNA lifecycle, defined by the pulse-chase timeline, corresponds to the progression of the cell cycle. To this end, cells were classified into three cell cycle phases (G1, G1 / S, and G2 / M) using cell cycle scoring based on the nascent expression of marker genes (Figures 16B-16C). 37 Interestingly, the direction of cell cycle progression is orthogonal to the progression at pulse chase time points (Figure 11E, II). This observation suggests that TEMPOmap can provide independent temporal information about the RNA lifecycle in addition to the cell cycle.

[0179] Next, we further investigated intracellular dynamics from the TEMPOmap dataset. For this purpose, cell-specific nucleocytoplasmic gene matrices were generated by aligning single-cell nuclear expression with cytoplasmic expression for trajectory analysis (Figure 11E, bottom). Apart from restoring the unidirectional trajectory of single cells with the time of labeling (Figure 11E, III), it was found that a small fraction of G2 / M cells formed narrow trajectories and projected into a separate space, suggesting that the distribution of nucleocytoplasmic RNA in this group of G2 / M cells is significantly different from that of the rest of the G2 / M cells. These spatially distinct cells were thought to be mitotic cells with their own unique RNA nucleocytoplasmic distributions. 38Indeed, cells along this orbit were in different stages of mitosis, during which RNA was almost completely removed from the chromatin region compared to that of G2 cells (Figure 11E, V). Furthermore, the uniform orientation of this unique orbit closely coincided with the temporal progression of mitosis (Figure 1E, V, 5-8), indicating that the temporal transition of mitosis can be inferred from the intracellular RNA localization pattern. As a result, by jointly utilizing time-gated nucleocytoplasmic distribution, this method not only separates G2 and M cells but also tracks the mitotic orbit, providing a higher temporal resolution of cell cycle progression in addition to single-cell transcript expression; here, it is shown that there is little change in RNA copy number in G2 / M, but there is a dramatic removal of RNA from chromosomes during mitosis. 39 .

[0180] Quantification of intracellular RNA dynamics throughout the cell cycle To further quantify the individual dynamic steps in the RNA lifecycle, a model was developed to estimate six key dynamic constants for each gene: synthesis (α), total cellular degradation (β), nuclear degradation (βn), nuclear export (λ), cytoplasmic degradation (βc) (Figure 12A), and cytoplasmic translocation (γ) (Figure 12B). To minimize the potential bias of physical cell volume towards intracellular RNA readouts, the constants were estimated based on the concentration (readout / voxel) of each RNA species in total cell, nucleus, and cytoplasm (Figures 17A-17B). In the model, α and β were initially estimated using the mean total cellular RNA concentration, and then βn, βc, and λ were estimated by combining the mean nuclear and cytoplasmic RNA concentrations (Figure 17C). 28,40 For this, we assume zero-order kinetics, and β 28,40 βn, βc 32 , and λ 32,41 For this, we assumed first-order kinetics with fitting threshold processing for quality control (911 out of 991 genes were R 2(≥0.5) (Figure 17C). In parallel, the DR values ​​for each gene were calculated over different time periods, and γ was fitted assuming a constant translocation rate for all genes (Figure 12B).

[0181] Notably, RNA export from the nucleus is based on previous RNA rate-based models. 40 It was previously thought to be constant, but the results this time show that under the first-order assumption, λ 41 This substantially changes between different RNA species, suggesting that this may regulate the homeostasis of nuclear and cytoplasmic transcript abundances. Furthermore, for the first time, we were able to systematically and simultaneously study the cytoplasmic translocation of RNA from numerous genes at a resolution of 1 hour. Most genes have γ>0 (Figures 17E-17F), suggesting a translocation direction from the nuclear membrane to the cytoplasmic membrane. However, γ<0 (R 2 A small subset of genes with >0.5 are significantly enriched in exosomes and membrane proteins (Figure 17G), suggesting a cytosolic-to-endoplasmic redistribution event or a faster degradation rate of non-ER-anchored RNAs than ER-associated RNAs. Further research is needed to investigate the dynamic mechanisms that direct the cytoplasmic translocation of different RNA molecules (Figure 17H).

[0182] Next, the relationships between these dynamic parameters were investigated by plotting their pairwise correlations using a matrix of 911 genes (Figure 12C). The gene set showed positive correlations between three degradation constants (β vs. βn, βn vs. βc, and βn vs. βc, R=0.86, 0.39, and 0.14, respectively), with the highest correlation being between β and βn (R=0.86). This observation suggests that while RNA stability is primarily determined by its inherent characteristics (sequence, motif, etc.), different genes have different distributions of nuclear vs. cytosolic RNA degradation. Furthermore, a significant correlation was observed between degradation and nuclear export (λ vs. β, βn, and βc, R=0.45, 0.36, and 0.14, respectively), suggesting a potential dynamic coupling between RNA degradation and nuclear export. Despite the aforementioned correlations, the correlations between other pairs of dynamic parameters were weak (R<0.1), demonstrating that individual steps of synthesis, transport, disintegration, and migration in different intracellular regions undergo different dynamic regulation during the RNA lifecycle.

[0183] Next, the question arose as to whether RNA dynamics differ depending on the cell cycle phase. For this purpose, a second pairwise correlation analysis of six parameters was performed at different cell cycle phases (808 genes passed quality control; Figure 12D). Interestingly, it was observed that correlations tended to decrease in the cell cycle phases according to the spatiotemporal order of the RNA lifecycle: in the early stages of RNA generation, α was highly correlated in all three states (R~1, Figure 18A); during post-transcriptional processing in the nucleus, both βn and λ had moderate correlations (R~0.7 and 0.6, Figures 18C~18D); and finally, near the end of the RNA lifecycle, the cytoplasmic constants βc and γ had much weaker correlations (R~0.3 and 0.1, Figures 18E~18F). This observation revealed that the kinetic sorting of RNA at various stages gradually shifts in direction as the cell cycle progresses, and that RNA shifts from a universal regulatory direction to independent regulation in different cellular states, in line with spatiotemporal regulation. Therefore, profiling the cell cycle-dependent kinetic landscape of RNA demonstrated a correlation between the regulation of the cellular life cycle and the regulation of the RNA life cycle.

