# PI

id: ansari_azim
name: Dr. Azim Ansari
location: Peter Medawar Building for Pathogen Research and Centre for Human Genetics
department: Nuffield Department of Medicine
group: Ansari: Host Pathogen Genomics
url: https://www.ndm.ox.ac.uk/team/azim-ansari
email: azim.ansari@ndm.ox.ac.uk
image: data/images/ansari_azim.jpg
titles:
  Sir Henry Dale Fellow, Group Leader in the Experimental Medicine Division, Associate Group Leader at the Centre for Human Genetics


id: brennan_paul
name: Professor Paul Brennan
location: Nuffield Department of Medicine Research Building
department: Nuffield Department of Medicine [edit as required]
group: Alzheimer’s Research UK Oxford Drug Discovery Institute
url: https://www.brennanresearchgroup.com/
email: paul.brennan@cmd.ox.ac.uk
image: data/images/brennan_paul.png
titles:
  Professor of Medicinal Chemistry, Head of Chemistry – Alzheimer’s Research UK Oxford Drug Discovery Institute, Group Leader


id: cader_zameel
name: Professor Zameel Cader
location: Weatherall Institute of Molecular Medicine
department: Nuffield Department of Clinical Neurosciences
group: Cader
url: http://im2pact.org/
email: zameel.cader@ndcn.ox.ac.uk
image: data/images/cader_zameel.png
titles:
  Head of Translational Molecular Neuroscience Research Group, Consultant Neurologist, Lead for IMI IM2PACT


id: casadei_barbara
name: Professor Barbara Casadei
location: West Wing, John Radcliffe Hospital
department: Cardiovascular Medicine
group: Myocardial Redox Biology
url: https://www.rdm.ox.ac.uk/people/barbara-casadei
email: barbara.casadei@cardiov.ox.ac.uk
image: data/images/casadei_barbara.jpeg
titles:
  British Heart Foundation Professor of Cardiovascular Medicine, Honorary Consultant Cardiologist and Group Leader / PI


id: channon_keith
name: Professor Keith Channon
titles: Field Marshal Earl Alexander Professor of Cardiovascular Medicine
location: Wellcome Centre for Human Genetics
department: Radcliffe Department of Medicine
group: Channon
email: keith.channon@cardiov.ox.ac.uk
image: data/images/channon_keith.jpeg
url:
  https://www.well.ox.ac.uk/research/research-groups/channon-group-cardiovascular-functional-genomics-and-redox-signalling-1


id: church_david
name: Dr. David Church
location: Centre for Human Genetics
department: Nuffield Department of Medicine
group: Tumour Genomics and Immunology Group
url: https://www.well.ox.ac.uk/research/research-groups/church-group
email: david.church@well.ac.uk
image: data/images/church_david.jpg
titles:
  Associate Professor, Cancer Research UK Advanced Clinician Scientist and Honorary Consultant Medical Oncologist


id: davies_james
name: Associate Prof. James Davies
titles: Group Leader / PI / Associate Professor of Genomics / Honorary Consultant
location: MRC Weatherall Institute of Molecular Medicine
department: Radcliffe Department of Medicine
group: James Davies Laboratory
email: james.davies@ndcls.ox.ac.uk
image: data/images/davies_james.jpeg
url:
  https://www.rdm.ox.ac.uk/about/our-divisions/nuffield-division-of-clinical-laboratory-sciences/nuffield-division-of-clinical-laboratory-sciences-research/davies-group-genome-function-and-advanced-cellular-therapy-development


id: fraser_christophe
name: Professor Christophe Fraser
location: Big Data Institute, Wellcome Centre for Human Genetics
department: Nuffield Department of Medicine
group: Pathogen Dynamics
url: https://www.bdi.ox.ac.uk/Team/christophe-fraser
email: hristophe.fraser@bdi.ox.ac.uk
image: data/images/fraser_christophe.jpg
titles:
  Professor of Pathogen Dynamics, Senior Group Leader in the Big Data Institute; Associate Group Leader in the Wellcome Centre for Human Genetics; Associate Faculty Wellcome Trust Sanger Institute; Independent Advisor to NHS Test and Trace.


id: hill_adrian
name: Professor Adrian Hill
location: Jenner Institute
department: Nuffield Department of Clinical Laboratory Sciences
url: https://www.jenner.ac.uk/team/adrian-hill
email: adrian.hill@ndm.ox.ac.uk
image: data/images/hill_adrian.jpeg
titles:
  Professor of Human Genetics, Director of The Jenner Institute, Wellcome Trust Senior Investigator, Group Leader


id: knight_julian
name: Professor Julian Knight
location: Wellcome Centre for Human Genetics
department: Nuffield Department of Medicine
group: Knight group
url: https://www.well.ox.ac.uk/people/julian-knight
email: julian.knight@well.ox.ac.uk
image: data/images/knight_julian.png
titles:
  Professor of Genomic Medicine, Director of GMS DPhil programme, Honorary Consultant Physician, Director of Graduate School Medical Sciences Division, Fellow of Merton College


id: mccullagh_james
name: Professor James McCullagh
location: Chemistry Research Laboratory
department: Department of Chemistry
group: McCullagh
url: http://research.chem.ox.ac.uk/james-mccullagh-.aspx
email: james.mccullagh@chem.ox.ac.uk
image: data/images/mccullagh_james.jpeg
titles:
  Director of the Mass Spectrometry Research Facility and group leader, Associate Professor of Analytical Chemistry


id: taylor_jenny
name: Professor Jenny Taylor
location: Wellcome Centre for Human Genetics
department: Nuffield Department of Medicine
group: Taylor Group
url: https://www.well.ox.ac.uk/people/jenny-taylor
email: jenny.taylor@well.ox.ac.uk
image: data/images/taylor_jenny.png
titles:
  Professor of Translational Genomics, Co-Theme Lead, Oxford Biomedical Research Centre Genomic Medicine Theme, Group Leader / PI, Fellow and Member of Congregation


id: udalova_irina
name: Professor Irina Udalova
location: Kennedy Institute of Rheumatology
department: NDORMS
group: Laboratory of Genomics of Inflammation
url: https://www.kennedy.ox.ac.uk/team/irina-udalova
email: Irina.udalova@kennedy.ox.ac.uk
image: data/images/udalova_irina.jpeg
titles:
  Professor of Molecular immunology. Associate Director of the Kennedy Institute of Rheumatology in Data Science. Head of Laboratory of Genomics of Inflammation, Group Leader / PI, Member of congregation


# research

pi_id: ansari_azim
themes: 1,3,5
overview:
  We investigate infectious diseases and the role of host and pathogen genetic variation on the outcome of infection. Genome-wide association studies (GWAS) aim to identify the genetic basis of phenotypic traits using the variation that exists within natural populations. Uniquely for infectious diseases, the inter-individual heterogeneity in disease phenotype is linked to both host and pathogen genetic variation. Traditionally, genetic studies of infectious diseases have sought to explain between-individual variation in disease phenotypes by assessing genetic factors separately in humans or pathogens, under the assumption that these factors are independent. We integrate host and pathogen genomic data from the same patients to better understand pathogenesis and between-individual heterogeneity in disease outcomes. Using paired host-pathogen data we aim to identify (a) host polymorphisms linked with pathogen sequence variation, (b) pathogen sites under strong host genetic selective pressures, (c) host and virus genetic factors independently contributing to disease phenotypes and (d) host-virus genetic interactions contributing to disease phenotypes. The findings have the potential to: (I) revolutionize our understanding of host-pathogen interactions and human biology; (II) aid in development of more effective vaccines, drug targets and immunotherapies; and (III) permit better use of therapies through patient stratification. 
  Our work focuses on viral infections of hepatitis B and C viruses (HBV and HCV), human immunodeficiency virus (HIV), SARS-CoV-2 and dengue. The datasets available for this project include host and virus genomic data from large cohorts of HCV infected individuals (5000 from the UK, 2000 from Pakistan and 1000 from Vietnam) where we have collected extensive clinical information; host and virus genomic data on a cohort of 5000 individuals with HBV infection (from China) with extensive clinical information and host and virus genomic data on a cohort of 2000 individuals with SARS-CoV-2 infection with treatment outcome and viral load measurements. 
  In the age of “Big Data” and “Personalised Medicine”, analysis of paired host-pathogen genomic data will become increasingly important to uncover the mechanisms driving pathogen adaptations and heterogeneity of infection outcomes.
  We are a cross‐disciplinary group, based both at the Peter Medawar Building for Pathogen Research and the Centre for Human Genetics (CHG). Our focus is data analysis and developing statistical and computational methodologies, although we do wet-lab work too. We have strong collaborations with clinicians, immunologists and wet-lab scientists nationally and internationally (Pakistan, Vietnam, China, South Africa, Uganda) and the students will have the opportunity to work with them. We are flexible about the projects, and they will be tailored around the interests of the students.
  Project areas: Infectious diseases, Evolution, Bioinformatics, Host Pathogen interactions, Population genetics, Computational Statistics, Machine Learning
  Specific project proposals:
  -- Developing Statistical Methodology for integrated analysis of host-pathogen genomic data
  -- Developing Statistical Methodology to model mixed infection and its contribution to maintenance of pathogen genetic diversity
  -- Understanding mechanisms of sex disparities in infectious diseases
  -- The impact of host genetic variation on the within-individual pathogen diversity
  We have many other projects in the group, please contact directly for further information on other possible projects on both data analysis and model development. We also will consider projects proposals from students.


pi_id: band_gavin
themes: 1,3,5
overview:
  Our group is focussed on host-pathogen interactions, with a particular focus on the malaria parasite Plasmodium falciparum. We are taking a range of experimental and computational approaches to try to understand the interactions that have been discovered so far (described in <a href="https://doi.org/10.1038/s41586-021-04288-3">Band et al Nature 2021</a> and <a href="https://doi.org/10.1101/2023.09.14.557461">Hamilton et al bioRxiv 2023</a>), and are building data and methods to search for currently unknown interactions.
  Genomic interactions form a rich area of study. One reason is that any interaction that affects the success of parasites to transmit (or that affects the ability of humans to survive their infections) places selective pressure on the populations. Rapid genome evolution is often a result. Because of this we are interested in complex regions of the parasite and human genomes, and in methods and technologies that can resolve structural variants and other complex variation. To this end we have been developing methods to use long-read sequencing to assemble genomes and resolve variation in some of the most complex genome regions - including those encoding the immune system (e.g. as described in <a href="https://doi.org/10.1371/journal.pcbi.1009254">Zhang et al 2021</a>).
  Project areas: Malaria genomics, host-pathogen coevolution, long read methods and genome assembly, structural variation and complex genome regions, population genetics and genome-wide association studies.


pi_id: bashford-rogers_rachael
themes: 1,2,3,4,5
overview:
  We aim to determine the development, regulation and function of B and T cell populations in health and immunological diseases. This will lead us to an understanding of why certain individuals are at greater risk of developing immunological disease, as well as to identify potential therapeutic targets or improved clinical management. This is achieved through the development and application of novel experimental and computational approaches, working in partnership with a global network of clinicians, immunologists and sample cohorts.
  Immunological health relies on a balance between the ability to mount an immune response against potential pathogens and tolerance to self. B and T cells are key to the immune response by producing antibodies and cytotoxic T cells. B/T cell clones selectively expand following antigen recognition by B and T cell receptors (BCR and TCR) respectively. BCRs are the membrane-form of antibodies and are generated through DNA recombination resulting in the potential to recognise a vast array of pathogens. Defects in the ability to mount effective B cell or T cell responses have been implicated in infectious susceptibility, impaired surveillance of cancer and immunodeficiencies, whereas a breakdown of immunological tolerance has been attributed to autoimmune diseases such as through autoantibody production and reduced numbers of regulatory B/T cells.
  Project areas: 
  -- Building patient-specific digital twins for cancer drug development and cancer treatment
  -- Resolving the rules of regulatory B cell (Breg) generation for therapeutic modulation in cancer and beyond
  -- How are Different B Cell Populations Developmentally Linked in Human Health and Disease?
  -- Immuno-surveillance in Cancer
  -- What is the Effect of Genetic and Environmental Variation on B and T Cell Fate?
  -- Single cell and spatial omics technology Development
  Specific project proposals:
  -- Building patient-specific digital twins for cancer drug development and cancer treatment
  -- Resolving the rules of regulatory B cell (Breg) generation for therapeutic modulation in cancer and beyond 
  -- Investigating the B and T cell mediated pro- and anti-tumour mechanisms in cancers 
  Please contact directly for further information.


pi_id: beagrie_robert
themes: 1,2,5
overview:
  Chromatin is highly organised in the nucleus. The correct distribution of histone marks and 3D folding of chromatin both contribute to normal gene expression and the maintenance of cell state. When these processes are disrupted, they can cause or contribute to human disease. Despite the universal nature of chromatin-based gene regulation, the consequences of chromatin disruption frequently impact the heart and the brain more than other tissues. My group’s aim is to understand the molecular basis of this tissue-specificity.
  We use single-cell RNA-seq and spatial transcriptomics to identify affected cell types and dysregulated genes in models of chromatin disruption. We assess how chromatin organisation is affected by using single-cell CUT&TAG and ATAC-seq to identify differences in the distribution of histone variants, histone modifications or nucleosome-free regions. We also use Genome Architecture Mapping (GAM) to measure chromatin folding. We develop and apply computational  analyses to identify common features of genes that are particularly sensitive to chromatin disruption.
  Project areas: Chromatin, rare genetic disorders, brain development, heart development
  Specific project proposals:
  DPhil projects will be tailored to a candidate’s interests – if you’re interested please contact Rob to discuss. Available rotation projects are outlined below.


pi_id: bhattacharya_shoumo
overview:
  Project areas: protein interactions, inflammation, chemokine, nanobody-peptide conjugates
  In inflammatory diseases such as arthritis, colitis, atherosclerosis or insulitis (in type 1 diabetes) immune cells migrate into the organ or tissue. Current treatments suppress the immune cells. The immune cells are no longer able to fight off infections or cancers. Could we simply stop immune cells from reaching inflamed tissues? Inflamed tissues make signals called “chemokines” which attract immune cells. Blocking chemokines could stop this. For over 30 years researchers have tried make chemokine-blocking drugs. As there are many chemokine types, blocking just one or two has no effect. Ticks solved the problem millions of years ago. They need to feed without being noticed by the immune cells. To do this, they inject “evasin” proteins under the skin. These evasins neutralize many chemokines. Evasins are effective in animal arthritis models but cannot be used in patients. We are developing treatments inspired by evasins. We identified the smallest effective bit of an evasin (called a "peptide"). This peptide blocks many chemokine types. We improved the peptide using lab-based evolution to make a “super-peptide”. This blocks immune cell migration to pools of chemokines. However, we cannot yet use it to treat patients. We need to target the anti-chemokine effects only to inflamed tissues. This would avoid blocking chemokines elsewhere, reducing side-effects. We need to make it last longer in the body. This allows fewer injections making the treatment more patient friendly. This is where camelids (camels and llamas) come in. The effective bit of a camelid antibody is a “nanobody”. Nanobodies are safe and are clinically approved. They can be chemically joined to a peptide. We think that nanobodies could be used to deliver a super-peptide “cargo” to the inflamed tissue. Nanobodies could also be used to stop the super-peptide from being removed by the kidney. In this project we will study nanobodies that could deliver a “super-peptide” to the inflamed tissue. We will improve these nanobodies so that they are not excreted by the kidney. We will first make sure that these nanobodies work in the lab. We will then conjugate them to our “super-peptide”. We will study these nanobody-peptide conjugates in lab and animal tests. We will make sure they block immune cell migration to inflammatory chemokines. We will study them in mice to make sure that they are not rapidly removed by the kidney. Finally, we will test if they can stop inflammation in a mouse. We will use a simple “air-pouch” model. The mouse work will also assure us of their safety. These agents should be safer than existing treatments as they will be targeted to the inflamed tissue. If successful, we will have an agent that is ready for patient trials.


pi_id: bottomley_matthew
themes: 1,4,5
overview:
  My research focuses using markers in the immune system to identify patients who may be at risk of complications after a renal transplant. I am particularly focused on exploring the effect of ageing in the immune system on transplant outcomes. As we age the immune system undergoes several changes through long-term exposure to viruses and other factors in the environment. We refer to these changes as ‘immunosenescence’ (immune ageing). Over time, this can lead to the immune system being less effective at protecting us from infection and less responsive to vaccination.
  Skin cancer is a major problem for organ transplant recipients and our current work focuses on (a) changes that occur within the immune cells present in the skin prior to the development of skin cancer and (b) how immune responses to skin malignancy change under immunosuppression.
  Specifically we are interested in the impact of immune ageing combined with the use of immunosuppression after transplantation. In evaluating this, we use a combination of functional immunology, immunohistology, and cutting-edge high-resolution spatial transcriptomic analysis. We benefit from access to the multiplatform Nanostring Spatial Profiling Hub available within the CAMS Oxford Institute, of which I am the academic lead. This permits near whole transcriptome (18,000 genes) and/or single-cell transcriptomic profiling of clinical tissue samples.
  The work we are undertaking in this area may allow us to use the immune system in clinical practice in the future, to guide the type and amount of immunosuppression we give to transplant recipients. 
  Project areas: Skin cancer; spatial transcriptomic analysis; Immunosuppression; organ transplantation.
  Specific project proposals:
  -- The effect of uraemia, immune ageing and iatrogenic immunosuppression upon cutaneous immunosurveillance.
  Please contact directly for further information.


pi_id: brennan_paul
themes: 1,2,3,4,5
overview:
  The focus of our group is on small molecule drug discovery and chemical biology. We develop open-access small molecule probes to enable target discovery of novel proteins in dementia, oncology and inflammatory disease. The group works in close collaboration with chemical biologists and biophysicists to decipher new mechanisms of disease propagation and action, and to design ways to prevent these diseases. 
  Chemical probes are available for only a small fraction of potential disease targets and often are less specific than small inhibiting RNA. The scarcity of chemical probes is disappointing as they are especially useful; a probe that shows a positive effect can also serve as a chemical starting point for drug discovery. If genetic or RNA interference methods identify an exciting disease target, it may still take many years to find a chemical starting point to move from target discovery to drug discovery, whereas using a chemical probe in target discovery jump-starts the process. A key technology we use in our research is fragment-based screening to discover chemical leads. The leads are optimised for potency, selectivity and cellular activity via iterative cycles of structure based drug design, parallel organic synthesis, biophysical testing and compound structure-activity relationship (SAR) analysis.
  Project areas: Medicinal chemistry, structural biology, GTPases, GAPs, DUBTACs
  Specific project proposals:
  --  ‘Development of deubiquitinase target chimeras (DUBTACs) to increase protein expression and modulate ubiquitin signalling.’
  Please contact directly for further information.


pi_id: cader_zameel
themes: 1,2,3,4,5
overview:
  The Cader laboratory focuses on target discovery and therapeutics in neurological disorders using human-centric approaches. We work extensively with human cellular disease models derived from induced pluripotent stem cells (iPSC) and complement this with mouse models. Our major disease areas of interest are migraine and pain, autism and dementia. These are major diseases of our time for which drug therapies are limited and drug discovery in this field is very challenging due to lack of access to human cells. We have developed unique methods to generate human cell types and investigate disease relevant phenotypes. Recently we have been investigating circadian mechanism in pain and as an opportunity to develop ‘chrono-medicines’.
  We have conducted compound and CRISPR/Cas9 cell phenotypic screens with iPSC disease models to identify currently available that might be repurposed as therapeutics and to reveal disease mechanisms. This has been combined with single cell RNA sequencing of iPSC models and human neuronal tissue to discover cell types relevant to neurological disease processes. Using advanced chemo-proteomic methods such as photo-affinity probe pull-downs, our lab is identifying novel drug targets. 
  The development of a successful central nervous system therapy requires penetration across the blood-brain-barrier. A major program in our lab is to develop better models of the blood-brain-barrier and understand how this might be disrupted in disease. We are using transcriptomics and proteomics to interrogate the barrier in human surgical and post-mortem brain tissue. We are also developing novel iPSC protocols to produce brain endothelial cells.
  Project areas: Human iPSC disease models, phenotypic screens, single cell RNA sequencing, CRISPR/Cas9 technology, target discovery and validation
  Specific project proposals:
  -- ‘The role of the mTOR pathway in neurological disease. The mTOR pathway is a major cellular signalling pathway regulating cell cycle, protein translation, response to inflammation and for neuronal function. We have completed a CRISPR/Cas9 screen and have identified important regulators of this pathway that now need deeper exploration in our iPSC neuronal tissue models. The project will involve investigating candidate mechanisms in depth using further genetic and pharmacological manipulation and assessing the effect on cellular and molecular phenotypes using single cell omics approaches and electrophysiological assays such as calcium imaging and multi-electrode arrays.’
  Please contact directly for further information.


pi_id: casadei_barbara
overview:
  My group’s research programme spans from basic aspects of myocardial nitroso-redox signalling to patient-based investigations and clinical trials with a focus on atrial fibrillation and heart failure. Examples of the scope and range of our ongoing work (in press) include the investigation of myocardial mechanisms promoting the maintenance of atrial fibrillation in humans (Reilly et al. Science Transl Med) and the impact of perioperative statin therapy on the new onset of atrial fibrillation after cardiac surgery and other postoperative complications (Zheng et al. New Engl Med J). My team and I have been awarded national and international prizes (e.g., The Joan Mott Prize Lecture of the Physiological Society, the William Harvey Lecture and Silver Medal of the ESC, the Thomas Lewis Lecture and Silver Medal of the British Cardiovascular Society, The Carmeliet-Coraboeuf-Weidmann Lecture of the European Heart Rhythm Association, the Melvin A. Marcus Young Investigator Award of the American Heart Association, the Young Research Worker Prize of the British Cardiovascular Society (4 times) and the Lord Leonard and Lady Estelle Wolfson Prize of the Academy of Medical Sciences. Our research is funded by a Programme Grant of the British Heart Foundation, EU grants from the FP7 and Horizon 2020 programme, and a Fondation Leducq Transatlantic Network of Excellence. In addition to my research and clinical role in Oxford, I hold a leadership position in the European Society of Cardiology (representing 90,000 cardiologists and cardiovascular scientists across Europe) where I have initiated and chaired the Society’s Research Strategy Plan, the Agenda for Women and the Research Regulators round table.
  Project areas: Integrative physiology; cardiac biology and disease; signaling; electrophysiology; clinical trials; atrial fibrillation; diabetic cardiomyopathy; myocardial ischaemia and remodeling; nitric oxide and reactive oxygen species.
  Specific project proposals:
  Please contact directly for further information.


pi_id: channon_keith
themes: 1,2,3,4,5
overview:
  :
  The Channon group bring together interdisciplinary expertise in biochemistry, vascular function, in vivo models of cardiovascular disease and immune cell biology to probe molecules involved in cardiovascular disease. Our work is split over 4 main themes: 
  --  The role of the endothelium and nitric oxide signalling in the development of vascular disease 
  --  NOS-independent roles of tetrahydrobiopterin 
  --  Leukocyte recruitment in cardiovascular inflammation 
  --  Evaluating novel GWAS candidate genes in experimental models of cardiovascular disease 
  Project areas: Endothelial function, GWAS, Redox Biology, Inflammation, Immunometabolism,
  Specific project proposals: 
  -- Defining the function of new causal atherosclerosis genes from coronary artery disease GWAS loci using in vitro and in vivo models
  -- Investigating the role of immune-metabolic mediators in endothelial and immune cell biology
  Please contact directly for further information.


pi_id: chen_yi-ling
themes: 1,2
overview:
  My research has been focussed on the innate lymphocyte mechanisms under inflammatory conditions. My aim is to understand, at the cellular and molecular level, the role of commensal and pathogen responses in both tissue homeostasis and microbial defence. Specifically, I am interested in the involvement of lipid-reactive T cells in these responses. With high dimensional transcriptomics, T cell clonality analysis, and TCR editing approaches, the main goal of my work is to progress translationally towards the evaluation of promising new therapeutic targets and the discovery of new lipid candidates for immune intervention.
  Project areas: Lipid biology, host-pathogen interactions, post-infection autoimmune sequelae
  Specific project proposals:
  -- Role of lipid-reactive T cells and lipid antigens in inflammatory disease
  Please contact directly for further information.


pi_id: church_david
themes: 2,4,5
overview:
  We study colorectal and endometrial cancer by <a href="https://www.nature.com/articles/s41586-024-07747-9">genome sequencing</a>, <a href="https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(23)00560-0/fulltext?rss=yes">spatial analysis</a> and <a href="https://www.embopress.org/doi/full/10.15252/emmm.202217094">functional models</a> to understand disease biology and to improve patient care. A current focus is the development of preventative vaccines against cancer in high-risk individuals such as people with Lynch syndrome. 
  Project areas: 
  Colorectal cancer; endometrial cancer; cancer genomics; digital pathology, biomarker, immune escape .
  Specific project proposals:
  -- Novel immune escape mutations in cancer
  -- Characterisation of driver mutations in endometrial cancer
  -- Immunobiology of precancer.
  Please contact directly for further information.


pi_id: cowley_sally
themes: 2,4
overview:
  Induced Pluripotent Stem cells (iPSC) derived from patients with genetic disease offers a new, hugely exciting opportunity to model human diseases in vitro. iPSC are particularly important for modelling neurological conditions, where patient material is generally unavailable until after death, and for rare genetic disorders, where patient material is severely limiting. To harness this potential, I have established and am Head of the James and Lillian Martin Centre for Stem Cell Research (within the Sir William Dunn School of Pathology, University of Oxford, and part of the Oxford Stem Cell Institute), with particular interests in the use of iPSC for modelling disease, and expertise in human iPSC derivation, genetic modification, and differentiation to myeloid and neuronal lineages. Key projects include: 1) Generation of a world-class panel of over 200 iPS cell lines from Parkinson’s patients, and CRISPR/Cas9 gene edited lines, as part of a large-scale study within the Oxford Parkinson’s Disease Centre and the EU IMI consortium StemBANCC, to study the early cellular pathology of PD; 2) Pioneering efficient methodologies for differentiation of macrophages and microglia from human iPS cells; 3) Interrogation of the role of the Parkinson’s-associated genes a-synuclein and LRRK2 in macrophages and microglia; 4) Investigation of the role of Alzheimer’s genes in iPS-macrophages/microglia, in collaboration with the Alzheimer’s Research UK Oxford Drug Discovery Institute; 5) Co-investigator in the MRC UKDP Experimental Medicine Dementia Stem Cell Network, a UK-wide network using iPSc for modelling dementia.
  Project areas: human Pluripotent Stem Cells; disease modelling; CRISPR; gene editing; neurodegenerative disease; Parkinson’s; Alzheimer’s; immunology; macrophage biology; microglia
  Specific project proposals:
  Please contact directly for further information.


pi_id: davies_james
themes: 1,2,3,4,5
overview:
  My lab is interested in understanding how the genome functions and leveraging this to develop genome editing strategies to treat human disease. 
  In higher eukaryotes many genes are controlled by regulatory elements called enhancers, which are often located hundreds of thousands of base pairs distant from the gene. Enhancers contain small sequences (~10bp) which bind transcription factors and these make physical contact with the proteins at the promoter to activate gene expression. Until recently, we have had limited ability to define the detail of physical contacts that control genes below 1kb resolution. 
  We have recently developed a new method (Micro Capture-C, Hua et al., Nature 2021) to define genome architecture in unprecedented detail (down to base pair resolution). We are using the new technique to study the fundamental mechanisms of gene regulation and to define how variation in genome sequence links to human disease. These assays are very challenging to analyse and we have developed novel computational approaches for interrogating these data sets.
  The lab also has expertise in cutting edge genome editing technology. As a haematologist with a specialist interest in bone marrow transplantation and cellular therapy, I am keen to develop novel clinical genome editing approaches. We have previously licenced a genome editing approach we have invented for treating thalassaemia and sickle cell disease to BEAM therapeutics and are hoping this will enter into the clinic in the near future. 
  The lab specialises in combining wet lab approaches with computational biology and we have a number of exciting projects in both functional genomics and clinical genome editing.
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Functional genomics, Chromsome conformation capture, Enhancer biology, Genome editing, Cellular Therapy, Bioinformatics
  Specific project proposals:
  --  ‘Using base pair resolution genome architecture to explore enhancer function’ 
  -- ‘Developing a pipeline for treating rare genetic disease using genome editing’
  Please contact directly for further information.


pi_id: davies_robbie
themes: 3,4,5
overview:
  We are a research group at the University of Oxford interested in problems at the interface of statistics, genetics and medicine. We have broad interests but are particularly focused on research that can eventually contribute towards more accurate phenotype prediction using genotypes in humans.
  Project areas: Statistical genetics, methods development, phasing and imputation, whole genome sequencing, polygenic risk scores
  Specific project proposals:
  --  ‘Investigating properties of de novo duplication or deletion detection using non-invasive prenatal testing data’ 
  Please contact directly for further information.


pi_id: dendrou_calli
themes: 1,2,4,5
overview:
  Our research aims to refine and to develop diagnostic and therapeutic strategies for improved healthcare provision to patients with immune-mediated and infectious diseases. 
  We are using functional genetics, in vitro, ex vivo and in vivo experimental approaches to:
  (i) Identify and functionally assess pleiotropic genetic variation to help uncover drug repurposing opportunities for immune-mediated diseases
  (ii) Benchmark drug-dependent modulation of immune system function against that of protective genetic variants
  (iii) Investigate the balance between protection against immune-mediated disease and the risk for malignancy and infection to help predict drug-associated side effects
  (iv) Utilise pleiotropic genetic variation for the development of novel, next generation treatment strategies for severe immune-mediated diseases
  We are using single-cell and spatial transcriptomics and proteomics, and hyperplexed imaging approaches to:
  (i) Perform deep immunoprofiling of the site of pathology and of peripheral blood to better characterise disease mechanisms and identify potential biomarkers and therapeutic targets
  (ii) Perform deep immunoprofiling of the site of pathology before and after therapeutic intervention to elucidate mechanisms and identify biomarkers of drug response and resistance and identify correlates 
  (iii) Spatiotemporally map immune response kinetics, across individuals with different ethnic backgrounds, to help improve therapeutic development and to help design ‘intelligent’ vaccines
  Projects can be tailored to personal interests but will mainly involve data analysis/bioinformatics and potentially a wet lab component.
  Project areas: Autoimmunity; Molecular & cellular immunology; Single-cell and spatial transcriptomics; Functional genomics; Gene regulation 
  Specific project proposals:
  -- ‘TYK2 as a genetically determined drug target against multiple immune-mediated diseases’ 
  -- ‘Spatially resolved molecular and cellular profiling of immunopathological responses’

  Please contact directly for further information.


pi_id: fowler_philip
themes: 3,4,5
overview:
  The Modernising Medical Microbiology Unit here in Oxford is pioneering genetics-based clinical microbiology. The central idea is to infer which antibiotics can be used to treat an infection by examining the genetics of a clinical sample. Our exemplar pathogen is Mycobacterium tuberculosis (MTB) which is the aetiology agent of tuberculosis due to its very slow growth rate and relatively straightforward genetics. I am working closely with the Ellison Institute of Technology (EIT) in Oxford to launch a free-to-use Mycobacterial genetics service that anyone worldwide can upload their raw genetics files (FASTQ) and get back in less than 30 minutes (i) the species contained, including subspecies/lineage, (ii) a prediction of which antibiotics will be effective and (iii) a list of which other samples are likely epidemiologically related.
   Through the earlier CRyPTIC project, we amassed about 84,000 MTB genomes which have a range of different phenotypic antibiotic susceptibility data (AST). This data was used by the WHO to create their first catalogue of resistance associated mutations in MTB which was released in June 2021 and updated in November 2023. As part of the CRyPTIC project I developed image processing software that determined the minimum inhibitory concentrations of the dozen drugs on a 96-well broth micro dilution plate; this also enabled a very large and successful citizen science project, BashTheBug, through which 46,427 volunteers classified 4,746,420 images of MTB growing on different antibiotics. 
   The current approach is inferential and therefore I am also developing predictive methods. These fall into two main classes: (1) protein structure-based machine learning and (2) calculating the effect of the mutation on the binding free energy of the antibiotic using alchemical free energy simulations. The former covers a range of machine learning methods, from relatively straightforward methods like random forest through to more advanced methods like graph-based convolution neural networks (gCNNs). Our hope with the latter is to begin to move into other species (like the ESKAPE pathogens) because we are predicting based off sequence rather than mutation.
  Project areas: infectious disease; diagnosis; genetics; antibiotic resistance
  Please contact directly for further information.


pi_id: fowler_steph
themes: 1,2,4
overview:
  Dr. Steph Fowler is a biochemist and neuroscientist with a diverse background in inducible heat stress responses, the role of gap junctional communication in murine neural regeneration potential, and the use of subcellular fractionation and interactome proteomics as tools to explore functional roles of protein complexes. To gain expertise in the field of human neurodegeneration, Steph undertook a postdoc with Dr. Karen Duff at Columbia University. Here, she worked extensively on the isolation and characterisation of diverse seed-competent tau species isolated from brain tissue of patients diagnosed with Alzheimer's Disease (AD) and various primary tauopathies. In 2019, Karen Duff's lab moved to the UK Dementia Research Institute at UCL (London), where questions concerning the heterogeneity of pathological tau species led to the discovery that short, seed-competent tau filaments are associated with extracellular vesicles (EVs) isolated from human post-mortem AD brain tissue, and that uniquely-modified tau filaments are tethered to the luminal membranes of secreted EVs. Currently, as a Fellow at the Oxford-GSK Institute of Molecular and Computational Medicine (IMCM), Steph's research team is generating new iNeuron and immortalised cell models of tauopathy that better recapitulate tau filament conformations isolated from post-mortem human brain tissue. Using spatial proteomics and super-resolution imaging techniques, these new models will be used to interrogate mechanisms of tau assembly and spread, and to define novel subcellular microenvironments associated with the aberrant assembly and secretion of tau. Steph's research interests also lie in detecting seed-competent tau species in human biofluids/EVs, and in developing a more sophisticated toolkit of conformation-specific antibodies and vaccines to diagnose, treat, and prevent human tauopathies.
  Project areas: Spatial proteomics, Tauopathies, Alzheimer's Disease, Neurodegeneration
  Specific project proposals:
  --  ‘Project title’ 
  -- ‘Second project title’.
  Please contact directly for further information.


pi_id: fraser_christophe
overview:
  In the Pathogen Dynamics research group, we study the spread, evolution and control of epidemic pathogens. We are a multidisciplinary team of investigators, including laboratory science, clinical science, bioinformatics, computing, modelling, statistics, and communications/outreach. Because the best way to understand a system is to disrupt it, our guiding principle is that the best way to understand pathogen dynamics is to work alongside medical and public health teams that implement epidemic interventions. 
   
  Epidemic modelling and interventions: 
  Most of the group works on HIV in sub-Saharan Africa. We are involved in major consortia (PANGEA: <a href="https://www.pangea-hiv.org/">https://www.pangea-hiv.org/</a> ). We have developed agent based simulations, and also simple mathematical models. We have supported universal treatment as prevention programmes, and we now support interventions based on outcomes of phylogenetic and social science studies that suggest new approaches to provide care and prevent infections, and we advise on the deployment of novel long-acting pharmaceutical agents. We work with international agencies (UNAIDS, Global Fund) and local investigators and country agencies. We seek to advance the state of the art in evidence synthesis based on agent-based simulations that bring in broad types of data sources: epidemiologic, clinical, phylogenetic, and ethnographic. 
   
