Palla, G., Fischer, D. S., Regev, A. & Theis, F. J. Spatial components of molecular tissue biology. Nat. Biotechnol. 40, 308–318 (2022).
Rao, A., Barkley, D., Franca, G. S. & Yanai, I. Exploring tissue architecture using spatial transcriptomics. Nature 596, 211–220 (2021).
Chen, Y. et al. Mapping gene expression in the spatial dimension. Small Methods 5, e2100722 (2021).
Moses, L. & Pachter, L. Museum of spatial transcriptomics. Nat. Methods 19, 534–546 (2022).
Lee, J. H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).
Alon, S. et al. Expansion sequencing: spatially precise in situ transcriptomics in intact biological systems. Science 371, eaax2656 (2021).
Chang, T. et al. Rapid and signal crowdedness-robust in situ sequencing through hybrid block coding. Proc. Natl Acad. Sci. USA 120, e2309227120 (2023).
Moffitt, J. R., Lundberg, E. & Heyn, H. The emerging landscape of spatial profiling technologies. Nat. Rev. Genet. 23, 741–759 (2022).
Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).
Vickovic, S. et al. High-definition spatial transcriptomics for in situ tissue profiling. Nat. Methods 16, 987–990 (2019).
Rodriques, S. G. et al. Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363, 1463–1467 (2019).
Stickels, R. R. et al. Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2. Nat. Biotechnol. 39, 313–319 (2021).
Cho, C. S. et al. Microscopic examination of spatial transcriptome using Seq-Scope. Cell 184, 3559–3572 (2021).
Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792 (2022).
Fu, X. et al. Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain. Cell 185, 4621–4633 (2022).
Longo, S. K., Guo, M. G., Ji, A. L. & Khavari, P. A. Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics. Nat. Rev. Genet. 22, 627–644 (2021).
Zhu, K. W. et al. Decoding the olfactory map through targeted transcriptomics links murine olfactory receptors to glomeruli. Nat. Commun. 13, 5137 (2022).
Wang, I. H. et al. Spatial transcriptomic reconstruction of the mouse olfactory glomerular map suggests principles of odor processing. Nat. Neurosci. 25, 484–492 (2022).
Kvastad, L. et al. The spatial RNA integrity number assay for in situ evaluation of transcriptome quality. Commun. Biol. 4, 57 (2021).
Liu, Y. et al. High-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue. Cell 183, 1665–1681 (2020).
Arima, H. & Keiichi, M. Recent findings concerning PAMAM dendrimer conjugates with cyclodextrins as carriers of DNA and RNA. Sensors 9, 6346–6361 (2009).
Larsson, C., Grundberg, I., Söderberg, O. & Nilsson, M. In situ detection and genotyping of individual mRNA molecules. Nat. Methods 7, 395–397 (2010).
Rouhanifard, S. H. et al. ClampFISH detects individual nucleic acid molecules using click chemistry-based amplification. Nat. Biotechnol. 37, 84–89 (2019).
Lein, E. S. et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).
Fan, Y. et al. Expansion spatial transcriptomics. Nat. Methods 20, 1179–1182 (2023).
Chéret, J. et al. Olfactory receptor OR2AT4 regulates human hair growth. Nat. Commun. 9, 3624 (2018).
Littman, R. et al. Joint cell segmentation and cell type annotation for spatial transcriptomics. Mol. Syst. Biol. 17, e10108 (2021).
Zhang, M. et al. Molecularly defined and spatially resolved cell atlas of the whole mouse brain. Nature 624, 343–354 (2023).
Yoon, Y. J. et al. Glutamate-induced RNA localization and translation in neurons. Proc. Natl Acad. Sci. USA 113, E6877–E6886 (2016).
Steward, O. & Worley, P. Local synthesis of proteins at synaptic sites on dendrites: role in synaptic plasticity and memory consolidation? Neurobiol. Learn. Mem. 78, 508–527 (2002).
Kosik, K. S. Life at low copy number: how dendrites manage with so few mRNAs. Neuron 92, 1168–1180 (2016).
Tushev, G. et al. Alternative 3′ UTRs modify the localization, regulatory potential, stability, and plasticity of mRNAs in neuronal compartments. Neuron 98, 495–511 (2018).
Ainsley, J. A., Drane, L., Jacobs, J., Kittelberger, K. A. & Reijmers, L. G. Functionally diverse dendritic mRNAs rapidly associate with ribosomes following a novel experience. Nat. Commun. 5, 4510 (2014).
Nakayama, K. et al. RNG105/caprin1, an RNA granule protein for dendritic mRNA localization, is essential for long-term memory formation. eLife 6, e29677 (2017).
Fu, T. et al. Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response. J. Hematol. Oncol. 14, 98 (2021).