[0184] Previous studies have reported that the RNA synthesis rate is higher in the G2 / M phase than in the G1 phase. 42 This is noteworthy. Repeating the calculations of α and β using the RNA copy number per cell from TEMPOmap data and publicly available scEU-seq data 25Consistent results were observed: RNA synthesis rates were approximately 15% higher in G2 / M, while overall cell cycle degradation rates showed different trends between the two datasets, potentially due to different cell lines (Figure 18G-18H). However, when α and β were estimated using RNA concentration (RNA copy number per unit nuclear volume for α, and RNA copy number per unit cell volume for β), no significant changes were observed in the distribution of α and β values ​​across different cell cycle stages (Figure 18I). When α and β were estimated and compared using RNA copy number per cell and RNA concentration, this is consistent with previous studies showing that transcription rates are proportional to the available chromosome sites and that gene expression homeostasis is regulated by cell size. 43 Furthermore, when G2 and M phase cells were subsetted from single-cell nucleocytoplasmic PHATE-embedded cells (Figure 16D), a significantly higher λ was found in the M phase, further supporting the observation of RNA removal from chromosomes during mitosis (Figures 18J, 11E, V).

[0185] Considering the correlation between kinetic constants and potential co-regulatory mechanisms (e.g., shared RNA motifs and RNA-binding proteins), the next question was whether different genes may have evolved shared kinetic patterns in the context of the RNA lifecycle and cell cycle. Clustering analysis using 18 parameters (six kinetic constants across three cell cycle stages) revealed four distinct kinetic landscapes (Figure 12E). A closer examination of the clusters revealed the following: genes with slow synthesis (low α), high stability (low β), and slow nuclear export (λ) were enriched in helicase activity and other ATP binding functions (Cluster 0); genes with low α and moderate β and λ (Cluster 1) were strongly enriched in transcription; genes with unstable and rapidly exported RNA (high β and λ) (Cluster 2) were enriched in terms related to ubiquitination and membrane proteins; and genes with faster synthesis (high α), higher stability (low β), and faster nuclear export (high λ) (Cluster 3) were enriched in constitutive cellular processes such as mRNA splicing and mitochondrial function (Figure 12F). Furthermore, the spatial patterns of these gene groups were compared (Figure 12G). Genes in clusters 0 and 3 appeared to be more dominant in the cytoplasm, while clusters 1 and 2 were observed to be more retained in the nucleus over time. RNA readings of four clusters in three intracellular regions further supported this observation, demonstrating that dynamically classified genes can result in different spatiotemporal distributions (Figure 18H).

[0186] Differential RNA dynamics sorting based on gene function Considering the differential enrichment of GO terms from gene clusters defined by RNA dynamics (Figure 12F), we further investigated how the features of RNA lifecycle dynamics contribute to gene function. Potentially co-regulated RNAs were first identified through pairwise single-cell covariance analysis of 991 genes from the aforementioned pulse-chase HeLa cell samples (1-hour pulse, 0–6-hour chase, Figure 13A). Across all time points on the heatmap, using co-gene sorting in the matrix, two groups of genes with significant inter-gene correlations were identified, their correlation coefficients steadily increasing from 0-hour to 6-hour chase (Figure 13B, Figure 19A), suggesting the potential for kinetic sculpting of gene co-regulation patterns through RNA processing and decay. Notably, while both genes in groups 1 and 2 are enriched with cell cycle-related functions (Figure 13C, bottom right, p<0.05 for group 1; p<1e-04 for group 2), they differ significantly in RNA dynamics: group 1 consists of genes from dynamic clusters 2 and 3 with faster RNA processing, and the covariance pattern of these genes was immediately apparent 0–2 hours post-synthesis; in contrast, group 2 is enriched with genes from dynamic clusters 0 and 1 with slower RNA processing, where the covariance pattern gradually appeared from 2 to 6 hours post-synthesis (Figures 12E, 13B, and 13D). This observation suggests that RNAs with different dynamic characteristics in the transcriptional and post-transcriptional steps cooperate to jointly form cell cycle progression.

[0187] Next, the dynamic landscape of RNA was systematically compared across different categories of molecular function. The top three functional categories in the list of 991 genes (Figure 19B) were DNA binding (97 genes), RNA binding (28 genes), and intercellular binding (25 genes). Comparing six dynamic parameters across the three gene categories, DNA-binding genes were found to exhibit significantly faster RNA decay than RNA-binding genes and genes with intercellular binding molecular functions (Figure 13E, p=4.6e-03 and 0.036). Further gene correlation analysis of dynamic parameters from the three functional categories across cell cycle stages revealed different co-regulatory patterns of RNA dynamics (Figure 13F). Specifically, from the upstream to the downstream of the RNA lifecycle, genes functioning as DNA-binding proteins showed high correlation until nuclear RNA degradation (βn, R~0.8); RNA-binding genes remained kinetically correlated until cytoplasmic RNA degradation (βc, R~0.6); while intercellular junction genes showed an expanded high correlation during cytoplasmic translocation (γ, R~0.5), indicating that these genes have additional co-regulatory functions in cytoplasmic RNA degradation and localization compared to DNA-binding proteins. These observations further support the concept that RNA is kinetically classified to perform its molecular function.

[0188] Finally, RNA dynamics are important post-transcriptional chemical modifications of RNA, namely N6-methyladenosine modification (m 6 The investigation was conducted in the context of A). 44,45 . m 6 A is known to promote RNA decay, however, m 6 The overall landscape of A-RNA dynamic regulation has not been systematically addressed. For this purpose, 6 RNA with A modification and RNA without modification (m 6 A-RNA or non-m 6 The gene encoding A-RNA (Figure 19C) was isolated. Consistent with previous reports, m 6 A-RNA showed low stability (higher β, Figure 13G). 46 Furthermore, the same trend is observed in m6 A and non-m 6 This was also observed when comparing βn and βc of A, and m 6 The regulation of A methylation is achieved by RNA decay in both the nucleus and cytoplasm, suggesting that this is consistent throughout the entire cell cycle (Figure 19E). In contrast, no significant difference in λ was observed between the two groups. Previous studies have shown that in mRNA nuclear export mediated by YTHDC1, m 6 A regulatory role has been proposed. 47 Therefore, to confirm the cellular role of YTHDC1, HeLa cells were treated with control siRNA and siRNA against YTHDC1 mRNA, and control and knockdown cells were separated based on single-cell YTHDC1 readouts normalized to the expression of six other functionally relevant genes (METTL3 / 14, YTHDF1-3, YTHDC2, Figure 19F). Consistent with previous studies, the nucleus-to-cytoplasmic ratio of YTHDC1-targeted genes was consistently higher over time than that of non-targeted genes, suggesting nuclear accumulation of RNA upon YTHDC1 knockdown (Figures 19D, 19G). Furthermore, these results confirmed that such nucleus-to-cytoplasmic changes induced by YTHDC1 knockdown are due to the fluctuating rate of RNA nuclear export (Figure 19H). This study exemplifies how TEMPOmap, combined with genetic perturbations (e.g., RNAi), can depict the function of RNA-binding proteins with unprecedented resolution.

