Abstract:
:Single-cell RNA sequencing (scRNA-seq) enables the systematic identification of cell populations in a tissue, but characterizing their spatial organization remains challenging. We combine a microarray-based spatial transcriptomics method that reveals spatial patterns of gene expression using an array of spots, each capturing the transcriptomes of multiple adjacent cells, with scRNA-Seq generated from the same sample. To annotate the precise cellular composition of distinct tissue regions, we introduce a method for multimodal intersection analysis. Applying multimodal intersection analysis to primary pancreatic tumors, we find that subpopulations of ductal cells, macrophages, dendritic cells and cancer cells have spatially restricted enrichments, as well as distinct coenrichments with other cell types. Furthermore, we identify colocalization of inflammatory fibroblasts and cancer cells expressing a stress-response gene module. Our approach for mapping the architecture of scRNA-seq-defined subpopulations can be applied to reveal the interactions inherent to complex tissues.
journal_name
Nat Biotechnoljournal_title
Nature biotechnologyauthors
Moncada R,Barkley D,Wagner F,Chiodin M,Devlin JC,Baron M,Hajdu CH,Simeone DM,Yanai Idoi
10.1038/s41587-019-0392-8subject
Has Abstractpub_date
2020-03-01 00:00:00pages
333-342issue
3eissn
1087-0156issn
1546-1696pii
10.1038/s41587-019-0392-8journal_volume
38pub_type
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