Zhang, Y. et al. Single-cell analyses of renal cell cancers reveal insights into tumor microenvironment, cell of origin, and therapy response. Proc. Natl Acad. Sci. USA 118, e2103240118 (2021).
Su, C. et al. Single-cell RNA sequencing in multiple pathologic types of renal cell carcinoma revealed novel potential tumor-specific markers. Front. Oncol. 11, 719564 (2021).
Kansler, E. R. et al. Cytotoxic innate lymphoid cells sense cancer cell-expressed interleukin-15 to suppress human and murine malignancies. Nat. Immunol. 23, 904–915 (2022).
Sanchez, D. J. & Simon, M. C. Genetic and metabolic hallmarks of clear cell renal cell carcinoma. Biochim. Biophys. Acta Rev. Cancer 1870, 23–31 (2018).
Hsieh, J. J., Le, V., Cao, D., Cheng, E. H. & Creighton, C. J. Genomic classifications of renal cell carcinoma: a critical step towards the future application of personalized kidney cancer care with pan-omics precision. J. Pathol. 244, 525–537 (2018).
Certo, M. et al. Endothelial cell and T‐cell crosstalk: targeting metabolism as a therapeutic approach in chronic inflammation. Br. J. Pharmacol. 178, 2041–2059 (2021).
de Visser, K. E. & Joyce, J. A. The evolving tumor microenvironment: from cancer initiation to metastatic outgrowth. Cancer Cell 41, 374–403 (2023).
Kareva, I. Metabolism and gut microbiota in cancer immunoediting, CD8/Treg ratios, immune cell homeostasis, and cancer (immuno)therapy: concise review. Stem Cells 37, 1273–1280 (2019).
Lewis, S. M. et al. Spatial omics and multiplexed imaging to explore cancer biology. Nat. Methods 18, 997–1012 (2021).
Gulati, G. S. et al. Single-cell transcriptional diversity is a hallmark of developmental potential. Science 367, 405–411 (2020).
Szabo, P. M. et al. Cancer-associated fibroblasts are the main contributors to epithelial-to-mesenchymal signatures in the tumor microenvironment. Sci. Rep. 13, 3051 (2023).
Jiang, F. et al. Simultaneous profiling of spatial gene expression and chromatin accessibility during mouse brain development. Nat. Methods 20, 1048–1057 (2023).
Zhang, J. et al. DNA nanolithography enables a highly ordered recognition interface in a microfluidic chip for the efficient capture and release of circulating tumor cells. Angew. Chem. 132, 14219–14223 (2020).
Vickovic, S. et al. SM-Omics is an automated platform for high-throughput spatial multi-omics. Nat. Commun. 13, 795 (2022).
Liu, Y. et al. High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq. Nat. Biotechnol. 41, 1405–1409 (2023).
Ben-Chetrit, N. et al. Integration of whole transcriptome spatial profiling with protein markers. Nat. Biotechnol. 41, 788–793 (2023).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Dries, R. et al. Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome Biol. 22, 78 (2021).
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).
Yang, M. et al. Spatiotemporal insight into early pregnancy governed by immune-featured stromal cells. Cell 186, 4271–4288 (2023).
Wang, W. et al. Lymphatic endothelial transcription factor TBX1 promotes an immunosuppressive microenvironment to facilitate post-myocardial infarction repair. Immunity 56, 2342–2357 (2023).
Wu, R. et al. Comprehensive analysis of spatial architecture in primary liver cancer. Sci. Adv. 7, eabg3750 (2021).
Aran, D., Hu, Z. & Butte, A. J. xCell: digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 18, 220 (2017).
He, Y., Jiang, Z., Chen, C. & Wang, X. Classification of triple-negative breast cancers based on immunogenomic profiling. J. Exp. Clin. Cancer Res. 37, 327 (2018).
Andreatta, M. & Carmona, S. J. UCell: robust and scalable single-cell gene signature scoring. Comput. Struct. Biotechnol. J. 19, 3796–3798 (2021).
Schubert, M. et al. Perturbation-response genes reveal signaling footprints in cancer gene expression. Nat. Commun. 9, 20 (2018).
Li, R. et al. Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer. Cancer Cell 40, 1583–1599 (2022).
Kuppe, C. et al. Spatial multi-omic map of human myocardial infarction. Nature 608, 766–777 (2022).
Kent, L. N. & Leone, G. The broken cycle: E2F dysfunction in cancer. Nat. Rev. Cancer 19, 326–338 (2019).
Hänzelmann, S., Castelo, R. & Guinney, J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics 14, 7 (2013).
Cao, J. et al. Decoder-seq enhances mRNA capture efficiency in spatial RNA sequencing. Gene Expression Omnibus https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE235896 (2023).