[0189] Consideration TEMPOmap constructs a novel in situ transcriptome platform that simultaneously profiles time- and spatially resolved transcriptomics in single cells, representing a multimodal single-cell transcriptome technology at subcellular resolution never before achieved. The research described here uses TEMPOmap to provide a comprehensive explanation of cellular and RNA regulation over tunable timescales, elucidating the laws governing how the cell cycle and RNA cycle are structured for the complex mechanisms of life. A strong correlation has been observed between RNA dynamics patterns and gene function, suggesting that such function-oriented regulation of the RNA lifecycle may have evolved under survival and energy constraints to control spatiotemporal gene expression in a precise and economical manner. 48 TEMPOmap also enables high-throughput single-cell functional genomics (e.g., CRISPR screening). 49 By combining this with other methods, it is also possible to determine key molecular factors that influence the dynamic landscape of the RNA lifecycle. Furthermore, by optimizing metabolic labeling conditions, 27,50,51 By applying such methodologies to ex vivo or in vivo tissue samples, dynamic events in histological biology can be systematically profiled.

[0190] method Chemicals and enzymes. Chemicals and enzymes listed by name (supplier, catalog number): Gel Slick Solution (Lonza, 50640). Plus One Bind-Silane (GE Healthcare, 17-1330-01). Poly-D-lysine solution, 50 μg / mL (ThermoFisher, A3890401). Ultrapure distilled water (Invitrogen, 10977-015). Glass-bottom 24-well plate (Greiner Bio-One, 662892, and MatTek, P24G-1.5-13-F). #2 microcoverslip, 12 mm diameter (Electron Microscope Sciences, 72226-01). 16% PFA, EM grade (Electron Microscope Sciences, 15710-S). Methanol for HPLC (Sigma-Aldrich, 34860-1L-R). PBS, 7.4 (Gibco, 10010-023 for 1x, 70011-044 for 10x). Tween-20, 10% solution (Calbiochem, 655206). Triton-X-100, 10% solution (Sigma-Aldrich, 93443). OminiPur formamide (Calbiochem, 75-12-7). 20× SSC buffer (Sigma-Aldrich, S6639). Ribonucleoside vanadyl complex (New England Biolabs, S1402S). Yeast tRNA (Invitrogen, AM7119). SUPERase·In (Invitrogen, AM2696). 5-ethinyluridine (5-EU) (Invitrogen, E10345). 1.5× click buffer (Lumiprobe, 61150). L-ascorbic acid (Sigma-Aldrich, A5960). T4 DNA ligase, 5 Weiss U / μL (Thermo Scientific, EL0011). Phi29 DNA polymerase (Thermo Scientific, EP0094). 10 mM dNTP mix (Invitrogen, 100004893). BSA, molecular biology grade (New England Biolabs, B9000S). 5-(3-aminoallyl)-dUTP (Invitrogen, AM8439).BSPEG9 (Thermo Scientific, 21582). NHS ester of methacrylic acid, 98% (Sigma-Aldrich, 730300). DMSO, anhydrous (Molecular Probes, D12345). Acrylamide solution, 40% (Bio-Rad, 161-0140). Bis solution, 2% (Bio-Rad, 161-0142). Ammonium persulfate (Sigma-Aldrich, A3678). N,N,N',N'-tetramethylethylenediamine (Sigma-Aldrich, T9281). OminiPur SDS, 20% (Calbiochem, 7991). Antarctica phosphatase (New England Biolabs, M0289S). DAPI (Molecular Probes, D1306). Flamingo fluorescent protein gel stain (Bio-Rad, 1610491). DMEM (ThermoFisher, 11995). FBS (HyClone, SH3007103). Lipofectamine RNAiMAX (Invitrogen, 13778075). NHS ester of azidobutyric acid (Lumiprobe, 63720). Bio-Spin® P-6 column, SSC buffer (Bio-Rad, 7326002).

[0191] Design and construction of the TEMPOmap3 probe. The TEMPOmap3 probe was designed to contain a set of three separate DNA oligonucleotide probes: the sprint, the primer, and the padlock. The DNA sprint was prepared by incubating a 40 μM 5'-amino-modified sprint oligo (manufactured by Integrated DNA Technologies (IDT)) overnight at room temperature in 0.1 M NaHCO3 with 25 mM NHS ester of azidobutyric acid (azido-NHS). The product was purified by ethanol precipitation and passed through a Bio-Spin® P-6 column (SSC buffer).

[0192] A representative sequence graph is shown in Figure 14C. The probe was designed as follows: (1) The 5' azide-modified sprint is divided into two regions: a linker containing 50 adenosine nucleotides connected to a 12nt sprint padlock annealing sequence. To protect from enzymatic amplification, the sprint contains an inverted dT at the 3' end and a phosphorothioate bond on the last three nucleotides of the 3' end of the oligo. The sprint padlock annealing sequence allows for hybridization of the sprint and padlock on the same RNA, creating a double-stranded DNA region with a sealable "nick" in the ligation step. (2) The 5' phosphorylated padlock consists of a complementary sprint padlock annealing sequence, two regions of the same 5nt barcode, a 10nt primer padlock annealing sequence, a 19-25nt target region for specific RNA binding, and several short linkers. (3) The primer contains a different 19-25 nt target region, a 2 nt mismatch base, a 5 nt linker, and a 5 nt gene-specific sequence that is inversely complementary to the barcode of the matching padlock. The two target regions of each set of primer and padlock are located 1-2 bases adjacent to each other on the same mRNA species.

