Modeling spatio-temporal enhancer expression in Drosophila segmentation

Thermodynamic models are a key tool to investigate transcription control in the segmentation of Drosophila. By modeling the binding of transcription factors to DNA sequences and their effect on transcription initiation, thermodynamic models predict expression patterns directly from the enhancer sequence, given the binding motifs and concentrations of all relevant transcription factors (TFs). However, many parameters of the model are impossible to measure, e.g. the interaction strength between the TFs and the core promoter. Hence, it is necessary to estimate these parameters by training the thermodynamic model on known data, i.e. to fit the model predictions to already measured expression patterns of known enhancers. The quality of the parameter training result, evaluated on independent test data, indicates how well the model recapitulates the biological measurements, which can help us to improve our understanding of the underlaying mechanisms of transcription control. Therefore, proper parameter training is a crucial step for the construction of thermodynamic models. In this thesis, I develop a thorough parameter training setup that uses the limited amount of available training data efficiently and reduces parameter overfitting significantly. This optimized training setup applies a global parameter training algorithm, a method to artificially increase the amount of training data, called data augmentation, and parameter penalties, which is a technique to limit overfitting. I apply the novel training setup to expand the scope of thermodynamic models of Drosophila segmentation considerably by incorporating additional TFs into the model, and to investigate many aspects of transcription control in greater detail than it was possible before. Among these topics are the specificity of TF binding motifs, the nature of TF cooperativity and DNA accessibility. With the help of the here developed impact score, I assess the influence of all relevant TFs in silico, delineate the cooperativity range of the key TF bcd, and determine the importance of weak binding sites. Finally, I develop and discuss two alternative models of transcription control that lack the prediction quality of thermodynamic models, but, nevertheless, give valuable insights into the architectural principles of enhancers. This project is part of a larger effort to advance our current understanding of transcription regulation by reconstructing the segmentation network of Drosophila in silico. The results of this thesis facilitate future modeling efforts by optimally leveraging the available data as well as by improving our understanding of thermodynamic models

On the epigenetic ageing clock in humans

Epigenetic clocks are mathematical models that predict the biological age of an organism using DNA methylation data, and which have emerged in the last few years as the most accurate biomarkers of the ageing process. However, little is known about the molecular mechanisms that control the rate of such clocks. In this thesis I focus on the study of the epigenetic ageing clock in humans. First, I review and benchmark statistical and computational tools required for the analysis of DNA methylation data in the context of human ageing. Next, I validate the performance of the Horvath epigenetic clock, the most widely used multi-tissue epigenetic clock in humans, in a control blood dataset and test its behaviour in patients with a variety of developmental disorders, which harbour mutations in proteins of the epigenetic machinery. I demonstrate that loss-of-function mutations in the H3K36 methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic ageing. Furthermore, I show that the normal ageing process and Sotos syndrome share methylation changes and the genomic context in which they happen. These results suggest that the H3K36 methylation machinery is a key component of the epigenetic maintenance system in humans, which controls the rate of epigenetic ageing, and this role seems to be conserved in model organisms. Finally, I provide a technological strategy to make epigenetic clocks (or any DNA methylation-based mathematical models) more cost-effective by exploiting the ability of restriction enzymes to perform genomic enrichment. This thesis provides novel insights (statistical, biological, technological) into the epigenetic ageing clock in humans, which will help to shed light on the different processes that erode the human epigenetic landscape during ageing.EMBL PhD programm

An Agent-Based Model of the IL-1 Stimulated Nuclear Factor-kappa B Signalling Pathway

The transcription factor NF-κB is a biological component that is central to the regulation of genes involved in the innate immune system. Dysregulation of the pathway is known to be involved in a large number of inflammatory diseases. Although considerable research has been performed since its discovery in 1986, we are still not in a position to control the signalling pathway, and thus limit the effects of NF-κB within promotion of inflammatory diseases. We believe that computational modelling and simulation of the NF-κB signalling pathway will complement wet-lab experimental approaches, and will facilitate a more comprehensive understanding of this example of a complex biological system. In this study, we have developed an agent-based model of the IL-1 stimulated NF-κB signalling pathway, which has been calibrated to wet- lab data at the single-cell level. Through rigorous software engineering, which followed a principled approach to design and development by adherence to the CoSMoS process, we believe our model provides an abstracted view of the underlying real-world system, and can be used in a predictive capacity through in silico experimentation. A novel approach to domain modelling has been presented, which uses linear and multivariate statistical techniques to complement the Unified Modelling Language. Furthermore, in silico experimentation with the newly developed agent-based model, has confirmed the robust yet fragile nature of the signalling pathway. We have discovered that the pathway is robust to perturbations of cell membrane receptor component number, intermediate component number, and the temporal lag between cell membrane receptor activation and subsequent activation of IKK. Conversely however, in silico experimentation predicts that the pathway is sensitive to changes in the ratio of free IκBα to NF-κB, and fragile to basal dissociation of NF-κB-IκBα outside of a narrow range of probabilities

