# PI

id: ansari_azim
name: Dr. Azim Ansari
location: Peter Medawar Building for Pathogen Research and Wellcome 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: images/ansari_azim.jpg
titles:
  Sir Henry Dale Fellow, Group Leader in the Experimental Medicine Division, Associate Group Leader at the Wellcome 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: 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: 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: 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: images/channon_keith.jpeg
url:
  https://www.well.ox.ac.uk/research/research-groups/channon-group-cardiovascular-functional-genomics-and-redox-signalling-1


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: 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: 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: 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@well.ox.ac.uk
image: images/knight_julian.png
titles:
  Professor of Genomic Medicine, Deputy Director of WHG, Director of GMS DPhil programme, Honorary Consultant Physician, 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: images/mccullagh_james.jpeg
titles:
  Director of the Mass Spectrometry Research Facility and group leader, Associate Professor of Analytical Chemistry


id: taylor_jenny
name: Associate 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: images/taylor_jenny.png
titles:
  Associate Professor, 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: images/udalova_irina.jpeg
titles:
  Professor of Molecular immunology. 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. Although reasonable for some variants, there is strong theoretical and empirical evidence that genetic interactions between host and pathogen play a major role in infectious disease aetiology. 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. 
  With the development of mobile and rapid sequencing platforms and exponential decrease in the cost of sequencing, the ability to generate pathogen and host data on the same subjects is becoming widely available. However, there is a lack of analysis tools and pipelines for pathogen GWAS, host-pathogen genome-to-genome analyses and to uncover interactions that modify disease phenotypes. We develop methodologies to integrate host and pathogen data with a focus on chronic infections of hepatitis B and C viruses (HBV and HCV) and human immunodeficiency virus (HIV) where we analyse data from large well characterised cohorts where we have generated paired host pathogen genomic data. 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 Wellcome Centre for Human Genetics (WCHG). 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: 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: 
  -- How are Different B Cell Populations Developmentally Linked in Human Health and Disease?
  -- Immuno-surveillance in Cancer
  -- How is B Cell Repertoire and Function Different in Health and Disease?
  -- What is the Effect of Genetic and Environmental Variation on B and T Cell Fate?
  -- Single cell and omics technology Development
  Specific project proposals:
  -- 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 ChIP-seq, CUT&RUN 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
themes: 5
overview:
  Protein interactions underlie most biological processes but are challenging to target using small molecule drugs. Many protein interactions are mediated by short-linear-interacting motifs (SLiMs) that range from 3-12 amino acid residues (1, 2). Small peptides designed from SLiMs can disrupt specific protein interactions and are broadly applicable to therapeutic development. A classic example is the ACE inhibitor drug series (e.g. captopril) that originated in the snake venom peptide teprotide. Our lab focusses on identifying SLiMs that mediate chemokine protein interactions. Chemokines are secreted signalling peptides that are produced by diseased or injured tissues - and underlie not only acute disease (e.g. COVID-19 lung inflammation) but also many chronic immuno-inflammatory diseases such as ulcerative colitis and rheumatoid arthritis. The 46 chemokines signal through 19 GPCRs to activate leucocyte (e.g. neutrophil, monocyte, T-cell) migration (3). The redundancy of the chemokine network with a single chemokine being able to target multiple receptors, and multiple receptor classes being expressed on leucocytes results in network robustness. This means that a single point of attack fails to effectively neutralize the chemokine network in disease. Natural chemokine-binding proteins (CKBPs) from ticks and viruses bind multiple chemokines, blocking chemokine-receptor binding, chemokine-dimerization, and chemokine-glycosaminoglycan binding, overcoming redundancy (4). CKBPs are effective in several disease models of inflammation, and as inflammation imaging agents. Work from our and other labs indicate that CKBP:chemokine, chemokine:chemokine, and chemokine:receptor interactions are mediated by short-linear-interacting-motifs (SLiMs) and that synthetic SLiM-peptides bind multiple chemokines and inhibit chemokine function (5, 6). These SLiM-peptide properties suggest their potential for development as theranostic (therapeutic and diagnostic) agents in immuno-inflammatory diseases. 