[0193] Detailed procedures for selecting target regions on primers and padlocks were applied as described above. 13 In short, only the shortest isoforms and coding regions excluding non-coding RNAs were considered. Using Picky2.2, target sequences were designed on each probe pair in the length range of 40–46 nt, and six sequences were selected for each gene. The complementary DNA (cDNA) sequences of the selected regions were split into two halves of 20–25 nt, separated by 0–2 nt intervals, containing the one with the best matching melting temperature. Probes were pooled, ordered, and manufactured by IDT. The read and decode probes used in SEDAL sequencing were designed and ordered according to Wang et al., 2018.

[0194] Design and construction of TEMPOmap2 probes. When constructing TEMPOmap2 probes (sprint and padlock), the design of the sprint probe was the same as described in the 3 Probes section. Each padlock probe contained a 40nt target region selected as described in the 3 Probe Designs section, with five sequences selected for each gene.

[0195] HeLa cell culture and siRNA knockdown. The human HeLa cell line used in this study was purchased from ATCC (CCL-2) and grown in DMEM (Gibco, 11995) medium supplemented with 10% FBS. Cells were plated onto pre-treated 24-well glass-bottom plates (process described in the next section) and grown at 37°C in 5% CO2 before siRNA knockdown. Qiagen's Allstars negative control siRNA (SI03650318) was used as the control siRNA for the knockdown experiment. YTHDC1 siRNA was ordered from Qiagen (SI04225851). Transfection was performed using Lipofectamine RNAiMAX (Invitrogen) for siRNA, according to the manufacturer's protocol.

[0196] For downstream analyses comparing siControl versus siYTHDC1(KD) cells, after in situ sequencing and TEMPOmap dataset processing (see below), control and KD cells were first separated based on single-cell YTHDC1 reads normalized to the mean RNA expression of six other functionally relevant genes targeted by the STARmap probe (METTL3 / 14, YTHDF1-3, YTHDC2, Figure 14E). The cells were then divided into control cells (n~5000) with the top 25% of normalized YTHDC1 reads and KD cells (n~5000) with the bottom 25%.

[0197] TEMPOmap experimental procedure. 24-well glass-bottom plates were sequentially treated with a 1% methacrylateoxypropyltrimethoxysilane (Bind-Silane) and poly-D-lysine solution before plating the cells. Cells were then plated onto the coated plates and maintained in growth medium (DMEM containing 10% FBS) in a 37°C, 5% CO2 wet culture incubator. Pulse chase experiments were performed using 200 μL 5-EU cells, washed with cell medium for the specified time. After metabolic labeling and washing, cells were fixed in PBS with 1.6% PFA for 10 minutes and permeabilized with pre-cooled (-20°C) methanol at -80°C for 30 minutes. Next, the sample was removed from -80°C, equilibrated to room temperature, and quenched for 10 minutes in a buffer containing PBSTR (PBS with 0.1% Tween-20 and 0.1 U / μL SUPERase·In) supplemented with 10 mM Tris, pH 7.5, and 0.1 mg / mL yeast tRNA.

[0198] To functionalize the newly synthesized ethynylated RNA, a 5' azide-modified DNA sprint (5 μM) was added to 1 × Lumiprobe click chemistry buffer. CuAAC was initiated by adding ascorbate (800 μM). The reaction mixture was incubated at 37°C for 1 hour with gentle shaking. The samples were then washed twice with PBSTR at 37°C for 10 minutes each.

[0199] Libraries of TEMPOmap primers and padlock probes (targeting 991 genes) and a set of STARmap SNAIL probes (targeting METTL3 / 14, YTHDF1-3) were pooled separately and ordered from IDT. All four probe pools were dissolved in RNase-free ultrapure water and adjusted to 100 nM per oligo for storage. The probe mixtures were then heated at 90°C for 5 minutes and cooled on ice. The samples were then incubated in 1× hybridization buffer (2× SSC, 10% formamide, 1% Tween-20, 20 mM RVC, 0.1 mg / mL yeast tRNA, 0.2 U / μL SUPERase·In) supplemented with 2 nM TEMPOmap probe per oligo and 10 nM STARmap probe per oligo for 14-16 hours with gentle shaking in a humidified oven at 40°C. Next, the sample was washed twice with PBSTR and once with high-salt buffer (4×SSC in PBSTR) for 20 minutes at 37°C each time, and then rinsed again with PBSTR. Then, the sample was incubated at room temperature with a T4 DNA ligation mixture (1:20 dilution of T4 DNA ligase, 1×BSA, and 0.2 U / μL of SUPERase·In) with gentle shaking for 2 hours, and then washed twice with PBSTR. Subsequently, the sample was incubated with an RCA mixture (1:20 dilution of Phi29 DNA polymerase, 250 μM of dNTPs, 20 μM of 5-(3-aminoallyl)-dUTP, 0.2 U / μL of SUPERase·In, and 1×BSA) with gentle shaking for 2 hours, and then washed twice with PBST (PBS containing 0.1% Tween-20). Next, the samples were treated with 25 mM methyl acrylate NHS ester (MA-NHS) in 0.1 M NaHCO3 at room temperature for 2 hours, and then washed once with PBST.

[0200] To cast the gel, the sample was first incubated at room temperature for 15 minutes with monomer buffer (4% acrylamide, 0.2% bisacrylamide, 2×SSC) supplemented with 0.2% TEMED. The buffer was removed, and 30 μL of polymerization mixture (0.2% ammonium sulfate, 0.2% TEMED dissolved in monomer buffer) was slowly added to the center of the sample, which was immediately covered with a coverslip coated with Gel Slick. The sandwich polymerization mixture was incubated in N2 for 1 hour, followed by two washes with PBST. The gelled sample was then treated overnight at room temperature with a dephosphorylation mixture (1:100 dilution of Antarctic phosphatase, 1×BSA), followed by two washes with PBST.

