Cell-type-specific expression and regulation in atypical Schinzel Giedion Syndrome (SGS)

Jordan Whitlock, Tabea Soelter, Timothy Howton, Elizabeth Wilk, Vishal Oza, Brittany Lasseigne 2023

The University of Alabama at Birmingham (UAB), Heersink School of Medicine

Data Availability

All data for this project is publicly available:

• GEO:

• SRA:

• Repository:

• Docker:

• Data:

• Cell-type-specific PANDA Networks:

  • kidney:
  • cerebral cortex:

Citation

Whitlock, Jordan H., Tabea M. Soelter, Timothy C. Howton, Elizabeth J. Wilk, Vishal H. Oza, and Brittany N. Lasseigne. 2023. “Cell-Type-Specific Gene Expression and Regulation in the Cerebral Cortex and Kidney of Atypical Setbp1S858R Schinzel Giedion Syndrome Mice.” Journal of Cellular and Molecular Medicine.

Authors

The Lasseigne Lab

• @jordanwhitlock

• @tsoelter

• @vishaloza

• @tchowton

• @lizzyjoan

• @blasseigne

Overview

Approach

This repository provides a framework for investigating the cell-type-specific impact of genetic variants on gene expression and regulation.

Here we provide code and data used to investigate SETBP1’s role as an epigenetic hub contributing to cell-type-specific differences in expression, TF activity, gene targeting, and regulatory rewiring:

• Process 10X single-nuclei RNA-sequencing data using Cell Ranger
• Perform Quality Control and process data with Seurat
• Assess TF Activity of SETBP1 and other TFs of interest (decoupleR)
• Construct cell-type-specific bi-partite TF-gene regulatory networks using message passing algorithm PANDA
• Carry out downstream network analyses
  • Differential Community Detection (ALPACA)
  • Differential Gene Targeting
  • Network Rewiring

Funding

This work was supported in part by the UAB Lasseigne Lab funds, UAB Pilot Center for Precision Animal Modeling (C-PAM)(1U54OD030167), the UAB Predoctoral Training Grant in Cell, Molecular, and Developmental Biology (CMDB T32)(5T32GM008111-35

Acknowledgements

The authors thank the Lasseigne Lab members Amanda Clark, Tabea Soelter, Emma Jones, and Victoria Flanary for their feedback throughout this study. We also thank the UAB Biological Data Science group (RRID:SCR_021766) for providing a script for helping to run containers on the UAB high-performance cluster (https://github.com/U-BDS/training_guides/blob/main/run_rstudio_singularity.sh).

License

This repository is licensed under the MIT License, see LICENSE documentation within this repository for more details.