Non-coding genome contributions to the development and evolution of mammalian organs

Protein-coding sequences only cover 1-2% of a typical mammalian genome. The remaining non-coding space hides thousands of genomic elements, some of which act via their DNA sequence while others are transcribed into non-coding RNAs. Many well-characterized non-coding elements are involved in the regulation of other genes, a process essential for the emergence of different cell types and organs during development. Changes in the expression of conserved genes during development are in turn thought to facilitate evolutionary innovation in form and function. Thus, non-coding genomic elements are hypothesized to play important roles in developmental and evolutionary processes. However, challenges related to the identification and characterization of these elements, in particular in non-model organisms, has limited the study of their overall contributions to mammalian organ development and evolution. During my dissertation work, I addressed this gap by studying two major classes of non-coding elements, long non-coding RNAs (lncRNAs) and cis-regulatory elements (CREs). In the first part of my thesis, I analyzed the expression profiles of lncRNAs during the development of seven major organs in six mammals and a bird. I showed that, unlike protein-coding genes, only a small fraction of lncRNAs is expressed in reproducibly dynamic patterns during organ development. These lncRNAs are enriched for a series of features associated with functional relevance, including increased evolutionary conservation and regulatory complexity, highlighting them as candidates for further molecular characterization. I then associated these lncRNAs with specific genes and functions based on their spatiotemporal expression profiles. My analyses also revealed differences in lncRNA contributions across organs and developmental stages, identifying a developmental transition from broadly expressed and conserved lncRNAs towards an increasing number of lineage- and organ-specific lncRNAs. Following up on these global analyses, I then focused on a newly-identified lncRNA in the marsupial opossum, Female Specific on chromosome X (FSX). The broad and likely autonomous female-specific expression of FSX suggests a role in marsupial X-chromosome inactivation (XCI). I showed that FSX shares many expression and sequence features with another lncRNA, RSX — a known regulator of XCI in marsupials. Comparisons to other marsupials revealed that both RSX and FSX emerged in the common marsupial ancestor and have since been preserved in marsupial genomes, while their broad and female-specific expression has been retained for at least 76 million years of evolution. Taken together, my analyses highlighted FSX as a novel candidate for regulating marsupial XCI. In the third part of this work, I shifted my focus to CREs and their cell type-specific activities in the developing mouse cerebellum. After annotating cerebellar cell types and states based on single-cell chromatin accessibility data, I identified putative CREs and characterized their spatiotemporal activity across cell types and developmental stages. Focusing on progenitor cells, I described temporal changes in CRE activity that are shared between early germinal zones, supporting a model of cell fate induction through common developmental cues. By examining chromatin accessibility dynamics during neuronal differentiation, I revealed a gradual divergence in the regulatory programs of major cerebellar neuron types. In the final part, I explored the evolutionary histories of CREs and their potential contributions to gene expression changes between species. By comparing mouse CREs to vertebrate genomes and chromatin accessibility profiles from the marsupial opossum, I identified a temporal decrease in CRE conservation, which is shared across cerebellar cell types. However, I also found differences in constraint between cell types, with microglia having the fastest evolving CREs in the mouse cerebellum. Finally, I used deep learning models to study the regulatory grammar of cerebellar cell types in human and mouse, showing that the sequence rules determining CRE activity are conserved across mammals. I then used these models to retrace the evolutionary changes leading to divergent CRE activity between species. Collectively, my PhD work provides insights into the evolutionary dynamics of non-coding genes and regulatory elements, the processes associated with their conservation, and their contributions to the development and evolution of mammalian cell types and organs

Systematic human/zebrafish comparative identification of cis-regulatory activity around vertebrate developmental transcription factor genes

AbstractPan-vertebrate developmental cis-regulatory elements are discernible as highly conserved noncoding elements (HCNEs) and are often dispersed over large areas around the pleiotropic genes whose expression they control. On the loci of two developmental transcription factor genes, SOX3 and PAX6, we demonstrate that HCNEs conserved between human and zebrafish can be systematically and reliably tested for their regulatory function in multiple stable transgenes in zebrafish, and their genomic reach estimated with confidence using synteny conservation and HCNE density along these loci. HCNEs of both human and zebrafish function as specific developmental enhancers in zebrafish. We show that human HCNEs result in expression patterns in zebrafish equivalent to those in mouse, establishing zebrafish as a suitable model for large-scale testing of human developmental enhancers. Orthologous human and zebrafish enhancers underwent functional evolution within their sequence and often directed related but non-identical expression patterns. Despite an evolutionary distance of 450 million years, one pax6 HCNE drove expression in identical areas when comparing zebrafish vs. human HCNEs. HCNEs from the same area often drive overlapping patterns, suggesting that multiple regulatory inputs are required to achieve robust and precise complex expression patterns exhibited by developmental genes