  Over 500 CKBP:chemokine, chemokine:chemokine, chemokine:glycosaminoglycan and chemokine:receptor interactions are known, precluding use of traditional structural biology approaches to identify the molecular mechanism of interaction. To systematically identify SLiMs that mediate these interactions we are using a phage display -nextGen sequencing (NGS) approach (2). Known CKBPs, chemokines and chemokine receptors have been deconstructed into overlapping 16-mer peptides that are expressed on phage. Binding of specific peptides to a target (e.g. a chemokine) is detected by affinity purification of phage bound to the target. Bound phage are sequenced using NGS and peptides enriched over the input (SLiMs) are identified using a series of custom-written R scripts. Synthetic SLiM-peptides are then used to validate the binding, determine binding affinity, and assay effect on chemokine function cell migration. These experiments provide an understanding of the molecular mechanisms by which CKBPs, chemokines and receptors display “one-to-many" binding interactions. The phage-display NGS approach can also be used to mutagenize and combine peptides to achieve optimal therapeutic efficacy. The phage-display NGS approach is broadly applicable to identifying the molecular basis of other protein interactions for instance in the cytokine network or the interaction of viral oncogenes with host proteins. 
  Project areas: protein interactions, inflammation, chemokine, phage-display, next-generation sequencing, theranostics
  Specific project proposals:
  -- ‘Identifying the molecular basis of chemokine:receptor binding using phage-display and application to peptide theranostic development’
  -- ‘Identifying the molecular basis of chemokine oligomerization using phage-display and application to peptide theranostic development’
  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: church_david
themes: 2,4,5
overview:
  We study colorectal and endometrial cancer to understand their biology and to improve patient care. Our main focus is the interaction between genomic instability and the antitumour immune response in these tumours, but we have several projects outside this area. 
  Project areas: 
  Colorectal cancer; endometrial cancer; cancer genomics; digital pathology, biomarker, immune escape .
  Specific project proposals:
  -- Novel immune escape mutations in mismatch repair deficient cancer
  -- Characterisation of driver mutations in endometrial cancer
  etc.
  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: 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: 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: 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
  Hughes JR, Roberts N, McGowan S, Hay D, Giannoulatou E, Lynch M, de Gobbi M, Taylor S, Gibbons R & Higgs DR Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment. Nat Genet, (2014).
  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
  Oudelaar AM, Davies JOJ, Hanssen LLP, Telenius JM, Schwessinger R, Liu Y, Brown JM, Downes DJ, Chiariello AM, Bianco S, Nicodemi M, Buckle VJ, Dekker J, Higgs DR & Hughes JR  Single-allele chromatin interactions identify regulatory hubs in dynamic compartmentalized domains. Nat Genet, (2018). 
  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
  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:
  My goal is to understand how changes in our DNA occur in the germline and how processes such as meiotic DNA break repair and recombination impact human diversity and health. Many of these processes are complex and dynamic, involving the interplay of numerous proteins.
  In our work we perform specialised wet-lab experiments and use statistical analyses that combine data from these assays to provide insight into in vivo interactions in complex processes. We also use UK Biobank and Genomics England to understand both the causes and impacts of germline mutations on human disease and other phenotypes. 
  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: 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: 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: 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 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 (for example using Priority Index http://pi.well.ox.ac.uk). We are also applying an integrated -omic approach to determine the regulatory epigenomic landscape of ankylosing spondylitis and the impact of disease-associated genetic variation in a disease context together with ongoing work focusing on drug targets involving IL12/23 pathways.
  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: 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:
  --  ‘What is the effect of genetic variation on XXX?’ 
  -- ‘Second project title’.
  etc.
  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 population genetics, deterministic and stochastic modelling, and the evolutionary analysis of viral sequence data. 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 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:
  -- Unravelling the role of transmission on SARS-CoV-2 evolutionary dynamics and vaccine escape
  -- Characterising the within-host compartmentalisation of Hepatitis C Virus
  -- Determining the role of Hepatitis C virus cccDNA transcriptional activity in increasing the lifespan of episomal cccDNA
  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 (Brenner, Mentzer et al PLOS One 2018, 2019) 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 (Muriuki*, Mentzer* et al Sci Adv 2019) and Asia. 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 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 (relocated to Oxford in spring 2021) focuses on comprehending neuronal functions at the molecular level, with the purpose of using this knowledge to address the mechanisms of neurodegenerative diseases, as well as 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 behavioral 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), endocytosis (e.g., J Cell Biol 2018; Neuron 2018; EMBO J 2019; Nature 2019) and vesicle acidification (eLife 2018). Notably, in the past four years we have discovered two new ways of v-ATPase regulation: by (1) clathrin coat (eLife 2018) and (2) rabconnectin-3 (unnder 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 do our utmost 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, neurodenerative diseases, Parkinson’s disease, ataxias, diabetes, experimental medicine, live cell imaging
  Specific project proposals:
  --  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: 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.


