Mathematical modelling of cis-regulatory landscapes

Dr. Edda Schulz

The Schulz lab studies epigenetic regulation with a systems biology approach. We seek to understand how threshold responses can establish transcriptional switches and epigenetic memory to allow quantitative information processing in mammalian cells. We use X-chromosome inactivation as a model to study epigenetic regulation, which is an essential developmental process. We complement our work on this biological question with synthetic biology approaches to uncover general rules that underlie quantitative gene control in mammalian cells. To solve fundamental problems in gene regulation we combine microscopy, genomics and genome engineering with mathematical modeling and computational biology.

 

This research project delves into the broader question of how multiple enhancers quantitatively orchestrate the regulation of a specific gene, necessitating a data-driven mathematical modeling approach. The central inquiry revolves around understanding the nuanced interplay of cis-regulatory elements (CREs) and their relative contributions to the quantitative control of gene expression.

The investigation begins with the development of a stochastic mathematical model that captures the intricate dynamics of gene regulation by multiple enhancers. Leveraging existing datasets within our laboratory, the project focuses on a paradigmatic case — the regulation of the Xist gene, the master regulator of X-chromosome inactivation.

Utilizing data from a non-coding CRISPR screen (Gjaltema*, Schwämmle* et al, Mol Cell, 2022), reporter assays depicting CRE activities, and perturbation experiments involving CRE knock-downs and knock-outs, the project aims to quantify how the temporal dynamics and contact probabilities of CREs with the Xist promoter influence Xist expression. Additionally, single-cell time course data (scRNA-seq) will be employed to parameterize the mathematical model (Pacini et al, Nat Comm, 2021), offering a comprehensive understanding of the quantitative aspects of Xist regulation.

We invite ambitious students with backgrounds in physics, bioinformatics, or biology, particularly those experienced in mathematical modeling of biological systems, to contribute to unraveling the intricate dynamics of gene regulation. Through this project, we aim to not only address fundamental questions about enhancer-driven gene control but also unravel the specific quantitative mechanisms governing Xist expression in the context of X chromosome inactivation.

 

For some of our recent work related to the project, please refer to:

Gjaltema RAF*, Schwämmle T*, Kautz P, Robson M, Schöpflin R, Lustig LR, Brandenburg L, Dunkel I, Vechiatto C, Ntini E, Mutzel V, Schmiedel V, Marsico A, Mundlos S, Schulz EG., Distal and proximal cis-regulatory elements sense X-chromosomal dosage and developmental state at the Xist locus, Molecular Cell (2022) 82, 190-208

 

Pacini, G, Dunkel, I, Mages, N, Mutzel, V, Timmermann, B, Marsico, A, and Schulz, E G, Integrated analysis of Xist upregulation and X-chromosome inactivation with single-cell and single-allele resolution, Nature Communications 2021, 12.1, 1–17.

 

Mutzel V & Schulz EG, Dosage Sensing, Threshold Responses, and Epigenetic Memory: A Systems Biology Perspective on Random X‐Chromosome Inactivation, BioEssays 2020 Apr;42(4):e1900163

 

Mutzel V, Okamoto I, Dunkel I, Saitou M, Giorgetti L, Heard E, Schulz EG, A symmetric toggle switch explains the onset of random X inactivation in different mammals, Nature Structural and Molecular Biology 2019 May;26(5):350-360. Epub 2019 Apr 8.

 

For further information on the lab and the Institute, visit the website of the Schulz lab.

 

Right: Mouse embryo at the 8-cell stage stained for the Xist RNA (green) and another X-linked gene (pink) © E. Schulz