Clustering and gene expression in baseline kidney samples. PT - proximal tubules, TAL - thick ascending limb, DCT - distal convoluted tubule, CNT - connecting tubule, CD-PC/IC - collecting duct principal/intercalated cells.
Left panel: In silico prediction of spatial gene expression in CD-PCs. Shown is the averaged in silico prediction from Hinze et al. 2020 and Ransick et al. 2019 (Dev Cell 51, 399-413 e397). Shades represent the standard error of mean. Right panel: Regional distribution of sorting of CD-PCs from dissected cortex, outer medulla (OM) and inner medulla (IM) from Hinze et al. 2020 using highly variable genes and 100 spatial positions. The percentage of all CD-PCs expressing the respective gene in dissected samples of Hinze et al. 2020 is depicted above the plot.

Kidney single-cell transcriptomes predict spatial corticomedullary gene expression and tissue osmolality gradients


Christian Hinze1,2,3, Nikos Karaiskos4, Anastasiya Boltengagen4, Katharina Walentin2, Klea Redo1,2, Nina Himmerkus5, Markus Bleich5, Steve Potter6, Andrew Potter6, Kai-Uwe Eckardt1,3, Christine Kocks4, Nikolaus Rajewsky4,#, 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.

This interface was created and is maintained by Christian Hinze.

Features

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.

Data availability

The raw (fastq files), as well as processed data is available at the GEO database under accession number GSE145690.

Release notes

  • tba: GEO data were made available for download.
  • 10-Sept-20: Version 1.0 uploaded.