2025-04-04
Zhang Li, Raksha P. Hombal, Jun Wang, Sreelakshmi Cherakara, Timothy C. Howton, Kurt A. Zimmerman, James F. Collawn, Reagan S. Andersen, Courtney J. Haycraft, Mandy J. Croyle, John M. Parant, Brittany N. Lasseigne and Bradley K. Yoder
Renal cyst formation occurs due to loss of cilia localized polycystin proteins (e.g., Pkd1 or Pkd2) or ciliary structure (e.g., Ift88 or Kif3a). However, cyst progression is more rapid in polycystin mutant mice compared to cilia mutant mice, and loss of cilia in the polycystin mutant background (e.g., Pkd2 and Kif3a mutation) greatly attenuates cyst development. This led to the proposal that the polycystins function to repress a cyst promoting pathway that is dependent on an intact cilium, this is referred to as the Cilia-Dependent Cyst Activating (CDCA) pathway. Renal macrophages are also involved in regulating cyst progression, but it is unknown whether this occurs through the CDCA or separate pathway. Here, we performed scRNA-seq on CD45+ cells from Pkd2 and Pkd2/Ift88 mouse kidneys to compare the macrophage populations.
This project uses CAPTURE v0.6.0 and SingularityCE v4.1.2 to ensure reproducibility.
Most scripts are designed to work on our HPC which uses Slurm as a queueing system. If you are working on an HPC which uses a different scheduler (or locally), modifications will need to be made to the “slurm_job.sh” scripts.
Links will take you to the necessary Docker image reference on Dockerhub that can be pulled with singularity to create the appropriate .sif file.
For example:
cd yoder-sc-macros/bin/docker
singularity pull docker://tchowton/yoder_sc_macros:1.2.0
Scripts can be submitted using the CAPTURE command cap run.
For example:
cap run src/00_download.sh
This script downloads the scRNA-seq data set used in this project as well as the 10x Genomics mouse reference.
This script creates the configuration files for the cellranger multi pipeline.
This script runs the cellranger multi pipeline.
This script generates the samplesheet used to create the seurat objects in the 04_seurat_preprocessing.R script.
This script creates the seurat objects for yoder sc macro datasets. It performs qc and filtering and integration with Harmony.
This script runs FindAllMarkers() to ID cluster specific genes and subset the list to the top 10 genes per cluster.
This script assigned cell type IDs to the harmony clusters to create the labeled seurat object.
This script generates the cell proportions by cell type plot
This script generates the sample pca for the DKO and PKD2 data sets
This script creates a heatmap of z scores of the mean expression of samples by genes for DKO and PKD2 for KRMs and IMs.
The script performs differential expression with DESeq2 in pseudobulked expression for DKO and PKD2.
This script performs pathway enrichment using gprofiler2 on the DGE results.
What is Happening in the Lasseigne Lab?
Polycystic Kidney Disease Research Foundation Fellowship 959949 (Z.L.) Polycystic Kidney Disease Research Foundation grant 214g16a (B.K.Y.) National Institutes of Health (NIH) R01 DK115752 (B.K.Y.) NIH R01 DK134310 (B.N.L.) PKD Foundation Research Grant (B.N.L.)
Tabea M. Soelter and Elizabeth J. Wilk in the Lasseigne Lab for suggestions and code review of the scRNA-seq analysis
This repository is licensed under the MIT License, see LICENSE documentation within this repository for more details.