  Pathogen genetics: 
  Together with Dr David Bonsall and core staff of the Wellcome Centre for Human Genetics and investigators at the Peter Medawar Building, we have been developing new sequencing methods that have both diagnostic applications and generate rich and granular insights into epidemic dynamics. RNA sequencing that minimises PCR provides quantitative evidence of the abundance of different pathogens, of their resistance to treatment, and of their epidemic history. The practical challenges are manifold, but the aim is clear: we proceed in steps towards a method that is cheap, fast, sensitive, with full length genomes of all the pathogens in the sample, free of contamination, and integrated with robust automated computational pipelines. Progress has been rapid, and there are many applications and opportunities. See (<a href="http://www.ampheus.org/">http://www.ampheus.org/</a>) 
   
  COVID-19: 
  Our group has mobilised as part of Oxford’s very broad response to the COVID-19 epidemic. We originated the idea that a contact tracing app could make a big impact on controlling COVID, due to contact tracing being a race against time. We support the NHS Test and Trace programme as independent advisors. See <a href="http://www.coronavirus-fraser-group.org/">http://www.coronavirus-fraser-group.org/</a> Alongside this, we have developed models, simulations, and participate in the national sequencing programme (COG-UK). Together with Dr Tanya Golubchik and Dr Katrina Lythgoe, we have investigated the within and between host diversity and evolution of COVID. 
  Project areas: Epidemiology. Modelling. Simulation. Machine learning. Sequencing methods. Bioinformatics. Software development. Statistics. Public health. 
  Specific project proposals: 

  Please contact directly for further information.


pi_id: gill_deborah
overview:
  The manipulation of nucleic acids for therapeutic purposes (gene therapy, gene editing, etc) is generating success in the clinic. A key challenge, however, is to understand and control the delivery and expression of genes in target tissues. My research focuses on the development of genetic treatments for respiratory conditions with a large unmet clinical need. We have substantial expertise in the development of novel non-viral and viral gene delivery systems; we developed a CpG-free plasmid DNA/cationic liposome formulation for the treatment of cystic fibrosis (CF) lung disease that successfully completed a Phase IIb clinical study in 136 CF patients, which showed for the first time that gene therapy could halt the inexorable decline of lung function that leads ultimately to the premature death of CF patients. In the viral vector space, we are developing novel, lung-targeted lentiviral and AAV vectors for a range of lung disorders and applications. 
  In particular, there is an urgent need for treatments for childhood Interstitial Lung Diseases (ILD), affecting the interstitium - the tissue in and around the alveoli (air sacs) of the lungs. In adults, ILD often occurs after a lung injury triggers an abnormal healing response causing thickened, fibrotic alveolar tissue, leading to poor lung function. In children, ILD is more typically caused by genetic conditions, several of which can be lethal at birth. There are very few interventions/treatments available for these rare genetic diseases, with life expectancy typically measured in weeks or months. For example, genes involved in lung surfactant production are essential for establishing a healthy lung in newborns and studies in transgenic mouse models have provided proof of principle for therapeutic gene therapy/gene editing approaches. We are therefore developing a genetic treatment for a range of childhood ILDs, including deficiencies in surfactant protein B, surfactant protein C, and adenosine triphosphate-binding cassette transporter A3 (ABCA3).
  Project areas: Gene editing, gene therapy, transgenic mouse models, human lung culture models.
  Please contact directly for further information.


pi_id: goriely_anne
themes: 1,2,3,4
overview:
  De novo mutations (DNMs) are a significant contributor to human disease, affecting ~1:300 new births. We study the mechanisms by which these spontaneous mutations arise in the first instance, concentrating on the tissue where most of them originate, the human testis. 
  Most (>80%) DNMs originate in the paternal germline during spermatogenesis, explaining why the main risk factor for DNMs is the age of the father at conception. The human testis represents a ‘repository’ of DNMs that can be exploited to study the processes by which new mutations are acquired at each generation. We have previously described a mechanism contributing to the paternal age-related increase in pathogenic DNMs called ‘selfish selection’, a process equivalent to ‘clonal hematopoiesis’ but occurring in the unique context of the male germline stem cell. These ‘selfish DNMs’ become enriched with age, because they “hijack” the normal homeostatic mechanisms controlling spermatogonial stem cells to their own advantage. We have suggested that the mechanisms involved in selfish selection are similar to those described for tumorigenesis. However, unlike somatic variants in cancer, selfish mutations are transmitted across generations and have the potential to shape human genome evolution. We aim to develop methods for identification of new genes/molecular pathways subject to selfish selection within the human testis and establish the potential impact that this process has on human disease and genome evolution. 
  Another mechanism by which DNMs can be introduced in our genomes is through the process of mosaicism, which is increasingly being recognised as an important contributor to spontaneous disease. In this case, the DNM would have arisen early during one of the parents’ development and will be present in multiple eggs or sperm, leading to an increased recurrence risk (as high as 50%). Hence in clinical practice, it is important to be able to single-out DNMs due to gonadal mosaicism from the more common one-off events which have no risk of recurring in another child.
  In the long-term, understanding the landscape of selfish mutations and developing strategies for personalised recurrence risk assessment will permit clinical implementation of non-invasive screening approaches for DNMs, similar to those currently in use for detection of aneuploidies.
  Project areas: de novo mutations, mosaicism, NGS, gonadal development, spontaneous disorders
  Specific project proposals: 
  -- Goriely Laboratory Project: ‘Probing selfish selection of de novo mutations’
  -- Estimating the genome-wide prevalence of mosaicism through analysis of large-scale genomic datasets (with Dr Nicky Whiffin)
  Please contact directly for further information.
  These pages were updated: [29.07.2021]


pi_id: green_cath
themes: 1,3
overview:
  I run two teams at the University: Chromosome Dynamics at the Wellcome Centre for Human Genetics and Clinical BioManufacturing for the Nuffield Department of Medicine. Our research interests are, respectively: Genome Stability and DNA mutagenesis, and GMP manufacturing of novel biologics medicines for early phase clinical trials
  Project areas: DNA replication, DNA repair, mutagenesis, Chromosome Biology, Cytogenetics, GMP manufacturing
  No specific projects will be offered this year, but I am always happy to discuss bespoke options.
  Please contact directly for further information.


pi_id: handgunetthis_lahiru
themes: 1,2,3,4,5
overview:
  Lahiru Handunnetthi aims to understand how inflammation and infections contribute to the development of psychiatric and neurological disease. He combines genomics methodology with stem cell derived model systems to better understand neuro-immune interactions and to identify therapeutic targets for neuroinflammatory disease.
  Lahiru is involved in the functional characterisation of genetic risk alleles discovered through genome wide association studies. This involves gene editing techniques, induced pluripotent stem cell (IPSC) derived neuronal and glial model systems, as well as working with biological samples from patients.
  Lahiru has a specific interest in understanding how the immune system contributes to psychosis. He is actively involved in discovering the roles that autoantibodies and viral infections play in psychosis.
  Project areas: [Neuroscience, Immunology, Genomics, Stem Cells]
  Specific project proposals:
  --  ‘Genomic insights into neuroinflammation’ 
  -- 
  Please contact directly for further information.


pi_id: higgs_doug
overview:
  I am currently Professor of Molecular Haematology at the University of Oxford and until recently Director of the MRC Molecular Haematology Unit (MHU). I was also Director of the MRC Weatherall Institute of Molecular Medicine (WIMM) at the University of Oxford (2012-2020). I am both clinically qualified (FMedSci) and scientifically active (FRS and member of EMBO) and currently run an internationally leading research laboratory studying the regulation of gene expression.
  GMS themes: 
  -- Genomic and –omic technologies
  -- Functional genomics
  -- Genome biology (genomes and genetic variation)
  -- Genomics of disease
  -- Genomic analysis (bioinformatics and statistical genetics)
  -- From genes to clinic (target discovery, structural biology, medicinal chemistry)
  -- Application of genomics in the clinic (diagnostics and therapeutics)
  Research Focus
  Our laboratory is interested in the general question of how mammalian genes are switched on and off during lineage commitment and differentiation. We use the most recent genomics technologies to study individual genes in detail and study gene expression using genome-wide analyses. We study all aspects of gene expression including the key cis-regulatory elements (enhancers, promoters and insulators), the transcription factors and co-factors that bind them, the epigenetic modifications of chromatin and DNA and the role of associated phenomena such as chromosome conformation and nuclear sub-compartmentalisation using imaging techniques. These studies are performed both in cell systems and in model organisms as well as in human patients with various inherited and acquired genetic and epigenetic abnormalities. We use all aspects of computational biology including machine learning to extract general biological principles from our genomic datasets. The translational goal of our work is to develop new ways to modify gene expression during blood formation with the aim of manipulating gene expression and ameliorating the clinical phenotypes of patients with a variety of blood disorders.
   
  Some recent references from our laboratory
  Hay D, Hughes JR, Babbs C, Davies JOJ, Graham BJ, Hanssen L, Kassouf MT, Marieke Oudelaar AM, Sharpe JA, Suciu MC, Telenius J, Williams R, Rode C, Li PS, Pennacchio LA, Sloane-Stanley JA, Ayyub H, Butler S, Sauka-Spengler T, Gibbons RJ, Smith AJH, Wood WG, Higgs DR. Genetic dissection of the α-globin super-enhancer in vivo. Nat Genet. 2016 
  Hanssen LLP, Kassouf MT, Oudelaar AM, Biggs D, Preece C, Downes DJ, Gosden M, Sharpe JA, Sloane-Stanley JA, Hughes JR, Davies B, Higgs DR. Tissue-specific CTCF-cohesin-mediated chromatin architecture delimits enhancer interactions and function in vivo. Nat Cell Biol. 2017

  Larke MSC, Schwessinger R, Nojima T, Telenius J, Beagrie RA, Downes DJ, Oudelaar AM, Truch J, Graham B, Bender MA, Proudfoot NJ, Higgs DR, Hughes JR. Enhancers predominantly regulate gene expression during differentiation via transcription initiation. Mol Cell. 2021 
  Hua P, Badat M, Hanssen LLP, Hentges LD, Crump N, Downes DJ, Jeziorska DM, Oudelaar AM, Schwessinger R, Taylor S, Milne TA, Hughes JR, Higgs DR, Davies JOJ. Defining genome architecture at base-pair resolution. Nature. 2021
  Joseph Blayney, Helena Francis, Brendan Camellato, Leslie Mitchell, Rosa Stolper, Jef Boeke, Douglas Higgs*, Mira Kassouf* Super-enhancers require a combination of classical enhancers and novel facilitator elements to drive high levels of gene expression. bioRxiv 2022.06.20.496856; doi: <a href="https://doi.org/10.1101/2022.06.20.496856">https://doi.org/10.1101/2022.06.20.496856</a> (2023 Cell in press).

  Project areas: gene regulation, epigenetics, chromatin structure and function, computational biology.
  Specific project proposals:
  Determining the grammar and syntax of regulatory elements using laboratory and computational approaches
  Please contact directly for further information.


pi_id: hill_adrian
overview:
  Project areas: 
  Specific project proposals:
  -- ‘The functional consequences of human genetic variation on response to infectious disease’
  Due to limited availability can only offer possible co-supervision, alongside Alex Mentzer.utics)
  Please contact directly for further information.


pi_id: hinch_anjali
themes: 1,3,5
overview:
  We use analytical and experimental approaches to address fundamental questions on the nature of human de novo mutations, the mechanisms that generate them and their consequences on our health.
  We have discovered a significant source of de novo mutations and disease in humans, namely, repair of DNA breaks induced by the meiotic recombination machinery [Hinch et al, Science, 2023]. Our team has done a body of pioneering work on understanding how DNA changes take place in the germline. We showed that the landscape of recombination varies between individuals in different human populations, demonstrating the evolution of a key recombination gene PRDM9 in the human lineage [Hinch et al, Nature 2011]. 
  PRDM9 is also the only known speciation gene in mammals, and our subsequent work characterised the molecular mechanisms underpinning its role in hybrid sterility [Davies et al, Nature 2016]. These discoveries opened up new research avenues, towards a mechanistic understanding of the underlying processes. 
  We developed a novel approach to DNA sequencing of single cells that allowed identification of key molecular factors that affect how DNA breaks are repaired in meiosis [Hinch et al, Science 2019]. Our specialised genome-wide experimental assays have since led to insights on the molecular drivers of DNA break repair in meiosis [Hinch et al, Mol Cell 2020]. 
  Project areas: genetics, genomics, meiosis, genome editing, CRISPR, mutation, recombination, disease, structural variants, ChIP-seq, biobank, GEL, big data, machine learning, wet lab, computational.
  Specific project proposals:
  -- The landscape of de novo mutations in humans 
  Please contact directly for further information.


pi_id: holmes_chris
themes: 3,4,5
overview:
  Modern scientific applications in genetics and genomics produce data sets that continue to challenge conventional statistical methods. Our group is focussed on developing new scalable statistical methods and statistical foundations for robust, reproducible, analysis involving high-throughput genomics data particularly with multivariate outcome measurements (phenotypes). For instance, in recent work (de Angelis et al, Nature Genetics 2015) we developed techniques based on statistical “modularisation” to allow for scalable robust analysis of genomic data taken across multiple labs at multiple times. The modularisation allows for a global baseline model to be used with then multiple simple sub-models are used for testing. The statistical analysis pipeline in our paper was highlighted in the News and Views section of Nature Genetics entitled “Genetic differential calculus”. Genomics data is often complex and high dimensional such that it is difficult to construct an accurate probability model, or likelihood function, for the samples. In a recent paper (Bissiri et al 2015) we developed an extension of Bayesian statistics that allows for learning from data when models are misspecified. This provides for a way to fit simple Bayesian models to data and then “temper” (or anneal) the likelihood function to account for the approximation. Such methods have widespread appeal in modern biomedical applications and we are currently investigating them in the retrospective analysis of randomised trial data as part of an MRC Stratified Medicine consortium.
  Project areas: Stratified medicine and statistical machine learning models for multi-view integrative genomics, particularly using Bayesian methods. Recent collaborations include MRC Stratified Medicine consortium, STOP-HCV and S-CORT, as well as working closely with UK Biobank.
  Specific project proposals:
  Please contact directly for further information.


pi_id: hughes_jim
themes: 1,2,3,4,5
overview:
  The Hughes group is interested in how mammalian genes are regulated and how their deregulation is linked with human disease. The ~22 thousand genes in the mammalian genome are present in the DNA of every cell but are used in complex patterns in different cell types and organs. This system to turn genes off or on, modulating their levels of activity in different cell types is central to maintaining the complex biological system that is a multicellular organism. 
  What has become clear from large-scale genetic studies of human predisposition to common disease is that it is the control of the use of genes, rather than the genes themselves, that is frequently damaged. It is now known that functional elements other that genes exist in our DNA and these elements act as molecular switches which interact with the genes and control their use, however the mechanisms involved are not well understood. The Hughes group integrates both bench technologies and computational approaches to try and understand how these regulatory switches or enhancer elements work and how variations in their activity in our genomes leads to increased risk of developing common diseases, such as anemia, cancer, diabetes and autoimmune diseases.
  The group has a track history in the development of novel genomics technologies as well as computational approaches. The group has a molecular biology arm that is expert in next-generation sequencing based genomics and a purely computational arm which forms part of the WIMM CCB computational unit, with many lab members working in both areas.  Due to this structure, the group is highly multi-disciplinary, including people from diverse backgrounds and skill sets, from nucleic acid chemistry, biochemistry and molecular biology to bioinformatics, deep neural networks and JavaScript programmers and is always keen to incorporate new approaches from different fields to help answer its central questions.
  Project areas: 
  Genomics and Machine Learning.
  Synthetic biology and gene regulation.
  Sequence variation and disease.
  Single cell multi-omics and sequence variation.


pi_id: johnson_jethro
themes: 1,2,5
overview:
  am an Innovation Track Principal Investigator at the Kennedy Institute of Rheumatology and Deputy Director of the Oxford Centre for Microbiome Studies. My research uses multi-omic and computational approaches to identify the molecular basis of host-gut microbiome interactions and understand their impact on health and disease.
  In 2012 I completed a PhD in nutritional ecology at the University of Auckland, New Zealand, focussing on the effects of temperature on microbially-mediated digestion in ectothermic herbivores. I subsequently transitioned from wet to dry-lab research via an MRC career development fellowship in computational genomics, working with Professor Chris Ponting and Dr Andreas Heger at the Oxford MRC Functional Genomics Unit. As a postdoctoral research associate, I moved to the lab of Professor George Weinstock at the Jackson Laboratory for Genomic Medicine, Connecticut, USA, where I applied next-generation sequencing and computational genomic approaches to characterize the human microbiome. In particular, I focussed on the role of the microbiome in metabolic disease, working on the type 2 diabetes arm of the NIH Integrative Human Microbiome Project. I joined the Kennedy Institute in 2020 to establish my own research group and help run the OCMS.
  Project areas: Inflammation, Microbiome [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  --  ‘What is the effect of genetic variation on XXX?’ 
  Please contact directly for further information.


pi_id: jostins-dean_luke
overview:
  Our research is focused on identifying genetic associations with diagnosis or disease presentation in a range of inflammatory diseases, and developing statistical techniques to understand the function of these genetic risk variants. To translate disease genetics into real diagnostic, prognostic or treatment solutions we need to understand these pathways from genetic variation through healthy immune variation to disease risk. It is only through close collaborations between statistical geneticists, immunologists and molecular biologists that we will start to untangle these pathways.
  Our group has three interrelated strands. The first is the analysis of large-scale human cohort data using statistical and computational techniques that are specifically designed to identify multi-gene signatures of shared underlying immune variation. The second is to collaborate with other researchers to generate and analyse human immune variation data (including host immune function and exposure to both commensal and pathogenic organisms) in order to tie genetic risk of disease to variation in specific measurable immune phenotypes. The final strand is to collaborate with immunologists, cell biologists and clinical researchers to develop new ways of measuring the function of the human immune system in order to profile the specific pathways that confer genetic risk of chronic disease.
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  -- Predicting the genetics of immune response from baseline quantitative traits
  Please contact directly for further information.


pi_id: kanellakis_nikolaos
themes: 1,2,3,4,5
overview:
  Nikolaos works within the laboratory of pleural translational research.
  The pleura is a thin double layer of mesothelial tissue that lines the inside of the chest cavity and covers the lungs. The area in-between these two mesothelial membranes is called the pleural cavity, which is normally filled with a small amount of fluid that allows the lungs to move smoothly within the chest cavity during breathing. 
  Pleural effusion is a condition in which excess fluid accumulates in the pleural cavity. This fluid buildup can be caused by a variety of conditions, including cancer (malignant pleural effusion, MPE), infection, heart failure, kidney and liver disease and other conditions. 
  In our lab we focus on understanding the underlying biology of pleural disease with the aim to phenotype patients and stratify them to different groups. For this we use high-throughput and molecular biology methods. The aim of the lab is to investigate the underlying biology of pleural disease and provide evidence for clinical trials. 
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  --  ‘What is the effect of genetic variation on XXX?’ 
  -- ‘Second project title’.
  etc.
  Please contact directly for further information.


pi_id: kelleher_jerome
themes: 5
overview:
  Computational genomics is increasingly being driven by very large datasets consisting of hundreds of thousands of whole genomes. Existing computational methods and infrastructure are struggling to cope with this scale, and there is an urgent need for efficient algorithms and high-quality software. Our research focuses on two fundamental problems in population and statistical genetics: the ability to analyse genetic variation datasets at the population scale and inference of the genealogical history of these vast datasets. The methods revolve around the “succinct tree sequence” data structure, which is a highly efficient encoding of genetic ancestry that has the potential to solve the most pressing problems of scale, as well as provide deep insights into evolutionary processes. We develop efficient algorithms, and implement them in production quality, open-source software using state-of-the-art software development practices, in collaboration with a globally distributed network of scientists and software engineers.
  Project areas: Large scale genomics, genealogical analysis, population genetics, software development
  Specific project proposals:
  --  ‘Improved inference of genetic ancestry’ 
  Please contact directly for further information.


pi_id: kessler_benedikt
themes: 1
overview:
  A bioinformatics approach to study the cellular ubiquitin system in health & disease 
  The Ubiquitin System is indispensable for a human cell as it controls several cellular functions including degradation, autophagy, DNA repair and cell proliferation. This control occurs through the conjugation of ubiquitin to proteins, which can influence multiple aspects of their functionality, such as their activity, localisation or half-life (turnover).
  The ubiquitination of target proteins is complex, with the formation/removal of various poly-ubiquitin chain linkages being carried out by the conjugating enzymes (E1, E2 and E3) as well as by the erasers deubiquitinating enzymes (DUBs). The balance between ubiquitin conjugation and de-conjugation is crucial and well-regulated in cells. Many studies indicate that a dysfunction of this system could lead to numerous human diseases including cancer and neurodegenerative disorders. 
  Global approaches to determine the molecular function of components of the ubiquitin system (E3 and DUBs) include deep proteome, ubiquitome and interactome based on mass spectrometry studies, which are applied in our laboratory. The cutting-edge of mass spectrometry technology as well as molecular tools give us the opportunity to gain unprecedented depth and novel molecular insights into these cellular processes. Nevertheless, the data analysis for such complex -omic studies is still challenging and merits the development of more advanced mining tools. Therefore, we are looking for a highly motivated individual with a keen interest in molecular/ cellular biology and experience in programming as well as bioinformatics to i) help in the development of an –omics data analysis workflow and ii) apply this to untangle complex cellular –omics (proteomics / transcriptomics / ubiquitomics) data sets.
  Project areas: Genomics and –Omics technologies, proteomics, mass spectrometry, bioinformatics, ubiquitin system in cancer cells, protein turnover
  Specific project proposals:
  -- A bioinformatics approach to study the cellular ubiquitin system in health & disease
  Please contact directly for further information: Benedikt Kessler
  Emai: benedikt.kessler@ndm.ox.ac.uk


pi_id: knight_julian
themes: 1,2,3,4,5
overview:
  My current research uses a genetics and -omics led approach to understand why some individuals develop an inappropriate or dysregulated immune response to infection, how this may contribute to disease, and opportunities to advance precision medicine approaches. Complementing this, we aim to characterise the nature and functional significance of disease associated genetic variants in disease relevant contexts and innovate ways to use such knowledge to validate drug targets.
  Understanding the nature and basis of individual variation in the response to infection 
  (a) Genetic and epigenetic modulators of the induced innate immune response 
  (b) Functional genomics of sepsis response and development of a precision medicine approach
  (c) Understanding heterogeneity in COVID-19 infection and vaccine response using a multi-omic approach
  Genetics-led drug target identification and prioritisation
  We are developing computational approaches to enhance the utility of human genetics for understanding disease pathogenesis and novel therapeutic targets. This involves use of functional genomic profiling and integrative analysis to understand genes and pathways responsible for GWAS together with knowledge of network connectivity
  Project areas: human disease genetics, functional genomics, epigenetics, infection, immunity, drug targets, multi-omics
  Specific project proposals:
  --  Validating a genetics-led approach to drug target prioritisation in immune traits
  -- Resolving heterogeneity in the response to infection using -omics
  Please contact me directly for further information.


pi_id: kong_augustine
themes: 3,4,5
overview:
  My current research interest is on direct and indirect genetic effects, the latter includes genetic nurturing (see ref 1 and the New York Times link given below). I am also studying participation in a genetic study as an independent genetic trait. My general research interests include (i) recombination, (ii) genotype associations of diseases/traits such as type 2 diabetes, heart diseases, Alzheimer disease, schizophrenia, educational attainment, and fertility (iii) parent of origin effects, (iv) de novo mutations, and (v) somatic mutations. Further information can be found in my google scholar page. 
  Project areas: 
  Methods to decompose various factors that contribute to genotype-phenotype associations

  Please contact directly for further information.


pi_id: larson_greger
themes: 3,5
overview:
  Our modus operandi involves combining the resolution afforded by DNA sequences and fine-scale morphological variation with the time depth of archaeology and palaeontology. Doing so allows us to establish the patterns of DNA and morphological variance through time and space. We then take advantage of a range of bioinformatic approaches to answer long-standing questions related to how, when, and where evolutionary processes (including domestication) took place that have led to the creation of the modern world.
  Approaches: Molecular biology, phylogenetics, bioinformatics, modern and ancient DNA
  Project areas: I am happy to discuss potential projects in any area that fit within our group. We already have two potential projects both co-supervised by Adrian Smith (Zoology) that relate immunity and infectious disease to past human and animal populations.
  Specific project proposals: 
  -- ‘Molecular archaeoparasitology approaches to interrogate past populations’ (Supervisors: Adrian Smith, Greger Larson and Patrik Flammer, page 60.
  -- ‘Using ancient DNA to understand the impact of humans on the immune system of domesticated animals’ (Supervisors: Greger Larson, Adrian Smith and Laurent Frantz), page 60.
  Please contact directly for further information.


pi_id: leedham_simon
themes: 1,2,4
overview:
  We are interested in the morphogenic control of intestinal stem cell fate in homeostasis, regeneration and cancer. Work ranges from cell fate disruption in the pathogenesis of inflammatory and neoplastic disease, to assessment of individual signalling pathways including preclinical drug testing, as well as cancer heterogeneity and evolution.
  Add other section headings as appropriate if desired – Heading 3 style.]
  Project areas: Intestinal stem cells, morphogen signalling, preclinical drug testing, cancer heterogeneity 
  Specific project proposals:
  Projects can be tailored according to student interests
  Please contact directly for further information.


pi_id: lindgren_cecilia
themes: 2,3,4,5
overview:
  Obesity is an urgent global health challenge with no imminent preventive solutions within reach. It is a heritable heterogeneous condition and a well-established predictor of adverse metabolic outcomes. Our research focuses on the integration of large-scale data sets of genomic sequence variation and transcriptional regulation (genetics and genomics) with phenotypic data to advance the understanding of the molecular pathogenesis of obesity and related traits. We have been playing a key role in the collaborative work that have brought forward over 7,000 loci associated with various obesity traits (body mass index, BMI, waist:hip ratio, WHR, fat% etc.) (GiANT – unpublished data). It is notable that many variants associated with overall obesity (BMI) are located near neuronal genes that affect appetite regulation and variants associated with fat distribution (WHR) are located near genes that affect insulin signalling, fat deposition and metabolic traits. My team is dedicated to translating genetic associations into functional and pathophysiological mechanisms, and establishing how this can improve our understanding of the physiology and biology underlying obesity traits. 
  Projects can be tailored to personal interests and can involve either a wet lab and/or a data analysis/bioinformatics component though the listed project is 100% dry lab, computer based.
  Project areas: Electronic phenotyping, bioinformatics, computational biology, SNP typing and statistical genetics, genomics, obesity, fat distribution, meta-analysis, genetic association and gene expression.
  Specific project proposals:
  --  ‘’Accelerate the discovery of causal variant(s) associated with fat distribution and central obesity’
  Please contact directly for further information.


pi_id: lu_xin
themes: 1,2,3,4,5
overview:
  My group studies the molecular mechanisms underlying cell plasticity and tumour suppression. Correct control of cell plasticity is fundamental in development, and dysregulation of cell plasticity leads to pathogenesis. The tumour suppressor p53 is the most mutated gene found in human cancers and one of the most well-known guardians of cell plasticity. In my early work, I was among the first to show that activation of certain oncogenes bypasses the tumour suppressive function of wild type p53 in cancers and that transcriptionally active p53 responds to DNA damaging agents. Therefore, a longstanding interest in my lab has been to understand how WT p53 loses its tumour suppressive function without genetic mutation in tumorigenesis with an aim to restore the tumour suppressive function of p53 in wild type p53-expressing cancer cells. This led to the discovery of the ASPPs as the first protein family that can selectively steer p53 towards killing cancer cells. Our subsequent study of ASPP biology and our cancer research journey has touched both heart and mind. We revealed that ASPPs are cytoplasmic-nuclear shuttling proteins that enter the nucleus through RaDAR pathway, a novel and the second general nuclear import pathway we discovered that is used by many ankyrin repeat containing proteins (>250 in the human genome). We conceptualized that many proteins, like the ASPPs, will drive selective transcription programs that determine cell fate/ phenotype after sensing external signals and shuttling to the nucleus. Consistent with this, we showed that ASPPs connect cell polarity and cell/cell adhesion to cell plasticity through their ability to regulate target selectivity of multiple transcription factors including p53, p63 and JunD/AP1. Germline mutation in ASPPs cause CNS developmental abnormalities and sudden cardiac death in animals and humans with ASPP2 deletion causes human 1q41-42 microdeletion syndrome and iASPP deletion causes cardiocutaneous syndrome and paediatric cardiomyopathy. We recently applied our molecular understanding of p53 and ASPP biology to study molecular regulation of cell plasticity in human pathological conditions, in particular H. pylori-infected gastric epithelial cancer cells, Barrett’s oesophagus and oesophageal adenocarcinomas in response to immunochemotherapy.  
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  --  ‘What is the effect of genetic variation on XXX?’ 
  -- ‘Second project title’.
  etc.
  Please contact directly for further information.


pi_id: lucassen_anneke
themes: 4
overview:
  Please see <a href="https://www.ndm.ox.ac.uk/team/anneke-lucassen">Anneke Lucassen — Nuffield Department of Medicine (ox.ac.uk)</a> and <a href="http://www.soton.ac.uk/cels">www.soton.ac.uk/cels</a> for types of research my group does. 
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  Please contact directly for further information.


pi_id: luo_yang
themes: 1,2,3,4,5
overview:
  Our group develops statistical and computational methods for understanding the contribution of genetic variations to immune-mediated traits. We focus in particular on the major histocompatibility complex (MHC) region. The MHC region encodes proteins that play a vital role in our immune response. For a vast number of immune-mediated traits, MHC accounts for more genetic heritability than all other genomic variations combined. However, the exact molecular mechanisms behind MHC disease risk are yet unsolved. Knowledge of this would have an impact on subsequent cellular and clinical outcomes. We leverage large biobank data (e.g. UK Biobank and Biobank Japan), gene expression data (e.g. from GTEx), and protein concentrations (e.g. from Omicscience), to understand the precise biological mechanisms through which genetic variation is mediated to modulate risk of immune-mediated traits.
  Project areas: 
  HLA, autoimmune diseases, eQTL, pQTL, single cell RNA-sequencing
  Specific project proposals:
  --  ‘Identifying causal HLA variants that regulate protein abundance using data from two large Biobanks’
  -- ‘Identifying selection signals among classical HLA alleles and long-range haplotypes in admixed populations’
  Please contact directly for further information.


pi_id: lythgoe_katrina
themes: 1,3,4,5
overview:
  In our group, we are interested in the evolutionary epidemiology of viral infections, including HIV, Hepatitis C and Hepatitis B. More recently, we have also been working on the within-host evolution and transmission of SARS-CoV-2.
  We use a combination of approaches, including the evolutionary analysis of viral sequence data and mathematical modelling. More specifically, we are interested in evolutionary and ecological processes operating at different ecological scales (e.g. within- and between-host), to assess the impact this integration of scales has on our understanding of the evolution and epidemiology of infectious disease. Our ultimate aim is to produce better predictive models of the consequences of interventions, including the spread of vaccine escape mutations, transmitted drug resistance, changing levels of viral virulence, and adaptation of viruses to host immunological backgrounds.
  Project areas: Viral Evolution, Evolutionary Epidemiology, Analysis of next generation sequencing data, Mathematical Modelling, Genomics, Phylogenetics, Population Genetics.
  Specific project proposals:
  -- Designing evolution proof CTL-based vaccines for Hepatitis C Virus
  -- Towards a cure for Hepatitis B Virus: Uncovering the role of integrated virus
  -- Linking the within- and between-host evolution of SARS-CoV-2

  Please contact directly for further information.


pi_id: mccullagh_james
overview:
  McCullagh group: Understanding the chemistry of small molecules in complex biological systems.
  Our aim is to better understand how small biological molecules function in the context of complex natural systems and what happens when these systems are purturbed. For example we focus on developing highly efficeint analytical approaches for comprehensive analysis of metabolites in cells, tissue and bio-fluids and applying these to understand how fundamental metabolic processes are altered in disease. We apply a multi-technique approach, including metabolomics, live cell imaging and real-time analysis of metabolism, to focus on comprehensive molecular phenotyping and capturing small molecule interactions at a systems-wide level.
  Project areas: 
  Specific project proposals:
  Please contact directly for further information.


pi_id: mentzer_alexander
themes: 1,4
overview:
  Human genetic diversity has both been shaped by, and influences how we respond to infectious disease which continues to pose an enormous global burden of morbidity and mortality as highlighted recently by the COVID-19 pandemic. It remains unclear the extent to which this genetic diversity influences immune responses in the context of vaccination and how we can use this information to target or tailor international vaccination efforts against a variety of infectious pathogens or use this information at the clinical front-line for patients unwell with infectious diseases. 
  Our research group uses antibody responses as a model of conserved antigen-specific immune response against infectious agents and then correlates these responses with human genetic diversity to understand these relationships both following natural infection exposure and vaccination. We have developed bespoke multi-antigen antibody assays to facilitate such measurements in very large cohorts around the world including UK Biobank (Mentzer et al, Nat. Comms. 2022), the China Kadoorie Biobank (Yao et al, BMJ Open, 2022), and various vaccinated infant cohorts across Africa (Mentzer et al, Nat. Medicine 2024), Asia (Butler-Laporte et al, MedRxiv 2024), and the UK (O’Connor* et al, Nat. Medicine, 2023). Using these approaches we have found that diversity in complex regions of the genome such as the major histocompatibility complex and immunoglobulin loci strongly affect responses to natural infectious challenge from agents such as the human herpesvirus family members and vaccination responses against agents such as SARS-CoV2 and B. pertussis, the cause of whooping cough. Our current objectives are to expand and combine these datasets to understand how much human genetic diversity affects responses against multiple infections simultaneously or whether such variation effect is pathogen-specific, and understand the scope of these effects to other emerging infections such as COVID-19. We also aim to use these population insights in unique samples collected in the acute hospital setting. Ultimately it is hoped that this work will inform both future vaccination efforts to help develop more tailored yet universally effective vaccines against multiple infectious agents, and also novel diagnostic and prognostic approaches for patients presenting to hospital with infectious diagnoses.
  Project areas: Genome-wide association studies, analysis of immune and complex traits, stratified and personalised medicine
  Specific project proposals:
  --  ‘The functional consequences of human genetic variation on response to infectious disease’ 
  Please contact directly for further information.


pi_id: milne_thomas
themes: 1,3,4,5
overview:
  My lab’s overall goal is to discover how epigenetic systems are leveraged in cancer to create pathogenic gene expression states and to use this basic knowledge to develop new targeted therapies. I focus on high-risk infant and childhood acute lymphoblastic leukaemias (ALLs), the most common form of paediatric cancer, for which relapse and refractory disease is largely untreatable. In this group of aggressive cancers, we have recently discovered that Mixed Lineage Leukaemia rearrangements (MLL-r) cause an altered epigenetic landscape which may drive the emergence of novel enhancers and pathogenic gene expression states. Epigenetics is often defined as heritable changes in gene expression that don’t alter the underlying DNA sequence, driven by many effectors including the covalent modification of histone proteins. Histones are part of the chromatin DNA/protein complex, and many histone modifications act as docking sites for the binding of chromatin protein complexes. Histone modifications are associated with key regulatory elements in the genome such as enhancers. Enhancers are essential for both normal and aberrant gene expression, but we currently have no understanding of how aberrant enhancer activity contributes to patient prognosis. To address this fundamental question, we will now exploit our novel CRISPR/Cas9 human fetal derived ALL models to discover whether enhancer emergence in ALL is dependent on a pre-existing permissive epigenetic state or is created de novo. We will also investigate how distinct chromatin proteins drive enhancer function and create the gene expression states that define prognosis in poor risk ALLs. 
  Project areas: epigenetics; 3D genome; enhancers; leukaemia; acute lymphoblastic leukaemia; infant leukaemias; gene regulation; transcription; epigenomics; bioinformatics
  Specific project proposals:
  --  How do chromatin proteins drive aberrant enhancer activity in leukaemia?
  Please contact directly for further information.


pi_id: milosevic_ira
themes: 1,2,4
overview:
  Our group focuses on comprehending neuronal functions at the molecular level, with the purpose of using this knowledge to address the mechanisms of neurodegenerative diseases, and to explore whether certain brain functions (e.g., memory, motor coordination, hearing) can be improved. The emphasis of our research is on the mechanisms underlying exocytosis and endocytosis, and the consequences of their dysfunction, such as impaired synaptic physiology and neurodegeneration. We now aim to ‘translate’ the obtained knowledge to understand the processes that happen at the onset of certain neurodegenerative diseases and to improve their diagnostics by identifying early disease markers. Notably, we also study regulation of organelle acidification and synaptic vesicle ‘maturation’ with a focus on protein-protein interactions underlying these processes. 
  We employ multi-disciplinary approaches that include behavioural studies, cell biology, electrophysiology, imaging and –omics approaches (transcriptomics, proteomics, metabolomics), and capitalize on a large collection of human cell lines and mouse models with defective SV recycling and/or acidification. Specifically, we are working on the molecular mechanisms underlying exocytosis (e.g., Nat Commun 2020; PNAS USA 2020; bioRxiv 2023.08.22.554276), endocytosis (e.g., J Cell Biol 2018; Neuron 2018; EMBO J 2019; Nature 2019) and vesicle acidification (eLife 2018). Notably, in the past years we have discovered two new ways of v-ATPase regulation: by (1) clathrin coat (eLife 2018) and (2) rabconnectin-3 (under review). We are also addressing the relevance of defective endocytosis and synaptic vesicle recycling to Parkinson’s disease (PD) and ataxias, e.g. by linking endophilin-A (key endocytic protein) to PD, protein homeostasis and autophagy - Cell Reports 2016, and α-synuclein (key exocytic protein) in endosomal trafficking – PNAS USA 2016. In the context of impaired cell physiology that leads to neurodegeneration, we are exploring the links between defective endocytosis and mitochondria (in collaboration with Raimundo’s lab: Autophagy 2018; eLife 2018; Nature 2019), and the links between protein quality control and aging (in collaboration with Krisko’s lab: Aging Cell 2017; Aging 2018; Nat Commun 2021). In sum, we work to advance the understanding of neuronal and synaptic physiology with a goal of exploring the extent of brain plasticity in health and disease.
  Project areas: 
  Neuronal cell biology, neurodegeneration, neurotransmission, exocytosis, endocytosis, neurogenerative diseases, Parkinson’s disease, ataxia, diabetes, experimental medicine, live cell imaging
  Specific project proposals:
  --  Endocytosis deficiency as a trigger of cellular senescence 
  -- Characterisation of amisyn, a negative regulator of exocytosis
   
  Please contact directly for further information: Ira Milosevic, <a href="mailto:imilose@well.ox.ac.uk">imilose@well.ox.ac.uk</a>; Phone: 87622


pi_id: myers_simon
overview:
  Our group works on analytical and experimental approaches to understand genetic variability and its impacts, in health and disease. 
   