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. Biorxiv 2021]. 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 perform statistically powerful and robust genome-wide association, and methods that use deep neural networks to infer genealogical relationships across samples.
  Several DPhil projects are available within these research areas, please get in touch to discuss these directions.
  Representative publications:
  -- B. Zhang, A. Biddanda, P. Palamara. Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits. Biorxiv.
  -- R. Fournier, D. Reich, P. Palamara. Haplotype-based inference of recent effective population size in modern and ancient DNA samples. Biorxiv.
  -- 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.
  -- S. Gazal, H. Finucane, N. Furlotte, P. Loh, P. Palamara, X. Liu, A. Schoech, B. Bulik-Sullivan, B. Neale, A. Gusev, A. Price. Linkage disequilibrium–dependent architecture of human complex traits shows action of negative selection. Nature Genetics, 2017.
  -- P. Palamara. ARGON: Fast, whole-genome simulation of the discrete time Wright-Fisher process. Bioinformatics, 2016.
  -- P. Loh, P. Palamara, A. Price. Fast and accurate long-range phasing in a UK Biobank cohort. Nature Genetics, 2016
  -- P. Palamara, et al.. Leveraging distant relatedness to quantify human mutation and gene conversion rates. The American Journal of Human Genetics, 2015.
  -- P. Palamara, T. Lencz, A. Darvasi, I. Pe'er. Length distributions of identity by descent reveal fine-scale demographic history. The American Journal of Human Genetics. 2012.


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: 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: sauka-spengler_tatjana
themes: 1,2,3,4,5
overview:
  Gene Regulatory Networks in Development and Disease
  Embryonic development is driven by a large set of finely orchestrated regulatory programs that control cell fate decisions, differentiation and morphogenesis, leading to formation of a complex organism. Understanding how these programs, encoded at the genome level, are translated into intricate networks of interacting biological components (genes, proteins, RNA) is essential to our understanding of mechanisms underlying developmental processes and human diseases, triggered when biological circuits go awry.
  Modern epigenomic techniques are powerful tools to dissect complex regulatory networks, providing the ability to systematically analyse chromatin landscape and on-going transcriptional programs. Epigenomic profiling of histone modifications allows genome-wide chromatin signature mapping and classification of sites of regulatory activity (e.g. distal elements/enhancers, promoters, repressed regions, etc.). Concomitantly, active transcriptome analysis provides information about upstream inputs and downstream outputs within the Gene Regulatory Networks (GRNs) that orchestrate diverse cellular processes.
  In order to mechanistically dissect GRNs during development, we are adapting systems level approaches, such as epigenomic and transcriptional profiling, to defined cell populations in the developing embryo. The data sets obtained allow us to annotate the sites of regulatory activity, and consequently assemble and test gene regulatory circuitry that controls given developmental process at the cellular level. We use two developmental models, the chicken (1) and the zebrafish (2) embryo.
  (1) One of the main efforts in our laboratory is building a systems level understanding of the gene regulatory network that orchestrates early steps of neural crest formation in vertebrate embryos. We use the chicken embryo, a classical model for studying neural crest, whose mode of early development closely resembles human. The neural crest is multipotent, embryonic stem cell-like population which gives rise to a plethora of derivative tissues and organs, such as sensory and autonomic ganglia, adrenal and thyroid glands, smooth muscle of major blood vessels, craniofacial skeleton and the vast majority of body’s pigmentation. Due to their unique multipotency, coupled with the developmental plasticity, there is broad interest in using the regenerative capacity of neural crest cells in stem cell-based treatments. By deciphering GRNs that orchestrate early steps of neural crest formation, we aim to understand the mechanistic basis of their multipotency and stem-cell like potential, as well as and the biochemical hierarchy that controls the maintenance of those properties.
  (2) In addition to being a powerful organism for studying embryonic development, in recent years zebrafish has become an important system for biomedical research, as one of the keys to understanding human disease and addressing critical questions in regenerative medicine. Zebrafish not only have the same genes as humans but also most of the same cell types, tissues, organs and biological circuits, assuring that the lessons from this model can be directly applied to other vertebrate systems and to human health.
  We have developed a versatile, genetically encoded, binary in vivo biotinylation approach in zebrafish, which allows for tissue-specific biotinylation of defined targets. This is achieved by co-expression of proteins tagged with biotin acceptor peptide (Avi-tag) and bacterial biotin ligase, BirA in the same cells, allowing to isolate specific proteins or cell populations, using single step affinity purification procedure. Isolated genetically defined cell populations can then be profiled using genome-wide assays, adapted to small cell numbers. We are using this technology to analyze cellular circuitry at as many levels as possible and to address transcriptional and epigenomic mechanisms at play in an array of developmental systems, such as neural crest and hematopoietic lineages, but also in processes activated during inflammatory response to injury and cancer, or during organ regeneration.
  Project areas: functional genomics, model organisms. Research: gene regulatory networks, epigenetics
  Specific project proposals:
  -- <a href="https://www.rdm.ox.ac.uk/study-with-us/supervisor-profiles/gene-regulatory-networks-in-development-and-disease">Gene Regulatory Networks in Development and Disease</a> (see website for details)
  Please contact directly for further information.


