Open Collections

Heydari, Tiam

University of British Columbia

This thesis explores two key aspects of stem cell research and gene regulation. The first part introduces IQCELL, a platform that I developed to analyze single cell RNA sequencing (scRNA-seq) data and infer executable logical Gene Regulatory Networks (GRNs). By simulating these GRNs, IQCELL enables the investigation of developmental programs and aids in the development of strategies to manipulate stem cell fate. The architecture of IQCELL is described, followed by its application to scRNA-seq datasets from early mouse T-cell and red blood cell development. The results demonstrate that IQCELL can accurately infer a substantial portion (over 74%) of previously reported causal gene interactions and simulate the effects of known gene perturbations. Additionally, an IQCELL gene selection pipeline is implemented, allowing the identification of candidate genes without prior knowledge. The simulations based on the inferred gene set yield comparable results to the original curated lists. The second part of the thesis focuses on characterizing the collective order of stem cells based on their entropy levels and the relationship between ordered system states. Specifically, the research explores the impact of cell density and Bone Morphogenetic Protein 4 (BMP4) ligands on the coordinated state of stem cells. Through analyzing the dynamics of gene expression, a minimal functional mathematical model of colonies is developed. This model serves to identify and implement mechanisms for controlling collective outcomes in stem cell colonies. By leveraging the insights gained from gene expression dynamics, the research provides a means to manipulate the collective behavior of stem cells. By combining these two approaches, the thesis offers a comprehensive framework for studying stem cell fate determination. The IQCELL platform facilitates the inference and simulation of GRNs, providing insights into the underlying gene interactions, while the analysis of collective order and gene expression dynamics enhances our understanding of how stem cells coordinate and respond to environmental cues. Together, these findings contribute to the advancement of stem cell research and the development of strategies for controlling stem cell fate.

Text

2025-03-31

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/86032

Biomedical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/