  One focus is studying meiosis and recombination, a fundamental and key biological process in most species. Recombination is essential for fertility in humans, and with mutation it generates all genetic variation that exists. Errors in recombination cause genomic rearrangements, resulting in many human diseases. One research focus of our group is studying this basic process, and specifically factors influencing recombination event positioning along the genome. This has led on to findings connecting the biological recombination machinery, evolution, fertility, speciation and disease, using a combination of analytical, statistical and experimental approaches. Our work identified the fast-evolving protein PRDM9 as the zinc-finger protein positioning mammalian recombination hotspots (Myers et al., Science, 2010, recently included within the top 21 achievements of WHG researchers, across the 21 years of the centre's existence). We showed that recombination hotspots vary across human populations (Hinch, Nature, 2011). Our recent work studies an example of ongoing speciation in mammals (Davies, Nature, 2016). We showed that humanization of PRDM9’s zinc-finger array in mice rescues fertility in mouse hybrids, reversing speciation. In turn, it gave key insights into the mysterious process of homologous chromosome pairing, which allows proper inheritance of genetic material from parents to children, showing this to depend on sequence matches only at a tiny fraction of the genome. 
   
  A second focus of the group is developing statistical approaches to understand admixture and population structure. This work was again chosen among the top 21 achievements of WHG researchers. Population structure is the major potential confounder in disease association studies, and its understanding can also provide direct historical insights. We co-developed (Lawson,
  PLoS Genetics, 2012) a method fineSTRUCTURE that has revealed that genetic differences exist at very fine geographic scales within the UK (Leslie, Nature, 2015). We also published work (Hellenthal,
  Science, 2014) characterizing, for the first time, the complex ways in which many different mixing events – relating to e.g. the Mongol expansion, and Slavic migrations - have impacted the DNA of human populations worldwide. Ongoing projects are studying UK Biobank data, and work on building the genealogical history of every position in the genome.
  Project areas: population genetics, stochastic models, mapping disease genes, methods for fine-mapping association signals.
  Specific project proposals:
  -- ‘Re‐engineering the DNA binding characteristics of a speciation gene’
  Please contact directly for further information.


pi_id: palamara_pier
themes: 4,5
overview:
  Our work is at the intersection of computer science, statistics, and genetics. We develop statistical and machine learning algorithms to enable new types of analyses in large human genomic data sets. Specific areas of research include:
  -- Developing algorithms for simulation, reconstruction, and analysis of large-scale genealogical data (gene genealogies, haplotype sharing, phasing, imputation).
  -- Studying demographic events and evolutionary parameters (migration, expansion/contraction of populations, natural selection, mutation/recombination rates).
  -- Studying the genetic architecture of complex traits and detecting disease-causing variation in the human genome (heritability, polygenic prediction, association).
  Project areas:
  During the past few years our group has been developing several new methods to infer the presence of hidden relatedness and to reconstruct deep genealogical structures from large genotyping and sequencing data sets [Palamara et al. Nature Genetics 2018; Nait Saada et al. Nature Communications 2020; Zhang et al. Nature Genetics 2023]. We have applied these algorithms to the UK Biobank data set, studying fine-scale population structure (<a href="https://ukancestrymap.github.io/">website</a>), recent evolutionary history, and association between heritable traits and unobserved genomic variation. We are working on extending this framework in several directions, which will create new opportunities for the study of human evolutionary history and disease.
  We have also been developing new machine learning methodology for analyses in statistical and population genetics. Examples include efficient stochastic variational inference approaches to increase the statistical power of genome-wide association studies [Loya et al. Nature genetics, in press], and methods that use deep neural networks to infer genealogical relationships across samples [Nait Saada, Tsangalidou et al. Molecular Biology and Evolution 2023].
  Several DPhil projects are available within these research areas, please get in touch to discuss these directions.
  Representative publications:
  -- H. Loya, G. Kalantzis, F. Cooper, P. Palamara. A scalable variational inference approach for increased mixed-model association power. Nature Genetics, in press.
  -- M. Stricker, W. Zhang, W. Cheng, S. Gazal, C. Dendrou, S. Nahkuri, P. Palamara. Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits. Cell Genomics, 2024.
  -- R. Fournier, Z. Tsangalidou, D. Reich, P. Palamara. Haplotype-based inference of recent effective population size in modern and ancient DNA samples. Nature Communications, in press.
  -- J. Nait Saada, Z. Tsangalidou, M. Stricker, P. Palamara. Inference of coalescence times and variant ages using convolutional neural networks. Molecular Biology and Evolution, 2023.
  -- B. Zhang, A. Biddanda, Á. Gunnarsson, F. Cooper, P. Palamara. Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits. Nature Genetics, 2023.
  -- J. Nait Saada, G. Kalantzis, D. Shyr, F. Cooper, M. Robinson, A. Gusev, P. Palamara. Identity-by-descent detection across 487,409 British samples reveals fine-scale population structure, evolutionary history, and trait associations. Nature Communications, 2020.
  -- P. Palamara, J. Terhorst, Y. Song, A. Price. High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability. Nature Genetics, 2018.
  -- P. Palamara. ARGON: Fast, whole-genome simulation of the discrete time Wright-Fisher process. Bioinformatics, 2016.


pi_id: pinto-fernandez_adan
themes: 1
overview:
  De. Adán Pinto-Fernández is a Career Development Fellow at the CAMS Oxford Institute (COI) since November 2021, working on cancer immunology and immunotherapy. 
  His current research involves the study of the roles of a class of druggable enzymes called deubiquitylating enzymes (DUBs) in the innate immune response and cancer inflammation using advanced proteomics, ubiquitomics, lipidomics, and immunology techniques as main tools.  
  Project areas: Innate immunity, Cancer Inflammation, Cancer Cell Biology, Proteomics, Lipidomics, and Target and Drug Discovery. Specific project proposals:
  --  DeISGylating enzymes as therapeutic targets in immuno-oncology.
  Please contact directly for further information.


pi_id: reinert_gesine
themes: 2
overview:
  [Please write details of your research interests here.
  Add other section headings as appropriate if desired – Heading 3 style.]
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  --  ‘What is the effect of genetic variation on XXX?’ 
  -- ‘Second project title’.
  etc.
  Please contact directly for further information.


pi_id: sanders_stephan
themes: 1,2,4
overview:
  My research uses genetics and ‘omics to understand the causes of neurodevelopmental disorders (NDD) including seizures and autism spectrum disorders. I pioneered methods to identify specific genes through the identification of rare de novo germline mutations identified by microarray and high-throughput sequencing. Through the international Autism Sequencing Consortium, which I co-lead, these efforts have identified hundreds of genes underlying NDD. We are working to extend these methods into noncoding regions, including the development of SpliceAI for cryptic splice sites. As a co-lead of BrainVar, we use large-scale functional data from the developing human brain to determine the cells, brain regions, processes, and developmental stages by which NDD-associated genes lead to symptoms. Severe cases of NDD are associated with high mortality and extensive developmental impairment. Working with colleagues at Oxford, Boston, UCSF, and Berkeley, we aim to develop nucleic acid therapies such as Antisense Oligonucleotides and CRISPR-based approaches, to improve the lives of affected individuals.
  Project areas: 
  Specific project proposals:
  ‘Therapeutic genomics: Integrating whole-genome sequencing and functional genomics data to identify loci for genome-targeted therapies in rare disorders’
  Please contact directly for further information.


pi_id: sansom_stephen
themes: 1,2,4,5
overview:
  The causes of immune-mediated inflammatory disease (IMIDs) are incompletely understood, but can include genetic factors, lifestyle factors, environmental factors and microbiome composition. Our research is based on the concept that such factors integrate at the cellular level, where they manifest in the form of pathogenic cellular phenotypes and signalling circuits in specific tissues. We use unbiased single cell and spatial genomics approaches to discover problematic cellular phenotypes and signalling circuits directly from patient biopsy samples. By doing so, we aim to understand the molecular and cellular basis of inflammatory disease and to enable the identification and prioritisation of novel targets for therapeutic intervention. Currently, the group has a focus on understanding the pathogenesis of inflammatory bowel disease and HLA-B*27 ankylosing spondylitis.
  Research Interests
  -- The pathogenesis of inflammatory bowel disease (IBD) is complex and multifactorial in nature. Recently, in proof-of-concept studies, we combined network and single-cell approaches to explore previously unknown heterogeneity in tissue pathotypes. A more complete understanding of the spectrum of cellular pathotypes that underly IBD will provide a rational basis for the development of novel and personalised treatments. In work recently funded by a 5-year MRC programme grant we are working with the group of Prof. Fiona Powrie, clinical scientists, mucosal immunologists and microbiome specialists to establish a comprehensive atlas of IBD pathotypes and their relationship with disease outcomes. 
  -- Why is the MHC class I molecule HLA-B*27 linked with inflammatory disease? Spondyloarthritis is a common disease for which the cellular causes remain mysterious despite an extraordinarily strong genetic association with HLA-B*27 (odds ratio=131). We are using single-cell and spatial genomics data from human patients to evaluate three competing biological hypotheses of how this molecule might act to initiate disease (the arthritogenic peptide hypothesis, the ER stress hypothesis and the free-heavy chain hypothesis). 
  -- The development of new computational pipelines and tools for single-cell and spatial genomics data analysis. 
  Project areas: Immunology, development, immune-mediated inflammatory disease, inflammation, single-cell genomics, functional genomics, cell-cell interactions, human cell atlas, computational biology
  Specific project proposals:
  Please contact directly for further information


pi_id: sarkies_peter
themes: 2,3,4,5
overview:
  -- My laboratory is focussed on the connections between epigenetics and evolution. Within this there are two distinct themes. First, we are interested in whether epigenetic changes can ever drive evolution, independent of DNA sequence variation. We are particularly interested in whether this could promote the early stages of evolution, both in species and within cancer. To do this we have been using the nematode C. elegans as a model system to study whether epigenetic changes, known as epimutations, occur during populations and measure their dynamics (Beltran et al., Nature Ecology Evolution, 2020; Wilson et al., PLoS Genetics 2023). This work involves using bioinformatic analyses of high-throughput sequencing data, developing new statistical analyses to robustly identify epimutations, and linking these to gene expression changes. We are currently investigating how evolution of drug resistance may be promoted by epimutations. Second, we are interested in what drives the evolution of epigenetic mechanisms, which show a great diversity across species and also in cancer cells where epigenetic pathways are frequently inactivated by somatic mutations. We discovered that DNA methylation has a toxic byproduct, alyklation damage (Rosic et al., Nature Genetics 2018), and are exploring the consequences of this in leukemia. We have also shown, using computational analysis of multi-omic data across cancer, that metabolism drives changes in epigenetic modifications in human cancer cells (Perez and Sarkies, PLoS Biology, 2023, <a href="https://doi.org/10.1371/journal.pbio.3002354">https://doi.org/10.1371/journal.pbio.3002354</a>). We are following this up by investigating more generally the links between epigenetics and metabolism using bioinformatic analyses of data across human cancers, especially histone acetylation. Work in my laboratory is funded by the Medical Research Council, the Wellcome Trust and the Leverhulme Trust. 
  Project areas: Epigenetics, Evolution, metabolism, cancer, single cell sequencing, computational biology, machine learning

  Specific project proposals
  How do histone post-translational modifications affect metabolism?


pi_id: smith_adrian
themes: 3,4,5
overview:
  The group employs a comparative biology approach to investigate the evolution and function of the immune system and interactions with pathogens. We work with an extremely wide range of host species including humans, rodents, badgers, bats, chickens, penguins, other vertebrates and corals considering immune processes and functional immunogenetics. Some projects are very focussed on a single host species whilst others consider processes more broadly across wider phylogenetic groups. We have expertise working with viral, bacterial and parasitic infections as well as the enteric microbiome. Although much of the work is with modern samples we also work with archaeological samples and ancient DNA (aDNA). Our current projects in the aDNA area include the molecular archaeoparasitology of helminth parasites that infect humans and the impact of past events on farm animal immune systems.
  Approaches: Molecular and cellular biology, bioinformatics, functional immunology, pathogen genetics, modern and ancient DNA
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  I am happy to discuss potential projects in any area that fits with the group. However, to begin with we have two potential projects both co-supervised by Greger Larson (Archaeology) that relate immunity and infectious disease to past populations.
  -- ‘Molecular archaeoparasitology approaches to interrogate past populations’ (Supervisors: Adrian Smith, Greger Larson and Patrik Flammer).
  -- ‘Using ancient DNA to understand the impact of humans on the immune system of domesticated animals’ (Supervisors: Greger Larson, Adrian Smith and Laurent Frantz).


pi_id: taylor_jenny
themes: 1,2,3,4,5
overview:
  Our group focuses on application of whole genome sequencing (WGS) for understanding the pathogenesis of a broad spectrum of rare diseases, with the primary aim of identifying novel disease genes and biological mechanisms of disease. The genome sequencing data is available from our own cohorts and the Genomics England 100,000 Genomes Project. Genetic analysis involves a suite of custom and commercial bioinformatics and protein informatics software packages to filter the likely pathogenic variants and assess the impact of the mutations. Links between rare and common disease are interrogated using a combination of the 100kGP and the UK Biobank datasets.
  Potential novel disease genes identified from WGS data are followed up using a range of functional studies including CRISPR gene editing, multi-omics and molecular/cellular biology approaches, often in collaboration with other groups. Several putative novel genes in neurodevelopmental conditions are currently under investigation experimentally in the lab.
  We are also using the datasets to identify genetic variants that may be amenable to intervention with nucleic acid therapeutics such as anti-sense oligonucleotides or CRISPR editing. 
  This group is linked with the Oxford NIHR Biomedical Research Centre’s Genomic Medicine Theme’ s translational research programme, the Oxford Harrington Rare Disease Centre and the Dept of Paediatrics. As a clinical genome sequencing programme, it is strongly connected with clinical diagnostic genomics labs. Our results therefore have the potential to inform molecular diagnoses and treatment selection for patients, which will appeal to the GMS students who are interested to see clinical and translational outcomes from their research projects. 
  Project areas: whole genome sequencing, bioinformatics, rare diseases, genetic and functional studies, genetic diagnostics to therapeutics 
  Specific project proposals:
  Please contact me, Prof Jenny Taylor, directly for further information.
  Please note that all projects can be adapted for the wet lab/dry lab components according to the interests of the students
  1) Genetic diagnoses to therapeutics for patients with rare neurological disorders
  2) Genetic variants underpinning early onset Parkinson’s disease (collaboration with Milosevic lab)
  3) Reverse genomics: from functional to genetics in neurodevelopmental and neurodegenerative disorders (collaboration with Milosevic lab)


pi_id: todd_john
themes: 1,2,3,4,5
overview:
  JDRF/Wellcome Trust Diabetes and Inflammation Laboratory (DIL)
  The DIL is led by John Todd (Director) and Linda Wicker (Co-Director). The lab is researching the causes of the autoimmune disease type 1 diabetes (T1D) in order to treat and prevent the disease by modulating the causative pathways. We achieve this by linking genetic determinants of disease with phenotypes and pathways in cells and in patients, using a wide range of molecular, metabolic, immunological, computational and statistical approaches.
  Genetics: identification of T1D genes and their pathways is essential for understanding the biology underpinning disease susceptibility. We are integrating the latest and emerging genomics data - genetic variation, RNA and protein gene expression, methylation, transcription factor binding sites and chromatin phenotypes – to better define the T1D causal genes. 
  Phenotypes and mechanisms: identify aberrant cellular interactions and pathways caused by susceptibility genes that mediate a loss of immune tolerance to insulin-producing beta cells culminating in their destruction. These will provide potential targets for therapeutic intervention, as demonstrated by our work in the IL-2 pathway. This knowledge will contribute to understanding cell interactions altered by disease genes, an essential step for prioritizing potential immune-modulating agents to be investigated in experimental studies in T1D patients. 
  Experimental medicine: our hypothesis is that determination of the optimal dosing regimen of a potential therapeutic in terms of its molecular and cellular responses in vivo will greatly improve the likelihood of a beneficial outcome in future clinical trials. We are testing the utility of this approach in the ongoing investigation of the effects of ultra-low doses of IL-2 in patients with T1D, and will consider and evaluate other potential therapeutics. Secondly, we are part of an randomised control trial for primary prevention T1D in children in the population by feeding newborn children oral insulin every day for three years to promote immune tolerance to insulin, the primary autoantigen in T1D. Thirdly, we are planning investigation of the enhancing the healthy state, including improving tolerance to insulin through cross reactivity with a commensal antigen that we have discovered, of the intestinal microbiome using combinations of bacterial probiotics and prebiotics, in the context of deep microbiome genome sequencing and interactions with the HLA class II genotypes that increase and decrease risk of autoimmune responses to insulin and to T1D.
  Potential project areas: Diabetes, autoimmunity, genomics, single cell omics, genetics, statistics, bioinformatics, immunology, experimental medicine, clinical trials.
  JDRF/Wellcome Diabetes and Inflammation Laboratory (DIL)
  The DIL is led by John Todd (Director) and Linda Wicker (Co-Director). The lab is researching the causes of the autoimmune disease type 1 diabetes (T1D) in order to treat and prevent the disease by modulating the causative pathways. We achieve this by linking genetic determinants of disease with phenotypes and pathways in cells and in patients, using a wide range of molecular, metabolic, immunological, computational and statistical approaches.
  Genetics: identification of T1D genes and their pathways is essential for understanding the biology underpinning disease susceptibility. We are integrating the latest and emerging genomics data - genetic variation, RNA and protein gene expression, methylation, transcription factor binding sites and chromatin phenotypes – to better define the T1D causal genes. 
  Phenotypes and mechanisms: identify aberrant cellular interactions and pathways caused by susceptibility genes that mediate a loss of immune tolerance to insulin-producing beta cells culminating in their destruction. These will provide potential targets for therapeutic intervention, as demonstrated by our work in the IL-2 pathway. This knowledge will contribute to understanding cell interactions altered by disease genes, an essential step for prioritizing potential immune-modulating agents to be investigated in experimental studies in T1D patients. 
  Experimental medicine: our hypothesis is that determination of the optimal dosing regimen of a potential therapeutic in terms of its molecular and cellular responses in vivo will greatly improve the likelihood of a beneficial outcome in future clinical trials. We are testing the utility of this approach in the ongoing investigation of the effects of ultra-low doses of IL-2 in patients with T1D, and will consider and evaluate other potential therapeutics. Secondly, we are part of a randomised control trial for primary prevention T1D in children in the population by feeding newborn children oral insulin every day for three years to promote immune tolerance to insulin, the primary autoantigen in T1D. Thirdly, we are planning investigation of the enhancing the healthy state, including improving tolerance to insulin through cross reactivity with a commensal antigen that we have discovered, of the intestinal microbiome using combinations of bacterial probiotics and prebiotics, in the context of deep microbiome genome sequencing and interactions with the HLA class II genotypes that increase and decrease risk of autoimmune responses to insulin and to T1D.
  Potential project areas: Diabetes, autoimmunity, genomics, single cell omics, genetics, statistics, bioinformatics, immunology, experimental medicine, clinical trials.
  Project areas: Genetics, genomics, multi-omics
  Specific project proposals:
  Single-cell omics of the immune system
  T cell receptor sequencing and autoimmunity 
  The role of Tau in pancreatic beta cells
  Please contact directly for further information: jatodd@well.ox.ac.uk


pi_id: tzima_ellie
overview:
  Our laboratory uses a cross-disciplinary approach that combines expertise in genetics, bioengineering, structural and cell biology, and physiology to understand how mechanical forces shape the development of the embryo, maintain homeostasis in the adult but can also instigate pathologies. 
  Project areas: genetics, cardiovascular science and molecular, cell & systems biology, mechanotransduction, protein translation .
  Specific project proposals:


pi_id: udalova_irina
themes: 1,2,3,4,5
overview:
  Inflammation is a normal and self-limiting physiological response to infection and injury but if sustained can lead to extensive tissue damage and disability, manifested in a variety of chronic inflammatory disorders, ranging from autoimmune diseases to atherosclerosis, Alzheimer’s and cancer. The main research interest of the group is understanding how the inflammatory response is controlled on the molecular level (Nature Immunology 2011, Science Immunology 2020). It is driven by changes in the tissue microenvironment, the activation of tissue-resident cells, such as macrophages, and the infiltration of effector myeloid effector cells, such as monocytes, neutrophils. By combining the state-of-the art functional genomic approaches, including single cell genomics, CRISPR screen, proteomics and imaging, with classical molecular and cellular immunology my laboratory is unravelling the transcriptional circuitry that control myeloid cell phenotypes in development and inflammation (Nature Immunology 2021). Our aim is to discover regulatory factors controlling cell development and activation under specific microenvironment, that will lead to new therapeutic strategies tailored to specific conditions (Nature Medicine 2015).
  Our recent pioneering work on neutrophil development and function has established the first transcriptional blueprint of neutrophil responses in acute inflammation (Nature Immunology 2021). It has opened possibilities for stage-specific therapeutic modulation of neutrophil function in disease. Projects will be tailored to personal interests and involve both a wet lab and a data analysis/bioinformatics component.
  Project areas: myeloid cell development; neutrophil genomics; state-of-the-art functional genomic approaches; high throughput imaging screens combined with single cell genomics; network analysis; model building. 
  Specific project proposals:
  -- Genomic landscape of neutrophil states in inflammation: morphology, behaviour, function, and interactions
  -- Granulopoiesis: chromatin topology and associated functions
  Please contact directly for further information.


pi_id: watkins_hugh
overview:
  The genetic contribution to heart disease is important across the allele frequency spectrum. Inherited, monogenic heart diseases are amongst the most common serious, yet treatable forms of inherited disease; coronary artery disease, a classic complex trait, is the single biggest killer worldwide. Our work in inherited cardiomyopathies has moved from gene discovery, through to mechanistic understanding in cell and rodent models to successful clinical trials of repurposed drugs in light of our new mechanistic understanding. We have shown that genetic testing is a cost-effective tool for saving lives. However, our recent large-scale data also indicate that improved, quantitative approaches are needed for reliable interpretation of pathogenicity for rare missense variants – either in gene panels or whole genome data (eg Genetics in Medicine 2017).
  Our large-scale studies in genetic susceptibility to coronary artery disease (as part of the Cardiogram+C4D Consortium, Nature Genetics 2013, 2015 & 2017) have led to the identification of a large number of new risk loci for CAD whose effect is not mediated by known risk factors; thus a major focus now is on identification of new biological pathways and targets. This uses computational and high-throughput screening tools to prioritise loci and variants for functional studies.
  Project areas: genetics, epigenetics & genomics, cardiovascular medicine, inherited heart disease.
  Specific project proposals:
  Please contact directly for further information.


pi_id: whiffin_nicola
themes: 3,4,5
overview:
  Although individually rare collectively, rare diseases affect ~300 million people globally. Identifying the genetic cause of disease is of huge benefit to both patients and their families; allowing screening of additional family members to identify those also at risk, enabling return of an accurate diagnosis to the patient, and dictating personalised treatment approaches. Clinical genetic testing has, therefore, become commonplace for rare disease patients. Through current approaches, however, we only find a genetic diagnosis in around half of all rare disease patients. These approaches almost exclusively focus on the regions of the genome that code directly for proteins.
  We believe that a subset of the undiagnosed patients will have genetic variants in regions outside of this protein-coding sequence, that have crucial roles in regulating the amount and location of proteins that are produced (by regulating transcript, translation, or cellular localisation). Our research uses large genomic datasets (including UK Biobank and the Genomics England 100,000 Genomes Project) and computational approaches to identify these disease-causing regulatory variants and determine how they lead to disease. By identifying these variants, we hope to influence clinical genetic testing guidelines and allow a valuable genetic diagnosis to be returned to more rare disease patients. We also create tools and resources to enable the results of our research to be used to help patients in the clinic.
  We are also interested more generally in the role of variants in untranslated regions (UTRs) in common as well as rare disease, and how they influence penetrance and disease severity. To study this, we integrate large-scale multi-omics data (from e.g. the UK Biobank) including ribosome profiling and proteomics datasets. Finally, we are increasingly interested in how gene regulation can be perturbed as a treatment for rare genetic diseases.
  Projects will be 100% bioinformatics based and tailored to individual interests. Please get in touch if you are interested in joining the team.
  Project areas: Bioinformatics, Genomics, Translational regulation, Rare Disease, Clinical Genetics, Genome targeting therapies


pi_id: wilson_daniel
themes: 3,5
overview:
  Danny is Professor of Infectious Disease Genomics at the University of Oxford. He holds a Robertson Fellowship at the Big Data Institute, and serves as Director of Studies in Data Science at the Department for Continuing Education. 
  His group’s research interests are in the genetic risk of infectious disease and the evolution of pathogen populations, which they study through comparative genome analysis. People in the group come from biology, statistics, medicine and machine learning backgrounds. Their research focuses on the analysis of bacterial diseases and populations, but covers viruses, non-pathogenic microorganisms and host genetics.
  Motivating themes in their work are (i) understanding the genomics of virulence and susceptibility and (ii) the effects of transmission, natural selection and recombination on shaping pathogen diversity. They have investigated the evolution of pathogen populations from the colonization of individual hosts and transmission between hosts, through to the whole-species and phylogenetics levels.
  The group’s research is supported by the Wellcome Trust and Robertson Foundation. They collaborate with the Modernising Medical Microbiology consortium based at the John Radcliffe Hospital, Oxford, and the Department of Statistics. Their work has been published in the top field-specific and general science journals.
  Project areas: Infectious disease genomics, GWAS, host-pathogen interactions, transcriptomics and proteomics, population genetics, evolution, epidemiology, statistical methods development
  Specific project proposals:
  -- Developing analysis methods to detect human-pathogen interactions
  -- Open to other projects in infectious disease genomics and statistical genetics, such as bacterial genome-wide association studies.
  Please contact directly for further information.


pi_id: wood_matthew
themes: 1,2,3,4,5
overview:
  The laboratory works at the interface of neuromuscular science and biotechnology. A major focus is the study of neuromuscular diseases such as Duchenne muscular dystrophy, myotonic dystrophy and spinal muscular atrophy and the development of gene-based therapies, in particular RNA-based therapies, for this class of disorders. A central challenge in our work is the effective delivery of such therapies to the target tissues of skeletal muscle, heart and nervous system. To address this the team has pioneered the development of numerous delivery technologies ranging from peptide to antibody to nanotechnologies based on natural nanoparticles known as exosomes. Our goal is to advance the science underlying these innovative therapies to develop the truly innovative precision medicines of the future and to advance their translation to the benefit of patients.
  Project areas: [please include several keywords or phrases reflecting your research area and proposed projects.]
  Specific project proposals:
  --  ‘What is the effect of genetic variation on XXX?’ 
  -- ‘Second project title’.
  etc.
  Please contact directly for further information.


pi_id: zondervan_krina
themes: 1,2,4,5
overview:
  Our group focuses on understanding the pathogenesis of common, benign women’s health conditions with large public health impact through genomic, molecular and environmental epidemiological approaches. Current focus is on endometriosis - a common chronic inflammatory disease, causing pelvic pain and reduced fertility in an estimated 5‐10% of pre‐menopausal women (190 million worldwide) - and uterine fibroids (leiomyomata), common extra-uterine growths leading to heavy menstrual bleeding, pelvic pain, and potential pregnancy complications. 
  We have led the discovery of most genetic variants associated with endometriosis to date through genome‐wide association studies (e.g. Nat Genet, 2011; Nat Genet, 2012; Nat Comm. 2017, NEJM 2020). We are further expanding on this work, in collaboration with academic groups as well as industry globally, with functional ‘omics’ approaches and efforts to understand phenotypic, clinical and biological heterogeneity and translation findings to inform patient-stratified drug target and biomarker investigations. 
  The work involves samples donated by >1000 women recruited in our ENDOX and FENOX studies and extensive collaboration with groups part of an international data and sample collection standardisation initiative we have founded (endometriosisfoundation.org/ephect), as well as publicly available resources such as the UK Biobank. We also explore direct translation to novel drug targets through a research alliance with Bayer AG, involving scientists across a wide range of disciplines and departments in the Medical Sciences Division: the Big Data Institute, the Botnar Research Centre, Target Discovery Institute, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Endometriosis CaRe centre/NDWRH, and Wellcome Centre for Human Genetics (http://www.medsci.ox.ac.uk/news/university‐of‐oxford‐and‐bayer‐healthcare‐join‐forces‐to‐develop‐innovativegynaecological‐treatments).
  Project areas: Genetic epidemiology and AI in women’s health, integrated phenotype and omics analyses; deep phenotyping and comorbidity, GWAS, tissue RNAseq, miRNA, metabolomics, proteomics, single cell RNAseq.
  We are a multi‐disciplinary, dynamic group, based both at the Wellcome Centre for Human Genetics (WCHG) and the Nuffield Department of Women’s and Reproductive Health (NDWRH), and therefore students will benefit from a strong combination of basic and clinical research environments offered. Projects would be tailored to a candidate’s preferences. They would allow extensive opportunity to gain knowledge and experience of state‐of the‐art computational, statistical, and technological methodologies for the generation and analysis of large‐scale genomic data such as genotyping microarray/sequencing, mRNAseq and miRNA, DNA methylation, metabolomics and proteomics. In NDOG, we are part of the Endometriosis CaRe centre, that focuses on the integration of clinical diagnosis, care and treatment of the disease with clinical and basic research. The group benefits from a strong network of collaborators in the fields of endometriosis, statistical genetics, genomics, bioinformatics, and functional biology locally, nationally and internationally with whom the student will collaborate 
  Example project proposal (can be tailored to specific interests):
  -- Does endometriosis lead to an increased cardiovascular disease risk and (how) is this link genetically/biologically mediated?
  Please contact directly for further information.


pi_id: schuster-böckler_benjamin
themes: 3,4,5
overview:
  My research group studies the processes that lead to cancer. On the one hand, we are interested in the fundamental questions of “how, why and where do mutations occur in the genome”. On the other hand, we investigate the epigenetic changes that accompany tumorigenesis. Our ultimate goal is to develop preventative interventions that would reduce cancer risk, and to develop better diagnostic and prognostic “liquid biopsy” tests. To achieve these goals, my group is not only working on computational approaches but also collaborates closely with others to develop new sequencing methods that could be brought to the clinic.
  We just published a paper in Nature Genetics on the role of DNA replication in mutagenesis where we show that several mutational signature can be explained by the intrinsic mis-incorporation signature of human polymerase ε, the enzyme that mainly replicates the leading strand. There are a range of projects that follow on from this insight: are replication errors fundamentally different between the germline and somatic cells? How does the error-rate of lagging-strand replication differ from leading-strand replication? How does replication error change during lifetime or under environmental stress?
  On the translational side, we have been involved in the development of a method to measure epigenetic alterations in DNA. This technique, called TAPS (Tet-Assisted Pyridine-borane Sequencing), is cheaper, more accurate and better suited for very small samples compared to older methods. Our preliminary data show that TAPS can e.g. be used to predict response to immunotherapy before onset of treatment from a simple blood draw. We also work to develop new machine-learning approaches to detect early signs of liver cancer in patients with liver cirrhosis.
  We are looking for both partially wet-lab as well as fully computational students. If you are keen to work on new sequencing methods, find yet-unknown causes of cancer, or apply machine-learning to improve cancer early detection, then get in touch!
  Project areas: Carcinogens/genomic toxicology, liquid biopsy, cancer epigenetics
  Specific project proposals:
  -- Determine the cell-type composition of cell-free DNA using AI/ML
  -- A cheap and high-throughput assay to detect variants in single molecules
  These pages were last updated: 7/10/2024


pi_id: németh_andrea
themes: 1,2,4
overview:
  My Group is interested in understanding how gene mutations contribute to human development and disease, particularly with relevance to the central nervous system. A key area of interest is ataxia, caused by abnormal development or function of the cerebellum or its functional pathways. As a practicing clinician I have access to numerous patients and our research is often based on ideas that are derived from clinical practice. The ultimate aim is to translate our findings back into the clinic, by providing better diagnostics and better treatments for patients and their families.
  The main technologies we use in the laboratory are high-throughput sequencing for diagnostics and cellular models of disease using CRISPR/Cas9 gene editing in embryonic stem cells and we have several projects using these technologies.
  Project areas: Cerebellar ataxia, intellectual disability, movement disorders, next-generation sequencing, whole genome sequencing, [please include several keywords or phrases reflecting your research area and proposed projects.
  Please contact directly for further information.