pi_id: schuster-böckler_benjamin
themes: 3,4,5
overview:
  My research group uses genomic data to study the processes that lead to cancer. We are interested in the fundamental questions of “how, why and where do mutations occur in the genome”. Lately, we have also begun to try to use our understanding of genetic and epigenetic changes that happen during tumour formation to develop better diagnostic tests for cancer. 
  My group is primarily funded through Ludwig Cancer Research and located at the Big Data Institute. We collaborate closely with many experimental and clinical teams in Oxford who provide us with data. In return we provide them not just with answers to their questions, but also with new hypotheses they could test experimentally, based on preliminary data we extract computationally.
  One area we are particularly interested in are cancers of the upper gastrointestinal tract. Oesophageal and stomach adenocarcinomas share a lot of molecular similarities. For unknown reasons, however, oesophageal cancers are becoming more common in the western world, while stomach cancers incidence is going down. One focus area of our research is therefore to try to understand which mechanisms underly the accumulation of mutations in oesophageal cancer.
  We have recently been involved in the development of a new 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 collaborators have generated plenty of data from different cancers, healthy tissue and from cell-free DNA. Leveraging our knowledge of cancer genetics and epigenetics, we are now working on algorithms to detect cancer-specific features that are predictive of treatment success or able to distinguish cancer patients from healthy controls.
  Project areas: cancer epigenetics, causes of mutagenesis, tumour evolution, cancer early detection, predicting response to immunotherapy
  Specific project proposals:
  -- ‘Early detection of liver cancer using cell-free DNA and other measurements’
  -- ‘What drives trophoblastic tumours?’
  Please contact directly for further information.


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:
  Jenny was a co-investigator on the WGS500 project, which was a forerunner to the UK’s 100,000 Genomes Project and also led a team to establish the clinical framework and infrastructure for WGS within the Oxford hospital setting. She continues to participate in the Genomics England programme through its Clinical Interpretation Partnerships.
  This group is part of the NIHR Oxford Biomedical Research Centre’s Genomic Medicine Theme, a translational research programme. As a clinical genome sequencing programme, strongly connected with clinical diagnostic genomics labs, our results also have the potential to inform molecular diagnoses and treatment selection for patients. We are also involved in analysing data from the Genomics England 100,000 genomes programme, which would present an ideal opportunity for GMS students to analyse a wealth of WGS data. 
  Our group focuses on application of whole genome sequencing for understanding the pathogenesis of a broad spectrum of rare diseases, with the aim of identifying novel disease genes. We also apply whole genome sequencing mutation profiling for cancer patients. 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. Potential novel disease genes may then be followed up using a range of functional studies including CRISPR gene editing and molecular/cellular biology approaches, often in collaboration with other groups. Currently, putative novel genes in neurological, developmental and immunological conditions are the focus of our research.
  Project areas: whole genome sequencing, bioinformatics, rare diseases, genetic and functional studies
  Specific project proposals:
  -- Exploring novel disease genes in 
  -- Exploring pathogenicity of non-coding and structural variants for Rare Diseases using 100,000 Genomes Project dataset 
  Please contact me directly for further information.


