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| Status |
Public on Mar 01, 2022 |
| Title |
Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling [human kidney] |
| Organism |
Homo sapiens |
| Experiment type |
Other
|
| Summary |
Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene or protein expression. Here we describe expanded chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probe pools targeting the protein-coding genes in the human and mouse transcriptomes, hereafter referred to as the human or mouse Whole Transcriptome Atlas (WTA). We validated the human and mouse WTA assays using cell lines to demonstrate concordance with orthogonal gene expression profiling methods in profiled region sizes ranging from ∼10-500 cells. By benchmarking against bulk RNAseq and single-molecule fluorescence in situ hybridization, we demonstrate robust transcript detection possible down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. We show that spatial profiling with WTA can detect expected spatial gene expression differences between tumor and tumor microenvironment, identify spatial disease-specific heterogeneity in gene expression in histological structures of the human kidney, and comprehensively map transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.
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| Overall design |
This dataset contains RNA expression from regions of 7 FFPE human kidneys using the human Whole Transcriptome Atlas for Digital Spatial Profiling
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| Contributor(s) |
Zimmerman S |
| Citation(s) |
36100434 |
| |
| Submission date |
Dec 03, 2021 |
| Last update date |
Jan 06, 2023 |
| Contact name |
Stephanie Zimmerman |
| E-mail(s) |
[email protected]
|
| Organization name |
NanoString Technologies
|
| Street address |
530 Fairview Ave N
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| City |
Seattle |
| State/province |
WA |
| ZIP/Postal code |
98109 |
| Country |
USA |
| |
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| Platforms (1) |
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| Samples (273)
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| This SubSeries is part of SuperSeries: |
| GSE190089 |
Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling |
|
| Relations |
| BioProject |
PRJNA785816 |
| SRA |
SRP349103 |
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