Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging.
IF: 47.990
Cited by: 8


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.



MeSH terms

Diagnostic Imaging
Sequence Analysis, RNA
Cell Count
Gene Library
Tumor Microenvironment


Haase, Christa
Gustafsson, Karin
Mei, Shenglin
Yeh, Shu-Chi
Richter, Dmitry
Milosevic, Jelena
Turcotte, Raphaël
Kharchenko, Peter V
Sykes, David B
Scadden, David T
Lin, Charles P