Description

This track displays data from Spatiotemporal immune zonation of the human kidney. Droplet-based single-cell RNA sequencing (scRNA-seq) was used to profile 40,268 mature human kidney cells. After principal component analysis, identified clusters were manually curated into four major cellular compartments using canonical markers as found in Stewart et al., 2019: endothelial, immune, fibroblast, and epithelium.

This track collection contains six bar chart tracks of RNA expression in the human kidney where cells are grouped by merged cell type (Kidney Cells), broad cell type (Kidney Broad CT), detailed cell type (Kidney Details), compartment (Kidney Compartment), experiment (Kidney Experiment), and project (Kidney Project). The default track displayed is Kidney Cells.

Display Conventions

The cell types are colored by which class they belong to according to the following table.

Cells that fall into multiple classes will be colored by blending the colors associated with those classes.

Data Access

The raw bar chart data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Method

14 mature healthy human kidney samples were obtained from individuals (ages 1-72) that either underwent tumor nephrectomy (n=10) or from kidneys donated for transplantation (n=4) but were unsuitable for use. Kidney tissues from tumor nephrectomies were collected from unaffected areas estimated to be corticomedullary. Samples were enzymatically dissociated and enriched for live cells (experiment set 1) or enriched for leukocytes with a density gradient and then for live cells (experiment set 2). Single cell libraries were prepared using 10x Genomics 3' v2 kit and sequenced on an Illumina HiSeq4000.

The cell/gene matrix and cell-level metadata was downloaded from the UCSC Cell Browser. The UCSC command line utility matrixClusterColumns, matrixToBarChart, and bedToBigBed were used to transform these into a bar chart format bigBed file that can be visualized. The coloring was done by defining colors for the broad level cell classes and then using another UCSC utility, hcaColorCells, to interpolate the colors across all cell types. The UCSC utilities can be found on our download server.

Data Access

The raw bar chart data can be explored interactively with the Table Browser or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Credit

Thanks to Benjamin J Stewart, John R Ferdinand, and to the many authors who worked on producing and publishing this data set. The data were integrated into the UCSC Genome Browser by Jim Kent and Brittney Wick then reviewed by Daniel Schmelter. The UCSC work was paid for by the Chan Zuckerberg Initiative.

References

Stewart BJ, Ferdinand JR, Young MD, Mitchell TJ, Loudon KW, Riding AM, Richoz N, Frazer GL, Staniforth JUL, Vieira Braga FA et al. Spatiotemporal immune zonation of the human kidney. Science. 2019 Sep 27;365(6460):1461-1466. PMID: 31604275; PMC: PMC7343525