# themes

pi_id: ansari_azim
theme_id: 3
theme: Genome biology
detail:
  (genomes and genetic variation, recombination, human history, evolution, palaeogenomics, pathogen genomes)


# project

pi_id: ansari_azim
title: Detecting and dissecting host-pathogen genetic interactions
supervisors: Dr. Azim Ansari and Dr. Gavin Band
mix: 0% wet lab, 100% dry lab
description:
  The outcome of infections depends on a complex interplay of interactions between host cells and the pathogens that invade and replicate inside them.  Underlying this is natural genetic variation, but little is known about the mutations involved, their biological function or how they interact.  In this project, you will work with Dr. Azim Ansari (Medawar) and Dr. Gavin Band (Wellcome Centre for Human Genetics) to develop and apply statistical genetic methods that will improve our understanding of this.  There are several key challenges to overcome which could form the source of a rotation project, including
  -- Population genetics and natural selection: infections are a major source of natural selection on the human genome, and human resistance alleles provide a strong selective force on pathogens.  But how this plays out at the level of populations is mostly unknown.  It could involve stable interactions between segregating mutations, but also selective sweeps or development of complex genetic diversity through diversifying or balancing selection.  Understanding this is important because it shapes attempts to discover genetic interactions and, ultimately, to discover new aspects of infection biology.  A key way to gain a better understanding of this will be to conduct population-genetic simulations, potentially incorporating host-pathogen interactions, spatial aspects, recombination and mutation, between-pathogen competition and potentially epistasis, to generate realistic population-genetic outcomes.  You will then compare that to real population datasets.
  -- Robust methods for genotyping complex variation in human and pathogen genomes are needed.  Both Dr. Ansari and Dr. Band are engaged in projects to leverage new developments in long-read sequencing.  There is an opportunity for you to contribute by developing targeted assays for genomic regions of interest, apply long-read methods such as Oxford Nanopore Technologies MinION, and conduct in silico work to call and analyse the resulting data, and apply results to existing datasets.
  -- An important feature of infections is that they are often mixed – that is, they consist of more than one genetic type of pathogen at the same time.  Current analysis methods deal with this in limited and ad hoc ways, such as simply taking a ‘majority’ or arbitrary genotype call at each locus, but as a result they can lose power.  You will develop better methods to handle this in the context of host-pathogen analyses, either by exploiting genome-wide data or panels of known sequences to estimate and exploit the mixture composition of infections, from genome-wide sequence data.
  This work will be carried out using large datasets on Hepatitis B and C, HIV and malaria infections.

training:
  The student will develop expertise in Statistical genomics, Statistical Modelling, Machine Learning, bioinformatics, infectious diseases, evolution and population genetics. This studentship will be based at the Peter Medawar Building for Pathogen Research (PMB) and the Wellcome Centre for Human Genetics (WHG) at Oxford. The PMB houses around 150 scientists working on HIV, HCV, influenza, TB, malaria, SARS-CoV-2 and dengue and many of the PIs are global leaders in the study of infections.

background_reading:
  -- Band, G, et al. “Malaria protection due to sickle haemoglobin depends on parasite genotype” Nature 602, 106–111 (2022). https://doi.org/10.1038/s41586-021-04288-3
  -- Ansari, M. Azim, et al. "Genome-to-genome analysis highlights the effect of the human innate and adaptive immune systems on the hepatitis C virus." Nature genetics 49.5 (2017): 666-673.
  -- Behr, Merle, et al. "Testing for dependence on tree structures." Proceedings of the National Academy of Sciences 117.18 (2020): 9787-9792.
  -- Crawford, Lorin, et al. "Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits." PLoS genetics 13.7 (2017): e1006869.


pi_id: ansari_azim
title: Understanding mechanisms of sex disparities in infectious diseases
supervisors: Dr. Azim Ansari
mix: 0% wet lab, 100% dry lab
description:
  The mortality rate for COVID-19 pandemic has been two to three times higher in men than women. Similar observation extends to susceptibility and outcome of most other infectious diseases. For instance, after initial Hepatitis C Virus infection women are more likely to spontaneously clear the virus without any interventions. The rate of progression to severe liver disease is also slower in women than men and there is some evidence that women respond better to direct-acting antiviral therapies. On the other hand, many auto-immune diseases (such as lupus) have a much higher rate of occurrence in women than men. Despite large evidence for sex differences in autoimmune diseases and susceptibility and outcome of infectious diseases, data addressing the biological mechanism are remarkably scarce.
  In this short project you will use computational and (and potentially experimental) methods to probe differences in immune system that lead to sex differences in infectious diseases. One hypothesis for the sex differences in immune responses are that in females, due to the random nature of X-chromosome inactivation process, organs are mosaic and consist of two populations of cells with preferential expression of either paternal or maternal X-chromosome. This increased level of genetic heterogeneity at organ level in females relative to males could explain, better immune responses against infections.
  To test this hypothesis, you will use liver RNA-seq and genomic data from a cohort of 200 patients infected with HCV to estimate what proportion of cells express paternal and maternal X-chromosomes in each patient. We will then test for association between clinical phenotypes (viral load and treatment outcome) and the level of X-chromosome expression heterogeneity.

training:
  The student will develop expertise in Statistical genomics, Statistical Modelling, Machine Learning, bioinformatics, infectious diseases, evolution and population genetics. This studentship will be based at the Peter Medawar Building for Pathogen Research (PMB) and the Wellcome Centre for Human Genetics (WHG) at Oxford. The PMB houses around 150 scientists working on HIV, HCV, influenza, TB, malaria, SARS-CoV-2 and dengue and many of the PIs are global leaders in the study of infections.

background_reading:
  -- Vieira VA, Zuidewind P, Muenchhoff M, Roider J, Millar J, Clapson M, Van Zyl A, Shingadia D, Adland E, Athavale R, Grayson N, Ansari MA, et al. Strong sex bias in elite control of paediatric HIV infection. AIDS (London, England). 2019 Jan 2;33(1):67.
  -- Shvetsova, E, et al. Skewed X-inactivation is common in the general female population, European Journal of Human Genetics, 2019.
  -- Tukiainen, T, et al. Landscape of X chromosome inactivation across human tissues, Nature, 2017.
  -- Oliva, Meritxell, et al. "The impact of sex on gene expression across human tissues." Science 369.6509 (2020).


pi_id: band_gavin
title: Discovering malaria parasite genetic effects on natural and induced immunity
supervisors: Dr. Gavin Band and +collaborators
mix: 27.5% wet lab, 71% dry lab
description:
  The malaria parasite Plasmodium falciparum is a major cause of disease and death throughout tropical regions.  It has a complex lifecycle that involves a diploid phase with meiosis whilst transmitting through female Anopheline mosquitos, and haploid liver and blood stages.  It is in the latter stage when most disease symptoms occur.
  To support this lifecycle, the parasite has a fascinating genome which is chock full of genes (about 50% of the genome is in coding sequence), yet their function is relatively poorly understood.  And it harbours millions of genetic mutations including simple single nucleotide polymorphisms, and larger, complex rearrangements.
  My group is a small but dynamic and is working to discover, unravel and exploit signals of parasite evolutionary response to the main challenges it faces in the host.  These are natural immunity (such as that conferred by the sickle haemoglobin allele, HbS) and induced immunity, including vaccine-induced immunity. This is an exciting time to be doing this work: new vaccines (such as <a href="https://doi.org/10.1016/S0140-6736(23)02511-4">R21/Matrix-M</a>) have recently been approved and others are in development; meanwhile, we have only recently discovered major signals of parasite coevolution with protective host mutations (<a href="https://doi.org/10.1038/s41586-021-04288-3">Band et al Nature 2021</a>) raising deep evolutionary and functional questions. We are therefore undertaking large-scale projects to sequence malaria parasite genomes, and unravel complex genetic effects on malaria vaccine efficacy, interactions with host mutations, and their evolutionary consequences.
  Depending on your interests and experience, you might:
  -- Develop statistical methods to handle mixed infections in the context of host-parasite association tests (<a href="https://doi.org/10.1038/s41586-021-04288-3">Band et al Nature 2021</a>) and vaccine-parasite association tests using samples from the recent <a href="https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(23)02511-4/fulltext">R21/Matrix-M Phase 3 trial</a>)
  --  Unravel complex genetic variation in parasite genomes, using cutting-edge genome-assembly and variant calling methods and data we have generated using <a href="https://www.illumina.com/">Illumina</a>, <a href="https://www.pacb.com/">PacBio</a>, <a href="https://nanoporetech.com/">Nanopore</a>, and <a href="https://www.elementbiosciences.com/">Element Biosciences</a> platforms.
  -- Build genealogical trees relating parasites and their ancestral species in large global sample sets, and using them to study signals of positive and balancing selection.
  -- Map parasite mutations of interest onto protein structure, using alphafold and other tools.
  -- Conduct large-scale host-parasite genetic association test scans and meta-analyse them in large sample sets from multiple populations.
  -- A particular project is to bring the deletions that cause alpha thalassaemia into our <a href="https://doi.org/10.1038/s41467-019-13480-z">severe malaria</a> and <a href="https://doi.org/10.1038/s41586-021-04288-3">host parasite association</a> studies. This will use data that collaborators have generated and there is also a lab opportunity to generate data for thousands of malaria cases and controls from The Gambia.
  -- Conduct lab work to develop long-read transcriptome sequencing from cultured or natural blood-stage infections.
  -- Analyse geographical relationships between malaria parasites and hosts using by developing novel geospatial regression models and evolutionary simulations.
  You will join a small, dynamic, and growing group based at the Centre for Human Genetics.  We work with collaborators across the globe, as well as in the UK, and in the CHG.  We have recently been awarded a 7-year Wellcome Discovery project to investigate function and epidemiology of host-parasite interactions, and funding from Serum institute for the vaccine genetics work.

training:
  The student will develop expertise in statistical genomics, statistical modelling, population genetics and host-pathogen coevolution, infectious disease modelling, genome assembly, and potentially functional genomics.  In addition you may learn computational skills – across the group we have expertise in python, R, Julia, C++, HTML5, WebGPU among others.

background_reading:
  -- “<a href="https://doi.org/10.1016/S0140-6736(23)02511-4">Safety and efficacy of malaria vaccine candidate R21/Matrix-M in African children: a multicentre, double-blind, randomised, phase 3 trial</a>”, Dahtoo et al The Lancet (2024)
  -- “<a href="https://doi.org/10.1038/s41586-021-04288-3">Malaria protection due to sickle haemoglobin depends on parasite genotype</a>”, Band et al Nature 2021
  -- “<a href="https://doi.org/10.1038/s41467-019-13480-z">Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania</a>“, Band et al, Nature Comm. (2019)


pi_id: band_gavin
title: Resolving T cell receptor diversity using long-read sequencing in the HV31 ‘omniome’
supervisors: Dr. Gavin Band, Prof. Julian Knight and Prof. John Todd
mix: 0% wet lab, 100% dry lab
description:
  Some of the most complex, diverse and important parts of the human genome are those that encode for adaptive immunity.  Among these, the immunoglobulin regions and the T cell receptor regions are particularly important.  But they are hard to study using traditional methods.  In this project you will develop new computational methods to try to resolve T cell receptor diversity using long-read sequencing data.
  image://data/images/band_gavin_01.png
  <b>Figure 1</b>: a schematic of the T cell receptor alpha / delta locus
  This approach exploits a key feature of T cell development: the T cell receptor regions undergo somatic recombination (so called 'VJ' or 'V(D)J' recombination) to generate a large number of different haplotypes carried by different T cells.  These recombinations splice together different gene components to make the functional receptor genes.  (This is a core component of what makes immunity 'adaptive' in the first place.)
  Working with both Pacific Biosciences (PacBio) and with Oxford Nanopore Technologies (ONT) we have recently generated high-coverage sequencing data for a healthy volunteer codenamed 'HV31'.  In this long-read data, sequencing reads from germline cells and those from recombinant T cells are easily distinguishable – the reads from T cells align to several different places due to the VJ recombination.  We now want to explore a method to extract these reads and assemble the repertoire.
  Your mission (if you choose to accept) it is to:
  -- Analyse long-read sequencing data from PacBio and ONT.
  -- Find a way to extract out reads in the T cell receptor regions, that come from the somatic recombinant T cells.
  -- Use the reads to estimate the proportion of T cells in the sample.
  -- Estimate the proportion of αβ versus γδ T cells in the sample (which can be distinguished as they undergo different recombination processes).
  -- Identify and determine the different T cell recombinant haplotypes - for example by clustering the reads and aligning them to each other - and predict gene content.
  -- Analyse the T cell receptor diversity in HV31, at broad scale.
  -- Analyse patterns of methylation on these recombinant haplotypes.
  The work is part of a larger ongoing project known as the ‘HV31 omniome project’, which is conducting methodological work to assemble a complete phased genome for HV31 with multiple functional datasets aligned, assessing the impacts of complex genetic variation on immune system function.

training:
  You'll learn to work with highly accurate long read genomic sequencing data, and will develop and apply algorithms to analyse it.  You'll also learn about the fundamental mechanisms of receptor diversity underpinning the adaptive immune system.

background_reading:
  -- Zhang et al., "Using de novo assembly to identify structural variation of eight complex immune system gene regions" PLOS Computational Biology (2021) <a href="https://doi.org/10.1371/journal.pcbi.1009254">https://doi.org/10.1371/journal.pcbi.1009254</a>
  -- The T cell Receptor Factsbook, <a href="https://www.sciencedirect.com/book/9780124413528/the-t-cell-receptor-factsbook">https://www.sciencedirect.com/book/9780124413528/the-t-cell-receptor-factsbook</a>


pi_id: bashford-rogers_rachael
title: Investigating the B and T cell mediated pro- and anti-tumour mechanisms in cancers
supervisors: Dr Rachael Bashford-Rogers
mix: can be wet or dry lab work, or mixture depending on student preference
description:
  B cell infiltration has prognostic significance in solid tumours, and ongoing studies are investigating their phenotypes through single cell transcriptomics and spatial imaging. Characterising the B cell response to tumour cells, particularly their antigenic specificities, will be key to developing more immunologically appropriate cancer therapies. However, currently, the B cell antibody (Ab) specificity cannot be coupled with the Ab sequence, phenotype or transcriptome in a high-throughput manner. Here we propose a DPhil studentship project to develop novel technologies to be able to bridge the gap between B cell populations and antibody reactivity, thus giving a unique perspective on the development of anti-self, anti-tumour and anti-non-self Ab responses. This project will involve the development a novel high-throughput method to probe the antigen specificities of B cells, which will be coupled with single cell resolution of clonal phenotype and single cell transcriptome. This will be used to investigate the development and role of tumour-infiltrating B cells across a range of tumours with varying degrees of immunogenicity. This study will provide a unique platform to understand the probe between tumour neo-antigen, B cell immune-surveillance and specificity, and B cell phenotype, with the overall aim of highlighting new therapeutic options. Furthermore, this method is not just broadly applicable to cancer, but will have wider applications in immunology and biotechnology.  This will be achieved through the development and application of novel experimental and computational approaches, working in partnership with a global network of clinicians, immunologists and sample cohorts. This information may be used to develop potential biomarkers of resistance to therapy and to determine potential therapeutic interventions that could be combined with the current standard of care that could target persistent clones in autoimmune diseases.
  This project will apply novel single-cell genetic technologies, imaging and functional experiments to link the development, regulation and function of B and T cell populations in health and immunological diseases to the underlying host genetics.
  This project aims to investigate the B and T cell immune response of circulating and tumour-infiltrating B cells across a range of tumours with different levels of immunogenicity and neo-antigen expression, including pancreatic and renal cancers. This will be done within the context of the tumour, stromal and myeloid cell populations to gain a global understanding of key immune cell dependencies and modes of modulation. This will involve the development of a novel platforms and methodologies to answer key questions in the field of tumour immunology including:
  -- What are the key features defining B and T cell infiltration into the tumour and how may this be modulated?
  -- What are the functions and cell-cell interaction effects of tumour infiltrating B and T cells?
  -- What determines the balance of whether B and T cells serve a pro- or an anti-tumourigenic function?
  -- Do tumour-associated B cells produce Abs against tumour cells, and how does tumour cell neo-antigen variation and expression level dictate Ab response? Are tumour-associated Abs cross-reactive to other self or non-self antigen, poly-reactive, or highly specific to tumour cells?
  Overall, this may help shed light on the B cell response to tumour cells, the specificity and breadth of response, and potentially highlight novel therapeutic targets. We envisage that this novel platform may be extended to the other areas of B cell biology, and could be a general tool that could be of great value other researchers.

training:
  The DPhil will gain experience and training in laboratory molecular biology and single cell methods, bioinformatics and immunology. These include:
  -- Single-cell RNA sequencing and analysis of patient samples.
  -- Integration of single-cell RNA sequencing and other “omics” datasets to associate information about the B/T cell receptor with the single-cell transcriptome.
  -- Development of novel functional, imaging and computational analyses to gain an understanding of the role ad communication of immune cells within the contexture of the tumour environment.
  -- Characterisation of B/T cell traits throughout development and tissues.
  -- Validation of associations using a wide range of immunological techniques.
  -- The project will work in partnership with a global network of clinicians, immunologists and sample cohorts.

background_reading:
  -- Double-jeopardy: scRNA-seq doublet/multiplet detection using multi-omic profiling (Cell Reports Methods, 2021).
  Bo Sun, Emmanuel Bugarin-Estrada, Lauren E. Overend, Catherine E. Walker, Felicia A. Tucci, Rachael J. M. Bashford-Rogers
  -- Activated regulatory T-cells, dysfunctional and senescent T-cells hinder the immunity in pancreatic cancer (Cancers, 2021) (<a href="https://doi.org/10.1101/2020.06.20.163071">https://doi.org/10.1101/2020.06.20.163071</a>)
  Shivan Sivakumar,  Enas Abu-Shah,  David Ahern,  Edward H Arbe-Barnes,  Nagina Mangal,  Srikanth Reddy, Aniko Rendek, Alistair Easton, Elke Kurz, Michael Silva,  Lara R Heij, Zahir Soonawalla,  Rachael Bashford-Rogers,  Mark R Middleton,  Michael Dustin
  -- B cell receptor repertoire analysis in six immune-mediated diseases (Nature, 2019)
  RJM Bashford-Rogers, L Bergamaschi, EF McKinney, DC Pombal, F Mescia, JC Lee, DC Thomas, SM Flint, P Kellam, DRW Jayne, PA Lyons, KGC Smith


pi_id: bashford-rogers_rachael
supervisors: Dr Rachael Bashford-Rogers
mix: can be wet or dry lab work, or mixture depending on student preference
title:
  Resolving the rules of regulatory B cell (Breg) generation for therapeutic modulation in cancer and beyond

description:
  Immune system dysregulation underlies many diseases, leading to infectious disease susceptibility, cancer, immunodeficiencies, and autoimmune disorders. B cells, known for antibody production, also play crucial pro- and anti-inflammatory roles, with regulatory B cells (Bregs) shown to potently suppress immune responses. The importance of regulatory B cells (Bregs) has become clearly evident over the last decade. Bregs can suppress CD4 and CD8 T cell responses and are associated with poorer outcome across many cancer types(1). Conversely, Bregs are often dysfunctional/deficient in autoimmunity and checkpoint-inhibitor-associated toxicities(2). Functionally deficient B regulatory cells (Bregs) are linked to unfavourable clinical outcomes in autoimmune disorders such as Systemic Lupus Erythematosus, Rheumatoid Arthritis, and Multiple Sclerosis, and animal models support Breg therapy as an approach to treat these autoimmune disorders (3). The application of Breg cellular therapy to promote or suppress operational tolerance, depending on disease context, is an exciting prospect. Therapeutically targeting Bregs holds promise for restoring immunological health in autoimmune disorders and enhancing tumour recognition in cancers.
  However, little is known about human Bregs, including their generation, functional and molecular heterogeneity, and maintenance. The lack of phenotypic markers and the rarity of Bregs hinder research. Our work shows that IL10 and other Breg-associated genes are expressed at all B cell differentiation stages, varying by tissue type and disease, suggesting Bregs as a transient state rather than a specific lineage. This proposal leverages my preliminary work and integrates cutting-edge techniques in single-cell multi-omics (scMulti-omics, transcriptomics, proteomics, B cell receptor) and cell culture to investigate human Breg biology. This promises to significantly advance Breg understanding and identify Breg-specific drug targets for cancer and autoimmune diseases.
  Research objectives and proposed outcomes: A DPhil will consist of some or all of the following aspects, depending on the interests of the candidate.
  In aim1, you will characterise the diversity, function and co-dependences of naturally occurring in vivo and ex vivo generated human Bregs from existing scMulti-omics datasets, and predict key signals (transcription factors (TFs) and pathways) associated with Breg generation.
  Aim 2 will resolve factors influencing the dynamics of ex vivo Breg generation, plasticity, function and stimulation via cell culture, transcriptomics and temporal modelling. You will then develop a novel experimentally-informed artificial intelligence (AI) model to decipher the complex relationships between factors, making this problem conceptually tractable. This open-source model will become a platform for the community to contribute to, including the effect of different experimental conditions and drugs.
  Finally, in aim 3 you will confirm the signals required for Breg generation which will be used to predict drugs that impact generation of Bregs in vitro. This will be achieved through gene knock-down and over-expression experiments of predicted TF and key receptors derived from scMulti-omics data analyses in aim 1 to finally confirm drug targets that influence dynamics and/or stability of Breg generation in vivo.
  This project couples the standardisation of experimental protocols and AI approaches to open up the field of Breg biology and will make experimentation interpretable for drug development prior to clinical translation.
  Translational Potential: Due to the critical role of Bregs in autoimmune disorders and cancer, the outcomes of this research will have significant translational implications across multiple immune-mediated conditions. Furthermore, the methods developed here will not just be broadly applicable to Bregs in cancer, but will have wider applications in biotechnology. This will be achieved through the development and application of novel experimental and computational approaches, working in partnership with a global network of clinicians, immunologists and sample/data cohorts.

training:
  The student will gain experience and training in laboratory molecular biology, immunology, cancer biology, and bioinformatics, depending on the agreed focus of the project (computational or wet lab). These include:
  -- Genomic, bulk and single-cell transcriptomic, and other ‘omic analyses across large patient cohorts.
  -- Cell culture, T cell suppression assays.
  -- Development and/or implementation of novel computational pipelines using generative AI.
  The Bashford-Rogers laboratory has a strong track record of collaboration over the last 15 years and established systems for co-supervision.

background_reading:
  1. Single-cell immune multi-omics and repertoire analyses in pancreatic ductal adenocarcinoma reveal differential immunosuppressive mechanisms within different tumour microenvironments (2023) (<a href="https://www.biorxiv.org/content/10.1101/2023.08.31.555730v1">https://www.biorxiv.org/content/10.1101/2023.08.31.555730v1</a>) Shivan Sivakumar, Ashwin Jainarayanan, Edward Arbe-Barnes, et al.
  2. Predicting risk of pancreatic cancer in individuals with new-onset type-2 diabetes in primary care: protocol for the development and validation of a clinical prediction model (QPancreasD, 2021) (<a href="https://www.medrxiv.org/content/10.1101/2021.12.22.21268161v1">https://www.medrxiv.org/content/10.1101/2021.12.22.21268161v1</a>) Pui San Tan, Ashley Kieran Clift, Weiqi Liao, et al.
  3. Analysis of the B cell receptor repertoire in six immune-mediated diseases. (Nature, 2019) RJM Bashford-Rogers, L Bergamaschi, EF McKinney, et al.
  4. Opportunities and challenges for digital twins in biomedical research: Proceedings of a workshop in brief (The National Academies Press, 2023). Linda Casola, et al.


pi_id: beagrie_robert
title: Studying histone modifications in a mouse model of schizophrenia
supervisors: Dr. Robert Beagrie, Dr. Lahiru Handunnetthi
mix: 100% dry lab
description:
  Mutations in SETD1A have been identified in several cohorts of schizophrenia patients. SETD1A encodes a histone methyltransferase that is responsible for mono- di- and tri-methylation of Histone H3 lysine 4, post-translational modifications that are strongly associated with transcriptional activation. Whether loss of one copy of SETD1A indeed results in transcriptional dysregulation, how this affects brain development and why it leads to an increased risk of schizophrenia is currently unknown.
  Previous studies have shown that early corticogenesis is a critical time period in schizophrenia pathogenesis. The Beagrie and Handunnetthi groups are trying to understand whether and how loss of one copy of Setd1a disrupts early corticogenesis in the mouse, which occurs at around 12.5 days post copulation (dpc). In this project you will analyse existing single-cell multiome (CUT&TAG + RNA) data from Setd1a+/- mouse embryonic brain to identify changes in gene expression and histone modifications that result from Setd1a deficiency.

training:
  Students would be trained in analysis of single-cell RNA-seq and single-cell CUT&TAG datasets. There may also be opportunities to incorporate other techniques.

background_reading:
  -- Singh T et al. (2022). Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature. Available at: <a href="https://doi.org/10.1038/s41586-022-04556-w">https://doi.org/10.1038/s41586-022-04556-w</a>
  -- Mukai J et al. (2019). Recapitulation and Reversal of Schizophrenia-Related Phenotypes in Setd1a-Deficient Mice. Neuron. Available at: <a href="https://doi.org/10.1016/j.neuron.2019.09.014">https://doi.org/10.1016/j.neuron.2019.09.014</a>
  -- Zhu C et al. (2021). Joint profiling of histone modifications and transcriptome in single cells from mouse brain. Nature Methods. <a href="https://doi.org/10.1038/s41592-021-01060-3">https://doi.org/10.1038/s41592-021-01060-3</a>


pi_id: beagrie_robert
title: How does disruption of chromatin organising proteins influence genome folding?
supervisors: Dr. Robert Beagrie
mix: 50% wet lab, 50% dry lab
description:
  Cellular identity is largely determined by the set of genes expressed by any given cell. Gene expression programs are in controlled by non-coding DNA regulatory elements. In order to function properly, these regulatory elements need to be packaged into the correct type of chromatin and folded such that they are located in close proximity to the genes they regulate. The Beagrie lab is interested in how disruption of these processes can contribute to human disease
  Genome Architecture Mapping (GAM) is a technique for measuring the 3D structure of DNA in the nucleus. GAM works by cutting thin slices through a population of nuclei and sequencing the DNA within each slice. Once enough slices are sequenced, the proximity of different DNA loci can be inferred based on the frequency with which any pair of loci are found in the same slices. Loci which are close to each other in the 3D space of the nucleus will usually be found in the same slices, whereas loci which are distant will not. We have two projects available that would allow interested students to learn how to carry out GAM experiments and analyse the resulting data whilst addressing a biological question relating to chromatin function. The first involves mouse embryos which do not produce enough cohesin (the protein complex responsible for co-ordinating DNA folding). The second involves sub-nuclear GAM on post-fertilisation mouse zygotes.

training:
  Students would be trained in generating and analysing GAM datasets and in immunofluorescence microscopy. Computational analyses will be conducted in Python.

background_reading:
  -- Beagrie R et al. (2017). Complex multi-enhancer contacts captured by genome architecture mapping. Nature. Available at: <a href="https://doi.org/10.1038/nature21411">https://doi.org/10.1038/nature21411</a>


pi_id: bhattacharya_shoumo
title: Developing nanobody-peptide conjugates to target inflammation
supervisors: Shoumo Bhattacharya
mix: 80% wet lab, 20% dry lab
training: Protein interactions, nanobodies, peptide therapeutics, chemotaxis, animal models.
description:
  Bioinformatic approaches will be used to identify suitable targets for nanobody development in inflamed tissues from gene & protein expression data in the public domain. Nanobodies developed against the identified targets will be expressed in bacteria and purified by nickel affinity chromatography. They will be validated for specific target binding using “pull-down” assays, conjugated to anti-chemokine peptides either genetically or using sortase A, and the nanobody-peptide conjugates tested for activity in cell migration assays, and then in animal (mouse) studies. Alternative ways of delivering nanobody-peptide fusions such as using mRNA will be explored.

background_reading:
  1. Vales, S., Kryukova, J., Chandra, S., Smagurauskaite, G., Payne, M., Clark, C.J., Hafner, K., Mburu, P., Denisov, S., Davies, G., Outeiral, C., Deane, C.M., Morris, G.M. & Bhattacharya, S. Discovery and pharmacophoric characterization of chemokine network inhibitors using phage-display, saturation mutagenesis and computational modelling. Nat Commun 14, 5763 (2023).
  2. Bao, G., Tang, M., Zhao, J. & Zhu, X. Nanobody: a promising toolkit for molecular imaging and disease therapy. EJNMMI Res 11, 6 (2021).
  3. Hanke, L., Sheward, D.J., Pankow, A., Vidakovics, L.P., Karl, V., Kim, C., Urgard, E., Smith, N.L., Astorga-Wells, J., Ekstrom, S., Coquet, J.M., McInerney, G.M. & Murrell, B. Multivariate mining of an alpaca immune repertoire identifies potent cross-neutralizing SARS-CoV-2 nanobodies. Sci Adv 8, eabm0220 (2022).
  4. Panova, E.A. et al. Single-domain antibody delivery using an mRNA platform protects against lethal doses of botulinum neurotoxin A. Front Immunol 14, 1098302 (2023).
  These pages were reviewed/updated: 10 Oct 2024


pi_id: bottomley_matthew
supervisors: Matt Bottomley, Graham Ogg
mix: 40% wet lab, 60% dry lab
title:
  The effect of uraemia, immune ageing and iatrogenic immunosuppression upon cutaneous immunosurveillance.

description:
  Skin complaints are common amongst patients with kidney disease, both before and after kidney transplant. Circulating immune dysfunction, partly arising from accelerated immune ageing, is well-described amongst this cohort, leading to increased risk of poor outcomes (such as hospitalisation and death) from infection.
  Whether there is overlap between these phenomena is unexplored. We are currently conducting a longitudinal case-control study, evaluating the effect of uraemia and immune ageing upon adaptive immunity in skin and blood, and the potential synergistic effect of iatrogenic immunosuppression.
  The proposed DPhil project will focus on the longitudinal phase of the study, utilising a combination of functional immunology, single-cell transcriptomic analysis and spatial transcriptomic profiling to evaluate changes in cutaneous and circulating immunity with the onset of immunosuppression after a kidney transplant.

training:
  The student will have the opportunity to develop their skills in:
  -- Handling and processing of tissue and blood samples from human participants;
  -- Phenotypic analysis of circulating leucocytes using methods such as flow cytometry and single-cell RNA sequencing;
  -- Evaluation of tissue immunity using approaches such as multiplex immunofluorescence, spatial transcriptomic profiling and bulk/single-cell transcriptomic analysis. The student will be expected to undertake the wet-lab work in conjunction with existing expertise in the group.
  -- Analysis of such datasets using appropriate (spatial) statistical methods, including cross-correlation to clinical phenotype.
  -- Use of R and Python to undertake such analyses, as well as use of proprietary analysis software.

background_reading:
  -- Bottomley MJ, Thomson J, Harwood C, Leigh I, 2019. The Role of the Immune System in Cutaneous Squamous Cell Carcinoma. Int J Mol Sci. Available at: <a href="https://www.mdpi.com/1422-0067/20/8/2009">The Role of the Immune System in Cutaneous Squamous Cell Carcinoma (mdpi.com)</a>
  -- Goel V, Sil A, Das A, 2021. Cutaneous manifestations of Chronic Kidney Disease, Dialysis and Post-Renal Transplant: A Review. Indian J Dermatol. Available at: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8061480/">Cutaneous Manifestations of Chronic Kidney Disease, Dialysis and Post-Renal Transplant: A Review - PMC (nih.gov)</a>
  -- Kumaran G, Carroll L, Muirhead N, Bottomley MJ, 2024. How Can Spatial Transcriptomic Profiling Advance Our Understanding of Skin Diseases? Journal of Investigative Dermatology. Available at: <a href="https://www.sciencedirect.com/science/article/pii/S0022202X24019262">How Can Spatial Transcriptomic Profiling Advance Our Understanding of Skin Diseases? - ScienceDirect</a>
  -- Zibandeh N, Li Z, Ogg GS, Bottomley MJ, 2024. Cutaneous Adaptive Immunity and Uraemia: A Narrative Review. Frontiers in Immunology. Available at: <a href="https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1464338/full">Frontiers | Cutaneous adaptive immunity and uraemia: a narrative review (frontiersin.org)</a>


pi_id: channon_keith
supervisors: Dr Gillian Douglas, Professor Keith Channon
mix: 70% wet lab, 30% dry lab
title:
  Defining the function of new causal atherosclerosis genes from coronary artery disease GWAS loci using in vitro and in vivo models

description:
  Genome wide association studies have enabled us to identify genes which are associated with cardiovascular disease at the level of the whole genome. These novel genes, which are not associated with traditional risk factors, have the potential to identify novel treatment strategies for coronary artery disease. The work in my lab aims to establish the role of novel candidate genes in cardiovascular disease.
  Working in close collaboration with bioinformaticians we identify novel candidate genes from GWAS implicated loci. Once candidate genes have been identified we use targeted cardiovascular disease relevant in vitro cell based assays in primary human cells to understand how the candidate gene impacts and cell function. Proteomic and genomic analysis is used to give an unbiased analysis of candidate gene function. This is complimented by advanced cellular imaging as well as molecular biology techniques. The information gained from these In vitro studies is then used in a targeted fashion to investigate the role of the candidate gene in models of In vivo cardiovascular disease, in particular the development and regression of atherosclerosis and models of altered vascular function such as vascular injury and ischaemia models. We also utilize data from local and international biobanks to investigate the role of candidate genes in vascular biology. Doctorial students have the flexibility to focus either on in vitro cell based assays or in vivo models of cardiovascular disease.

training:
  This DPhil will be based in the Division of Cardiovascular Medicine at the Welcome Centre for Human Genetics. We are part of a wider scientific community with expertise in Cardiovascular Disease allowing for collaborative work with other senior scientist. By the end of this project the candidate will have developed a wide range of laboratory skills such as molecular biology techniques (protein and RNA analysis), cell culture techniques and In vivo models of cardiovascular disease. Training in scientific techniques as well as scientific presentation and writing will be given throughout the project.

background_reading:
  -- Douglas G, Mehat V, Al Haj Zen A, Akoumianak I, Goel A, Rashvrook VS, Trelfa L, Donovan L, Drydale E, Chuaiphichai S, Antoniades C, Watkins H, Kyriakou T, Tzima E, Channon KM. A key role for the novel coronary artery disease gene JCAD in atherosclerosis via shear stress mechanotransduction. Cardiovascular Research, doi:10.1093/cvr/cvz263. 2019


pi_id: chen_yi-ling
title: Role of lipid-reactive T cells and lipid antigens in inflammatory disease
supervisors: Dr. Yi-Ling Chen; Prof. Graham Ogg
mix: 20% wet lab, 80% dry lab
description:
  Recent advancements in human immunity have described a family of unconventional T cells that, instead of being classically MHC-restricted, recognise lipid antigens presented by a family of MHC I-like CD1 molecules. CD1-restricted T cells are abundant in the periphery and tissues, and play diverse roles in disease. We aim to study CD1-restricted T cells to investigate their fundamental biology and signatures, and the molecular mechanisms underlying their activities in disease. In recent years, the study of CD1-reactivity has rapidly progressed following the establishment of several techniques that allow the efficient isolation of CD1-restricted T cells from human samples, allowing direct ex vivo characterisation and in vitro T-cell clonal expansion. We will utilise T cell platforms established in our lab and institute using high-dimensional technologies [single cell CITESeq, spatial multiomics, lipidomics analysis, and Mass Cytometry (CyTOF and Hyperion)] and T-cell receptor repertoire analysis to define potential pathways where CD1-restricted T cells contribute to disease.