[0201] Imaging and in situ sequencing of TEMPOmap samples. TEMPOmap imaging and in situ sequencing were performed with modifications to the description in Wang et al. (2018). Briefly, six rounds of four-color confocal imaging were performed for 998 gene measurements, with a final round including DAPI-stained nuclear detection, flamingo-stained cell morphology, and concanavalin A-stained endoplasmic reticulum (ER) region, as described in the manufacturer's instructions. Each round of imaging was initiated by incubating the sample with a sequencing mixture (1:25 dilution of T4 DNA ligase, 1× BSA, 10 μM reading probe, and 5 μM fluorescence decoding oligo) at room temperature for 3 hours, and before imaging, the sample was rinsed three times for 5 minutes each with wash / imaging buffer (2× SSC, 10% formamide). After image acquisition, the samples were treated twice for 10 minutes with stripping buffer (60% formamide, 0.1% TritonX-100), followed by three washes with PBST. After imaging six rounds, DAPI-stained cell nuclei, flamingo-fluorescent gel-stained cytoplasm, and concanavalin A-stained ER were imaged. Images were acquired using a Leica SP8 confocal microscope with a 405 diode, white light laser, and a 40x oil immersion objective lens (NA 1.3). For each round, image acquisition was performed at illuminations of 488 nm, 546 nm, 594 nm, and 647 nm, and at 30 focal planes. The voxel size of the images was 200 nm × 200 nm × 350 nm.

[0202] Image processing and amplicon decoding. Image processing was performed with modifications to the description in Wang et al. (2018). First, image deconvolution was applied using Huygens Essential v20.10.1p2. Next, the deconvoluted images were normalized using a Min-Max strategy and further refined by histogram equalization, with the images from the first sequencing round used as reference. Furthermore, customized top-hat filtering was applied to enhance the fluorescence signal. To better identify the barcode of each cDNA amplicon, both global and non-rigid registration were performed on the preprocessed images. Global image registration was performed using a 3D Fast Fourier Transform (FFT) to calculate the cross-correlation between two image volumes at all translation offsets. The location of the maximum correlation coefficient was identified and used to transform the image volume and compensate for the offset. Non-rigid registration was implemented using the "imregdemons" function in MATLAB 2020b. After registration, individual amplicons were identified in each color channel of the first round of sequencing. In this experiment, amplicon dot identification was performed by finding local maxima in 3D using the MATLAB function "imregionalmax". Dots with centroid intensity below a threshold were removed. Based on the estimation of the amplicon size, the dominant color of each dot across all four channels in each round was determined by the 5x5x3 voxel volume surrounding the dot's centroid. The combined intensity of the voxel volume for each channel was used to determine the color. In this case, each dot in each round had an L2 normalized vector with four elements. The color of each dot was determined by the corresponding channel with the highest value in the vector. Dots with multiple maximum values ​​in the vector were discarded. Next, the dots were filtered based on a quality score (the mean of -log(color vector value of the dominant channel) across all sequencing rounds). The quality score quantified how much each dot in each sequencing round originated from a single color rather than a mixture of colors.The barcode codebook was converted to a color space based on the expected color sequence, according to the 2-base coding of the barcoded DNA sequence. Dots that exceeded the quality threshold and had matching barcode sequences within the codebook were retained, while all other dots were rejected. Both the physical location and gene identity of the filtered dots were saved for downstream analysis.

[0203] Image segmentation of single cells and intracellular regions. Image segmentation was performed using CellProfiler v4.1.3 and other customized MATLAB scripts. 2D reference segmentation masks were generated using a customized pipeline for both DAPI-stained images and composite images combining amplicon channels and flamingo fluorescent gel-stained images.

[0204] For 3D segmentation, images targeting different cell compartments were first processed with a median filter and then binarized using Otsu's method. All connected components (objects) smaller than 100 pixels were removed from the binary image. The image was then expanded using disk structure elements with a radius of 3. Finally, 3D segmentation masks targeting each cell region were generated by an element-wise multiplication process between the binary image and the 2D reference cell segmentation from the previous step. The nuclear region was removed from the 3D cell segmentation mask to create cytoplasmic segmentation.

[0205] Next, filtered amplicons that overlapped with each segmented cell region in 3D were assigned to specific intracellular regions (Figure 15B), and the cell-specific gene expression matrix in each cell compartment was calculated.

[0206] Analysis of intracellular RNA distribution using distance ratio (DR) calculation. To quantify the relative location of cytoplasmic reads, the distance ratio (DR) was calculated for each cytoplasmic read. The DR value for intracellular RNA reads was defined as the shortest distance to the nucleus (d1), determined by nuclear segmentation, and normalized by the sum of this distance and the shortest distance to the cell membrane (d2), determined by cell segmentation (Figure 15D). The shortest distance was calculated using the Euclidean distance transformation function provided by Scipy. Using a cutoff DR value of 10, the cytoplasmic region was further segmented into "intermediate" and "peripheral" regions to examine the intracellular distribution of RNA reads across each time point in the TEMPOmap dataset in detail.

[0207] Dynamic modeling of RNA cytoplasmic translocation (γ). The RNA cytoplasmic translocation parameter γ was estimated using linear regression of the mean DR values ​​(details above) for each gene across different pulse chase time points (Figure 16B). For each gene, the mean DR value representing cytoplasmic localization at a specific time point was obtained by averaging the DR values ​​of all readings from all corresponding cells. Linear regression was performed across all time points for each gene using the Scipy "linregress" function in Python.

[0208] Visualization of cell clustering via PHATE based on single-cell and intracellular degradation gene expression matrices. Single-cell clustering was performed on cell-specific gene expression matrices, normalized to have the same total number of cell readings. Intracellular degradation clustering was performed on horizontally concatenated nuclear and cytoplasmic expression matrices, both of the same dimensions as the cell-specific gene expression matrices, and normalized in the same manner as above. For both matrices, PHATE (Potential of Heat-diffusion for Affinity-based Trajectory Embedding) was used as the clustering and visualization method, which has been shown to preserve both local and global structures of the data. The PHATE neighbor parameter 30 was used in both analyses.

[0209] Visualization of RNA degradation dynamics vectors and animation of transcriptome vector fields by dynamo. Arrows overlaid on points in PHATE coordinates (Figures 11E, I, and III) were constructed by modeling transcriptome dynamics considering total RNA degradation dynamics in single cells. The total RNA degradation rate for vector visualization was estimated by -degradation rate * nascent RNA.

[0210] The transcriptome vector field animation was constructed using dynamo from the same RNA degradation dynamics as above 35 .

