Spatially resolved single-cell RNA-sequencing reveals expression heterogeneity in tumor microenvironment
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Summary:
To better understand how individual cells function within an anatomical space, we developed XYZeq, a novel scRNA-seq workflow that uses combinatorial indexing in microwells to encode spatial metadata into scRNA-seq libraries. We used XYZeq to profile heterotopic mouse liver and spleen tumor models to capture transcriptomes from tens of thousands of cells across a total of eight tissue slices.Overall design:
Spatially resolved single-cell RNA-sequencing from eight tissue sections of MC38-injected liver and spleen organs (samples L30C and L30C8 are from the same slice). Additional experiments using cell lines and comparing to droplet-based single-cell RNA-seq.Technology:
XYZeq
Platform:
GPL21103
Species:
Homo sapiens(hg38)
Mus musculus(mm10)
Cell types:
mouse cell line:3T3, human cell line:HEK293T
Citation:
Lee, Youjin et al. “XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment.” Science advances vol. 7,17 eabg4755. 21 Apr. 2021, doi:10.1126/sciadv.abg4755Submission date: 2021-01-07Update date: 2021-05-12
Sample number: 12Section number: 12
Contributors
Y Lee; D Bogdanoff; Y Wang; G Hartoularos; A Marson; E D Chow; C J Ye
Contact: george.hartoularos@ucsf.edu
Accessions
GEO Series Accessions:
GSE164430