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:
  From the moment the heart starts beating, endothelial cells that line blood vessels are subjected to haemodynamic (or mechanical) forces due to blood flow. Mechanical forces are crucial not only for normal development of the embryonic heart and vascular system, but also play an important role in maintaining homeostasis on the adult organism. Mechanical forces, however, can also be instigators of vascular pathologies, such as atherosclerosis. Our research focuses on the role of mechanotransduction in regulating cardiovascular function in health and disease. We use a multi-disciplinary approach that includes expertise in bioengineering, molecular and cell biology and physiology to understand mechanisms of mechanotransduction. The aim is not only to understand at a fundamental level how cells sense mechanical force and transduce it into biochemical signalling, but also to identify the molecular mechanisms by which mechanical forces regulate cardiac and vessel function. This should facilitate development of therapeutics that ultimately promote beneficial signalling or disrupt pathological responses. We have recently identified a pathway by which endothelial cells sense and respond to blood flow (Mehta et al, Nature 2020; Mehta et al, Science Advances 2021) that dictates development of atherosclerosis and cardiovascular disease. We plan to extend these studies to understand the molecular mechanisms responsible using a combination of in vitro and in vivo approaches.
  Project areas: cardiovascular science and molecular, cell & systems biology, mechanotransduction, shear stress, cardiovascular disease, endothelium, intercellular junctions, integrins, PECAM, Rho GTPases, tRNA synthetases, protein translation, redox signaling, angiogenesis, vascular remodeling and myocardial infarction.
  Specific project proposals:
  Please contact directly for further information.


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:
  -- Transcriptional blueprint of neutrophil development during homeostasis and disease
  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 (affecting <1/2000 individuals) collectively, rare diseases affect >250 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.
  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


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: 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.


# 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: Developing Statistical Methodology for integrated analysis of host-pathogen genomic data
supervisors: Dr. Azim Ansari and Dr. Gavin Band
mix: 0% wet lab, 100% dry lab
description:
  To date, most human pathogen genetic interaction studies have focused on HLA-associated escape variants and the lack of complete host and pathogen genetic variation data has meant study of other selective effects has been neglected. Host-to-pathogen genome-to-genome analysis will detect host genetic “footprinting” on the pathogen in a non-biased fashion. At present, there is a paucity of such studies.  Some of key challenges are as follows:
  -- Pathogen and host populations are co-structured. If not accounted for, this co-structuring will result in many false positive associations. There is a need to develop statistical methodologies and associated software to account for the strong co-structuring between the pathogen and the host.
  -- The current methods have low Statistical power as typically one would test for association between millions of host SNPs and thousands of pathogen SNPs. There is a need to develop methods that will increase the power of such studies. Two possible strategies are either marginalising over one set of variables or using omnibus tests that combine evidence across many hypotheses.
  -- A third area for methodological development relates to within-infection diversity. For instance, in the case of malaria this occurs when multiple mosquito bites generate overlapping infections (superinfection) or when mosquitos themselves carry several strains (coinfection). In the context of chronic infections (such as HCV) within-patient diversity occurs because mutations arise during the long infection periods, with the level of pathogen diversity typically varying between patients.  These features are not well handled by current association testing methods, and we would like to develop new methods that account for this.
  The methods will be applied to large HCV, HBV, HIV and malaria cohorts where we have generated both host and pathogen genomic data.
  We can shape the short project around the student’s interest.

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 and Dr. Gavin Band
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: 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. There is likely to be the opportunity to undertake the dedicated Centre for Computational Biology training course in bioinformatics.

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
  Insert any additional project description(s) on subsequent pages if applicable.  Please use the same template and use separate pages for each project.


