Highly Constrained Kinetic Models for Quantitative Single-Cell Gene Expression Analysis

Cells are for the most part genetically identical, and it is the gene expression which determines different cell types in the body. Transcription, the first step in gene expression, is a complex, multi-step process initiated by transcription factors (TFs) binding to DNA promoter regions, followed by recruitment of proteins like chromatin remodelers, general transcription factors, and RNA polymerase II in eukaryotes. Variability in transcriptional outcomes arises from both regulatory mechanisms and stochastic events, making it essential to understand transcription dynamics to better grasp heterogeneity within gene regulatory networks. This dissertation investigates transcription from a kinetic biochemical perspective, leveraging steady-state and kinetic gene data. I hypothesize that single-cell variation can be utilized to infer dynamic mechanisms of transcriptional regulation. I employ single-cell RNA sequencing (scRNA-seq) and single-molecule Fluorescence in situ Hybridization (smFISH) to quantify mRNA levels, alongside live-cell imaging to measure TF dwell time and transcriptional bursting kinetics. By integrating these methods into a computational model, we aim to simulate transcriptional dynamics and assess existing models, such as the telegraph and kinetic proofreading models, in capturing regulatory steps. This research offers insights into transcriptional regulation and its implications for disease, while improving gene expression prediction models in molecular biology. In conclusion, gene expression and regulation are highly dependent on the biochemical aspects of the proteins associated with transcription. A thorough study of transcriptional mechanisms will help us understand multiple diseases that are caused by mis-regulation of transcription. Furthermore, a robust model that can mimic the multiple-step transcription mechanism will also help us quantitatively analyze single-cell gene expression, which is an emerging problem in molecular biology.

Department dc:contributor.department

Biology

Year dc:date.issued

2025

Author dc:creator

• Cho, Hyeon Jin

Advisors dc:contributor.advisor

• Patro, Rob
• Larson, Daniel

Language dc:language.iso

en

Identifier

https://doi.org/10.13016/lhcf-oztx

OAI identifier oai:identifier

oai:drum.lib.umd.edu:1903/34202