[0211] Classification and validation of cell cycle phases. Three cell cycle phases (G1, G1 / S, G2 / M) of single cells were classified using TEMPOmap nascent RNA expression by the scanpy cell cycle scoring function "score_genes_cell_cycle". To verify whether the 1-hour labeled nascent transcriptome can accurately assign cell cycle phases, the cell cycle scoring analysis was repeated using 1-hour pulses and total transcripts (22-hour pulses and 0-hour chases) from a previously published scEU-seq dataset, and a correlation analysis of the assigned cell cycle results was performed (Figure 16C).

[0212] Dynamic modeling and fitting of RNA synthesis (α), degradation (β, βn, βc), and nuclear export (λ) constants. RNA concentration calculation. After obtaining the RNA copy number for each of the 991 genes in the nucleus and cytoplasm of a single cell, the reads were first normalized across different chase time points to the average reads of six control genes (i.e., genes targeted by the STARmap probe: METTL3, METTL14, YTHDC2, YTHDF1-3); these were expected to show uniform expression under different pulse chase conditions because the total RNA of each gene is targeted. Next, the normalized RNA copy number in each assigned region (Figure 15B) was divided by the unit cell volume (voxels), unit nuclear volume (voxels), and unit cytoplasmic volume (voxels) to calculate the RNA concentration in the single cell (X(t)), nucleus (N(t)), and cytoplasm (C(t)), respectively. The unit of RNA concentration is reads / voxels and will be abbreviated as [RNA] in the following section.

[0213] Modeling. Let α be the transcription constant ([RNA] / h), β be the total cellular degradation constant (1 / h), βn be the nuclear degradation constant (1 / h), λ be the nuclear export constant (1 / h), and βc be the cytoplasmic degradation constant (1 / h). X(t) in a 1-hour pulse is described by the following linear dynamic equation: dX(t)dt = α - β*X(t) (1) And the time evolution of X(t) between subsequent chase points is described as follows: dX(t)dt = -β*X(t) (2) Here, we assume that no new RNA is synthesized after a 1-hour pulse. Using equations (1) and (2), we estimate the time-dependent α and β from the total cellular RNA concentration for each gene, assuming that α and β are approximately constant during the pulse and chase periods.

[0214] Next, in order to estimate the remaining dynamic parameters (βn, λ, and βc), we assumed the following: RNA is either degraded in the nucleus or transported out of the nucleus to the cytoplasm after transcription, which can be mathematically incorporated into a single parameter p (nuclear processing constant). Thus, the time evolution of N(t) is described as follows: dN(t)dt = -p*N(t) (3) on the other hand, p = βn + λ (4) Here we assumed the following: (1) All cellular RNA moves unidirectionally from the nucleus to the cytoplasm, so all values ​​of λ are positive; (2) βn, λ, and βc are constant with respect to time. Using equation (3), we estimated p for each gene. Next, we assumed that the total cellular degradation rate is equal to the sum of nuclear and cytoplasmic degradation. Thus, we obtain the following equation: X(t)*β=N(t)*βn+C(t)*βc (5) Based on (4), X(t)*β=N(t)*(p-λ)+C(t)*βc (6)

[0215] In this way, cytoplasmic degradation (βc) and nuclear export (λ) were estimated. The p value for each gene was estimated, and then nuclear degradation (βn) was calculated. It should be noted that data from the 1-hour pulse-1-hour chase condition proved to be outliers in the linear model, likely due to residual EU in the cells after washing. Therefore, cells were removed from the 1-hour chase, and only cells from the 0, 2, 4, and 6-hour chases were used for modeling.

[0216] Fitting and thresholding. For the estimated β and p, the model is fitted to the data in R. 2 The evaluation was performed using R. Therefore, the model is (1): limited to genes where all estimated parameters have positive values, thereby eliminating all genes with at least one parameter with a negative value; and (2): when equations (2) and (3) are fitted to the corresponding data for the estimation of β and p respectively, 2The analysis was limited to genes with a value >= 0.5. Therefore, a constant degradation (β) coefficient and nuclear processing (p) coefficient for RNA concentration over time were assumed. When all cell cycle phases were combined, 915 genes exceeding the fitting threshold were obtained for all five parameters. When cells were separated into different phases, 808 genes (five parameters across three phases) were obtained for all 15 parameters.

[0217] Validation of the estimation of dynamic parameters. To validate these models, synthesis (α) and total cell degradation (β) calculations were repeated using the RNA copy number per cell from the TEMPOmap dataset and the publicly available scEU-seq dataset (1-hour pulse, 0, 2, 4, and 6-hour chases) to obtain 549 duplicate genes. The results from these two datasets were then compared by dimensionality reduction and gene clustering, and the Z-scores derived from the variation in estimated gene cluster rates were visualized using heatmaps (Figures 18H-18J). Details of the gene clustering and visualization methods are described in the following sections.

[0218] Correlation and clustering analysis of dynamic parameters. Matrices describing the pairwise correlation coefficients of the estimated dynamic parameters were constructed using R for both the six combined cell cycle parameters (consisting of 915 genes) and the 18 cell cycle-degraded parameters (consisting of 808 genes). These were visualized using scatter plot matrices (Figure 12C) and heatmaps (Figure 12D), respectively. Several important examples of correlations among the 18 cell cycle-degraded parameters were also visualized as scatter plots in Figures 218A–218F.

[0219] Next, dimensionality reduction was performed using UMAP on 18 dynamic parameters obtained by cell cycle decomposition of 808 genes. Subsequently, gene clustering was performed using Louvain embedded in Seurat v4 based on UMAP, and four gene clusters were identified. It was noted that the range of the dynamic parameters varied more significantly than the variance of the same parameter across different cell cycle phases. Therefore, to better visualize the dynamic differences between the four clusters, Z-scores were calculated for each dynamic parameter calculated for all genes during three cell cycle phases, and these Z-scores were plotted as a heatmap in Figure 12E.

[0220] For each of the four clusters identified by UMAP analysis, a gene ontology (GO) was performed using DAVID (david.ncifcrf.gov / content.jsp?file=quote.htm) for each of the genes in each of the four clusters identified by UMAP analysis against the background list of 991 genes in TEMPOmap. All statistically significant GO terms (p-value close to or less than 0.05) are shown in Figure 12F.