training:
  The student will be mentored by Dr. Yi-Ling Chen and Professor Graham Ogg. The projects will involve high-dimensional technologies and bioinformatics.
  In addition, the student will take part in the activities such as lab meetings, journal clubs, seminars, and other training opportunities through the many research institutes and centres based in Oxford. They will also have opportunities to participate in manuscript preparation. Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

background_reading:
  Please include references as desired.  Suggested format:
  -- Chen YL, Ng JSW, Ottakandathil Babu R, Woo J, Nahler J, Hardman CS, Kurupati P, Nussbaum L, Gao F, Dong T, Ladell K, Price DA, Duncan DA, Johnson D, Gileadi U, Koohy H, Ogg GS.
  -- 2023. Group A induces CD1a-autoreactive T cells and promotes psoriatic inflammation. Sci Immunol, 8 (84), pp. eadd9232.
  -- Monnot GC, Wegrecki M, Cheng TY , Chen YL, Sallee BN, Chakravarthy R, Karantza IM, Tin SY , Khaleel AE, Monga I, Uwakwe LN, Tillman A, Cheng B, Youssef S, Ng SW, Shahine A,
  -- Garcia-Vilas JA, Uhlemann AC, Bordone LA, Han A, Rohde CH, Ogg G, Moody DB, Rossjohn J, de Jong A. 2023. Staphylococcal phosphatidylglycerol antigens activate human T cells via
  -- CD1a. Nat Immunol, 24 (1), pp. 110-122.
  -- Hardman CS, Chen YL, Wegrecki M, Ng SW, Murren R, Mangat D, Silva JP, Munro R, Chan WY , O'Dowd V , Doyle C, Mori P, Popplewell A, Rossjohn J, Lightwood D, Ogg GS. 2022. CD1a
  -- promotes systemic manifestations of skin inflammation. Nat Commun, 13 (1), pp. 7535.
  -- Chen YL, Gomes T, Hardman CS, Vieira Braga FA, Gutowska-Owsiak D, Salimi M, Gray N, Duncan DA, Reynolds G, Johnson D, Salio M, Cerundolo V , Barlow JL, McKenzie ANJ, Teichmann
  -- SA, Haniffa M, Ogg G. 2020. Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation. J Exp Med, 217 (3),
  -- Cotton RN, Wegrecki M, Cheng TY , Chen YL, Veerapen N, Le Nours J, Orgill DP, Pomahac B, Talbot SG, Willis R, Altman JD, de Jong A, Van Rhijn I, Clark RA, Besra GS, Ogg G, Rossjohn J,
  -- Moody DB. 2021. CD1a selectively captures endogenous cellular lipids that broadly block T cell response. J Exp Med, 218 (7),


pi_id: church_david
title: Novel immune escape mutations in mismatch repair deficient cancer
supervisors: David Church, Tim Elliott, Nicola Ternette
mix: 75% wet lab, 25% dry lab
description:
  DNA mismatch repair deficiency (MMRd) occurs in many cancer types where it causes hypermutation and instability at DNA microsatellites (MSI). MMRd/MSI tumours have been shown to be especially immunogenic, owing to the enrichment of mutated peptides they present as a conseequence of their mutation burden. Accordingly, these tumours frequently demonstrate loss of function alterations in components of the antigen presentation pathway machinery, the consequence of which is to enable escape from immune surveillance. However, current understanding of these is limited. Our unpublished analysis of >10,000 cancer whole genome sequences (WGS) from the Genomics England 100,000 Genomes Project (GEL 100KGP) has identified two novel genes which commonly subject to loss of function mutations in MMRd/MSI cancer. Both function in class I antigen processing and presentation and thus represent candidate immune escape mutations. This project seeks to perform detailed characterisation of both. Briefly, it will entail:
  -- Definition of genomic, transcriptomic and immunologic correlates of novel immune escape mutations in GEL 100KGP cases and additional clinical trial cohorts
  -- Functional analysis of novel immune escape mutations in model systems including cutting edge methods of immunopeptidomics and protein trafficking
  Supervision will be available for all aspects of the project by postdoctoral scientists. There will be opportunity to travel to collaborators institutes for a period if desired.

training:
  Analysis of whole genome sequence data; analysis of AI based image analysis; general molecular biology techniques; exposure to specialist methods including protein trafficking and immunopeptidomics.


pi_id: church_david
title: Characterisation of driver mutations in endometrial cancer
supervisors: David Church
mix: 75% wet lab, 25% dry lab
description:
  Endometrial cancer is the most common gynaecological malignancy in the developed world, yet has been understudied until the publication of the TCGA molecular analysis in 2013. More recently, our unpublished analysis of the unique cohort of endometrial cancers with whole genome sequencing (WGS) from the Genomics England 100,000 Genomes Project has revealed identified more than 50 driver genes, which vary across molecular subgroups and in combinations. While the function of some is well characterised, for many current understanding is minimal or lacking. This project will address this by genomic and functional analyses. Specifically it will:
  -- Perform detailed analysis of driver mutations in the GEL 100KGP endometrial cancers under the umbrella of the GeCIP
  -- Develop functional models of novel alterations to test their effect on cellular phenotype and therapeutic sensitivity
  -- Examine the basis of mutation cooperativity and antagonism using in selected cases using these systems
  Supervision will be available for all aspects of the project by postdoctoral scientists. There will be opportunity to travel to collaborators institutes for a period if desired.

training:
  Analysis of whole genome sequence data; ; general molecular biology techniques; experience in the development of and analysis of functional model systems.


pi_id: davies_james
title: Using base pair resolution genome architecture to explore enhancer function
supervisors: James Davies
mix: 50% wet lab, 50% dry lab, but will tailor to the candidate
description:
  Careful study of the chromatin architecture and the effects of perturbations of regulatory elements using genome editing at individual genes has led to huge progress in our understanding of gene regulation. However, to date only a handful of genes have had their regulatory landscape defined in detail and the general principles by which genes are controlled are not defined on a molecular scale. In addition, there is very significant variability in chromatin architecture at different loci and there is little understanding of why this has evolved and how it impacts gene expression.
  In this project we aim to use and adapt the new Micro Capture-C technique that we have developed to explore how enhancers make contact with gene promoters in detail and how this varies between different genes. We have preliminary data which shows how enhancers physically contact the promoter and gene body in far greater detail than has previously been possible. In this project we will use the method to define how enhancer promoter contacts are variable between different genes and how this alters when we make perturbations to the system using genetically engineered cellular models. We would also attempt to explore why the genome architecture is so variable at different sites in the genome using computational methods to interrogate why genes with distal enhancers would provide a selective advantage.

training:
  All basic approaches in molecular and cellular biology (PCR, Cloning, Cell culture etc.).  We also offer training in more specialised functional genomics techniques including chromatin immunoprecipitation, chromosome conformation capture, RNA-seq and single cell techniques.  We also have expertise in using cutting edge genome editing technology to modify the genome sequence in both cell lines and primary cells. There will be excellent training in the state-of-the-art FACS facility at the WIMM including isolation and purification of populations of haematopoietic cells.
  We also have expertise in bioinformatics. We are particularly interested in developing novel bioinformatic approaches to analyse next generation sequencing data. In particular, we have recently developed novel methods of analysing chromosome conformation capture datasets, which allow the data to be generated at much higher resolution than was previously possible.

background_reading:
  -- Hua P, Badat M, Hanssen LLP, Hentges LD, Crump N, Downes DJ, Jeziorska DM, Oudelaar AM, Schwessinger R, Taylor S, Milne TA, Hughes JR, Higgs DR and Davies JO (2021) ‘Defining genome architecture at base pair resolution’ Nature; 595, 125-129


pi_id: davies_robbie
supervisors: Robert Davies
mix: 100% dry lab
title:
  Investigating properties of de novo duplication or deletion detection using non-invasive prenatal testing data

description:
  During pregnancy, the blood of the mother contains cell free DNA derived both from maternal cells, and from fetal cells. By sequencing and analyzing this cell free DNA, it is possible to detect abnormal numbers of chromosomes in the fetus (aneuploidies). This process, called non-invasive prenatal testing (NIPT), is now the clinical standard of care for aneupolidy detection, and is in widespread use around the world. However, traditional use of this method cannot detect de novo sub-chromosomal abnormalities very well, as it uses the difference in counts of reads between chromosomes or regions, and these are not very precise due to the low fraction of fetal DNA in the sample and number of reads. Recently, I had a paper accepted on a method (QUILT) for low coverage imputation that can probabilistically assign reads to maternal or paternal origin. In this project, you would study how using the principle of assigning reads to their haplotypic origin (here maternal transmitted, untransmitted or paternally transmitted) and then looking for differences in the levels in between them, can facilitate sub-chromosomal aneuploidy detection. An outline for this project could be as follows. First, to set up a simulation framework, so that for sub-chromosomal event, that simulated sequencing reads could be generated. Second, to assing reads to their haplotypic background, using either truth data or by estimating it programatically (QUILT). Third, to develop a probabilistic model to determine the probability of different mutational events (normal DNA vs duplication vs deletion), conditional on the observed sequencing reads and prior probabilities. Fourth, to evaluate this model, and compare it to one where we don’t estimate what haplotypes reads come from. Time-permitting, this evaluation would be done across a variety of factors, for example different human populations, sequencing depths, different genomic regions, etc. Taken together, this project will help us determine whether assigning sequencing reads to their chromosomal backgrounds can improve de novo subchromosomal variant detection in NIPT.

training:
  In this project you’ll develop skills in methods development, statistics, and whole genome sequencing

background_reading:
  -- Liu Siyang, …, 2018. Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, Patterns of Viral Infections, and Chinese Population History. Cell. <a href="https://doi.org/10.1016/j.cell.2018.08.016">https://doi.org/10.1016/j.cell.2018.08.016</a>
  -- Davies Robert, …, 2021. Rapid genotype imputation from sequence with reference panels . Nature Genetics. <a href="https://www.nature.com/articles/s41588-021-00877-0">https://www.nature.com/articles/s41588-021-00877-0</a>


pi_id: dendrou_calli
title: TYK2 as a genetically determined drug target against multiple immune-mediated diseases
supervisors: Dr Calliope Dendrou
mix: 10% wet lab, 90% dry lab
description:
  Cross-trait genetic associations are common for the immune-mediated diseases (IMDs), indicating a sharing of etiological mechanisms, despite variation in the precise organs affected for each disorder. However, more systematically profiling these associations - not just between IMDs but across the broader disease phenome - is beginning to provide valuable translational insights. Given the hundreds of loci that can be associated with any single IMD, the scale and nature of cross-trait association patterns can help to pinpoint genetic variants and biological pathways to be prioritized for further investigations in a therapeutic context. For example, associations across multiple diseases can reveal targets amenable to drug repositioning approaches, whilst different directions of association for different diseases may suggest trade-offs that can inform patient stratification and that may predict potential side effects as a result of therapeutically manipulating particular biological pathways.
  Based on such cross-trait analyses and investigating genetic variants with the same patterns of association, the TYK2 locus serves as an immunological ‘hub’ around which several other associated loci can be organized, suggesting that TYK2 functions at the centre of several different signalling pathways each implicated in different IMDs. Moreover, TYK2 has emerged as a promising drug target. The project will involve interrogating the relationship between disease-associated genetic variation and the dynamics of TYK2-dependent immune cell signalling, as well as assessing the how the genetic effect relates to the impact of a novel allosteric TYK2 inhibitor. The project will be well suited to a student interested in bioinformatics/data analysis but can also include a wet-lab component depending on interest.

training:
  The proposed project will involve single-cell RNA sequencing, bulk RNA-seq, proteomics and/or imaging data analysis.

background_reading:
  -- Cortes A et al. (2020) Identifying cross-disease components of genetic risk across hospital data in the UK Biobank. Nature Genetics, 52, 126-134.
  -- Cortes A et al. (2017) Bayesian analysis of genetic association across tree-structures routine healthcare data in the UK Biobank. Nature Genetics, 49, 1311-1318.
  -- Dendrou CA et al. (2016) Resolving TYK2 locus genotype-to-phenotype conflict reveals therapeutic optimum for autoimmunity. Science Translational Medicine, 8, 363ra149.
  -- Makin S (2021) Cracking the genetic code of autoimmune disease. Nature, 595, S57-S59.


pi_id: dendrou_calli
title: Spatially resolved molecular and cellular profiling of immunopathological responses
supervisors: Dr Calliope Dendrou
mix: 100% dry lab
description:
  Molecular profiling techniques are valuable tools for understanding cellular function in health and disease, investigating pathophysiological mechanisms, setting clinical diagnoses, monitoring disease prognosis and identifying drug targets.
  The project will involve the integration of biochemical signatures derived from Fourier-transform infrared microspectroscopy with gene expression signatures derived from the application of spatial transcriptomics and single-nuclear transcriptomics techniques, using central nervous system tissue from patients with neuroinflammatory disease versus controls. A particular interest is in cross-correlating the biochemical and gene expression signatures and intercellular interactions in the tissue areas around the infiltrating immune cells to assess how the damage spreads from the immune lesions to the adjacent tissue.

training:
  The proposed project will involve: microspectroscopy, single-nuclear RNA sequencing, spatially resolved transcriptomics and spatial proteomics data analysis; depending on interest there may be opportunities for wet lab analyses.


pi_id: fowler_philip
supervisors: Dr Philip W Fower
mix: 100% dry lab
title:
  Improving the detection of novel pathogens and the prediction of antimicrobial resistance from clinical samples using whole genome sequencing

description:
  One of our main objectives in the Modernising Medical Microbiology Unit is the translation of genetics into Clinical Microbiology; previous research from the Unit led to UKHSA (then PHE) adopting in 2017 whole genome sequencing for Mycobacteria (especially M. tuberculosis, the aetiological agent of tuberculosis). Today we are working closely with the Ellison Institute of Technology in Oxford and in Autumn 2024 they launched a free-to-access cloud platform (https://www.eit-pathogena.com) that allows anyone to upload for research use raw genetic files from suspected Mycobacterial samples.
  With this cloud-platform in place we now have an excellent route to translation and adoption by researchers and public health organisations worldwide. There are lots of ideas for short- or long-research projects that could be developed into rotation or DPhil projects. The current list includes
  1) Developing algorithms that can screen genetic reads from clinical samples in real-time to detect the emergence of novel pathogens (like SARS-CoV-2). The idea is to develop an efficient algorithm that can “sniff” the torrent of genetic reads being uploaded and, by correlating novel reads between different samples, identify putative novel species whilst minimising the false positive rate.
  2) Building a catalogue of resistance-associated genetic variants for other Mycobacterial species. These include M. abscessus, which, whilst not an obligate pathogen, can cause serious lung disease, especially in patients with cystic fibrosis. Non-tuberculosis mycobacteria (NTMs) are lagging M. tuberculosis complex (MBTC) in the association between genetic variants and antibiotic resistance. This project will produce early catalogues for several of the more clinically relevant NTMs, thereby helping NTMs “catchup” with MBTC.
  3) Improving the sensitivity of genetics-based prediction for bacterial pathogens by assessing and including the impact of subpopulations. Clinical laboratories usually pick single colonies for sequencing but if there is genetic heterogeneity (as we have shown is the case for M. tuberculosis) then demonstrating this would change the paradigm for genetics-based microbiology.
  If any of these sound interesting, please get in touch. Each of these ideas depend relevant large numbers of samples being available. Also other ideas will, no doubt, present themselves and we are also open to students presenting their own, complementary ideas.

training:
  All projects are interdisciplinary and therefore students will be exposed to and learn
  1) clinical microbiology
  2) bacterial genetics
  3) bioinformatics, including both assembly and mapping based approaches
  4) cloud-based computing
  5) software development best practices (incl. testing, version control, pull requests, continuous integration)
  The student will therefore need to learn
  -- Python3 (incl. pandas and possibly scikit-learn/PyTorch)
  -- Git/GitHub
  -- NextFlow (possibly)
  The student will work with Infectious Disease Clinicians, Statisticians, Bioinformaticians, Research Software Engineers and Microbiologists (here in the Modernising Medical Microbiology Unit at the John Radcliffe Hospital).


pi_id: gill_deborah
title: Strategies to facilitate targeted high-efficiency gene editing for treatment of lung diseases
supervisors: Professor Deborah Gill & Dr Altar Munis
mix: 75% wet lab, 25% dry lab
description:
  The clustered regularly interspersed palindromic repeats (CRISPR) system, a powerful genome editing tool, has now been used ubiquitously in medical research including gene therapy. Several proof-of-concept studies have demonstrated the feasibility of in vivo gene editing to correct disease-causing mutations using both Homology Directed Repair (HDR) and Homology-Independent Targeted Integration (HITI) strategies. A successful therapeutic gene editing strategy to tackle lung disorders will require the targeted and highly efficient repair action of the CRISPR-Cas9 system adapted for specific cell types; for example, targeting alveolar type II pneumocytes in the case of interstitial lung diseases, and also ionocytes and ciliated cells for cystic fibrosis. We have developed a novel transgenic reporter mouse model, which ubiquitously expresses the fluorescent TdTomato transgene, to evaluate genome editor tools and delivery methods in vivo. We aim to use this model to explore, validate, and demonstrate the utility of in vivo genome editing strategies for lung disorders.
  The rotation project, which can serve as a starting point for subsequent DPhil study, focuses on gene editing using a range of delivery vectors, specifically comparing recombinant Lentiviral and AAV vectors and also vectors encoding cell-specific promoters. Gene editing strategies will first be tested in vitro using primary human lung airway cultures and surfactant air-liquid interface (SALI) cultures modelling human lung parenchyma. Off-targets and editing efficiencies will be assessed via droplet-digital PCR (ddPCR) and Nanopore MinION-based third generation next-generation sequencing (NGS) method AFIS-Seq. Utilising in vitro data to optimise experimental design (e.g. gRNA and donor design, Cas9 to donor ratios, etc), targeted, cell-specific, gene editing experiments can be performed in the reporter TdTomato mouse model. In parallel, a (partly) humanised mouse model can be generated for surfactant B deficiency (a lethal rare genetic disorder affecting the lung parenchyma) and those candidates with the ‘best’ combination of vector and cell-specific promoter will be used to demonstrate proof-of-concept.  We also have a conditional surfactant protein B knockout mouse model, which can be utilised as proof-of-principle if needed. Demonstrating efficient gene editing of specific and rare disease-causing mutations will support the use of personalised medicine to treat rare lung diseases where no other treatment options exist.

training:
  The proposed project will involve: human cell culture including cell manipulation via vector transfection & transduction; recombinant virus (lentiviral & AAV) vector design, production & titration; general recombinant DNA techniques including plasmid DNA manipulation, DNA & RNA purification, cloning, etc; gene quantification by PCR and droplet digital PCR; flow cytometry; confocal and immunofluorescence microscopy; immunoblotting; CRISPR‐Cas9 genome engineering; Nanopore MinION based, third-generation next generation sequencing & relevant bioinformatics pipeline involving Python3 and R coding/programming; use and design of transgenic mouse models of human disease, including handling, processing, and analysing mouse blood and tissue samples, and training for a Home Office Personal Licence. The student will also receive training in scientific writing, oral presentations and public engagement activities. The project would suit someone who would like to focus on wet lab techniques and contribute to the overall translation of a genetic therapy to the clinic.

background_reading:
  Munis, A. M., Hyde, S. C., & Gill, D. R. (2020). A human surfactant B deficiency air-liquid interface cell culture model suitable for gene therapy applications. Molecular therapy. Methods & clinical development, 20, 237–246. <a href="https://doi.org/10.1016/j.omtm.2020.11.013">https://doi.org/10.1016/j.omtm.2020.11.013</a>
  van Haasteren, J., Munis, A. M., Gill, D. R., & Hyde, S. C. (2021). Genome-wide integration site detection using Cas9 enriched amplification-free long-range sequencing. Nucleic acids research, 49(3), e16. <a href="https://doi.org/10.1093/nar/gkaa1152">https://doi.org/10.1093/nar/gkaa1152</a>
  Miura, H., Imafuku, J., Kurosaki, A., Sato, M., Ma, Y., Zhang, G., Mizutani, A., Kamimura, K., Gurumurthy, C. B., Liu, D., & Ohtsuka, M. (2021). Novel reporter mouse models useful for evaluating in vivo gene editing and for optimization of methods of delivering genome editing tools. Molecular therapy. Nucleic acids, 24, 325–336. <a href="https://doi.org/10.1016/j.omtn.2021.03.003">https://doi.org/10.1016/j.omtn.2021.03.003</a>
  Hu, J., Bourne, R. A., McGrath, B. C., Lin, A., Pei, Z., & Cavener, D. R. (2021). Co-opting regulation bypass repair as a gene correction strategy for monogenic diseases. Molecular therapy: the journal of the American Society of Gene Therapy, S1525-0016(21)00204-5. Advance online publication. <a href="https://doi.org/10.1016/j.ymthe.2021.04.017">https://doi.org/10.1016/j.ymthe.2021.04.017</a>
  Kelly, J. J., Saee-Marand, M., Nyström, N. N., Evans, M. M., Chen, Y., Martinez, F. M., Hamilton, A. M., & Ronald, J. A. (2021). Safe harbor-targeted CRISPR-Cas9 homology-independent targeted integration for multimodality reporter gene-based cell tracking. Science advances, 7(4), eabc3791. <a href="https://doi.org/10.1126/sciadv.abc3791">https://doi.org/10.1126/sciadv.abc3791</a>


pi_id: goriely_anne
title: Goriely Laboratory Project: ‘Probing selfish selection of de novo mutations’
supervisors: Prof Anne Goriely
mix: 80% wet lab, 20% dry lab
description:
  As mutations are at the origin of all genetic variations, understanding the factors that influence mutational rates and patterns (and the reason for which they occur) is crucial to the study of disease, evolution and genome diversity. It is now well established that ~60 new point mutations are acquired spontaneously at each generation. Although these point mutations initially arise as random miscopying events, preferentially from the paternal germline, we have described a process (selfish selection) by which some pathogenic de novo mutations (DNMs) become progressively enriched in the testis as men age. This project will aim to develop multi-disciplinary strategies to identify new genes/molecular pathways subject to selfish selection and establish the potential impact of this process on human disease and genome heterogeneity.
  Because selfish variants are selected in ageing testes and are present at elevated levels in the sperm of most men, they are anticipated to recur more frequently as DNMs in patient cohorts. Hence, one of the approaches we will follow consists in mining large DNM datasets derived from analysis of WES/WGS family trios. This analysis will generate a list of candidate variants/genes that are recurrently transmitted as DNMs. We will then assess whether these variants are enriched in human testes or sperm using custom assays for ultra-rare mutation detection (such a ‘RED-PCR’, rhAMPSeq or duplex sequencing).

training:
  This project represents a unique opportunity to gain in-depth training in Human Genetics, germline stem cell biology and the application of Next-generation sequencing technologies for detection of ultra-rare variants. The project can be tailored to suit personal interests and need for training but will typically involve both a wet-lab component and bioinformatic analysis of genomic datasets.

background_reading:
  -- Maher GJ, Ralph HK, Ding Z, Koelling N, Mlcochova H, Giannoulatou E, Dhami P, Paul DS, Stricker SH, Beck S, McVean G, Wilkie AOM & Goriely A, 2018: Selfish mutations dysregulating RAS-MAPK signaling are pervasive in aged human testes, Genome Res. 28(12):1779-1790
  -- Giannoulatou E, McVean GAT, Taylor IB, McGowan SJ, Maher GJ, Iqbal Z, Pfeifer SP, Turner I, Burkitt-Wright EMM, Shorto J, Itani A, Turner K, Gregory L, Buck D, Rajpert-De Meyts E, Looijenga LHJ, Kerr B, Wilkie AOM & Goriely A, 2013: Contributions of intrinsic mutation rate and selfish selection to levels of de novo HRAS mutations in the paternal germline. Proc Natl Acad Sci USA, 110(50):20152-20157.
  -- Goriely A & Wilkie AOM, 2012: Paternal age effect mutations and selfish spermatogonial selection: causes and consequences for human disease. Am J Hum Genet. 90(2):175-200


pi_id: goriely_anne
supervisors: Dr Nicky Whiffin and Prof Anne Goriely
mix: 20% wet lab, 80% dry lab (flexible)
title:
  Estimating the genome-wide prevalence of mosaicism through analysis of large-scale whole-genome dataset from family trios

description:
  Although most de novo mutations (DNMs) occur as one-off events during spermatogenesis, they can also originate through a process called ‘mosaicism’. Mutations occurring during early embryonic development result in somatic and/or gonadal mosaicism and can be found at elevated levels across multiple tissues.  Mosaicism is increasingly recognised as a significant contributor to spontaneous disease, with recent studies highlighting that ~10% of ‘apparently’ DNMs found in children have actually arisen early during one of the parents’ development. This has important implications for genetic counselling as mosaic DNMs are likely present in multiple eggs or sperm and are associated with an increased recurrence risk (as high as 50%). Moreover, DNMs can also occur during the child’s own development, potentially causing a variable phenotype compared with the equivalent constitutive mutation. However, the contribution of mosaicism has been difficult to establish and is frequently overlooked in the analysis of large datasets because of the technical challenges associated with mosaic variant detection and calling.
  We propose to use and compare state-of-the-art calling algorithms (e.g. MuTect, Streka, DeepMosaic, MosaicHunter) to systematically analyse the whole-genome sequencing (WGS) data derived from the Genomics England 100K Genomes family trios dataset (~5000 trios). This will allow us to interrogate this dataset and single-out different classes of mosaic variants such as those that:
  1) Are apparently de novo but are present at low levels in one of the parental samples
  2) Are present at levels deviating from the expected 50:50 ratio in the child
  3) Are present in one parent at elevated levels but are in fact mosaic in this individual - this situation is anticipated to lead to missed diagnoses due to exclusion by bioinformatics pipelines used for DNM calling.
  For cases where we have access to biological samples, we will use ultra-deep NGS techniques to validate candidate mosaic variants derived from this analysis – this may include the analysis of paternal semen samples that provide a direct means to establish the contribution of gonadal mosaicism.

training:
  This project represents a unique opportunity to gain in-depth training in Human Genetics, analysis of large-scale genomics datasets and the application of Next-generation sequencing technologies for detection of rare variants. The project can be tailored to suit personal interests and need for training but will typically involve both bioinformatic and statistical analysis of large-scale genomic datasets combined with a wet-lab component to provide validation of the data generated in silico.

background_reading:
  Bernkopf M, Abdullah UB, et al, under review: The PREGCARE study: Personalized recurrence risk assessment following the birth of a child with a pathogenic de novo mutation <a href="https://www.biorxiv.org/content/10.1101/2022.07.26.501520v1">https://www.biorxiv.org/content/10.1101/2022.07.26.501520v1</a>


pi_id: higgs_doug
supervisors: Professor Doug Higgs, Professor Jim Hughes
mix: ~50% wet lab, ~50% dry lab
title:
  Determining the grammar and syntax of regulatory elements using laboratory and computational approaches

description:
  A major goal of current biology is to understand how DNA sequences are read by the nuclear machinery to direct normal development and differentiation and how this is perturbed in human disease. Whole genome sequences of a wide range of organisms spanning 500 million years of evolution are now available for detailed analysis. We currently know that there are ~20,000 structural genes in humans but their expression is regulated by as many as 1,000,000 regulatory elements including enhancers, promoters and boundary elements. Of particular interest, enhancers integrate external cell signals with the internal transcriptional and epigenetic programmes and communicate this information to their cognate promoters thereby controlling when and where specific genes are switched on and off. Many single genes are controlled via clusters of enhancers which are each bound by a variety of cell specific and general transcription factors which relay information from enhancers to promoters. Although structural genes are in general well conserved, the positions and DNA sequences of regulatory elements which control their expression change quite rapidly throughout evolution.
  These observations beg the question of how the precise timing and cell-specific expression of a particular gene is maintained in the face of such dramatic changes in the regulatory elements? This question gets to the heart of our lack of understanding of the mechanism by which enhancers communicate with promoters. If regulatory elements can change so much during evolution how is specific information passing from enhancers to promoters encoded?  We will study this key issue by initially studying the well characterised alpha globin locus as a model. The globin genes are expressed in a very similar developmental and tissue-specific manner in diverse species spanning 500 million years of evolution and the structure of the genes encoding the globin proteins is well conserved. By contrast, the cluster of enhancers (so called super-enhancer) controlling their expression varies considerably. Using a combination of established lab-based assays together with extensive computational analysis of the regulatory elements we will initially determine how the positions and sequences of the regulatory elements have evolved in a wide variety of species including fish, amphibians, birds and mammals including a wide range of primates. Based on our consequent understanding of the evolution of globin gene regulation, we will test new hypotheses using synthetic biology as described in Blaney et al (Cell in press) and extend and generalise these observations to other complex enhancers throughout the genome.

training:
  Our laboratory of ~12-14 scientists, includes post-docs, students and research assistants. Students undertaking their studies in the lab have day-to-day supervision from a team of scientists who have considerable experience in all aspects of current genomics including, for example, RNA-seq, ATAC-Seq, ChIP-seq, and various forms of chromosome conformation capture. We also have considerable expertise in cell biology and imaging. A key aspect of our work in collaboration with the WIMM Centre for Computational Biology involves a full range of analytical approaches using computational biology.

background_reading:
  The Tree of Life Project:  <a href="https://www.sanger.ac.uk/programme/tree-of-life/">https://www.sanger.ac.uk/programme/tree-of-life/</a>
  Oudelaar AM, Higgs DR. The relationship between genome structure and function. Nat Rev Genet. 2021 Mar;22(3):154-168. doi: 10.1038/s41576-020-00303-x.
  Joseph Blayney, Helena Francis, Brendan Camellato, Leslie Mitchell, Rosa Stolper, Jef Boeke, Douglas Higgs*, Mira Kassouf* Super-enhancers require a combination of classical enhancers and novel facilitator  elements to drive high levels of gene expression.  bioRxiv 2022.06.20.496856; doi: <a href="https://doi.org/10.1101/2022.06.20.496856">https://doi.org/10.1101/2022.06.20.496856</a> (2023 Cell in press).
  Buffry AD, Mendes CC, McGregor AP. The Functionality and Evolution of Eukaryotic Transcriptional Enhancers. Adv Genet. 2016;96:143-206. doi: 10.1016/bs.adgen.2016.08.004.


pi_id: hinch_anjali
title: The landscape of de novo mutations in humans
supervisors: Dr Anjali Hinch
mix: Flexible
description:
  The chromosomes we inherit from our parents are not exact copies but mosaics of their chromosomes. These mosaics are created during the formation of eggs and sperm when cells cut chromosomes up and re-attach them, sometimes in new combinations (recombination). We have discovered that our cells make an unexpectedly large number of errors in this process leading to changes in DNA (mutations) [Science, 2023].
  In your DPhil, you will address one or more of the following key questions:
  -- Do we vary in our propensity to acquire de novo mutations? If so, why?
  -- How do de novo mutations impact our health?
  -- What are the mechanisms underlying de novo mutation?
  Within this larger framework, we are offering the following rotation projects:
  -- Mapping genetic determinants of de novo mutation rate in the British population using a genome-wide association study (GWAS) (dry lab)
  -- Identifying de novo mutations using long-read Nanopore and PacBio sequence data in a model for a genetically-modified Breast Cancer gene (BRCA2) (dry lab)
  -- Mapping sites of DNA synthesis following DNA break repair in a genetically-engineered model (wet lab)
  Our approach is data driven. We utilise large-scale genetic and phenotypic datasets in humans as well as performing a range of experimental assays, including CRISPR-Cas9 mediated genome-editing. We then use machine learning and other statistical techniques to characterise their interactions. For further details, please get in touch (<a href="mailto:anjali.hinch@well.ox.ac.uk">anjali.hinch@well.ox.ac.uk</a>).

training:
  We offer computational, statistical and wet-lab projects and the flexibility to combine them for a comprehensive, in-depth and well-rounded training in genomic science. We are based at the internationally recognised multidisciplinary research institute, Wellcome Centre for Human Genetics, with state-of-the-art facilities for genomic research.
  We are a close-knit and multidisciplinary team with a track record of highly influential work and our students and postdocs regularly present work at international conferences.
  Specifically, projects in our lab include opportunities to perform
  -- Genome-wide association studies (GWAS)
  -- Machine learning and other statistical methods to decode mutations in the germline and in cancers and de novo mutation discovery
  -- CRISPR/Cas9-mediated genome-engineering in murine models
  -- Single-cell DNA and RNA sequencing
  -- Protein occupancy and interaction assays

background_reading:
  R Hinch, P Donnelly, AG Hinch. Meiotic DNA breaks drive multifaceted mutagenesis in the human germline. Science, 382 (2023).
  AG Hinch et al. The Configuration of RPA, RAD51, and DMC1 Binding in Meiosis Reveals the Nature of Critical Recombination Intermediates. Mol Cell, 79 (4), pp. 689-701.e10. (2020)
  AG Hinch et al. Factors influencing meiotic recombination revealed by whole-genome sequencing of single sperm. Science, 363 (2019)
  B Davies et al. Re-engineering the zinc fingers of PRDM9 reverses hybrid sterility in mice. Nature, 530 (7589), pp. 171-6 (2016)
  AG Hinch et al. The landscape of recombination in African Americans. Nature, 476 (7359), pp. 170-5.


pi_id: hughes_jim
title: Various computational and bench projects
supervisors: Professor Jim Hughes
mix: varies
description:
  The group has opportunities for purely computational projects and bench projects although bench scientists are strongly encouraged and trained to do their own bioinformatic analysis and develop their own coding skills.
  Computational projects combine the integration of genomics data, including single cell epigenomic and transcriptomic data, with the development of machine learning based approaches to predict fundamental aspects of gene regulation in the mammalian genome.  The ultimate goals of these projects are to use the deep neural network based approaches to understand the basic principles of how cell type specific gene regulation is achieved and to provide predictive platforms to identify casual changes in the non-coding genome and to identify the underlying mechanism and genes linked to human disease.
  Relevant publications.
  -- Schwessinger, R., et al  (2017). Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints. Genome Res. 27: 1730-1742.
  -- Schwessinger, R., et al. (2020). DeepC: predicting 3D genome folding using megabase-scale transfer learning. Nat Methods. 17: 1118-1124.
  -- Downes, D.J., et al (2019). An integrated platform to systematically identify causal variants and genes for polygenic human traits. bioRxiv: 813618.
  Bench projects involve using the latest genomics technologies, including those developed by the group to understand the basic regulation of genes and the impact of sequence variation on it.  The group is expert in chromosome conformation capture technologies and have developed the suite of Capture-C technolgies (Capture-C, Tiled-C and Tri-C) used to interogate the regulatory landcapes of genes. Projects include using these and high-resolution variants such as Micro Capture-C (with J Davies) in primary cells to understand the effect of human variation on specific genes and en masse to understand basic principles.  The group also leaverges large-scale synthetic biology to build regulatory domains from first principles (<a href="https://www.thedarkmatterproject.org/main">https://www.thedarkmatterproject.org/main</a>) to discover the principles of how they are built and to provide a practical toolkit to build and exploit functional bespoke gene regulatory domains in the mammalian genome.  Projects also exist to develop new methods to fill in our current “blindspots” in our ability to assess activity and function in the genome.
  Relevant publications.
  -- Larke, M.S.C., et al. (2021). Enhancers predominantly regulate gene expression during differentiation via transcription initiation. Mol Cell. 81: 983-997 e7.
  -- Oudelaar, A.M., et al. (2018). Single-allele chromatin interactions identify regulatory hubs in dynamic compartmentalized domains. Nat Genet.
  -- Oudelaar, A.M., and Beagrie, R.A., et al (2020). Dynamics of the 4D genome during in vivo lineage specification and differentiation. Nat Commun. 11: 2722
  -- Hua, P., et al (2021). Defining genome architecture at base-pair resolution. Nature. 595: 125-129.
  Please contact directly for further information.
  These pages were reviewed/updated: [23-07-21]


pi_id: kelleher_jerome
title: Improved inference of genetic ancestry
supervisors: Jerome Kelleher
mix: 0% wet lab, 100% dry lab
description:
  Recent breakthroughs in computational genomics have made it possible to infer genetic ancestry in recombining organisms at scale for the first time, making numerous downstream applications possible. A number of different methods have recently been proposed, providing deep insights into human evolution. However, these methods are in their infancy, and much work remains to be done before they are ready for mainstream genomics. Our group developed the "tsinfer" method, which is capable of accurately inferring genetic ancestry for millions of whole genomes, based on the "succinct tree sequence" data structure. This method of encoding genetic ancestry has also lead to performance improvements of multiple orders of magnitude in genome simulation and statistical computation, and has the potential to solve many of the major computational problems facing large scale genomics. For example, the data compression levels achieved by the tree sequence data structure are so high that it is in principle possible to store the ancestral history of 10 billion humans in around 1TB of storage.
  In this rotation project and potential extension into a DPhil, you will use simulations and human data to investigate areas in which tsinfer's accuracy and computational performance can be improved. You will implement updates to the core algorithms in tsinfer's Python and C codebase as part of an open-source development process. Specific areas for development include:
  -- Better heuristics for ancestral haplotype generation
  -- Improved recombination breakpoint detection
  -- Detailed analysis of patterns of recurrent mutations and their relation to sequencing error
  -- Incorporation of uncertainty via probabilistic ancestor generation and stochastic HMM traceback
  --  Better performance via more fine-grained parallelisation strategies
  -- Better scalability by distribution across multiple machines

training:
  This project will suit a student interested in a DPhil focused on computational statistical genomics, and will include a large software development component.

