Genetic and transcriptional studies have demonstrated that shared aetiology between immune-mediated diseases (IMD) is reflected in shared patterns in both data types, and suggested new targets for treatment. However, the huge number of variants and genes measured mean that only a minority of potential information in these data has been harnessed, and disease prognosis and treatment success remains variable and unpredictable. My goal is to overcome this dimensional challenge by developing genomic feature engineering which exploits these shared patterns, to extract new insight from jointly analysing over a hundred existing datasets. I will generate summary features by tailoring dimension-reduction strategies and applying them to genetic and transcriptomic data from patients and cohorts with related traits measured. I will investigate how each feature contributes to rare and common IMD risk, and prognostic variability within diseases. I will correlate features with molecular measurements and clinical data to understand the gene products they represent, and the situations (cell type, disease state/subtype) in which they are relevant. Finally, through predictive modeling, I will explore the expected impact of targeting these gene products in different diseases and subtypes, to generate, and test, hypotheses about which targets might modify specific IMD activity or progression. Genetic and transcriptional studies of immune-mediated diseases (IMD) have demonstrated complex sharing of features between these diseases, suggested new treatments, and collectively generated data on 100,000s of IMD patients. However, successes have been limited because huge sample sizes are required to robustly assess the millions of genetic variants or thousands of genes measured. Disease prognosis and treatment success in IMD remain variable and unpredictable. I will mine these data across diseases, to generate orders of magnitude fewer summary features describing shared IMD factors in a more parsimonious manner. I will use molecular measurements and clinical data to understand the gene products the features represent, and their relevant contexts (cell type, disease state/subtype). Through this targeted feature engineering, I aim to describe the relationships between different IMD, both common and rare, and identify new therapeutic treatment targets or diseases/disease-subtypes where existing treatments may be newly applicable.

To understand how the genome directs development, we need to know the cell-to-cell changes in genomic activity at individual loci and how changes are regulated. Advances in single-cell profiling provide a new ability to determine the regulatory configuration of individual cells genome-wide through profiling gene expression and chromatin accessibility. However, determining the connections between mother and daughter cells remains difficult. The invariant and known cell lineage of C. elegans solves this problem, making it possible with single-cell profiling to determine locus-specific activity in every cell from the zygote to the differentiated state. In Aim 1 we study the early events of genome quiescence, zygotic genome activation (ZGA), and lineage commitment by profiling all cells from the zygote to the 26-cell stage, and germ cells through their later ZGA. In Aim 2 we use the 20-cell intestine as a paradigm to study progression through a complete developmental trajectory. We will investigate mechanisms of key transitions and further study the relationship of activity patterns to genome 3D structure. In Aim 3, we focus on the impacts and regulation of active and PRC2/Polycomb chromatin domains. Our work will impact understanding of core principles of genome regulation relevant across animals. During animal development, the single celled embryo has the remarkable ability to give rise to all of the different cells and tissues of the organism, directed by instructions in the genome sequence. As new cells are produced, their identities are progressively defined by patterns of activation and repression of the genome, which generates correct gene expression programmes. We do not yet know this progressive series of events in any animal. Recent technical advances have made it possible to map which regions of the genome are active in individual cells (single-cell profiling). We will use this technology to study development in the nematode C. elegans, which has just 959 body cells. We will study the precise cell-to-cell changes in genome activity along development, revealing how specific information in the genome sequence is progressively read to produce correct cell types. Our findings will illuminate core principles of development relevant across animals.

Importance of Barrier and Potential to Overcome it: Biomedical research is performed at multiple scales, ranging from the molecular up to populations. To capitalize on discoveries made at one particular scale, we must work smoothly across scales, for example to translate a molecular discovery into a new treatment. Particularly for research focused on human biology and disease, the tissue or organ scale is a major bottleneck. Stem cells build, maintain, and repair our tissues. The Cambridge Stem Cell Institute represents the leading centre for stem cell research in Europe, and is therefore in prime position to tackle the Tissue Scale bottleneck. We have identified organs in a dish, lineage analysis, tissue scale imaging/molecular profiling and computational modelling as specific barriers which we will break down to empower a new era of Tissue Scale Biology research. Breadth of Impact: Underpinned by a new network of technologists from local and international centres of excellence, our innovations will enable a new wave of discovery and translational science relevant for most areas of biomedical research. Research Environment: Personal development and positive culture are integral to this application, bolstered by over £2M Institutional Support, including new degree apprenticeships with Anglia Ruskin University to widen participation.

The endoplasmic reticulum (ER), as a single continuous membrane network, coordinates a variety of biological processes across the entire cell, providing a platform for the spatiotemporal segregation of cytoplasmic biochemistry – a crucial feature for cell survival. Despite this, our understanding of how the ER corrals most cytoplasmic clients to specific sites on its membrane remains slim. ER structure is partially governed by a series of hairpin proteins known to stabilise specific membrane curvatures. The Reticulons (RTNs) and Receptor Expression-Enhancing Proteins (REEPs) are two such families of protein. We have shown that RTN/REEPs cluster into ER microdomains and contain cytosolic-facing intrinsically disordered regions which enable the formation of biomolecular condensates, potentially tethering specific cytosolic proteins to the ER membrane. Thus, we propose the novel and testable hypothesis that membrane curvature-stabilising RTN/REEPs drive regional functional specificities at ER microdomains. To test this, we will generate a comprehensive spatial map of RTN/REEP-microdomains using single-molecule localisation microscopy, with a custom optical-tweezer configuration used to quantify precise membrane curvature preferences for each hairpin. Using two orthogonal screens we aim to identify a complement of cytosolic proteins capable of co-condensing with each RTN/REEP, performing appropriate bioassays to assess the functional consequences of destabilising hairpin:cytoplasmic-partner interactions. The endoplasmic reticulum (ER) comprises a single continuous membrane network that extends across the entire cell, coordinating diverse cytosolic activities essential for cell survival. Despite this, our understanding of how the ER confines cytosolic proteins to specific regions of its membrane remains tenuous. We have demonstrated that several ER resident hairpin proteins cluster into unique spatial microdomains. Many of these hairpins contain large cytoplasmic-facing intrinsically disordered regions that we believe form biomolecular condensates with specific cytosolic partners. We aim to generate a comprehensive spatial map of ER-hairpin microdomains, subsequently using a series of screening approaches with targeted bioinformatics to identify cytosolic partners. Ultimately we will look to destabilise hairpin:partner interactions and observe the consequences on localisation and function for each partner. Our work will provide a novel molecular mechanism for ER-mediated cytoplasmic organisation, a fundamental cellular process, and set a basis for understanding misregulation of ER:cytoplasmic crosstalk in disease

Embryonic cells must have their identity specified in order to generate functionally distinct organs. Neuromesodermal progenitors (NMPs) are a progenitor cell population that resides in the tailbud of vertebrate embryos. The specification of the NMP population must be correctly balanced in order to generate axial body structures such as spinal chord, muscle and bone. Though little is known about how cell fate specification is regulated, it happens reproducibly and robustly in the majority of embryos, for example preliminary work I have done shows that normal development still occurs if a quarter of the NMPs are ablated. I aim to ablate NMPs in the zebrafish tailbud using targeted laser ablation. I will then use clonal analysis, live imaging, and quantitative gene expression techniques to observe and quantify the response to ablation. I will combine this with generating mathematical models to predict potential mechanisms. To explore the mechanisms which are involved in regulating the pattern of cell fate specification I will use quantitative live imaging and embryonic manipulation of transgenic fish lines. I expect this work to provide insight into how cell fates are decided in vertebrate embryos and how they are affected by internal or external perturbations.