[0221] Visualization of four clusters in representative cells was performed using a customized script written in Python.

[0222] Analysis of the time-course co-variation of nascent RNA expression in single cells. For the time-course co-variation analysis of single-cell RNA expression (Figure 13A, Figure 19A), a matrix describing the correlation of expression levels between each gene pair was first constructed using all cells from the 0, 2, 4, and 6-hour chases. Then hierarchical clustering was performed to organize the genes, using R, based on their correlation coefficients in these time-coupled cells. The matrix was rearranged by the clustering results and visualized by a heatmap (Figure 13A, left). Then, heatmaps describing the correlation coefficients of the expression levels at individual time points were created while maintaining the same grouping and order of the genes in all matrices (Figure 19A). Comparing the heatmaps across the four time points, two small gene clusters were identified (annotated as 1 and 2 in Figure 13A), which show correlated expression when all time points are combined but also show variation along individual time points (Figure 19A). GO analysis was performed for the genes in each of the two clusters using DAVID against the above background gene list.

[0223] m in the TEMPOmap gene list 6 Identification of m 6 For m 6 A-related gene labels, highly reliable m 6 A-modified transcripts encoding genes were identified by previously reported PAR-CLIP and immunoprecipitation (IP) data. Briefly, m 6 A-RNA was defined as (1) having at least 1-fold enrichment in non-fragmented m6A RIP-seq and (2) transcripts that bound to each replicate of PAR-CLIP. Similarly, non-m 6 A-RNA was defined as (1) having less than 0-fold enrichment in non-fragmented m 6 A RIP-seq and (2) transcripts with no peaks in any replicate of PAR-CLIP. Using these criteria, 573 genes encoding m 6111 genes encoding A-RNA were identified from the TEMPOmap gene list.

[0224] For YTHDC1 target-related gene labeling, reliable target-encoding genes were identified by previously reported YTHDC1 PAR-CLIP and IP data. Briefly, YTHDC1 targets were defined as (1) having at least a 1-fold enrichment in YTHDC1-IP measurements, (2) having a significant p-value in IP measurements, and (3) transcripts bound in each PAR-CLIP replication. Next, non-targets were defined as (1) non-fragmented m 6 (A) Transcripts were defined as having less than zero enrichment in RIP-seq and (2) no peaks in any of the PAR-CLIP replications. Using these criteria, 158 genes encoding target transcripts and 160 genes encoding non-targets were identified.

[0225] Example 7: In vivo TEMPOmap Next, to elucidate spatiotemporal transcriptomics in whole animal tissues (e.g., cardiac tissue), TEMPOmap was tested in vivo. To achieve this objective, 1 mg of EU was injected into mice via post-orbital administration, and organs were harvested 2 hours later. Mice administered with PBS were used as controls. Organs (e.g., heart) were frozen-sectioned into 20 μm tissues and chemically processed using the TEMPOmap workflow (Figure 20A). The in vivo applicability of TEMPOmap in cardiac tissue sections is demonstrated. Targeting of four genes highly expressed in the heart (Myh6, Flt1, Dach1, and Lamc1) is shown in Figure 20B. The results show significant enrichment of newly transcribed RNA signals compared to PBS-administered control tissue, thus demonstrating TEMPOmap's ability to detect and measure metabolically labeled RNA on living animal tissue sections. Therefore, the TEMPOmap method is applicable in vivo to analyze multiplexed spatiotemporal transcriptomics in systems, tissues, organoids, and organs.

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[0277] Embedding by reference This application references various published patents, published patent applications, scientific journal articles, and other publications, all of which are incorporated herein by reference. Details of one or more aspects of the present invention are described herein. Other features, purposes, and advantages of the present invention will become apparent from the detailed description, drawings, examples, and claims.

[0278] Equivalents and range Articles such as "a," "an," and "the" can mean one or more unless otherwise indicated or made clear from the context. A description or aspect involving "or" between one or more members of a group is considered satisfied if, unless otherwise indicated or made clear from the context, one, more than one, or all of the group members are present in, used in, or otherwise related to a given product or process. This invention includes aspects in which exactly one member of a group is present in, used in, or otherwise related to a given product or process. This invention includes aspects in which more than one, or all, of the group members are present in, used in, or otherwise related to a given product or process.

[0279] Furthermore, this disclosure encompasses all variations, combinations, and substitutions in which one or more limitations, elements, clauses, and descriptive terms from one or more of the enumerated claims are introduced into another claim. For example, any claim dependent on another claim may be modified to include one or more limitations found in other claims dependent on the same basic claim. Where elements are presented as a list, for example in Marcouche group format, each subgroup of elements is also disclosed, and any element(s) may be removed from a group. In general, where the present invention or an aspect of the present invention is said to include certain elements and / or features, it should be understood that certain aspects of this disclosure or aspects of this disclosure consist of, or essentially consist of, such elements and / or features. For simplicity, these aspects are not specifically described in this specification in these exact terms. Note that the terms “includes” and “contains” are intended to be open and allow for the inclusion of additional elements or steps. Where a scope is specified, an endpoint is also included. Furthermore, unless otherwise indicated, or unless it is obvious from the context and the understanding of those skilled in the art, the values ​​expressed as a range may take any specific value or subrange within the ranges described in the various embodiments of the present invention, up to one-tenth of the lower limit unit of the range, unless otherwise clearly indicated in the context.

[0280] This application references various published patents, published patent applications, journal articles, and other publications, all of which are incorporated herein by reference. In the event of any conflict between any of the incorporated references and this specification, this specification shall prevail. Furthermore, certain aspects of the present invention that constitute prior art may be expressly excluded from one or more aspects. Such aspects are considered to be known to those skilled in the art and may be excluded even if the exclusion is not expressly stated herein. Any particular aspect of the present invention may be excluded from any aspect for any reason whatsoever, whether or not it relates to the existence of prior art.

[0281] Those skilled in the art will be able to recognize or confirm many equivalents to the particular embodiments described herein by means of routine experiments alone. The scope of the embodiments described herein is not intended to be limited to the above description, but rather as described in the appended embodiments. Those skilled in the art will understand that various changes and modifications to this description are possible without departing from the spirit or scope of the invention as defined in the following claims.

