4.8 Article

Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging

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NATURE METHODS
卷 19, 期 12, 页码 1622-+

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NATURE PORTFOLIO
DOI: 10.1038/s41592-022-01673-2

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资金

  1. NIDDK Hematology Centers Pilot and Feasibility Grant [U24DK126127-01]
  2. Bullock-Wellman postdoctoral fellowship award
  3. Swedish Research Council International Postdoc award
  4. International Postdoc grant from the Swedish Research Council [2018-06724]
  5. [R01 CA194596]
  6. [R01 DK115577]
  7. [R01 DK123216]
  8. [P01 HL142494]
  9. Swedish Research Council [2018-06724] Funding Source: Swedish Research Council

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Image-seq is a technology that allows single-cell transcriptional data to be obtained from cells isolated from specific spatial locations under image guidance, preserving the spatial information of the cells. It can be used with in situ and in vivo imaging to document the temporal and dynamic history of the cells being analyzed. This technology combines spatial information with highly sensitive RNA sequencing, providing valuable insights into cellular organization and function.
Image-seq isolates cells from specific tissue locations under image guidance for analysis by single-cell RNA sequencing. The technique can be combined with in vivo imaging to document the temporal and dynamic history of the cells prior to sequencing. Tissue function depends on cellular organization. While the properties of individual cells are increasingly being deciphered using powerful single-cell sequencing technologies, understanding their spatial organization and temporal evolution remains a major challenge. Here, we present Image-seq, a technology that provides single-cell transcriptional data on cells that are isolated from specific spatial locations under image guidance, thus preserving the spatial information of the target cells. It is compatible with in situ and in vivo imaging and can document the temporal and dynamic history of the cells being analyzed. Cell samples are isolated from intact tissue and processed with state-of-the-art library preparation protocols. The technique therefore combines spatial information with highly sensitive RNA sequencing readouts from individual, intact cells. We have used both high-throughput, droplet-based sequencing as well as SMARTseq-v4 library preparation to demonstrate its application to bone marrow and leukemia biology. We discovered that DPP4 is a highly upregulated gene during early progression of acute myeloid leukemia and that it marks a more proliferative subpopulation that is confined to specific bone marrow microenvironments. Furthermore, the ability of Image-seq to isolate viable, intact cells should make it compatible with a range of downstream single-cell analysis tools including multi-omics protocols.

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