background_reading:
  -- Kelleher et al. (2019). Inferring whole-genome histories in large population datasets. Nature Genetics.  <a href="https://doi.org/10.1038/s41588-019-0483-y">https://doi.org/10.1038/s41588-019-0483-y</a>
  -- Wohns et al. (2021). A unified genealogy of modern and ancient genomes. Preprint. <a href="https://doi.org/10.1101/2021.02.16.431497">https://doi.org/10.1101/2021.02.16.431497</a>
  -- Project website: <a href="https://tskit.dev">https://tskit.dev</a>


pi_id: kessler_benedikt
title: A bioinformatics approach to study the cellular ubiquitin system in health & disease
supervisors: Dr Andreas Damianou, Dr Philip Charles, Prof Benedikt Kessler
mix: 66% wet lab, 33% dry lab
description:
  The Ubiquitin System is indispensable for a human cell as it controls several cellular functions including degradation, autophagy, DNA repair and cell proliferation. This control occurs through the conjugation of ubiquitin to proteins, which can influence multiple aspects of their functionality, such as their activity, localisation or half-life (turnover).
  The ubiquitination of target proteins is complex, with the formation/removal of various poly-ubiquitin chain linkages being carried out by the conjugating enzymes (E1, E2 and E3) as well as by the erasers deubiquitinating enzymes (DUBs). The balance between ubiquitin conjugation and de-conjugation is crucial and well-regulated in cells. Many studies indicate that a dysfunction of this system could lead to numerous human diseases including cancer and neurodegenerative disorders.
  Global approaches to determine the molecular function of components of the ubiquitin system (E3 and DUBs) include deep proteome, ubiquitome and interactome based on mass spectrometry studies, which are applied in our laboratory. The cutting-edge of mass spectrometry technology as well as molecular tools give us the opportunity to gain unprecedented depth and novel molecular insights into these cellular processes. Nevertheless, the data analysis for such complex -omic studies is still challenging and merits the development of more advanced mining tools. Therefore, we are looking for a highly motivated individual with a keen interest in molecular/ cellular biology and experience in programming as well as bioinformatics to i) help in the development of an –omics data analysis workflow and ii) apply this to untangle complex cellular –omics (proteomics / transcriptomics / ubiquitomics) data sets.

training:
  -- Introduction to background biology of the cellular ubiquitin system and its  function in normal physiology as well as cancer and  neurodegeneration
  -- Training on getting familiar with –omics data, such as transcriptomics,  mass spectrometry derived data sets such as proteomics,  metabolomics, but also ubiquitomics, interactomics data sets
  -- Introduction to bioinformatics tools to process –omics data, such as R  (training courses) and more specialised –omics analysis software  including Mascot, MaxQuant, Perseus, SAINT, Progenesis IQ, Proteomics Discoverer, PEAKS, MS Fragger, Fragpipe; possibilities to  follow advanced courses on programming (Python, JavaScript, HTML,  Elm etc).

background_reading:
  -- Interaction  mapping of endoplasmic reticulum ubiquitin ligases identifies  modulators of innate immune signalling. Fenech EJ, Lari F, Charles  PD, Fischer R, Laétitia-Thézénas M, Bagola K, Paton AW, Paton JC,  Gyrd-Hansen M, Kessler BM, Christianson JC. Elife. 2020 Jul  2;9:e57306. doi: 10.7554/eLife.57306.
  -- Comprehensive  Landscape of Active Deubiquitinating Enzymes Profiled by Advanced  Chemoproteomics. Pinto-Fernández A, Davis S, Schofield AB, Scott  HC, Zhang P, Salah E, Mathea S, Charles PD, Damianou A, Bond G,  Fischer R, Kessler BM. Front Chem. 2019 Aug 29;7:592. doi:  10.3389/fchem.2019.00592.
  -- Molecular  basis of USP7 inhibition by selective small-molecule inhibitors.  Turnbull AP, Ioannidis S, Krajewski WW, Pinto-Fernandez A, Heride C,  Martin ACL, Tonkin LM, Townsend EC, Buker SM, Lancia DR, Caravella  JA, Toms AV, Charlton TM, Lahdenranta J, Wilker E, Follows BC, Evans  NJ, Stead L, Alli C, Zarayskiy VV, Talbot AC, Buckmelter AJ, Wang M,  McKinnon CL, Saab F, McGouran JF, Century H, Gersch M, Pittman MS,  Marshall CG, Raynham TM, Simcox M, Stewart LMD, McLoughlin SB,  Escobedo JA, Bair KW, Dinsmore CJ, Hammonds TR, Kim S, Urbé S,  Clague MJ, Kessler BM, Komander D. Nature. 2017 Oct  26;550(7677):481-486. doi: 10.1038/nature24451.
  image://data/images/kessler_benedikt_02.png
  1) Figure/Photo  – Cellular Ubiquitin System
  Figure 1: Cellular ubiquitin system – The turn-over of most proteins in cells are controlled by the attachment of ubiquitin, a small protein (black dots), to protein substrates. These are then recognised by the 26S proteasome complex for destruction into peptides and further degraded to amino acids (AAs). AAs are serving as building blocks for protein synthesis. The protein’s life cycle is perturbed in cancer and other human diseases, a trait that is the focus of this bioinformatics based research project.


pi_id: knight_julian
title: Resolving heterogeneity in the response to infection using -omics
supervisors: Prof Julian Knight, Dr Alex Mentzer
mix: 40% wet lab, 60% dry lab (flexible)
description:
  The dysregulated host response to infection results in organ dysfunction and death, accounting for substantial morbidity and mortality in intensive care but the basis for why this develops in only specific individuals with an infection remains unclear.  We are taking novel integrative multi-omics approaches to understand this, with a view to developing personalised therapy that is appropriate to the individual patient at a particular stage in their illness.
  This project would form the basis of a laboratory rotation or a 3-year doctoral research project. In sepsis, we have established one of the largest cohorts of patients for genomic studies worldwide, the UK Genomic Advances in Sepsis (GAinS) Study. With our collaborators we performed the first substantive genome-wide association study for outcome in sepsis and complemented this with functional genomic analysis showing that transcriptomic signatures predict underlying response state, outcome and response to therapy. Moreover, we found that a patient's genetic background influenced this with specific genetic variants associated with differences in gene expression dependent on their immune response state. This was further emphasised by our findings in healthy volunteers of expression quantitative trait loci for the response to bacterial endotoxin.
  The COVID-19 Multi-omic Blood ATlas (COMBAT) Consortium has performed deep phenotyping of COVID-19 patients in Oxford using multi-omic profiling in blood, combined with knowledge of host genetics, pathogen diversity and immunological response, to allow an integrated systems biology approach to understanding the nature and basis of observed disease heterogeneity and drivers of severe illness. This includes bulk and single-cell transcriptomics, proteomics, repertoire sequencing and epigenomics, plasma profiling using timsTOF mass spectrometry and multiplexed immunoassays, serology, host genetics and viral sequencing.
  This project will aim to follow up on this work to understand individual variation in the response to infection leveraging ongoing patient recruitment, and how this could be used to develop and apply therapy. The work provides the opportunity to define the individual response to infection, the specific modulated genes and pathways that may be important in pathogenesis and potential drug targets, and how to use this knowledge effectively to develop personalised therapy. The project will benefit from access to large genomic and clinical datasets, both publicly available and those generated in house. Depending on the structure and duration of the project this could involve using statistical genetics and epidemiology to fine map genetic associations and establish their functional basis; bioinformatics to leverage genomic and epigenomic data, functionally annotate and integrate with diverse related data types to identify and prioritise potential novel drug targets; systems biology and integrative analysis approaches to maximise the informativeness of complex multidimensional datasets; genome editing to knockdown expression of specific genes or investigate the impact of particular genetic variants to establish mechanism; and application of single cell -omic and immune profiling approaches to further define pathogenesis.

training:
  This project will offer a comprehensive training programme in genomic science together with molecular biology and immunology. As described above, this can include both dry (bioinformatics/statistics/computational science) and wet lab (molecular biology/functional genomics/immunology) work, making it an ideal DPhil project for students wishing to gain skills in both areas. There are established sample and data collections for the proposed work, together with a very strong collaborative research network with other researchers on the GMS programme in this area. The required wet lab and bioinformatic approaches are well established with expertise in complex trait genetics, gene expression profiling, next generation sequencing technologies including RNA-seq and ChIP-seq, expression quantitative trait mapping, epigenomic profiling, genome editing, immunological assays and other approaches. Students will benefit from working within a supportive research group with a strong track record in graduate student training and mentoring. You will have the opportunity to regularly present your work within the group, to your peers within the Centre as well as at international conferences. Students are encouraged and supported to undertake further relevant training courses in Oxford and elsewhere depending on need.

background_reading:
  -- Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, Rautanen A, Gordon AC, Garrard C, Hill AVS, Hinds CJ & Knight JC. 2016 Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med 4, 259-271.
  -- COMBAT Consortium. 2022 A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. Cell 185, 916-938 e958.
  -- Maslove DM, Tang B, Shankar-Hari M, Lawler PR, Angus DC, Baillie JK, Baron RM, Bauer M, Buchman TG, Calfee CS, dos Santos CC, Giamarellos-Bourboulis EJ, Gordon AC, Kellum JA, Knight JC, Leligdowicz A, McAuley DF, McLean AS, Menon DK, Meyer NJ, Moldawer LL, Reddy K, Reilly JP, Russell JA, Sevransky JE, Seymour CW, Shapiro NI, Singer M, Summers C, Sweeney TE, Thompson BT, van der Poll T, Venkatesh B, Walley KR, Walsh TS, Ware LB, Wong HR, Zador ZE and Marshall JC (2022). Redefining critical illness. Nature Medicine 28, 1141-1148.
  -- Cano-Gamez E, Burnham KL, Goh C, Malick ZH, Kwok A, Smith DA, Peters-Sengers H, Antcliffe D, Investigators G, McKechnie S, Scicluna BP, van der Poll T, Gordon AC, Hinds CJ, Davenport EE and Knight JC (2022). An immune dysfunction score for stratification of patients with acute infection based on whole blood gene expression. Science Translational Medicine 14, eabq4433.
  -- Kwok AJ, Allcock A, Ferreira RC, Cano-Gamez E, Smee M, Burnham KL, Zurke Y-X, Emergency Medicine Research Oxford (EMROx), McKechnie S, Mentzer AJ, Monaco C, Udalova I, Hinds CJ, Davenport EE, Todd JA and Knight JC (2023). Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis. Nature Immunology 24, 767-779
  -- Mi Y, Burnham KL, Charles PD, Heilig R, Vendrell I, Whalley J, Torrance HD, Antcliffe DB, May SM, Neville MJ, Berridge G, Hutton P, Geoghegan CG, Radhakrishnan J, Nesvizhskii AI, Yu F, Davenport EE, McKechnie S, Davies R, O'Callaghan DJP, Patel P, Del Arroyo AG, Karpe F, Gordon AC, Ackland GL, Hinds CJ, Fischer R and Knight JC (2024). High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response. Science Translational Medicine 16, eadh0185
  -- Burnham KL, Milind N, Lee W, Kwok AJ, Cano-Gamez K, Mi Y, Geoghegan CG, Zhang P, McKechnie S, Soranzo N, Hinds CJ, Knight JC and Davenport EE (2024). eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis. Cell Genomics 4, 100587


pi_id: knight_julian
title: Validating a genetics-led approach to drug target prioritisation in immune traits
supervisors: Prof Julian Knight
mix: 30% wet lab, 70% dry lab (flexible)
description:
  The high attrition rate in late-stage drug development requires new approaches to establish evidence for target validation, the therapeutic hypothesis that perturbing a target will benefit patients with minimal toxicity. Human genetic evidence predicts successful progress along the drug development pipeline but systematic use in drug target validation has not yet been achieved.
  This project would be an opportunity to join an established research effort within the Knight group to develop approaches to maximise the informativeness of genetics for drug target identification and validation as well as related questions such as prediction of adverse effects, predicting mechanisms of therapeutic modulation and identifying repurposing opportunities.
  The relative balance of computational and wet lab work in the project will depend on the individual student’s interests. We aim to build and validate computational tools and pipelines, and to generate experimental evidence to support this.  You would apply cutting-edge functional genomic approaches and gain significant expertise in bioinformatics. The project would provide relevant training for a laboratory rotation or form the basis for a 3-year doctoral research project.

training:
  You would have the opportunity to gain valuable bioinformatic skills in the analysis of genetic and -omic datasets and more broadly within the drug target prioritisation approaches we are establishing that integrates and leverages information involving common and rare disease alleles, functional genomic and epigenomic annotations, population genetic diversity, systems immunology, connectivity, interactions, model organism phenotypes and ontologies. Examples of experimental approaches that you would use include high throughput CRISPR screens and siRNA knock down together with use of highly selective chemical probes (small molecule inhibitors generated by Centre for Medicines Discovery) to determine the consequences of modulating specific targets. You would apply these to patho-physiologically relevant phenotypic readouts for the trait of interest, including using iPSC, primary human cells and where possible patient-derived cellular assays. You would also leverage publicly accessible data, for example from compound screens within the Library of Integrated Network-based Cellular Signatures together with existing genome-wide mutagenesis and CRISPR screens. This work is made tractable by our established collaborations with academia and industry. You will benefit from working within a supportive research group with a strong track record in graduate student training and mentoring. You will have the opportunity to regularly present your work within the group, to your peers within the Centre as well as at international conferences. Students are encouraged and supported to undertake further relevant training courses in Oxford and elsewhere depending on need.

background_reading:
  -- Fang H, Consortium U-D, De Wolf H, Knezevic B, Burnham KL, Osgood J, Sanniti A, Lledo Lara A, Kasela S, De Cesco S, Wegner JK, Handunnetthi L, McCann FE, Chen L, Sekine T, Brennan PE, Marsden BD, Damerell D, O'Callaghan CA, Bountra C, Bowness P, Sundstrom Y, Milani L, Berg L, Gohlmann HW, Peeters PJ, Fairfax BP, Sundstrom M & Knight JC. 2019 A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat Genet 51:1082-1091
  -- Fang H, Chen L & Knight JC. 2019 From genome-wide association studies to rational drug target prioritisation in inflammatory arthritis. The Lancet Rheumatology 2, 50-62
  -- Zhang P, Amarasinghe HE, Whalley JP, Tay C, Fang H, Migliorini G, Brown AC, Allcock A, Scozzafava G, Rath P, Davies B & Knight JC. 2022 Epigenomic analysis reveals a dynamic and context-specific macrophage enhancer landscape associated with innate immune activation and tolerance. Genome Biology 23, 136
  -- Brown AC, Cohen CJ, Mielczarek O, Migliorini M, Costantino F, Allcock A, Davidson C, Elliott KS, Fang H, Lledó Lara A, Martin AC, Osgood JA, Sanniti A, Scozzafava G, Vecellio M, Zhang P, Black MH, Li S, Truong D, Molineros J, Howe T, B. Wordsworth BP, Bowness P and Knight JC. 2023 Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis. Cell Genomics 3, 100306.


pi_id: kong_augustine
title: Methods to decompose various factors that contribute to genotype-phenotype associations
supervisors: Augustine Kong
mix: 100% dry lab
description:
  Genotype-phenotype associations result from direct and indirect genetic effects and confounding due to population stratification and assortative mating (refs 1, 2, 3). Data of nuclear families and/or first-degree relative pairs can be used to separate out these effects. Methods to do so exist. Our aim is to further develop these methods: (a) to increase statistical power (refs 4, 5), and (b) to incorporate more complex models. For example, with (b), most analyses currently do not take into account ascertainment bias, i.e. the individuals in a study such as the UK Biobank is not a random sample drawn from the population.

background_reading:
  1) Kong A, Thorleifsson G, Frigge ML, Vilhjalmasson BJ, Young AI, Thorgeirsson TE, Benonisdottir S, Oddsson A, Halldorsson BV, Masson G, Gudbjartsson DF, Helgason A, Bjornsdottir G, Thorsteinsdottir U, Stefansson K. The nature of nurture: Effects of parental genotypes. Science. 2018, Jan 26, 359(6374):424-428.
  2) Young AI, Benonisdottir S, Przeworski M, Kong A. Deconstructing the sources of genotype-phenotype associations in humans. Science. 2019, Sep 27, 365(6460):1396-1400.
  3) Young AI, Frigge ML, Gudbjartsson DF, Thorleifsson G, Bjornsdottir G, Sulem P, Masson G, Thorsteinsdottir U, Stefansson K, Kong A. Relatedness Disequilibrium Regression estimates heritability without environmental bias. Nat Genet. 2018 Sep, 50(9):1304-1310.
  4) Kong A, Benonisdottir S, Young AI. Family analysis with Mendelian Imputations. bioRxiv. 2020.
  5) Young AI, Nehzati SM, Lee C, Benonisdottir S, Cesarini D, Benjamin D, Turley P, Kong A. Mendelian Imputations of parental genotypes for genome-wide estimation of direct and indirect genetic effects. bioRxiv. 2020.
  https://www.nytimes.com/2018/01/25/science/children-parents-genes-education.html


pi_id: larson_greger
title: Using ancient DNA to understand the impact of humans on the immune system of domesticated animals.
supervisors: Professor Greger Larson, Professor Adrian Smith and Dr Laurent Frantz
mix: mixed
description:
  Domestication of animals was a key process in the emergence of modern societies and it is clear that various traits were deliberately selected by early populations including temperament, resilience and production traits. However, by changing the character and environment of animals we also altered the pathogen profiles that affected these animals (and sometimes spilled over to us). Whilst the genetics of some traits has received considerable attention (e.g. behavior and production) others have been neglected, in particular the influence of domestication (and more recently intensification) on the immune system of these animals.
  This project will employ ancient DNA based approaches to identify the effects of humans on the immunogenetic profiles of domesticated animals. Understanding these historical selective events can be used to improve the welfare and resilience of modern domesticated animals and may help to reduce the impact of infectious diseases including those where domesticated animals represent a primary source of zoonotic disease in humans.

training:
  The DPhil will support training in a wide range of molecular biology (aDNA and standard methods) and bioinformatics techniques and these may also extend to testing the function of selected variants of immune genes in relevant cellular assays.

background_reading:
  -- Flammer PG, Dellicour S, Preston SG, Rieger D, Warren S, Tan CKW, Nicholson R, Přichystalová R, Bleicher N, Wahl J, Faria NR, Pybus OG, Pollard M and Smith AL. (2018) Molecular archaeoparasitology identifies cultural changes in the Medieval Hanseatic trading centre of Lübeck. Proc. R. Soc. B.285:20180991. <a href="http://doi.org/10.1098/rspb.2018.0991">http://doi.org/10.1098/rspb.2018.0991</a>
  -- Flammer PG, Ryan H, Preston SG, Warren S, Přichystalová R, Rainer Weiss, Valerie Palmowski, Sonja Boschert, Katarina Fellgiebel, Isabelle Jasch-Boley, Madita-Sophie Kairies, Ernst Rümmele, Dirk Rieger, Beate Schmid, Ben Reeves, Rebecca Nicholson, Louise Loe, Christopher Guy, Tony Waldron, Jiří Macháček, Joachim Wahl, Mark Pollard, Greger Larson and Adrian L. Smith (2020) Epidemiological insights from a large-scale investigation of intestinal helminths in Medieval Europe. PLOS Neglected Tropical Diseases 14(8): e0008600. <a href="https://doi.org/10.1371/journal.pntd.0008600">https://doi.org/10.1371/journal.pntd.0008600</a>


pi_id: leedham_simon
title: Stem cells and adaptive molecular phenotype in colorectal cancer (STAMP-CRC)
supervisors: Professor Simon Leedham
mix: can be wet or dry lab work, or mixture depending on student preference
description:
  Tumour heterogeneity plays a key role in cancer adaption and resistance to therapies, but understanding genetic heterogeneity alone cannot paint a complete picture. The forces of natural (and therapeutic) selection act upon phenotypic characteristics, and phenotype is a function of both the genotype and the microenvironment. The capacity to measure and understand relevant cancer cell phenotypic variation is key to monitoring neoplasia evolutionary trajectory. We believe that cancer stem cell molecular phenotype is an informative readout of dynamic evolutionary change within a tumour and is an important, and currently unmeasured metric that can improve prediction of tumour response to treatments, biologically inform existing therapy scheduling and drive the development of cancer cell adaption drug targets. Here we will assess demonstrable cross-species stem cell phenotypic heterogeneity in intestinal tumours, investigate the driving co-evolutionary interaction between the mutant epithelium and surrounding stromal/immune cell compartments, and assess the spatio-temporal impact of therapeutic selective pressures.
  image://data/images/leedham_simon_03.png

training:
  This would suit a student from any of the eligible pathways with an interest in understanding cancer heterogeneity and tracking tumour evolution and adaption. The project will involve mouse modelling and preclinical drug testing but requires no previous experience. Wet and dry lab training opportunities exist and can be discussed to tailor needs for students


pi_id: lindgren_cecilia
title: Accelerate the discovery of causal variant(s) associated with fat distribution and central obesity
supervisors: Prof Cecilia Lindren
mix: 100% dry lab
description:
  Background
  Our research focuses on the integration of large-scale data sets of genomic sequence variation and transcriptional regulation (genetics and genomics) with phenotypic data to advance the understanding of the molecular pathogenesis of obesity related traits. We have been playing a key role in the collaborative work that have brought forward over 7,000 loci associated with various obesity traits (body mass index, BMI, waist:hip ratio, WHR, fat% etc.) (Ref below, and GiANT – unpublished data).
  My team is dedicated to translating genetic associations into functional and pathophysiological mechanisms, and establishing how this can improve our understanding of the physiology and biology underlying obesity traits.
  This project seeks to expand our previous efforts on using large-scale genomic approaches to identify causal genetic variants influencing fat distribution. It builds on the global collaboration I lead through the GiANT consortium and the International Common Disease Alliance, aimed at identifying the genetic determinants of obesity and fat distribution.
  Description of the work
  The first strand of genetic analysis in this project will identify and fine-map common/low frequency associations to fat distribution using large scale meta-analysis as well as exome sequencing analysis from UKBB.
  In the second strand of this project, we will explore novel strategies to further accelerate the discovery of novel genetic loci for fat distribution (collaboration with the Neale lab – Broad Institute, and Kong lab – Big Data Institute).
  Lastly, we will systematically identify which molecular, cellular, and physiological processes are relevant to genetic risk for central obesity and fat distribution (collaboration with Ebener group- TDI, Finucane lab – Broad Institute and Pers lab – Copenhagen university).
  We aim to answer the following questions:
  -- What additional phenotypes can be derived out of electronic health records and images that paired with genetics can advance our understanding of the mechanisms underlying obesity, and its different facets?
  -- What are the causal variants in loci associated in genome wide association studies with these obesity traits?
  -- Which are the low-frequency and rare variants not picked up in genome wide association studies of obesity traits and how do we best detect them?
  -- Can we annotate these associated variants for fat distribution with rich regulatory information to elucidate likely effector genes (these will then be followed up functionally, both in our own budding wet lab as well as in large scale international collaborations, particularly with Claussnitzer lab – Broad Institute)?

training:
  The candidate will have ample in-house support for any necessary statistical, bioinformatics package/pipelines. The candidate will have the ability to go to relevant summer schools in the fields of (but not limited to): genetics, bioinformatics, statistical genetics and machine learning. The candidate will have the opportunity to present work in both national and internationally renowned conferences. The candidate will be exposed to a vast network of local, national and international collaborators across a range of areas and disciplines.

background_reading:
  -- [Glastonbury CA, et al. Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits. PLoS Comput Biol. 2020 Aug 14;16(8):e1008044.
  --  Censin JC, et al. Causal relationships between obesity and the leading causes of death in women and men. PLoS Genet. 2019 Oct 24;15(10):e1008405.
  -- Justice AE, et al. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution. Nat Genet. 2019 Mar;51(3):452-469.
  -- Turcot V,  et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat Genet. 2018 Jan;50(1):26-41.
  -- Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, Yengo L, Ferreira T, Marouli E, Ji Y, Yang J, Jones S, Beaumont R, Croteau-Chonka DC, Winkler TW; GIANT Consortium, Hattersley AT, Loos RJF, Hirschhorn JN, Visscher PM, Frayling TM, Yaghootkar H, Lindgren CM. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019 Jan 1;28(1):166-174.
  -- Claussnitzer, Melina, et al. "FTO obesity variant circuitry and adipocyte browning in humans." New Engl J Med 2015.373 (2015): 895-907.
  -- Locke, Adam E., et al. "Genetic studies of body mass index yield new insights for obesity biology." Nature 518.7538 (2015): 197.
  -- Shungin, Dmitry, et al. "New genetic loci link adipose and insulin biology to body fat distribution." Nature 518.7538 (2015): 187.
  -- Heid IM, et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat Genet. 2010 Nov;42(11):949-960.
  -- Loos RJ, Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet. 2008 Jun;40(6):768-75.
  --


pi_id: luo_yang
title: Identifying causal HLA variants that regulate protein abundance using data from two large Biobanks
supervisors: Yang Luo, Alexander Mentzer
mix: 100% dry lab
description:
  Our bodies rely on recognizing harmful pathogens to trigger the appropriate immune responses, a process managed by Human Leukocyte Antigens (HLA) proteins. These proteins play a crucial role in immune-related conditions, including infectious diseases, autoimmune disorders and cancer.
  While large-scale, genome-wide association studies (GWAS) have identified hundreds of HLA association with complex traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with protein quantitative trait loci (pQTLs) and identification of shared genetic architecture have been widely adopted to nominate proteins and candidate causal variants. However, the resolution of statistical fine-mapping for pQTL and GWAS is incomplete due to limited sample sizes and lack of trans-ancestry analysis.
  This project seeks to address these limitations by leveraging HLA-pQTL data from two large biobanks—the UK Biobank and the China Kadoorie Biobank. By integrating these datasets, the project aims to increase the statistical power for fine-mapping causal HLA variants that regulate protein abundance, providing deeper insights into the molecular mechanisms of immune regulation.

training:
  The successful candidate will be benefit from supervision by a team of scientists with key expertise in statistical genetics, immunology and clinical science. You will be based in the Kennedy Institute of Rheumatology, a world-leading centre in genomics and inflammatory biology. Training will be provided in data science techniques including statistical data analysis and visualisation with R, the writing of computational pipelines with Python/Nextflow, and the use of high-performance compute clusters. The student will gain expertise in analysing cutting-edge datasets including genotyping and proteomic sequencing.

background_reading:
  Please include references as desired.  Suggested format:
  -- Luo, Yang et al.  (2021). A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response. Nature genetics vol. 53,10: 1504-1516. doi:10.1038/s41588-021-00935-7
  -- Krishna, C., Chiou, J., Sakaue, S. et al. (2024). The influence of HLA genetic variation on plasma protein expression. Nat Commun 15, 6469. <a href="https://doi.org/10.1038/s41467-024-50583-8">https://doi.org/10.1038/s41467-024-50583-8</a>
  -- Said, Saredo, Pozarickij, Alfredet al. (2023). Ancestry diversity in the genetic determinants of the human plasma proteome and associated new drug targets. MedRxiv. doi: https://doi.org/10.1101/2023.11.13.23298365


pi_id: luo_yang
supervisors: Yang Luo, Jason Torres
mix: 100% dry lab
title:
  Identifying selection signals among classical HLA alleles and long-range haplotypes in admixed American populations

description:
  Immune-mediated diseases are among the strongest selective pressures driving human evolution. The major histocompatibility complex (MHC) locus that encodes human leukocyte antigen (HLA) proteins plays a vital role in our adaptive immune responses, and thus is crucial in understanding the human evolutionary process. Several non-competing natural selective regimes exist to explain how the MHC locus evolved, including balancing, and pathogen-driven positive and negative selection. However, owing to the complicated genomic structure of the MHC locus, it remains challenging to nominate specific genomic variations and haplotypes driving the observed selection signatures.
  In this project, we will leverage 10,000 deep-coverage whole-genome sequences from Latino American individuals included in the Mexico City Prospective Study to:
  - Characterize HLA alleles and long-range haplotypes in Indigenous and admixed American populations.
  - Test for deviations in local ancestry within the MHC region.
  - Identify specific classical HLA alleles and long-range haplotypes under recent selection pressure.
  This project will advance our understanding of how selection-driven alleles have shaped susceptibility to immune-mediated diseases today.

training:
  The successful candidate will be benefit from supervision by a team of scientists with key expertise in statistical genetics, population genetics and immunology. Training will be provided in data science techniques including statistical data analysis and visualisation with R, the writing of computational pipelines with Python/Nextflow, and the use of high-performance compute clusters. The student will gain expertise in analysing cutting-edge datasets including whole genome sequencingjasonjason.

background_reading:
  Please include references as desired.  Suggested format:
  -- Ziyatdinov, A., Torres, J., Alegre-Díaz, J. et al. (2023). Genotyping, sequencing and analysis of 140,000 adults from Mexico City. Nature 622, 784–793 . https://doi.org/10.1038/s41586-023-06595-3
  -- Luo, Yang et al.  (2021). A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response. Nature genetics vol. 53,10: 1504-1516. doi:10.1038/s41588-021-00935-7


pi_id: lythgoe_katrina
title: Designing evolution proof CTL-based vaccines for Hepatitis C Virus
supervisors: Dr Katrina Lythgoe, Dr Azim Ansari, and Professor Paul Klenerman
mix: 100% dry lab
description:
  Hepatitis C virus (HCV) is characterized by high mutation and evolutionary rates, often with long durations of infection between transmission events. Direct Acting Antivirals have been a game-changer in terms of treatment, but realistically only vaccines will be able to halt the spread of HCV. Rapid progress has been made in the development of CTL-based vaccines, with Oxford playing a leading role. However, the evolutionary potential of the virus makes the development of vaccines that will remain effective in the long-term a challenge.
  Our previous work shows HCV infection is characterised by different subpopulations which are only intermittently observed in plasma, and that different subpopulations have different rates of evolution. Consequently, virus sequenced from a single time point is unlikely to be representative of the viral diversity present in that individual, including the presence of CTL-escape mutations. This has major implications for how CTL-based vaccine escape mutations might emerge and spread.
  We have developed a method to generate long-read within-host whole-genome sequence data in order to generate high-resolution next generation sequencing data from a large number individuals sampled over many years. Using this data you will characterise the spread, emergence and reversion of CTL-escape mutations among individuals, building up a picture of the tempo of evolution. This will take into account the within-host population structure of the virus and the between-host HLA structure of the human population. You will use this information to inform the optimal viral epitopes to target as part of CTL-based vaccine design, with a view to making these vaccine evolution proof.

training:
  --       During this DPhil you will learn how to analyse next-generation viral whole-genome sequencing (WGS) data
  --       Develop and use phylogenic and population genetic models to determine the extent and tempo of CTL-escape and reversion
  --       Develop viral transmission models to determine the effect of within-host and between-host population structure on the emergence and spread of vaccine-escape mutations.
  --       You will be given the opportunity to attend a specialised course on viral phylogenetics, and to audit the Health Data Science CDT lectures, particularly those on the dynamics and evolution of infectious disease.

background_reading:
  --      Zhao, L. et al. Lineage-aware evolutionary analysis of hepatitis C virus within-host dynamics. MedRxiv 2024 (will be preprinted soon, please ask if you would like a copy of the draft)
  Pybus, O.G. & Rambaut, A. Evolutionary Analysis of the Dynamics of Viral Infectious Disease. Nature Reviews Genetics 2009. Doi:10.1038/nrg2583
  --       Raghwani J, Wu C, Ho CKY, Jong M De, Molenkamp R, Schinkel J, et al. High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection. 2019; 1–8. doi:10.1093/infdis/jiy747
  --       Rose R, Rodriguez C, Dollar JJ, Lamers SL, Massaccesi G, Osburn W, et al. Inconsistent temporal patterns of genetic variation of HCV among high-risk subjects may impact inference of transmission networks. Infect Genet Evol. Elsevier; 2019;71: 1–6. doi:10.1016/j.meegid.2019.02.025


pi_id: lythgoe_katrina
title: Towards a cure for Hepatitis B Virus: Uncovering the role of integrated virus
supervisors: Dr Katrina Lythgoe and Professor Jane A. McKeating
mix: 100% dry lab
description:
  Hepatitis B virus (HBV) infection is a major global health problem with over 240 million infected individuals at risk of developing progressive liver disease and hepatocellular carcinoma. HBV is an enveloped DNA virus that establishes its genome as an episomal, covalently closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. However, the virus can also integrate into the host genome to form integrated DNA (iDNA) and which can remain transcriptionally active.
  Currently available standard-of-care treatments for chronic hepatitis B (CHB) include nucleos(t)ide analogues (NA) that suppress HBV replication but do not target the cccDNA and hence rarely cure infection. Moreover, the presence of iDNA likely has profound consequences for the progression of disease and our interpretation of markers indicating the state of the disease in an individual. A better understanding of the role of iDNA is vital if we are to develop an effective cure.
  We have developed a method of targeted long-read sequencing enabling the sequencing of the viral transcriptome, and crucially for the first time enables researchers to differentiate between cccDNA and iDNA derived transcripts. In this project you will develop new methods to analyse this data, and specifically to uncover the dynamics of circulating and integrated virus within individuals. As a starting point, you will draw on the phylogenetic methods that have recently been developed to analyse the HIV viral reservoir.

training:
  -- Development and analyse of evolutionary models of viral infection
  --  You will be given the opportunity to attend a specialised course on modelling of infectious disease, and to audit the Health Data Science CDT lectures, particularly those on the dynamics and evolution of infectious disease.
  -- Experience working in a collaborative team environment and presenting data at internal lab meetings, journal clubs and seminars.
  -- Contribute data towards publication in peer-peer reviewed journals

background_reading:
  --      Pybus, O.G. & Rambaut, A. Evolutionary Analysis of the Dynamics of Viral Infectious Disease. Nature Reviews Genetics 2009. Doi:10.1038/nrg2583
  --      Lythgoe et al. Estimating hepatitis B virus cccDNA persistence in chronic infection. Virus Evolution 2021. Doi:10.1093/ve/veaa063
  Jones et al. Phylogenetic approach to recover integration dates of latent HIV sequences within-host. 2018. https://www.pnas.org/doi/full/10.1073/pnas.1802028115
  --      Testoni et al. Serum hepatitis B core-related antigen (HBcrAg) correlates with covalently closed circular DNA transcriptional activity in chronic hepatitis B patients. J Hepatol 2019. Doi:10.1016/j.hep.2018.11.030
  --      Bimodal distribution and set point HBV DNA viral loads in chronic infection: retrospective analysis of cohorts from the UK and South Africa. Wellcome Open Research 2020. Doi:10.12688/wellcomeopenres.15941.2


pi_id: lythgoe_katrina
title: Linking the within- and between-host evolution of SARS-CoV-2
supervisors: Dr Katrina Lythgoe and Prof. David Clifton
mix: 100% dry lab
description:
  Over the last few years a huge amount SARS-CoV-2 genomic data has been collected, enabling the global community to track the emergence and spread of new variants at an unprecedented scale. For new variants to spread locally and globally, they must first emerge within an infected individual, with the leading hypothesis that the major variants emerged in long term chronically infected individuals. The hope is that through an understanding of the evolutionary process within infected individuals, and at the point of transmission, we can better predict key features of new major variants in the short to medium term, which would be helpful for vaccine design, and potentially prevent new variants from emerging in the first place through effective identification and treatment of individuals with persistent infections.
  Overarching aim:
  1) Characterise SARS-CoV-2 mutations that are beneficial and/or deleterious and the within- and between-host levels.
  2) Identify mutations that facilitate or are detrimental to transmission
  3) Provide a framework for understanding the evolution of SARS-CoV-2 and other emerging viruses taking into account within- and between-host evolution.
  We are part of the Office of National Statistics Covid-19 infection survey, and this project will give you access to >125,000 sequenced samples plus metadata, including household transmission data.
  During the rotation project you will:
  1.     Perform a short literature review.
  2.     Undertake preliminary analyses to determine variants that facilitate and/or are detrimental to transmission using household transmission data.
  3.     Write up.
  This could form the foundation of a DPhil, which could help inform, for example, future vaccine development and roll-out.