Claims

1. A method for profiling spatiotemporal gene expression in cells, the following: a) Cells under the presence of a pool of nucleoside analogs １ The nucleic acids synthesized by the cells are incubated for a certain period of time to be metabolically labeled, where each nucleoside analog in the pool of nucleoside analogs contains a reactive chemical moiety; b) Contacting a metabolically labeled nucleic acid with a group of first oligonucleotide probes, where each first oligonucleotide probe in the group of first oligonucleotide probes contains a chemical moiety that reacts with the reactive chemical moiety of a nucleoside analog; c) Contacting a metabolically labeled nucleic acid with one or more oligonucleotide probes, including a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion of the first oligonucleotide probe in the group of first oligonucleotide probes complementary to the first oligonucleotide probe, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe; d) Ligate the 5' and 3' ends of a third oligonucleotide probe to generate a cyclic oligonucleotide; e) Perform rolling circle amplification to amplify a cyclic oligonucleotide using a second oligonucleotide probe as a primer, thereby generating one or more ligated amplicons; f) Embedding one or more linked amplicons into a polymer matrix; g) Contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe having a sequence complementary to the second barcode sequence of the third oligonucleotide probe; and h) Image the fourth oligonucleotide probe to determine the location of one or more linked amplicons embedded in the polymer matrix. The method, including the method described above.

2. Steps (a) to (h) at different times t ２ The method according to claim 1, further comprising profiling the spatiotemporal expression of the metabolically labeled nucleic acid of interest by repeating the process at least once.

3. The method according to claim 1 or 2, wherein spatiotemporal gene expression is profiled simultaneously in multiple cells.

4. The method according to claim 3, wherein the cells include a plurality of cell types.

5. The method according to claim 1 or 2, wherein the cells are present within intact tissue.

6. The method according to claim 5, wherein the tissue is in vivo during incubation in step (a) and before contact in step (b).

7. The method according to claim 1 or 2, wherein spatiotemporal gene expression is simultaneously profiled for up to 1000 target metabolically labeled nucleic acids.

8. The method according to claim 1 or 2, wherein one or more target metabolically labeled nucleic acids are nascent RNA, messenger RNA (mRNA), transfer RNA (tRNA), or ribosomal RNA (rRNA).

9. The method according to claim 1 or 2, wherein the reactive chemical portion of each nucleoside analog in a pool of nucleoside analogs is a reactive bioorthogonal functional group, and the chemical portion of each first oligonucleotide probe in a group of first oligonucleotide probes is a reactive bioorthogonal functional group.

10. The method according to claim 1 or 2, wherein each first oligonucleotide probe in the group of first oligonucleotide probes further comprises a polymerization blocker.

11. Each of the first oligonucleotide probes in the group of first oligonucleotide probes has the following structure: 5'-[Reactive chemical part]-[PolyA linker sequence]-[Part complementary to the third oligonucleotide probe]-[Polymerization blocker]-3' The method according to claim 1 or 2, wherein each example, therein, independently comprises an arbitrary nucleotide linker.

12. The second oligonucleotide probe has the following structure: 5'-[Part complementary to the target metabolically labeled nucleic acid]-[Barcode sequence]-3' This includes, where ]-[ includes any nucleotide linker, The method according to claim 1 or 2.

13. The method according to claim 1 or 2, wherein a portion of a third oligonucleotide probe complementary to the first oligonucleotide probe in a group of first oligonucleotide probes is split between the 5' and 3' ends of the third oligonucleotide probe.

14. The third oligonucleotide probe has the following structure: 5'-[First portion complementary to the first oligonucleotide probe]-[First barcode sequence]-[Part complementary to the target metabolically labeled nucleic acid]-[Second barcode sequence]-[Second portion complementary to the first oligonucleotide probe]-3' The method according to claim 1 or 2, wherein each example includes an arbitrary nucleotide linker.

15. The method according to claim 1 or 2, wherein the step of performing rolling circle amplification further comprises providing an amine-modified nucleotide, wherein the amine-modified nucleotide is incorporated into one or more linked amplicons.

16. The method according to claim 15, wherein the step of embedding one or more linked amplicons in a polymer matrix comprises reacting the amine-modified nucleotides of the one or more linked amplicons with N-hydroxysuccinimide methacrylate, and copolymerizing the one or more linked amplicons with the polymer matrix.

17. The method according to claim 1 or 2, wherein the second barcode sequence of the third oligonucleotide probe is a gene-specific sequence used to identify a metabolically labeled nucleic acid of interest.

18. The method according to claim 1 or 2, wherein the step of contacting one or more linked amplicons embedded in a polymer matrix with a fourth oligonucleotide probe is performed to identify a metabolically labeled nucleic acid of interest.

19. A plurality of oligonucleotide probes comprising a first oligonucleotide probe, a second oligonucleotide probe, and a third oligonucleotide probe, wherein, i) The first oligonucleotide probe comprises a reactive chemical portion; ii) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the metabolically labeled nucleic acid of interest; and iii) The third oligonucleotide probe comprises a portion complementary to the metabolically labeled nucleic acid of interest, a first barcode sequence, a portion complementary to the first oligonucleotide probe, and a second barcode sequence. Here, the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe. The plurality of oligonucleotide probes.

20. A system for profiling spatiotemporal gene expression in cells, which includes the following: a) Cell; b) A pool of nucleoside analogs, where each nucleoside analog in the pool contains a reactive chemical moiety; c) A group of first oligonucleotide probes, where each oligonucleotide probe in the group of first oligonucleotide probes includes a chemical moiety that reacts with a reactive chemical moiety of a nucleoside analog; and d) One or more oligonucleotide probes comprising a second oligonucleotide probe and a third oligonucleotide probe, where: i) The second oligonucleotide probe comprises a barcode sequence and a portion complementary to the nucleic acid of interest; and ii) The third oligonucleotide probe comprises a portion complementary to the nucleic acid of interest, a first barcode sequence, a portion of the first oligonucleotide probe in the group of first oligonucleotide probes complementary to the first oligonucleotide probe, and a second barcode sequence, wherein the first barcode sequence of the third oligonucleotide probe is complementary to the barcode sequence of the second oligonucleotide probe. The system including the above.

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