Abstract: FR-OR14
A Cross-Model Single-Cell and Spatial Transcriptomic Atlas of Polycystic Kidney Disease
Session Information
- Cystic Kidney Diseases: Basic and Translational Research
October 25, 2024 | Location: Room 23, Convention Center
Abstract Time: 05:10 PM - 05:20 PM
Category: Genetic Diseases of the Kidneys
- 1201 Genetic Diseases of the Kidneys: Cystic
Authors
- Zimmerman, Kurt, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States
- Miller, Sarah Jane, The University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, United States
- Jiang, Yi, The Ohio State University, Columbus, Ohio, United States
- Stubbs, Jason R., The University of Kansas Medical Center, Kansas City, Kansas, United States
- Ma, Qin, The Ohio State University, Columbus, Ohio, United States
- Ma, Anjun, The Ohio State University, Columbus, Ohio, United States
Background
Polycystic kidney disease (PKD) affects over 12 million people worldwide and is caused by mutations in cilia related genes. In humans, mutations in the PKD1 or PKD2 gene account for about 93% of Autosomal Dominant Polycystic kidney disease (ADPKD) cases, although recent reports highlight that other genes, such as GANAB5, DNAJB116, IFT1407, and ALG98, can also cause an ADPKD phenotype. Further adding to the complexity, different types of genetic mutations are present within the PKD1 and PKD2 family and result in varying disease severity. To model PKD in mice, researchers use both orthologous (i.e. mutations in Pkd1 or Pkd2 gene) and non-orthologous (i.e. Cys1cpk, Ift88, etc) models, which can be either congenic or inducible. Because of this, there is likely significant variation in the cellular and molecular features associated with each mouse model of disease.
Methods
To unbiasedly analyze the cellular and molecular features associated with mouse models of PKD, we generated a single cell RNA sequencing (scRNAseq) atlas comprised of 5 different mouse models of PKD as well as respective non-cystic controls. We also performed spatial transcriptomics on two of the cystic mouse models.
Results
Analyses of scRNAseq data reveal model specific differences in cell type abundance and gene expression. For example, our data indicate that rapidly progressing mouse models of PKD have little S3 nephron segment expansion whereas slowly progressing models have massive S3 nephron expansion, independent of the type of genetic mutation. Further analyses of the data indicate that almost all of the cystic epithelium in all models is derived from the distal nephron. Using the scRNAseq atlas as a reference, we mapped cell-type specific signatures to spatial transcriptomics data and inferred spatially-resolved signaling niches within cystic mice. These analyses identified several ligand-receptor interactions that were significantly enriched within cystic niches including Spp1-Cd44. Loss of Spp1 in one PKD mouse model resulted in worsened cystic disease verify the in vivo relevance of our computational approach.
Conclusion
Our single cell and spatial transcriptomic atlas in mice can be used to identify novel biological targets for treating PKD.
Funding
- NIDDK Support