Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients
Kai M. Schmidt-Ott1,2,3,#
1 Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin, Berlin, Germany.
2 Molecular and Translational Kidney Research, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.
3 Berlin Institute of Health, Berlin, Germany.
4 Systems Biology of Gene Regulatory Elements, Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.
5 Physiology of Membrane Transport, Department of Physiology, Christian-Albrechts-Universität, Kiel, Germany.
6 Division of Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, USA.
# Corresponding authors.
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The following features are currently supported in the atlas:
- Gene analysis offers an overview of the single-cell RNA sequencing data and 2D tSNE representation
of the major cell types from Hinze et al. 2020. Clustering can be queried for the expression of a given gene. Gene symbols
are required. Only genes which are expressed in more than 10% of cells in any region (cortex, outer medulla, inner medulla) of a cell type are selectable.
- This is supported by violin plots, showing expression of the selected genes in
major cell types in kidney regions (cortex, outer and inner medulla).
- Spatial expression enables the analysis of in silico spatial gene expression in
collecting duct principal cells (CD-PCs) from dissected samples which were sorted with highly variable genes
(HVGs). Only genes which were expressed in more than 10% of either cortical, outer medullary or inner medullary CD-PCs in dissected samples from Hinze et al. 2020 and which showed consistent spatial
expression when compared to sorting of CD-PCs from Ransick et al. 2019 (Dev Cell 51, 399-413 e397; Spearman correlation coefficient > 0.75 and correlation p-value < 0.001 over pseudospace) are selectable.
The raw (fastq files), as well as processed data
is available at the GEO database under accession number
- tba: GEO data were made available for download.
- 10-Sept-20: Version 1.0 uploaded.