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: 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: knight_julian
title: Validating a genetics-led approach to drug target prioritisation in immune traits
supervisors: Prof Julian Knight
mix: 50% wet lab, 50% dry lab
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 Structural Genomics Consortium) 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 publically 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. A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat Genet 2019; 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


pi_id: knight_julian
title: Resolving heterogeneity in the response to infection using -omics
supervisors: Prof Julian Knight, Dr Alex Mentzer
mix: 50% wet lab, 50% dry lab
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 in sepsis and COVID-19, 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 work in sepsis and COVID-19 through the UK GAinS and COMBAT studies, 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 (including within COMBAT Rachael Bashford-Rogers, Calli Dendrou, John Todd, Jim Hughes, Tatjana Sauka-Spengler, Ben Fairfax, Steve Sansom and Irina Udalova). 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:
  -- Burnham KL, Davenport EE, Radhakrishnan J, Humburg P, Gordon AC, Hutton P, Svoren-Jabalera E, Garrard C, Hill AVS, Hinds CJ, Knight JC. Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia. Am J Respir Crit Care Med 196, 328-339 (2017).
  -- Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, Rautanen A, Gordon AC, Garrard C, Hill AVS, Hinds CJ & Knight JC. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med 4, 259-271 (2016).
  -- Fairfax BP, Humburg P, Makino S, Naranbhai V, Wong D, Lau E, Jostins L, Plant K, Andrews R, McGee C & Knight JC. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014).
  -- COMBAT Consortium 2021 A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. medRxiv, 2021.05.11.21256877.


pi_id: lythgoe_katrina
title: Unravelling the role of transmission on SARS-CoV-2 evolutionary dynamics and vaccine escape
supervisors: Dr Katrina Lythgoe and Professor Christophe Fraser
mix: 100% dry lab
description:
  SARS-Cov-2 has had a devastating effect on public health and economies globally. With the arrival of effective vaccines we are about to enter a different phase of the pandemic. What this looks like will depend on whether, or to what degree, vaccines block transmission, how vaccines are rolled out, and the evolution of vaccine escape. Although we should remain ambitious, eradication seems unlikely, and therefore SARS-Cov-2 is likely to remain endemic, at least in the medium term.
  Evolution of vaccine escape mutations requires their emergence within an individual, successful transmission, followed by ongoing chains of transmission. The level of SARS-Cov-2 sequencing (including in Oxford) and sharing of this data is unprecedented, enabling a unique insight into the evolution and transmission of this pathogen. We have shown that the virus has low levels of within-host diversity, is under strong evolutionary constraint, and that only one or a few variants are transmitted; this resulted in our assertion that vaccine escape is unlikely (Lythgoe & Hall et al., Science 2021). This contrasts with subsequent rapid emergence of variants of concern that have large numbers of mutations that could move the virus significantly closer to vaccine escape. It has been hypothesised that these variants evolved in individuals who remained chronically infected for months.
  Overarching aim:
  The overarching aim of this project, if taken to DPhil, is to model and predict the evolution of vaccine escape, and to design optimal vaccination strategies that are ‘evolution-proof’. This will involve the development of models of SARS-CoV-2 evolution that include within- and between- host processes, and that are informed by, and fitted to, within-host whole-genome deep-sequencing data, estimates of transmission bottleneck size, and between-host phylogenies. We are part of the Office of National Statistics Covid-19 infection survey, and this project will give you access to >100,000 sequenced samples (and growing) plus metadata.
  During the rotation project you will:
  1.     Perform a literature review.
  2.     Develop a model of within-host SARS-CoV-2 evolution and transmission, informed using within-host deep-sequencing data, and calculate the likelihood that and escape mutation will emerge and spread. This could use a branching-process type approach.
  3.     Write up.
  This could form the foundation of a DPhil, which could help inform 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 viral transmission models, including phylodynamic models, and test these using WGS 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”
  -- Rambaut et al., Virologcal 2020, “Preliminary genomic characterisation of an emergent SARS-CoV-2 lineage in the UK defined by a novel set of spike mutations” (virological.org)
  -- Antia et al., Nature 2003, “The role of evolution in the emergence of infectious diseases”
  -- Lythgoe, Pellis & Fraser, Evolution 2013, “Is HIV short-sighted? Insights from a multistrain nested model”