training:
  -- During this DPhil you will learn how to analyse next-generation viral whole-genome sequencing (WGS) data
  -- Develop advanced statistical methods, including machine learning, to analyse complex data
  -- You will be given the opportunity to attend a specialised course on viral phylogenetics, and to audit the Health Data Science CDT lectures, particularly those on the dynamics and evolution of infectious disease.

background_reading:
  -- Lythgoe & Hall et al., Science 2021, “SARS-CoV-2 within-host diversity and transmission”
  -- Ghafari et al. 2024 https://www.nature.com/articles/s41586-024-07029-4
  -- Ghafari et al. 2024 https://www.medrxiv.org/content/10.1101/2024.06.21.24309297v1
  -- Antia et al., Nature 2003, “The role of evolution in the emergence of infectious diseases”


pi_id: mentzer_alexander
title: The functional consequences of human genetic variation on response to infectious disease
supervisors: Dr Alexander Mentzer, Professor Julian Knight, Professor Adrian Hill
mix: can be varied but may be 20-50% wet lab, 50-80% dry lab
description:
  In close collaboration with Professor Adrian Hill at the Jenner Institute and other collaborators in the Centre for Human Genetics, UK Biobank and other institutes around the world we have generated multiple independent datasets looking at how human genetic diversity affects response to natural infection and vaccination. We have found that variation at multiple loci across the human genome contribute to immune responses against infectious antigens and, in some cases, protection against disease. An overall goal of this project is to combine these datasets to understand how much of this variation is infection- or population-specific, and then to use downstream approaches to understand the impacts of these changes to a molecular level. Currently, the genomic region of particular interest includes the major histocompatibility complex (MHC) that influences susceptibility and outcomes with a huge range of diseases including viral infections (such as herpes, hepatitis, HIV and coronavirus) and bacterial diseases that may cause sepsis. As part of this project there is the opportunity to contribute, and potentially lead, a multi-centre assessment of the MHC locus in UK Biobank, using cutting-edge technologies to understand with power, and in depth the functional mechanisms underlying MHC associations with disease.
  The Mentzer lab ensures that projects are tailored to the student’s skillsets and interests. Thus the details below are generic but encompassing. Any sub-project under this project proposal would be designed in 2 stages; the first being a meta-analysis of relevant datasets central to the core objectives of the Mentzer group, and the second phase being an opportunity to follow up these findings using a combination of approaches dependent on the earlier findings. The first stage would be well suited to a laboratory rotation giving an excellent introduction to computational or dry lab skills whereas both could form the basis of a 3-year doctoral project giving the opportunity for a combined dry and wet-lab experience. At the time of writing, specific sub-projects include fine-mapping and molecular characterisation of MHC association signals with multiple infections, and metagenomic approaches for pathogen detection in whole blood RNA. Our group has a strong emphasis on tailoring the project to the individual and supporting the individual to achieve outstanding scientific output.

training:
  This project is designed to give an excellent introduction to computer science with rapid availability of datasets and tailored pipelines for data integration and analysis under close supervision that would provide necessary skills for interpretation and hypothesis testing. There is flexibility in the project and connections with multiple labs within the University to enable a diverse and complete follow-up of findings tailored to the interests of the candidate that can provide exposure and comprehensive training in molecular biology, immunology and functional genomics using experimental analysis or direct wet-lab exposure to methods such as flow cytometry, antigen peptide processing, binding and presentation, gene expression analysis, ELISA and other immunoassays. There will be regular opportunities to present work to laboratory colleagues and internationally at conferences and meetings.

background_reading:
  -- Mentzer AJ, Dilthey AT et al. 2024; High-resolution African HLA resource uncovers HLA-DRB1 expression effects underlying vaccine response; Nature Medicine, <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/pmc11108778/">http://www.ncbi.nlm.nih.gov/pmc/articles/pmc11108778/</a>
  -- Mentzer AJ*, O’Connor D* et al. 2023; Human leukocyte antigen alleles associate with COVID-19 vaccine immunogenicity and risk of breakthrough infection; Nature Medicine; <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/pmc9873562/">http://www.ncbi.nlm.nih.gov/pmc/articles/pmc9873562/</a>
  -- Chong A et al, Mentzer AJ, 2024; A common NFKB1 variant detected through antibody analysis in UK Biobank predicts risk of infection and allergy; American J. Hum. Gen, <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/pmc10870136/">http://www.ncbi.nlm.nih.gov/pmc/articles/pmc10870136/</a>
  -- Butler-Laporte G et al, Mentzer AJ, 2023; Targeting hepatitis B vaccine escape using immunogenetics in Bangladeshi infants. MedRxiv, <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/pmc10327284/">http://www.ncbi.nlm.nih.gov/pmc/articles/pmc10327284/</a>
  -- Mentzer AJ*, Brenner N* et al 2022; A scalable 20-agent Multiplex Serology platform applied to UK Biobank to define host-pathogen-environment relationships and disease susceptibility; Nature Communications; <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983701/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983701/</a>
  -- COMBAT Consortium 2022; A blood atlas of COVID-19 defines hallmarks of disease severity and specificity; Cell <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776501/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776501/</a>
  -- Antibody evasion by the P. 1 strain of SARS-CoV-2; Dejnirattisai W*, Zhou D*, Supasa P*, Liu C*, Mentzer AJ* et al 2021; Cell. 184 (11) 2939
  -- Broad and strong memory CD4+ and CD8+ T cells induced by SARS-CoV-2 in UK convalescent COVID-19 patients 2020; Peng Y*, Mentzer AJ*, Liu G*, Yao Z*, Dejnirattisai W* et al; Nat. Imm 21, 1336 (2020)
  -- Mentzer AJ*, Muruiki JJ*, Band G, et al. 2019; The ferroportin Q248H mutation protects from anemia, but not malaria or bacteremia; Science Advances; 4;5(9):eaaw010
  -- Dilthey AT, Mentzer AJ, Carapito R et al. 2018; HLA*PRG:LA - HLA typing from linearly projected graph alignments; Bioinformatics; pii: btz235
  -- Brenner N, Mentzer AJ, Butt J, Braband KL, Michel A, Jeffery K, Klenerman P, Gärtner B, Schnitzler P, Hill A, Taylor G, Demontis MA, Guy E, Hadfield SJ, Almond R, Allen N, Pawlita M, Waterboer T 2019; Validation of Multiplex Serology for human hepatitis viruses B and C, human T-lymphotropic virus 1 and Toxoplasma gondii; PLoS One:14(1):e0210407
  -- Brenner N, Mentzer AJ, Butt J, Michel A, Prager K, Brozy J, Weißbrich B, Aiello AE, Meier HCS, Breuer J, Almond R, Allen N, Pawlita M, Waterboer T 2018; Validation of Multiplex Serology detecting human herpesviruses 1-5; PLoS One: 13(12):e0209379


pi_id: milne_thomas
title: How do transcription factors create new enhancers?
supervisors: Prof Thomas Milne
mix: 50% wet lab, 50% dry lab
description:
  Enhancers are key regulatory elements that control gene expression and function by acting as docking sites for transcription factors. Most work on enhancers (including our own) has concentrated on methods of removing specific factors to determine their effect on endogenous enhancer function. This is essentially a loss of function approach and provides useful information on what factors are necessary for enhancer function. However, to really understand what each factor contributes to enhancer behaviour, gain of function approaches are required to test for sufficiency of a factor. To accomplish this, we used a TetO array inserted into a gene desert region in mouse ES cells. By fusing a protein of interest to the TetR DNA binding domain, it is possible to anchor a protein or domain of interest at this gene desert region and determine whether it can recruit specific activities de novo. Our preliminary findings demonstrate that anchoring the MYB transactivation (TA) domain is sufficient to initiate transcription from regions more than 50kb distal to the TetO locus, and this is associated with increases in H3K27ac and increased DNA interactions as measure by chromosome conformation capture techniques. Conversely, we have found that other major transcription factors such as RUNX1 lack this intrinsic ability to create enhancers de novo. This suggests that transcription factors have varying abilities to impact enhancer function.
  The goal of this project will be to screen key transcription factors from haematopoietic stem cells for their ability to create novel enhancers de novo, in order to better understand the relationship between transcription factor function and enhancer activity. This project will involve interactions with other labs in the WIMM (such as the Hughes, Davies and Wilkinson labs) and will use a broad range of cutting-edge technologies.

training:
  This project will use a broad range of cutting-edge technologies including state of the art techniques for the analysis of gene regulation on a genome-wide level (single cell ATAC-seq, ChIP-seq, Capture C, nascent RNA-seq, Micro Capture-C), and genome editing (e.g. CRISPR/CAS9) approaches. Training will be specifically provided in these molecular biology techniques as well as in bioinformatics, including machine learning approaches where appropriate.

background_reading:
  -- Harman, J.R. etal  (2021). A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes. Genome Res. DOI: <a href="https://doi.org/10.1101/gr.268490.120">10.1101/gr.268490.120</a>
  -- Crump, N.T. et al (2021). Chromatin accessibility governs the differential response of cancer and T cells to arginine starvation. Cell Rep. 35: 109101. DOI: <a href="https://doi.org/10.1016/j.celrep.2021.109101">10.1016/j.celrep.2021.109101</a>
  -- Crump, N.T. etal (2021). BET inhibition disrupts transcription but retains enhancer-promoter contact. Nat Commun. 12: 223. DOI: <a href="https://doi.org/10.1038/s41467-020-20400-z">10.1038/s41467-020-20400-z</a>


pi_id: milosevic_ira
supervisors: Ira Milosevic, Thibaud MartialIra Milosevic, Meenakshi Bhardwaj
mix: about 75% wet lab, 25% dry lababout 75% wet lab, 25% dry lab
title:
  Endocytosis deficiency as a trigger of cellular senescenceAmisyn at the crossing of modulated neurotransmission and brain pathologies

description:
  Several endocytic proteins, including endophilin-A, amphiphysin, dynamin-1, synaptojanin-1, auxilin and intersectin-1, have been linked to neurodegeneration. One family of abovementioned proteins, endophilin A1, A2, and A3 (henceforth endophilin 1, 2, and 3) seems central in this role. Endophilins belong to a protein superfamily containing BAR-domains, which are known to be responsible for sensing and generating membrane curvature, and for recruiting the relevant endocytic factors from the cytosol to the membrane. Our previous work on endophilin-A clarified its role in clathrin-mediated endocytosis, and established that endophilin recruits the phospholipid phosphatase synaptojanin-1 to the bud necks prior to fission by the GTPase dynamin, which also interacts with endophilin.
  Senescence or biological aging is the gradual deterioration of functional characteristics in living cells and organisms. Cellular senescence is a phenomenon characterized by the permanent cell growth arrest in normal and altered physiological processes. Many factors stimulate the appearance of this phenomenon, such as aging, tissue repair, tumor treatments, etc. Senescent cells remain viable, but show metabolic alterations and undergo dramatic changes in gene expression developing a complex senescence-associated secretory phenotype that contributes to senescence spreading to other cells and tissues. Cellular senescence can also compromise tissue repair and regeneration, thereby contributing toward aging.
  Here, we will test if endocytosis deficiency acts as a trigger of cellular senescence by focusing on the functions of two endocytic protein, the key endocytic adaptor endophilin-A that belongs to the family of BAR-domain proteins and synaptojanin-1, a lipid phosphatase. You will be joining our efforts to understand how lack of endophilin or synaptojanin-1 triggers cellular senescence, and consequently neurodegeneration and shorter lifespan. We will capitalize on the cells with partial or complete lack of endophilin or synaptojanin-1 to explore the link between proteins and senescence. We use a multi-disciplinary approach that combines genomics, cell biology, physiology and live imaging.
  Keywords: ageing, geroscience, neuroscience, neurodegenerative diseases, cell biology, live imagingThe human brain is astonishing: it is the source of our thoughts, actions, memories, perceptions and emotions. It confers on us the abilities that make us human, while simultaneously making each of us unique. Through deepened knowledge and understanding of how human brain works, we will comprehend ourselves better and treat brain diseases more incisively. Over recent years, neuroscience has advanced to the level that we can envision spanning molecules, cells and neuronal circuits in action. In particular, there is an emerging view that subtle aspects of presynaptic dysfunction are implicated in an increasing number of brain disorders.
  We are particularly interested in exocytosis, a process of vital importance for neuronal cells that is controlled by a set of both positive and negative regulators. While promotors of exocytosis are well studied, negative regulators are poorly understood. We discovered that a small SNARE protein amisyn (STXBP6) acts as a vertebrate-specific competitor of synaptobrevin-2, a key player in exocytosis. Amisyn contains an N-terminal pleckstrin homology domain that mediates its transient association with the plasma membrane by binding to phospholipid PI(4,5)P2. Both the pleckstrin homology and SNARE domains are needed to inhibit exocytosis. Of note, amisyn is poorly studied despite several studies have emphasized its importance for exocytosis and reported the occurrence of amisyn mutations in autism-spectrum disorders and diabetes.
  This project aims to analyse transcriptome and proteome of transgenic mouse model without amisyn already generated for these studies (the model is not yet unpublished). The candidate will then use transgenic mice tissue, as well as human and rodent cell lines, to verify own findings. If time allows, the studies will extend to amisyn patient mutants, and how lack or impaired function of amisyn modulates exocytosis.

training:
  Brain dissection. Transcriptome and proteome analyses of amisyn mutant tissue. Western blotting. Culturing human and/or rodent clonal cells. Immunocytochemistry. Live cell imaging using custom-made fast spinning-disk confocal microscope.

background_reading:
  1. Revisiting the Role of Clathrin-Mediated Endoytosis in Synaptic Vesicle Recycling.
  Milosevic I. Front Cell Neurosci. 2018 Feb 6;12:27. doi: 10.3389/fncel.2018.00027. eCollection 2018. PMID: 29467622
  2. Endophilin-A coordinates priming and fusion of neurosecretory vesicles via intersectin.
  Gowrisankaran S, Houy S, Del Castillo JGP, Steubler V, Gelker M, Kroll J, Pinheiro PS, Schwitters D, Halbsgut N, Pechstein A, van Weering JRT, Maritzen T, Haucke V, Raimundo N, Sørensen JB, Milosevic I.
  Nat Commun. 2020 Mar 9;11(1):1266. doi: 10.1038/s41467-020-14993-8. PMID: 32152276
  3. PI3K/AKT/MTOR and ERK1/2-MAPK signaling pathways are involved in autophagy stimulation induced by caloric restriction or caloric restriction mimetics in cortical neurons.
  Ferreira-Marques M, Carvalho A, Cavadas C, Aveleira CA.
  Aging (Albany NY). 2021 Mar 14;13(6):7872-7882. doi: 10.18632/aging.202805. Epub 2021 Mar 14.
  PMID: 33714946
  4. Endophilin-A regulates presynaptic Ca2+ influx and synaptic vesicle recycling in auditory hair cells.
  Kroll J, Jaime Tobón LM, Vogl C, Neef J, Kondratiuk I, König M, Strenzke N, Wichmann C, Milosevic I, Moser T.EMBO J. 2019 Mar 1;38(5):e100116. doi: 10.15252/embj.2018100116. Epub 2019 Feb 7. PMID: 30733243
  5. Endophilin-A Deficiency Induces the Foxo3a-Fbxo32 Network in the Brain and Causes Dysregulation of Autophagy and the Ubiquitin-Proteasome System.
  Murdoch JD, Rostosky CM, Gowrisankaran S, Arora AS, Soukup SF, Vidal R, Capece V, Freytag S, Fischer A, Verstreken P, Bonn S, Raimundo N, Milosevic I.Cell Rep. 2016 Oct 18;17(4):1071-1086. doi: 10.1016/j.celrep.2016.09.058. Epub 2016 Oct 6. PMID: 27720640
  OPTIONAL: Recruitment of endophilin to clathrin-coated pit necks is required for efficient vesicle uncoating after fission.
  Milosevic I, Giovedi S, Lou X, Raimondi A, Collesi C, Shen H, Paradise S, O'Toole E, Ferguson S, Cremona O, De Camilli P.Neuron. 2011 Nov 17;72(4):587-601. doi: 10.1016/j.neuron.2011.08.029. PMID: 22099461Kondratiuk I, Jakhanwal S, Jin J, Narayanan U, Kroppen B, Krisko A, Meinecke M, Asheri U, Jahn R, D. Fasshauer, Milosevic I@ (2020) PI(4,5)P2-dependent regulation of exocytosis by amisyn, a vertebrate-specific competitor of synaptobrevin 2. PNAS USA, 117(24):13468-79


pi_id: palamara_pier
title: Large-scale analysis of complex traits
supervisors: Prof Pier Palamara
mix: 0% wet lab, 100% dry lab
description:
  Human genomes are connected through complex networks of genealogical relationships, which are shaped by demographic and evolutionary history. We have developed several statistical and computational approaches to infer details of these genealogical connections [1-5]. We have used these genealogical structures to study natural selection [1,2,5,6] and fine-scale population structure [2], and to develop strategies that use inferred genome-wide genealogies to analyze heritable traits such as estimating trait heritability, performing polygenic prediction, and detecting associations [3,4]. These strategies use an inferred graph, called the ancestral recombination graph (ARG), that compactly represents the evolutionary history of a set of analyzed genomes. An inferred ARG can be used to detect the presence of genomic variants that are missing in reference imputation panels, which are not available for all populations. This framework can be extended in several directions, with the goal of improving complex trait heritability estimation, polygenic prediction, or association. This rotation, and the subsequent DPhil project, will focus on developing these extensions.
  Several additional projects focused on the development of statistical and machine learning methods for large-scale analysis of complex traits are available (see e.g., [7]). Please reach out if interested.

training:
  Depending on the specific direction of the project, the student will develop expertise in statistical genetics, population genetics, machine learning, programming in high-level (e.g. Python) and compiled (e.g. C++) languages, and working with very large genomic data sets.

background_reading:
  [1] Palamara et al. High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability. Nature Genetics, 2018.
  [2] Nait Saada et al. Identity-by-descent detection across 487,409 British samples reveals fine scale population structure and ultra-rare variant associations. Nature Communications, 2020.
  [3] Zhang et al. Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits. Nature Genetics, 2023.
  [4] Harris, K. Using enormous genealogies to map causal variants in space and time. Nature Genetics, 2023.
  [5] Nait Saada et al. Inference of coalescence times and variant ages using convolutional neural networks. Molecular Biology and Evolution, 2023.
  [6] Yasumizu et al. Genome-Wide Natural Selection Signatures Are Linked to Genetic Risk of Modern Phenotypes in the Japanese Population. Molecular Biology and Evolution, 2020.
  [7] H. Loya, G. et al. A scalable variational inference approach for increased mixed-model association power. Nature Genetics, in press.


pi_id: pinto-fernandez_adan
title: DeISGylating enzymes as therapeutic targets in immuno-oncology
supervisors: Dr. Adán Pinto-Fernández; Prof. Benedikt Kessler
mix: 80% wet lab, 20% dry lab
description:
  [The proposed research involves the study of a class of druggable enzymes called deubiquitylating enzymes (DUBs) in the innate immune response and cancer inflammation using advanced proteomics, ubiquitomics, lipidomics, bioinformatics, and immunology techniques as main tools.
  For instance, and following this approach, we have recently discovered that cancer cells lacking the DUB USP18, a negative regulator of the interferon pathway, are more antigenic and radiosensitive. At a molecular level, USP18-deficient cells accumulate innate immune ligands such as dsRNA, enhance the antigen presentation machinery, and hence they can activate more efficiently cytotoxic T cells, resulting in enhanced T cell killing and immunotherapy responses.
  Thanks to this studentship, we will study the translational potential of additional deISGylating enzymes acting as regulators of the innate immune response with similar effects to USP18.

training:
  We are experts in the study of the ubiquitin system in disease-relevant models using advanced ubiquitomics (GG-petidomics), activity-based protein profiling (ABPP), proteomics, lipidomics, chemical biology, cellular biology, and immunology techniques. These methodologies and matching data analysis approaches can be applied and learnt in our laboratory. Importantly, as part of the COI-NDM environment, we have access to innovative technology assuring the highest available standards in terms of data quality.
  Finally, our laboratory has been always extremely interested in the translational aspect of our research and consequently, we have been involved in several collaborations with industry partners (including Pfizer, Incyte, Xcellomics, ONO, FORMA therapeutics, and others). This provides an excellent opportunity to learn the complementary research dynamics happening in pharmaceutical companies].

background_reading:
  1) Pinto-Fernandez A, Salio M, Partridge T, Chen J, Vere G, Greenwood H, Olie CS, Damianou A, Scott HC, Pegg HJ, Chiarenza A, Díaz-Saez L, Smith P, Gonzalez-Lopez C, Patel B, Anderton E, Jones N, Hammonds TR, Huber K, Muschel R, Borrow P, Cerundolo V, Kessler BM. Deletion of the deISGylating enzyme USP18 enhances tumour cell antigenicity and radiosensitivity. Br J Cancer. 2021 Feb;124(4):817-830. doi: 10.1038/s41416-020-01167-y. Epub 2020 Nov 20. PMID: 33214684; PMCID: PMC7884788.
  2) Turnbull AP, Ioannidis S, Krajewski WW, Pinto-Fernandez A, Heride C, Martin ACL, Tonkin LM, Townsend EC, Buker SM, Lancia DR, Caravella JA, Toms AV, Charlton TM, Lahdenranta J, Wilker E, Follows BC, Evans NJ, Stead L, Alli C, Zarayskiy VV, Talbot AC, Buckmelter AJ, Wang M, McKinnon CL, Saab F, McGouran JF, Century H, Gersch M, Pittman MS, Marshall CG, Raynham TM, Simcox M, Stewart LMD, McLoughlin SB, Escobedo JA, Bair KW, Dinsmore CJ, Hammonds TR, Kim S, Urbé S, Clague MJ, Kessler BM, Komander D. Molecular basis of USP7 inhibition by selective small-molecule inhibitors. Nature. 2017 Oct 26;550(7677):481-486. doi: 10.1038/nature24451. Epub 2017 Oct 18. PMID: 29045389; PMCID: PMC6029662.
  3) Pinto-Fernandez A, Kessler BM. DUBbing Cancer: Deubiquitylating Enzymes Involved in Epigenetics, DNA Damage and the Cell Cycle As Therapeutic Targets. Front Genet. 2016 Jul 28;7:133. doi: 10.3389/fgene.2016.00133. PMID: 27516771; PMCID: PMC4963401.
  4) Vere G, Kealy R, Kessler BM, Pinto-Fernandez A. Ubiquitomics: An Overview and Future. Biomolecules. 2020 Oct 17;10(10):1453. doi: 10.3390/biom10101453. PMID: 33080838; PMCID: PMC7603029.
  5) Jones HBL, Heilig R, Davis S, Fischer R, Kessler BM, Pinto-Fernández A. ABPP-HT*-Deep Meets Fast for Activity-Based Profiling of Deubiquitylating Enzymes Using Advanced DIA Mass Spectrometry Methods. Int J Mol Sci. 2022 Mar 17;23(6):3263. doi: 10.3390/ijms23063263. PMID: 35328685; PMCID: PMC8955990. https://doi.org/10.3390/biom10101453.


pi_id: sanders_stephan
supervisors: Dr. Stephan Sanders
mix: 100% dry lab (collaboration with neighbouring labs to develop therapies)
title:
  Therapeutic genomics: Integrating whole-genome sequencing and functional genomics data to identify loci for genome-targeted therapies in rare disorders

description:
  The past decade has seen tremendous progress in identifying genes underlying rare single-gene disorders, including hundreds of genes that lead to neurodevelopmental delay (NDD, e.g., seizures, cognitive impairment, autism spectrum disorder). The most common mechanism of NDD is the disruption of one of the two copies of a gene (haploinsufficiency), often by germline de novo mutations. For haploinsufficient disorders, upregulating the unaffected copy could act as a therapy, for example, with an antisense oligonucleotide (ASO). By using whole-genome sequencing data of thousands of cases and large-scale bulk and single-cell functional genomic data (RNA, ATAC, ChIP, reporter assays), we aim to identify regulatory processes of genes that can be modified to act as a therapy in specific patients.

training:
  Analysis of whole-genome sequence data to identify and interpret rare genetic variants; analysis of single-cell RNA-seq and ATAC-seq data from the human brain; analysis of RNA-seq data to identify patterns of splicing; genotype-phenotype analysis of rare genetic variants; AI-based methods for identifying noncoding regulatory sequences; participation in a large-scale international collaboration that includes Boston (Harvard), Berkeley (UC Berkeley), and San Francisco (UCSF).

background_reading:
  • Fu et al. 2022. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nature Genetics. PMID: 35982160. https://pubmed.ncbi.nlm.nih.gov/35982160/
  • Jaganathan et al. 2019. Predicting Splicing from Primary Sequence with Deep Learning. Cell. PMID: 30661751. https://pubmed.ncbi.nlm.nih.gov/30661751/
  • An et al. 2018. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science. PMID: 30545852. https://pubmed.ncbi.nlm.nih.gov/30545852/
  • Sanders et al. 2018. Progress in Understanding and Treating SCN2A-Mediated Disorders. Trends in Neuroscience. PMID: 29691040. https://pubmed.ncbi.nlm.nih.gov/29691040/


pi_id: sansom_stephen
title: Projects in Infectious and autoimmune-related disease
supervisors: Stephen Sansom, Paul Bowness
mix: 20% wet lab, 80% dry lab
description:
  Our research involves the generation and analysis of bulk, multi-modal single-cell and spatial genomics datasets from human patients. For data generation, the group has the 10x Chromium and BD rhapsody single cell and the nanoString GeoMx spatial transcriptomics platforms. We are expecting delivery of the higher-resolution nanoString CosMx spatial transcriptomics platform later this year.
  Currently, we have opportunities for computational projects in two areas:
  1) Network analysis of cellular pathotypes in inflammatory bowel disease. In our initial studies we applied weighted gene co-expression (WGCNA) to bulk RNA-seq profiles from ~100 patients. In this project, you will use more advanced kernel clustering, modularity optimisation and random walk-based algorithms to perform network module identification using a larger RNA-seq dataset from ~1000 patients (IBD Plexus cohorts). The initial goal of the project will be to compare the ability of the algorithms to recover known heterogeneity. The best approach(es) will then be taken forward for novel pathotype discovery. The project will also involve the analysis of single-cell datasets for cell type deconvolution. Discovered pathotypes will be further investigated using spatial transcriptomics and experimental approaches in mouse models. The project will be performed in close collaboration with the group of Professor Fiona Powrie and the wider MRC project team.
  2) Investigating the role of HLA-B*27 in ankylosing spondylitis. Ankylosing spondylitis is a common form of arthritis for which the cellular causes remain mysterious despite a remarkably strong genetic association with HLA-B*27 (odds ratio=131). Projects in this area will use single-cell and spatial genomics data from human patients to evaluate three competing biological hypotheses of how HLA-B*27 might act to initiate disease (the arthritogenic peptide hypothesis, the ER stress hypothesis and the free-heavy chain hypothesis). This work will involve the modelling of cell-cell interactions and the integration of spatial and genetic data. It will be co-supervised by Prof Paul Bowness.

training:
  You will learn how to use network approaches to model large transcriptomics dataset and to analyse and interpret single-cell genomics data. This will involve writing bioinformatics pipelines in Python, performing statistical analysis and data visualisation in R and the use of high-performance compute clusters. You will have the opportunity to work closely with wet-lab and clinical colleagues.

background_reading:
  -- IL-1-driven stromal-neutrophil interaction in deep ulcers defines a pathotype of therapy non-responsive inflammatory bowel disease. Friedrich M. et al. Nature Medicine. 2021
  -- Deconvolution of monocyte responses in inflammatory bowel disease reveals an IL-1 cytokine network that regulates IL-23 in genetic and acquired IL-10 resistance. Aschenbrenner D et al. Gut, 2020.
  -- IRF5 guides monocytes toward an inflammatory CD11c+ macrophage phenotype and promotes intestinal inflammation. Alastair L Corbin, et. al. Science Immunology, 2020.
  -- Distinct fibroblast subsets drive inflammation and damage in arthritis. Adam P. Croft, et. al. Nature, 2019
  -- Progress in our understanding of the pathogenesis of ankylosing spondylitis. Simone D, Al Mossawi and Bowness P. Rheumatology (Oxford), 2018


pi_id: sarkies_peter
title: How do histone post-translational modifications affect cellular metabolism in cancer?
supervisors: Peter Sarkies
mix: 80% dry lab, 20% wet lab
description:
  Histone post-translational modifications are ubiquitous in eukaryotic genomes.  Different histone modifications show strong associations with specific transcriptional states, and in some cases changes in histone modifications can bring about changes in transcription.  However, modifications of histones are also enzymatic processes that consume core metabolites, therefore have the potential to affect cellular metabolic regulation.  The effects of the enzymatic processes of histone modification on metabolism are still largely unknown.  In previous work, we discovered using computational analysis across cancer cells and healthy tissues that histone methylation on several different residues on the histone tail, affects S-adenosyl-methionine (SAM) metabolism through the use of SAM as a cofactor for the methylation reaction.  Importantly, changes in histone methylation levels affect SAM metabolism without affecting transcription, suggesting that this is an important function of histone methylation beyond gene regulation (Perez and Sarkies, PloS Biology 2023, see reference list).  Remarkably, we also showed that the tumour suppressor protein Rb is responsible for controlling total histone methylation levels, affecting many types of histone methylation simultaneously.  In this project we aim to follow up these results in two directions.  First, using analysis of data across cancers, and particularly focussing on single cell sequencing data, we will investigate further links between Rb, histone methylation, and SAM metabolism to explore the functional consequences of this regulatory axis and how this might contribute to the cancer predisposition caused by loss of the Rb protein.  Second, we will extend our computational approach to further histone modifications, in particular histone acetylation, to identify further links between histone modifications and metabolism.  Finally, we will test whether perturbing histone modifications experimentally can lead to changes in metabolism directly in human cells.

training:
  The project will be predominantly computational, using correlation analysis to identify links between expression of histone modifying enzymes, the genome-wide levels of the modifications themselves, metabolite levels, and metabolic pathway activity.  We will use machine learning to identify the strongest links between metabolism and histone modifications.  Moreover, we will test whether the associations apply within individual cells and how cell type affects the relationships using analysis of single cell RNA sequencing data from a variety of different cancers.  This will provide training in data science, machine learning/AI methods for computational biology and sophisticated statistical methods to identify causative relationships from the data.  Wet lab experiments may be performed towards the end of the project and will involve cell culture and CRISPR-cas9 genome editing of human cells, however, these will be optional depending on the interest of the student.

background_reading:
  -- Perez, M and Sarkies, P Histone methyltransferase activity affects metabolism independently of transcriptional regulation.  2023, PLos Biology, 2023  <a href="https://doi.org/10.1371/journal.pbio.3002354">https://doi.org/10.1371/journal.pbio.3002354</a>
  -- Karamian et al., Metabolic sinkholes: Histones as methyl repositories. 2023, PLoS Biology <a href="https://doi.org/10.1371/journal.pbio.3002371)">https://doi.org/10.1371/journal.pbio.3002371)</a> Commentary on our publication.
  -- Findlay, L What is Cancer Metabolism? 2023 Cell, 186: 1670-1688 <a href="https://doi.org/10.1016/j.cell.2023.01.038">https://doi.org/10.1016/j.cell.2023.01.038</a>
  -- Morgan, M and Shilatifard, A Reevalulating the role of histone modifying enzymes and their associated chromatin modifications in transcription (2020) Nature Genetics, 52, 1271-1281. https://doi.org/10.1038/s41588-020-00736-4


pi_id: smith_adrian
title: Molecular archaeoparasitology approaches to interrogate past populations
supervisors: Professor Adrian Smith, Professor Greger Larson and Dr Patrik Flammer
mix: mixed
description:
  Humans can be infected by a wide range of intestinal parasites including helminths and protozoa and many of these parasites are important in large parts of the world, particularly low and middle income countries. Many of these parasites were much more widespread in past populations. Indeed, our recent work demonstrates that a range of helminths were highly prevalent in Medieval Europe (Flammer et al., 2020). As well as being important for human health the diverse life histories of these parasites offer much more information on other aspects of life including sanitation, hygiene, diet and culinary practices (Flammer et al., 2018). The transmission stages of enteric parasites are incredibly robust preserving ancient DNA. Using a combination of parasitological and aDNA approaches we can interrogate many aspects of life in past populations and can also impact on the approaches used in modern control programmes.
  The project: Molecular archeaoparasitology is an emerging area of research that combines both parasitological and aDNA methods to interrogate infection biology and life of past populations. This project will continue to develop these powerful approaches exploring how pathogen genetics cab be used to identify links between human populations. We anticipate that the project will extend the aDNA approaches including developing baiting based aDNA technologies as well as broadening the array of target parasites to include protozoa as well as helminths.

training:
  The DPhil will support training in a wide range of parasitological and molecular approaches, in particular those employing ancient DNA. The project will also involve extensive bioinformatics training and will provide an appreciation of how we can use aDNA approaches to understand the past and influence the present.

background_reading:
  -- Flammer PG, Dellicour S, Preston SG, Rieger D, Warren S, Tan CKW, Nicholson R, Přichystalová R, Bleicher N, Wahl J, Faria NR, Pybus OG, Pollard M and Smith AL. (2018) Molecular archaeoparasitology identifies cultural changes in the Medieval Hanseatic trading centre of Lübeck. Proc. R. Soc. B.285:20180991. <a href="http://doi.org/10.1098/rspb.2018.0991">http://doi.org/10.1098/rspb.2018.0991</a>
  -- Flammer PG, Ryan H, Preston SG, Warren S, Přichystalová R, Rainer Weiss, Valerie Palmowski, Sonja Boschert, Katarina Fellgiebel, Isabelle Jasch-Boley, Madita-Sophie Kairies, Ernst Rümmele, Dirk Rieger, Beate Schmid, Ben Reeves, Rebecca Nicholson, Louise Loe, Christopher Guy, Tony Waldron, Jiří Macháček, Joachim Wahl, Mark Pollard, Greger Larson and Adrian L. Smith (2020) Epidemiological insights from a large-scale investigation of intestinal helminths in Medieval Europe. PLOS Neglected Tropical Diseases 14(8): e0008600. <a href="https://doi.org/10.1371/journal.pntd.0008600">https://doi.org/10.1371/journal.pntd.0008600</a>


pi_id: taylor_jenny
title: Genetic diagnoses to therapeutics for patients with rare neurological disorders
supervisors: Prof. Jenny Taylor
mix: 0% wet lab, 100% dry lab
description:
  This project will focus on identifying genetic variants underpinning rare neurological disorders which may be amenable to targeting with individualised nucleic acid therapeutics.
  Whole genome sequencing data available from the Genomics England 100,000 Genomes Project will be mined to identify suitable genetic variants using a range of bioinformatics algorithms, including Splice AI and GREEN-DB, for splice site and regulatory variants, respectively. Additional patient samples or phenotypic data can be obtained for follow-up studies through re-contact of the referring clinicians through an established Genomics England pathway. Functional studies, such as RNASeq, RT-PCR, mini-gene analyses and a range of molecular and cellular biology approaches in iPSC or relevant cell lines will be used to confirm effect of variants. Suitability of genetic variants for intervention with anti-sense oligonucleotides will be reviewed with our colleagues in the Dept of Paediatrics. The project will provide training in analysis of genome sequencing data to identify pathogenic variants for rare disease patients from 100kGP data and functional studies to confirm effect of these, potentially leading to genetic diagnoses for patients and development of novel therapeutics such as antisense oligonucleotides.


