Predictive Genetics and Multicellular Systems

Life arises out of the dynamic interactions of numerous actors, at the level of cells and at the level of the molecules of which the cells are composed. To understand a biological system, this plurality of actors has to be characterized and formally represented. Technological advances now allow to systematically characterize actors in parallel, for instance the measurement of the full transcriptome of an individual cell or measuring in all cells of an embryo the location and quantity of several proteins. This wealth of data requires computational models to characterize and understand the dynamical behavior, as well as integrate the observations with detailed knowledge of a protein’s biochemical activity, amongst many other kinds of potentially relevant biological knowledge.

We are a interdisciplinary group and we combine both experimental and computational approaches. The research questions revolve around crucial fundamental biological problems that can also yield important applications. At the moment we work on two main projects. First, we aim to improve our understanding of the gene to phenotype map for complex traits. For this project we use the budding yeast Saccharomyces cerevisiae as a model organism. Second, we try to better understand the self organizing behaviour of multicellular systems. Here we use embryogenesis of the roundworm C. elegans as a model. Below both topics are introduced in a bit more detail.

Complex traits

A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. One original motivation behind sequencing the human genome was predicting an individual’s risk of disease from their genome sequence. However, this promise has not yet been fulfilled. Model organisms can be used to readdress this problem. In a model organism such as budding yeast, we can make diverse phenotypic predictions from whole genome sequences, and then crucially we can use large-scale experiments to evaluate the accuracy of these predictions. We currently study how to model the contribution of many genes to so-called complex traits. We employ experimental evolution on a large-scale, in combination with genome and transcriptome sequencing to better understand the process that underlie a trait. The experiments are supplemented by genome-scale modeling of metabolism and other processes.

C. elegans embryogenesis

During development and maintenance of organs and tissues cells move autonomously, and interact with their neighbors to guide cell differentiation. We use the embryogenesis of C. elegans to advance our understanding of these fundamental processes. The roundworm is an excellent model for development; the animal’s transparency makes microscopic observation straightforward, and both the small number of cells and invariant cell lineage make it a tractable system and a powerful model for more complex organisms. These features have made it feasible to follow at high temporal and spatial resolution the complete set of cells as the embryo proceeds through development. This opens up the possibility to develop computational models that can reproduce the observed processes and help identify the key factors that drive them.

Schematic view of movements on the dorsal surface of the C. elegans embryo at 88-cell stage. From Jelier et al. 2016

About the group leader

Rob Jelier studied bioprocess engineering at Wageningen University, specialized in molecular and cellular biology, and graduated in 2002. He then switched to the computational sciences, as he researched data-mining of large bibliographic databases towards his PhD degree, which was awarded at the Erasmus MC in Rotterdam in 2008. He returned to biological research during a post-doctoral fellowship at the EMBL-CRG systems biology department in the group of Ben Lehner in Barcelona, where he pioneered whole genome reverse genetic predictions. He was awarded a BOF-ZAP Research Professor position to join the KU Leuven in October 2013. 

Group members

Michiel Vanslambrouck - PhD student

Wim Thiels - PhD student

Nick Van Looy - PhD student

Casper Van Bavel - PhD student

Keyu Xiao - PhD student

Peter Jonckx - master thesis student CGE

Majid Redouani - master thesis student Bioinformatics

Alumni

Francesca Caroti - Post doctoral researcher -- 2018-2021; Lab tech/Researcher EMBL Heidelberg

Jana Helsen - PhD student -- graduated Februari 2021; Bridging Excellence Fellow (Life Science Alliance) at EMBL Heidelberg - Stanford

Key publications

• Vanslambrouck, M., Thiels, W., Vangheel, J., Smeets, B., Jelier, R., 2024 Image-based force inference by biomechanical simulation, PLoS Comput Biol 20(12):e1012629.
• Van Bavel, C., Thiels, W., Jelier, R., 2023 Cell shape characterization, alignment and comparison using FlowShape. Bioinformatics, btad383.
• Caroti, F., Thiels, W., Vanslambrouck, M., Jelier, R., 2021 Wnt Signaling Induces Asymmetric Dynamics in the Actomyosin Cortex of the C. elegans Endomesodermal Precursor Cell. Front. Cell Dev. Biol. 9:702741
• Thiels, W., Smeets, B., Cuvelier, M., Caroti, F., Jelier, R., 2021 spheresDT/Mpacts-PiCS: cell tracking and shape retrieval in membrane-labeled embryos. Bioinformatics btab557.
• Jankele, R., Jelier, R., Gönczy P., 2021 Physically asymmetric division of the C. elegans zygote ensures invariably successful embryogenesis. eLife 10:e61714.
• Helsen, J., Jelier R., 2021. Experimental evolution to understand the interplay between genetics and adaptation. In: Evolutionary Systems Biology 2.0, Advances in Experimental Medicine and Biology. Springer, New York, NY, 115-134; preprint
• Helsen, J., Voordeckers, K., Vanderwaeren, L., Santermans, T., Tsontaki, M., Verstrepen, K.J., Jelier R. 2020 Gene loss predictably drives evolutionary adaptation. Molecular Biology and Evolution 37 (10), 2989-3002
• Jelier, R*., Krueger, AV., Swoger, J., Zimmermann, T., and Lehner, B*., 2016 Compensatory cell movements confer robustness to mechanical deformation during embryonic development, Cell Syst. 2016 Aug; 3(2):160-71. (* shared corresponding author)
• Jelier, R*., Krueger. AV.*, Dzyubachyk, O., Zimmerman, T., Meijering, EM., Lehner, B., 2015 Comprehensive single cell-resolution analysis of the role of chromatin regulators in early C. elegans embryogenesis.2015; 398 (2): 153–162. (* shared first author)
• Jelier, R., Semple JI., Garcia-Verdugo R., Lehner B., Predicting phenotypic variation in yeast from individual genome sequences. Nat Genet. 2011 Dec; 43(12):1270– 1274.