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| Status |
Public on Oct 10, 2022 |
| Title |
An atlas of healthy and injured cell states and niches in the human kidney [Slide-seq2] |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
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| Overall design |
Slide-Seq2 was performed on kidney (cortex and medulla) tissue pucks from six healthy reference (Ref) individuals. This data was produced as part of the Human BioMolecular Atlas Program (HuBMAP - in the labs of Fei Chen and Evan Macosko) and Kidney Precision Medicine Project (KPMP - in the labs of Fei Chen and Anna Greka).
>>> Submitter declares that the raw data are deposited in HuBMAP due to patient privacy concerns. <<<
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| Contributor(s) |
Lake BB, Kalhor K, Murray E, Knoten A, Salamon D, Gaut JP, Marshall JL, Noel T, Greka A, Chen F, Macosko EZ, Zhang K, Jain S |
| Citation(s) |
37468583 |
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| Submission date |
Sep 02, 2021 |
| Last update date |
Aug 07, 2023 |
| Contact name |
Kun Zhang |
| Organization name |
UCSD
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| Street address |
9500 Gilman Drive
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| City |
La Jolla |
| State/province |
California |
| ZIP/Postal code |
92093 |
| Country |
USA |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (67)
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| This SubSeries is part of SuperSeries: |
| GSE183279 |
An atlas of healthy and injured cell states and niches in the human kidney |
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| Relations |
| BioProject |
PRJNA759873 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE183274_RAW.tar |
3.4 Gb |
(http)(custom) |
TAR (of CSV, MTX, RDS, TSV, TXT) |
SRA Run Selector |
| Raw data not provided for this record |
| Processed data provided as supplementary file |
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