pi_id: taylor_jenny
title: Genetic variants underpinning early onset Parkinson’s disease
supervisors: Prof. Jenny Taylor, Dr. Ira Milosevic
mix: 50% wet lab, 50% dry lab
description:
  This project will focus on investigating the genetic basis of early onset Parkinson’s disease using genome sequencing data from 100,000 Genomes Project to identify potential novel disease genes, and to validate these using a range of functional genomics and molecular / cellular biology approaches.
  Genome sequencing data from the 100,000 Genomes Project has already led to a list of approx. 70 candidate genes for PD being identified. Further evidence for these genes will be sought using the 100kGP and UK Biobank datasets and using a gene burden approach.
  The biological candidacy of selected genes can be explored using a range of cell biology approaches to explore pathways known to be involved in pathogenesis of PD including vesicular and non-vesicular transport and interactions between organelles, including mitochondria and lysosomes. Relevant assays can be conducted in our lab and in collaboration with the Milosevic group
  This project will enable further exploration of the candidate genes identified to date and also provide an opportunity to identify genetic diagnoses for patients.


pi_id: taylor_jenny
title: Reverse genomics: from functional to genetics in neurodevelopmental and neurodegenerative disorders
supervisors: Prof. Jenny Taylor, Dr. Ira Milosevic
mix: 50% wet lab, 50% dry lab
description:
  Multiple genes have been shown to be implicated in pathways which are associated with neurodevelopmental and neurodegenerative conditions, such as vesicular and non-vesicular transport, lysosomal biology and autophagy, yet many of these genes have not as yet been implicated in human disease.   In a reverse approach, this project will use this functional data as a basis for identifying potential novel disease genes. The project will use whole genome sequencing data from the 100,000 Genomes Project to identify patients with variants in these genes who also have relevant neurological phenotypes. Re-contact of patients through the Genomics England process would allow patient-derived samples to be obtained for conducting experiments to validate these using a range of molecular and cellular biology assays available in our lab and in the Milosevic group. it is anticipated that this project will lead to novel associations of these genes with rare neurological conditions.


pi_id: todd_john
title: Genetics of type 1 diabetes
supervisors: Dr Dan Crouch & Prof John Todd
mix: 100% dry
training: Genetics, coding, MR
description:
  Using latest genetic information for T1D to study geographical variation across the UK and to use Mendelian Randomisation (MR) to determine causal factors.

background_reading:
  <a href="https://www.medrxiv.org/content/10.1101/2021.04.19.21255222v1">Disentangling the direct and indirect effects of childhood adiposity on type 1 diabetes and immune-associated diseases: a multivariable Mendelian randomization study</a>
  Tom G Richardson, Daniel J M Crouch, Grace M Power, Fernanda Morales Berstein, Emma Hazelwood, Si Fang, Yoonsu Cho, Jamie R J Inshaw, Catherine C Robertson, Carlo Sidore, Francesco Cucca, Steven S Rich, John A Todd, George Davey Smith
  medRxiv 2021.04.19.21255222; doi: <a href="https://doi.org/10.1101/2021.04.19.21255222">https://doi.org/10.1101/2021.04.19.21255222</a>


pi_id: todd_john
title: Single-cell dynamics of the immune system and its evolutionary partner, the microbiome
supervisors: Dr Ricardo Ferreria, Dr Dominik Dominik Trzupek, Dr Marcin Pekalski & Prof John Todd
mix: 50% dry
description: Deep dive into the immune system using latest methods
training: Genetics, single-cell omics, immunology, T cell receptor and metagenomic sequencing
background_reading:
  <a href="https://www.medrxiv.org/content/10.1101/2021.04.19.21255222v1">Disentangling the direct and indirect effects of childhood adiposity on type 1 diabetes and immune-associated diseases: a multivariable Mendelian randomization study</a>
  Tom G Richardson, Daniel J M Crouch, Grace M Power, Fernanda Morales Berstein, Emma Hazelwood, Si Fang, Yoonsu Cho, Jamie R J Inshaw, Catherine C Robertson, Carlo Sidore, Francesco Cucca, Steven S Rich, John A Todd, George Davey Smith
  medRxiv 2021.04.19.21255222; doi: <a href="https://doi.org/10.1101/2021.04.19.21255222">https://doi.org/10.1101/2021.04.19.21255222</a>
  <a href="https://www.biorxiv.org/content/10.1101/2019.12.18.881433v1">Peripheral tolerance to insulin is encoded by mimicry in the microbiome</a>
  Arcadio Rubio García, Athina Paterou, Mercede Lee, Hubert Sławiński, Linda S. Wicker, John A. Todd, Marcin Ł. Pękalski
  bioRxiv 2019.12.18.881433; doi: <a href="https://doi.org/10.1101/2019.12.18.881433">https://doi.org/10.1101/2019.12.18.881433</a>
  <a href="https://www.medrxiv.org/content/10.1101/2021.04.27.21256106v2">Single-cell multi-omics analysis reveals IFN-driven alterations in T lymphocytes and natural killer cells in systemic lupus erythematosus</a>
  Dominik Trzupek, Mercede Lee, Fiona Hamey, Linda S. Wicker, John A. Todd, Ricardo C. Ferreira
  medRxiv 2021.04.27.21256106; doi: <a href="https://doi.org/10.1101/2021.04.27.21256106">https://doi.org/10.1101/2021.04.27.21256106</a>


pi_id: todd_john
title: The role of Tau in pancreatic beta cells
supervisors: Dr Irina Stefana & Prof John Todd
mix: 80% wet
training: Cell biology, microscopy
description:
  Tau is expressed in neurons but also in the insulin-producing beta cells.  It can be expressed in the nucleus and is under cell cycle control.


pi_id: tzima_ellie
title: Genetics of rare diseases (primary lymphoedema)
supervisors: Professor Ellie Tzima, Professor John Reader, Dr Kar Lai Pang
mix: 80% wet/ 20% dry
description:
  Primary Lymphoedema is a lymphovascular disease caused by an underlying abnormality of the lymphatic system, which is inherited, and clinically and genetically heterogenous. Crucially, of all patients tested for Primary Lymphoedema, only 41% are given a molecular diagnosis. A common feature of these patients is insufficient or inadequate lymphatic valve formation or function. Lymphatic valves are initially formed by lymphatic endothelial cells which express lymphatic valve-forming genes. Most notably, the stimulus responsible for activation of the lymphatic valve programme and formation of valves is fluid shear stress due to lymph fluid. Our laboratory has previously identified a gene that is crucial for mechanosensing in arteries; we now seek to understand if this gene also plays a role in lymphatic valve formation and lymphoedema development. This a collaborative project with a leading group at St George’s University of London that has access to the UK’s largest lymphoedema clinic. You will work on a set of newly identified variants and assess their function in lymphatic endothelial cells. The end result will be a comprehensive understanding of how variants in a single gene can disrupt mechanotransduction mechanisms that result in lymphatic disease. We hope that by adding this gene to the list of lymphoedema associated genes, we can provide the much-needed diagnosis to thousands of patients.

training:
  The DPhil will be based at the Wellcome Centre for Human Genetics. The student will get to experience and learn a wide array of in vitro and in vivo techniques. These include bioinformatics, genetics, cell culture, transfections, western blotting, co-immunoprecipitation, qPCR, dissection of animal tissue, staining, confocal microscopy and analysis of RNA sequencing and mass spec proteomic data. Training in scientific writing and presentation skills will be provided, and writing of reviews and presentation at conferences will be strongly encouraged.
  These pages were reviewed/updated: 26/09/2024


pi_id: tzima_ellie
title: How do cells respond to mechanical forces?
supervisors: Professor Ellie Tzima, Professor John Reader, Dr Vedanta Mehta
mix: 80% wet/ 20% dry
description:
  Cells are constantly exposed to forces that dictate their function. In blood vessels, endothelial cells that line arteries are exposed to forces due to flowing blood; these forces are critical determinants of their physiologial functions but can also instigate development of diseases, such as atherosclerotic plaques and cardiovascular disease. The mechanisms by which cells sense and respond to mechanical forces is a mystery in biology and has implications in a number of diseases, including cancer, immune cell dysfunctions and neurobiology. We have bespoke in vitro systems that allow us to apply different forces on cultured cells and complement these studies with transgenic mouse models in vivo. We generate large datasets from RNA sequencing and proteomics with the ultimate goal of understanding at the genetic, molecular and physiological level how cells respond to forces.

training:
  The DPhil will be based at the Wellcome Centre for Human Genetics. The student will get to experience and learn a wide array of in vitro and in vivo techniques. These include cell culture, transfections, western blotting, co-immunoprecipitation, qPCR, dissection of animal tissue, staining, confocal microscopy and analysis of RNA sequencing and mass spec proteomic data. Training in scientific writing and presentation skills will be provided, and writing of reviews and presentation at conferences will be strongly encouraged.

background_reading:
  Please include references as desired.  Suggested format:
  -- 1          Mehta, V. et al. Mechanical forces regulate endothelial-to-mesenchymal transition and atherosclerosis via an Alk5-Shc mechanotransduction pathway. Sci Adv 7, doi:10.1126/sciadv.abg5060 (2021).
  -- 2          Sweet, D. T. et al. Endothelial Shc regulates arteriogenesis through dual control of arterial specification and inflammation via the notch and nuclear factor-kappa-light-chain-enhancer of activated B-cell pathways. Circ Res 113, 32-39, doi:10.1161/CIRCRESAHA.113.301407 (2013).
  -- 3          Liu, Y., Sweet, D. T., Irani-Tehrani, M., Maeda, N. & Tzima, E. Shc coordinates signals from intercellular junctions and integrins to regulate flow-induced inflammation. J Cell Biol 182, 185-196, doi:10.1083/jcb.200709176 (2008).
  --


pi_id: udalova_irina
title: Granulopoiesis: chromatin topology and associated functions
supervisors: Professor Irina Udalova, Dr Ananda Mukherjee, Prof Jim Hughes
mix: 50% wet lab, 50% dry lab
description:
  Granulopoiesis, the generation of new neutrophilic granulocytes, is crucial to health. During healthy neutrophil development its nucleus goes through dramatic morphological changes, from a simple round nucleus to a multi-segmented, lobulated nucleus. Indeed, the nuclear morphology is the main parameter used by pathologists to define the states of human neutrophil development. However, the molecular mechanisms controlling nuclear segmentation and the functional impacts of it are not understood.
  Chromatin architecture is what connects global nuclear shape and local regulation of gene expression. Chromatin is organized into distinct compartments within the nucleus and further segregated into spatially distinct regions. While neutrophils develop from progenitor cells to their multi-lobed form, long-range interactions are induced, leading to the chromatin contraction that may facilitate the folding of the neutrophil genome into the confined geometry of a toroid and segmented nucleus [1].
  image://data/images/udalova_irina_04.png
  Our recent work and results of others clearly demonstrate that neutrophils acquire different functions, such as production of reactive oxygen species, secretion of inflammatory molecules, formation of neutrophil extracellular traps, phagocytosis, bacterial killing etc, at different stages of their differentiation [2,3]. Moreover, we have identified and validated several key transcriptional regulators of neutrophil morphological development and/or functional responses [4]. This indicates that the transcriptional programming of morphological and functional maturation may be partially intertwined and are likely to be connected via changes in chromatin architecture.
  Here we will apply cutting edge chromatin conformation assays and gene expression analysis to correlate dynamic changes in the chromatin organization of the neutrophil genome to changes in gene expression and acquisition of specific functions during neutrophil maturation. Specific objectives:
  1.  To capture global chromatin topology changes during neutrophil differentiation using various cutting edge chromatin conformation capture (3-C) analyses of neutrophils throughout the differentiation trajectory [5]. Established computational pipelines would be used for visualization of contact maps, chromatin compartment analysis, chromatin compaction analysis, and finding differentially enriched topologically associating domains. The experimental setup would be used to assess changes to chromatin topology when key transcription factors for neutrophil development are depleted.
  2. To identify regions of local ‘topology dependent’ open and closed chromatin using ATAC-seq analysis to classify regions that show chromatinization changes (open/closed) in regions that gain/loss chromatin interactions. Single-cell ATAC-seq would be used for accessing heterogeneity in local chromatin conformation.
  3. To identify chromatin topology-dependent gene expression alterations using RNA-seq analysis to pin point genes that show topology and chromatin changes in their regulatory promoter/enhancer regions along the differentiation trajectory. The identified gene list will be checked for motifs for the previously identified key transcriptional regulators and validated in neutrophils with specific knock-out of these factors.
  The outcomes of this study are expected to unravel the regulation and functional consequences of the fundamental biological process, such as segmentation of neutrophil nucleus during the differentiation. This will lead to setting up a framework for further analysis of selective perturbations to this process during immunopathologies.

training:
  The Kennedy Institute is a world-renowned research centre and is housed in a state-of-the-art research facility. Training will be provided in a wide range of functional genomics approaches (e.g. RNA-Seq, ATAC-Seq, ChIP-Seq etc), immunological (cell isolation, tissue culture, FACS), and imaging (immunofluorescence on tissue sections) approaches, as well as cutting edge single cell platforms (10x, Nanostring GeoMx, Nanostring CosMx) and computational pipelines. Recently developed novel in vivo models of inflammatory diseases will be extensively used and new models will be generated.  A core curriculum of lectures will be taken in the first term to provide a strong foundation across a broad range of subjects, including musculoskeletal biology, inflammation, epigenetics, translational immunology and data analysis. The student will attend weekly seminars within the department and those relevant in the wider University. They will present their research regularly to the department and the Genomics of Inflammation group, and at the Computational Genomics Forum. They will also attend external conferences at which they will present their research to a global audience.  The student will also have the opportunity to work closely with members of the Genome Biology laboratory, MRC Weatherall Institute of Molecular Medicine, University of Oxford, and to further broaden their experimental expertise and theoretical knowledge of the chromatin organisation in health and disease.

background_reading:
  (1)  Zhu, Y. … Murre C. Comprehensive characterization of neutrophil genome topology. Genes Dev 2017 Jan 15;31(2):141-153
  (2) Ballesteros I, … Udalova IA, Ng LG, Ostuni R, Hidalgo A. Co-option of Neutrophil Fates by Tissue Environments. Cell. 2020 Nov 25;183(5):1282-1297.e18.
  (3) Wang L, Luqmani R, Udalova IA. The role of neutrophils in rheumatic disease-associated vascular inflammation. Nature Reviews Rheumatology. 2022 Mar;18(3):158-170.
  (4)  Khoyratty T*, Ai Z*, …, Udalova IA. Distinct transcription factor networks control neutrophil-driven inflammation. Nature Immunology, 2021 Sep;22(9):1093-1106.
  (5)  Oudelaar AM, …, Hughes JR. Dynamics of the 4D genome during in vivo lineage specification and differentiation. Nature Communications. 2020 Jun 1;11(1):2722.


pi_id: udalova_irina
title: Transcriptional networks controlling neutrophil development
supervisors: Professor Irina Udalova, Dr Abhinandan Devaprasad, Prof Helen Byrne
mix: 50% wet lab, 50% dry lab
description:
  Neutrophils represent a major arm of the innate immune defence system, with a long- held view of them being transcriptionally inactive, fast responders, mobilised in response to microbial and tissue insults. Recent developments in the field have changed this perception and firmly positioned neutrophils as transcriptionally active cells with the ability to adapt their transcriptional program. Our recent findings demonstrate that, despite limited residence times in tissues, neutrophils can tailor their properties to support organ homeostasis and mount tissue specific and transcriptionally regulated inflammatory response1,2. Importantly, in inflammation neutrophils are presented as functionally, morphologically, and behaviourally heterogeneous cells in circulation and tissue3.
  image://data/images/udalova_irina_05.png
  Figure: Model of transcriptional regulation of neutrophils during inflammation. Adopted from Chevre and Soehnlein, Nature Immunology News and Views on Ref 2, 2021. In the process of differentiation in bone marrow, lineage-determining transcriptional factors, including RUNX1, KLF6, CEBPE, and PU.1, are highly expressed and ensure gene expression programmes that promote proper neutrophil maturation. During the mobilization from the bone marrow into the blood, RFX2, RELB, IRF5 and JUNB become upregulated and transcriptionally accessible to support neutrophil cell survival and establish their effector function repertoire, whereas RUNX1 and KLF6 expression are silenced. Upon inflammation, circulating neutrophils migrate into the inflammatory sites, where they are exposed to inflammation-derived signals and become activated. Neutrophil activation leads to the activation of TFs, including RELB, IRF5 and JUNB, and subsequent TF binding to already accessible binding sites, thereby resulting in diverse TFs genomic occupancy and distinct transcriptional outputs (see Ref 2).
  The goal of this project is to reveal transcriptional circuits that control neutrophil differentiation and function in a signal-driven microenvironment. We aim to discover what transcriptional regulators control stage-specific expression of (1) cytoskeletal genes, that establish structural function and transcriptional regulation in the cell nucleus and distinct morphological features; (2) leukocyte migration and cell-cell interaction genes, responsible for distinct behaviour of neutrophils in the vasculature and tissue and (3) inflammatory response genes. This will be done by using a combination of cutting-edge imaging, genomic and spatial single cell transcriptomic approaches, as well as advanced immunological techniques2. Mathematical modelling of transcriptional circuits will be applied to understand the interaction between neutrophil development and activation. The project will also explore the spatial interactions of neutrophils with other immune cells in tissue using spatial transcriptomic and multimodal imaging data4. It will benefit from the already generated by us multiple genomic datasets and unique tools, such as genetically modified in vitro and in vivo models based on the recently discovered new key regulators2.
  The outcomes of this study are expected to progress fundamental biology of neutrophils and increase our understanding of neutrophil subsets in disease. This will ultimately lead to the development of a new class of therapeutic strategies, based on selective modulation of neutrophil biology, for therapeutic interventions in inflammatory disorders5.

training:
  The Kennedy Institute is a world-renowned research centre and is housed in a state-of-the-art research facility. Training will be provided in a wide range of functional genomics approaches (e.g. RNA-Seq, ATAC-Seq, ChIP-Seq etc), immunological (cell isolation, tissue culture, FACS), and imaging (immunofluorescence on tissue sections) approaches, as well as cutting edge single cell platforms (10x, Nanostring GeoMx, Nanostring CosMx) and computational pipelines. Recently developed novel in vivo models of inflammatory diseases will be extensively used and new models will be generated.  A core curriculum of lectures will be taken in the first term to provide a strong foundation across a broad range of subjects, including musculoskeletal biology, inflammation, epigenetics, translational immunology and data analysis. The student will attend weekly seminars within the department and those relevant in the wider University. They will present their research regularly to the department and the Genomics of Inflammation group, and at the Computational Genomics Forum. They will also attend external conferences at which they will present their research to a global audience.  The student will also have the opportunity to work closely with members of the Wolfson Centre for Mathematical Biology at the Mathematical Institute, University of Oxford, and to further broaden their theoretical knowledge by attending lecture courses in mathematical biology, statistics and related subjects.

background_reading:
  (1) Ballesteros I, Rubio-Ponce A, Genua M, Lusito E, Kwok I, Fernández-Calvo G, Khoyratty TE, van Grinsven E, González-Hernández S, Nicolás-Ávila JÁ, Vicanolo T, Maccataio A, Benguría A, Li JL, Adrover JM, Aroca-Crevillen A, Quintana JA, Martín-Salamanca S, Mayo F, Ascher S, Barbiera G, Soehnlein O, Gunzer M, Ginhoux F, Sánchez-Cabo F, Nistal-Villán E, Schulz C, Dopazo A, Reinhardt C, Udalova IA, Ng LG, Ostuni R, Hidalgo A. Co-option of Neutrophil Fates by Tissue Environments. Cell. 2020 Nov 25;183(5):1282-1297.e18.
  (2)  Khoyratty T*, Ai Z*, Ballesteros I, Mathie S, Eames HL, Martín-Salamanca S, Wang L, Hemmings A, Willemsen N, von Werz V, Zehrer A, Walzog B, van Grinsven E, Hidalgo A, Udalova IA. Distinct transcription factor networks control neutrophil-driven inflammation. Nature Immunology, 2021 Sep;22(9):1093-1106.
  (3) Wang L, Luqmani R, Udalova IA. The role of neutrophils in rheumatic disease-associated vascular inflammation. Nature Reviews Rheumatology. 2022 Mar;18(3):158-170.
  (4)  O Vipond, JA Bull, PS Macklin, U Tillman, CW Pugh, HM Byrne, HA Harrington (2021). Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumours. PNAS 118 (41): e2102166118.
  (5) Devaprasad A, Radstake TRDJ, Pandit A. Integration of Immunome With Disease-Gene Network Reveals Common Cellular Mechanisms Between IMIDs and Drug Repurposing Strategies. Frontiers in Immunology. 2021 May 24;12:669400.


pi_id: wilson_daniel
title: Developing analysis methods to detect human-pathogen interactions
supervisors: Associate Professor Daniel Wilson
mix: 100% dry lab
description:
  Infection is fundamentally an interaction between the human and pathogen. Consequently there is long-standing interest in the role of human-pathogen genetic interactions in infection traits, including disease severity and clinical outcome. While the biological questions are readily framed, logistic and analytic challenges have held back progress in this area. The chief difficulties are genotyping and whole genome sequencing large cohorts of humans and pathogens, and devising sensitive analyses that do not generate large numbers of false positives. Research groups around the world are now pursuing such cohorts in earnest. The focus of this project therefore is on the development and application of tools for performing trillions of tests of association between the millions of human genetic variants and millions of pathogen genetic variants, while controlling the false positive rate without loss of statistical power. This is critical for the emerging field of human-pathogen genome-wide association studies. Focusing on published data or new data generated in-house (subject to the project's progress by the commencement of this internship), we will develop and apply the harmonic mean p-value method to this problem. Depending on the student, there will be opportunity to focus more on the applied or theoretical side of the project, and to apply the approach to related problems such as epistasis. Subject to satisfactory progress, there may be opportunity to publish the results of the internship.

training:
  The students will learn about genome-wide association studies and statistical genetics with the help of the supervisor and other group members. Students are welcome to attend other training courses at the university or elsewhere.

background_reading:
  -- The COVID-19 Host Genetics Initiative (2021)
  Mapping the human genetic architecture of COVID-19
  Nature doi:10.1038/s41586-021-03767-x (<a href="http://www.danielwilson.me.uk/abstracts/covid19hgi_2021.html">abstract</a> <a href="https://www.nature.com/articles/s41586-021-03767-x">pdf</a>)
  -- D. J. Wilson (2019)
  The harmonic mean p-value for combining dependent tests.
  Proceedings of the National Academy of Sciences USA 116: 1195-1200. (<a href="http://www.danielwilson.me.uk/abstracts/wilson_2019.html">abstract</a> <a href="https://www.pnas.org/content/116/4/1195">pdf</a>)
  -- Young, B. C., et al. (2019)
  Panton-Valentine leukocidin is the key determinant of Staphylococcus aureus pyomyositis in a bacterial genome-wide association study.
  eLife 8: e42486 (<a href="http://www.danielwilson.me.uk/abstracts/young_etal_2019.html">abstract</a> <a href="https://www.biorxiv.org/content/early/2018/09/29/430538">preprint</a> <a href="https://elifesciences.org/articles/42486">pdf</a>)
  See <a href="http://www.danielwilson.me.uk">www.danielwilson.me.uk</a> for further group information.


pi_id: zondervan_krina
supervisors: Dr Nilufer Rahmioglu, Prof Krina Zondervan, and others
mix: 100% dry lab
title:
  Does endometriosis lead to an increased cardiovascular disease risk and (how) is this link genetically/biologically mediated?

description:
  Endometriosis is a common chronic inflammatory disease, causing pelvic pain and reduced fertility in an estimated 5‐10% of pre‐menopausal women (190 million worldwide). It features the presence of tissue that resembles endometrium (the lining of the uterus) outside the uterus, mainly on pelvic organs, but causes remain largely unknown. Diagnosis is often delayed for years as it requires surgery, while treatments are limited to surgery and/or hormonal drugs with many side effects. The chronic inflammatory pelvic environment present in women with endometriosis leads to the question whether the disease is associated with more systemic inflammation-association morbidity. Limited data has emerged that there is an elevated post-menopausal risk of cardiovascular disease among women diagnosed with endometriosis pre-menopausally. However, confirmation and specification of this association is required, along with investigation of the biological mechanisms through which the association may act. This project will leverage data from the UK Biobank, which contains data from more than 8,000 women diagnosed with endometriosis to investigate longitudinal cardiovascular (and potential other inflammatory) outcomes and the genetic vs. causal basis for associations. The analysis will include integrated analysis of clinical phenotypic, (gen)omic, inflammatory biomarker and other available data, as well as the analysis of publicly available data resources.

training:
  Training will involve genetic epidemiological research methods including (bivariate) GWAS and LD score regression, Mendelian randomisation and SMR, eQTL and integrated omics analyses, and functional pathway analyses. Opportunities to work with AI/machine learning methodology in analysing multidimensional data and link with other groups working in this methodological space. In addition to a base in WCHG, students will be part of the Oxford Endometriosis CaRe centre, that focuses on the integration of clinical diagnosis, care and treatment of the disease with clinical and basic research. The group benefits from a strong network of national and international collaborators in the fields of endometriosis, statistical genetics, genomics, bioinformatics, and functional biology. Students will be strongly encouraged to publish their work, participate and lead in outreach activities, present at international conferences, attend bi‐weekly group meetings, journal clubs, as well as departmental seminars and training courses.

background_reading:
  -- Zondervan KT, Becker CM, Missmer SA. Endometriosis. N Engl J Med. 2020;382:1244-1256
  -- Gallagher CS, Mäkinen N, Harris HR, Rahmioglu N, [....] Chasman DI, Missmer SA, Zondervan KT*, Morton CC. Genome-wide association and epidemiological analyses reveal common genetic origins between uterine leiomyomata and endometriosis. Nat Commun. 2019; 10: 4857.
  -- Nilufer Rahmioglu, Karina Banasik, […] Piraye Yurttas Beim, Stacey A Missmer, Grant W Montgomery, Andrew P Morris, Krina T Zondervan. Large-scale genome-wide association meta-analysis of endometriosis reveals 13 novel loci and genetically associated comorbidity with other pain conditions. BioRxiv pre-release, Aug 2018.  Under review, Jul 2021.
  -- Zondervan KT, Becker CM, Koga K, Missmer SA, Taylor RN, Viganò P. Endometriosis. Nat Rev Dis Primers 2018 Jul 19;4(1):9


pi_id: schuster-böckler_benjamin
title: Determine the cell-type composition of cell-free DNA using AI/ML
supervisors: Benjamin Schuster-Böckler, Hellen Byrne
mix: 100% dry lab
description:
  The TAPS assay that my group helped to develop has been used to sequence hundreds of samples of patient-derived cell-free DNA. We use this data to look for signs of cancer in the methylome, which allows us to detect cancer quite sensitively. However, early detection is not the only use of cell-free methylation data.
  Recently, we noticed that immune-cell derived DNA in the blood appears to predict which patients will respond to immunotherapy treatment. For this analysis, we used our in-house atlas of cell-type specific methylomes from a variety of blood and solid-tissue cells and applied an existing algorithm to “deconvolute” the cell-free methylation profile into the most likely mix of “pure” tissue methylomes that together would generate the observed pattern.
  Going forward, we plan to investigate how immune-cell activity as measured by circulating cell-free DNA can be used to diagnose e.g. inflammatory disorders, and whether it can accurately predict response to different types of immunotherapy.
  One step along this way is to improve the sensitivity and specificity of the deconvolution approach. To this end, we want to develop a more sophisticated algorithm that integrates across a wider range of informative regions in the genome, uses “fragmentomics” in addition to methylation information, takes into account the background error rate of the chemistry. In this project, you could investigate the effect of technical variance on deconvolution accuracy, or you could attempt to develop a fragmentomic-based deconvolution method, or attempt to come up with a better machine-learning framework to estimate cell-type contributions in the presence of multiple signals.
  Beyond the project phase, we have collaborations with many clinical scientists who are able to provide us with cfDNA samples from patients. In a DPhil coming out of this project, we would aim to bring this methodology to bear on a variety of real-world use-cases, such as the detection of inflammatory disorders (eg. IBD), the evaluation of vaccination efficacy, or the prognosis of response to immunotherapy treatment.

training:
  This project would suit a statistically minded person with a knack for coding. Our group has expertise in ML methods and algorithm development, as well as the epigenetics and cancer biology, so you would get a lot of support with that. You would get an opportunity to learn more about epigenetic biology and cell-free DNA, with a view towards clinical translation.

background_reading:
  -- Liu, Y. et al. Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat Biotech 37, 424-429 (2019).
  -- Fox-Fisher, I. et al. Remote immune processes revealed by immune-derived circulating cell-free DNA. Elife 10, e70520 (2021).
  -- Loyfer, N. et al. A DNA methylation atlas of normal human cell types. Nature 613, 355-364 (2023).
  --


pi_id: schuster-böckler_benjamin
title: A cheap and high-throughput assay to detect variants in single cells
supervisors: Benjamin Schuster-Böckler, Skirmantas Kriaucionis
mix: 50% dry lab, 50% wet lab (but can be adjusted in either direction)
description:
  Mutations accumulate stochastically in somatic cells. We are therefore all “mosaics” consisting of many cells with subtly different genomes. Normal DNA sequencing cannot detect this mosaicism, because the error rate of sequencing and library preparation exceeds the mutation frequency. Special sequencing methods are therefore being developed to understand the complex mechanisms that affect mutagenesis and clonal competition in healthy cells.
  My group recently established a collaboration with Ultima Genomics (UG), a company that develops an exciting new sequencing platform that reduces cost (<$100 for a human genome) while simultaneously increasing per-base accuracy through a clever approach called “ppmSeq”. We are currently exploring a number of technical approaches to push the accuracy to the “single-molecule” level. This could be a game-changer not just for clinical applications like cell-free DNA sequencing, but also for our ambition to interrogate somatic mutation heterogeneity across tissues and populations.
  For the project phase, we want to evaluate how UG-derived data improves mutation and methylation calling from samples that we already characterised deeply using more conventional Illumina sequencing. Depending on your preference, you could get involved both on the wet-lab and the dry-lab side, or both. We are planning to both re-sequence DNA for which we have accurate sub-clonal variant information to determine the true error rate of ppmSeq, using either existing or our newly developed library-prep approaches. We are also trying to computationally “clean up” ppmSeq data from TAPS libraries which would generate a particular type of artefact.
  Moving beyond the project phase, the idea is to apply this high-throughput assay in two distinct areas of research: first, we hope to use this method to screen a range of environmental exposures that are potentially mutagenic. Second, we hope to apply this approach to liquid biopsies, where rare variants can be an indicator for the presence of cancer. In this context, sequencing accuracy is the single-most important factor for disease detection. We will leverage our collaboration with a wide range of clinical groups to apply this method in a real-world setting.

training:
  The ideal candidate would have some wet-lab experience, and/or some experience with machine-learning. You would have the chance to work with a totally new methodology and develop (potentially patentable) new methods. You would receive training in wet-lab methods as well as on computational analysis techniques.
  Background Reading/References
  -- <a href="https://www.ultimagenomics.com/ppmseq-for-rare-event-detection">https://www.ultimagenomics.com/ppmseq-for-rare-event-detection</a>
  -- Liu, Y. et al. Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat Biotech 37, 424-429 (2019).
  -- Abascal, F. et al. Somatic mutation landscapes at single-molecule resolution. Nature 593, 405-410 (2021).
  -- Tomkova, M. et al. Human DNA polymerase ε is a source of C>T mutations at CpG dinucleotides. Nat Genet in press (2024).


pi_id: németh_andrea
title: Missing mutations in cerebellar ataxias
supervisors: Prof Andrea Németh
mix: 10% wet lab, 90% dry lab (partly depending on results and also on Covid)
description:
  My group has been extensively involved in the identification of novel genes causing cerebellar ataxias and related disorders (cognitive impairment, other movement disorders, and sometimes related systemic conditions).
  The main focus has been on next generation sequencing, most recently whole genome sequencing, and we were the first team in the world to identifying a novel cerebellar ataxia using this technology. Since then we have identified several others.
  We have a large cohort of patients with ataxias, but despite being extensively analysed the disease causing mutations have not been identified, even when a genetic cause is the most probable. This is a very common problem and likely reflects limitations of the sequencing technologies being used, the bioinformatics pipelines currently available and our understanding of the human genome.
  Some of the data is within the 100,000 Genomes Project and this remains an extremely rich source of mutations which are yet to be identified as well as our own clinical cohorts.
  The specific aim of this project would be to access the data within the 100,000 Genomes and search for mutations in novel genes in this group. And additional option would be to investigate these patients using alternative sequencing technologies.
  A wide variety of methods are used starting with the analysis of sequencing data and then confirming the findings using a vast array of cellular and functional methodologies, either in our own lab or with collaborators.

training:
  Working within the 100,000 Genomes environment, determining the links between gene mutations and human disease, improving diagnostics, identifying novel cohorts.

background_reading:
  -- Lise S, Clarkson Y, Perkins E, Kwasniewska A, Sadighi Akha E, Parolin Schnekenberg R, Suminaite D, Hope J, Baker I, Gregory L, Green A, Allan C, Lamble S, Jayawant S, Quaghebeur G, Cader MZ, Hughes S, Armstrong RJE, Kanapin A, Rimmer A, Lunter G, Mathieson I, Cazier J-B, Buck D, Taylor JC, Bentley D, McVean G, Donnelly P, Knight SJL, Jackson M, Ragoussis J, Németh AH. Recessive mutations in SPTBN2 implicate β-III spectrin in both cognitive and motor development. PloS Genetics, 2012;8:e1003074.
  -- Németh AH, Kwasniewska AC, Lise S, Parolin Schnekenberg R, Becker  EBE, Bera KD, Shanks ME, Gregory L, Buck D, Cader MZ, Talbot K, de Silva R, Fletcher N, Hastings R, Jayawant S, Morrison PJ, Worth P, Taylor AM, Tolmie J, O’Regan M, UK Ataxia Consortium, Valentine R, Packham E, Evans J, Seller A, Ragoussis J. Next Generation Sequencing for Molecular Diagnosis of Neurological Disorders using Ataxias as a Model. Brain. 2013;136:3106-18.
  -- Parolin Schnekenberg R, Perkins EM, Miller JW, Davies WI, D'Adamo MC, Pessia M, Fawcett KA, Sims D, Gillard E, Hudspith K, Skehel P, Williams J, O'Regan M, Jayawant S, Jefferson R, Hughes S, Lustenberger A, Ragoussis J, Jackson M, Tucker SJ, Németh AH, 2015. De novo point mutations in patients diagnosed with ataxic cerebral palsy. Brain. 2015:138;1817-32.
  -- Sleven H, Welsh SJ, Yu J, Churchill ME, Wright CF, Henderson A, Horvath R, Rankin J, Vogt J, Magee A, McConnell V, Green A, King MD, Cox H, Armstrong L, Lehman A, Nelson TN; Deciphering Developmental Disorders study, CAUSES study, Williams J, Clouston P, Hagman J, Németh AH. De Novo Mutations in EBF3 Cause a Neurodevelopmental Syndrome. Am J Hum Genet. 2017;100:138-150.
  -- Watson LM,  Bamber E, Parolin Schnekenberg R, Williams J, Bettencourt4 C, Lickiss J, Fawcett7, Samuel Clokie K, Wallis Y, Clouston P, Sims D, Houlden H, Becker EBE, Németh AH. Dominant mutations in GRM1 cause a spinocerebellar ataxia with therapeutic potential. Am J Hum Gen. 2017;101:451-458.
  -- Rexach J, Lee H, Martinez-Agosto JA, Németh AH, Fogel BL. Clinical application of next-generation sequencing to the practice of neurology. Lancet Neurol. 2019;18:492-503.
  -- Loss of function mutations in GEMIN5 cause a neurodevelopmental disorder. Kour S, Rajan DS, Fortuna TR, Anderson EN, Ward C, Lee Y, Lee S, Shin YB, Chae JH, Choi M, Siquier K, Cantagrel V, Amiel J, Stolerman ES, Barnett SS, Cousin MA, Castro D, McDonald K, Kirmse B, Nemeth AH et al. Nat Commun. 2021;12:2558.