pi_id: lythgoe_katrina
title: Characterising the within-host compartmentalisation of Hepatitis C Virus
supervisors: Dr Katrina Lythgoe, Professor Oliver Pybus and Professor Jane A. McKeating
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. Fundamentally, the evolution and epidemiology of this virus at the epidemiological scale cannot be properly elucidated without a detailed understanding of the link between within-host evolutionary dynamics and transmission. Mathematical modeling and evolutionary analysis of genetic data, particularly HIV, has helped answer key questions, including whether HIV continues to replicate whilst on treatment, how many HIV variants are transmitted among individuals, and how HIV spreads within and among population. However, similar work on HCV is in its infancy.
  Our previous work shows HCV infection is characterised by different subpopulations which are only intermittently observed in plasma. Consequently, virus sequenced from a single time point is unlikely to be representative of the viral diversity present in that individual, resulting in the potential to incorrectly infer transmission. However, poor resolution of phylogenetic trees using short/moderate reads make it difficult to test which processes generated these patterns.
  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 ascertain whether multiple long-lived lineages of virus exist, and whether they are consistent across the whole genome. Further, you will test whether population subdivision is due to selective or non-selective processes, and whether it differs for cirrhotic and non-cirrhotic individuals. Finally, you will use this data to determine the consequences for determine who-infected-whom using genetic data. This is a crucial question for public health, as it will help determine where intervention efforts should be focussed.

training:
  --       During this DPhil you will learn how to analyse next-generation viral whole-genome sequencing (WGS) data
  --       Develop and use phylogenic models, including structured coalescent models, to determine the extent and tempo of within-host population turnover
  --       Develop viral transmission models to determine the effect of within-host population structure on between-host evolutionary dynamics
  --       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:
  --      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
supervisors: Dr Katrina Lythgoe and Professor Jane A. McKeating
mix: 100% dry lab
title:
  Determining the role of Hepatitis B virus cccDNA transcriptional activity in increasing the lifespan of episomal cccDNA

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. 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. There is considerable interest in determining the lifespan of cccDNA molecules, and the mechanisms resulting in its longevity, to design and evaluate new curative treatments.
  We previously reported an evolutionary mathematical model of cccDNA persistence (Lythgoe et al., 2021), based on within-host next-generation sequencing to data, to estimate cccDNA lifespan. However, our estimated values cannot explain the long-term persistence of cccDNA in most patients, suggesting that key processes are missing from our understanding. Working closely with the McKeating group, you will incorporate new data to refine these models, and to better understand the mechanisms regulating cccDNA half-life. This will include both the replenishment of cccDNA via pgRNA-rcDNA, where encapsidated genomes recycle to the nucleus, and the variation in cccDNA transcriptional activity over the course of infection. Specifically, you will test the hypothesis that HBV cccDNA transcriptional activity increases the lifespan of episomal genomes.

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
  --      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: mentzer_alexander
title: The functional consequences of human genetic variation on response to infectious disease
supervisors: Dr Alexander Mentzer, 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 Wellcome Centre, 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 but there are multiple complex regions and diseases that can be studied allowing for a programme tailored to any interested student. The genomic regions of particular interest include the major histocompatibility complex and immunoglobulin loci with diseases including viral infections (such as herpes, hepatitis, HIV and coronavirus) and bacterial diseases that may cause sepsis.
  Any sub-project under this 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, long-range sequencing characterisation and mapping of RNA-Seq reads for Immunoglobulin loci, and metagenomic approaches for pathogen detection in whole blood RNA. There may also be increasing opportunities to look at the effects of human genetics on responses to novel agents of interest such as SARS-CoV-2, the cause of COVID-19. 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*, 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>
  Insert any additional project description(s) on subsequent pages if applicable.  Please use the same template and use separate pages for each project.


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: schuster-böckler_benjamin
title: Early detection of liver cancer using cell-free DNA and other measurements
supervisors: Benjamin Schuster-Böckler, Ellie Barnes
mix: 100% dry lab
description:
  Liver cancer is common amongst patients who have been diagnosed with liver cirrhosis, but so far it is not possible to reliably predict which cirrhosis patient will develop cancer. This makes it costly and difficult to screen the large at-risk population.
  My group is participating in a large trial funded by CRUK to address this critical clinical need. There are two cohorts, a retrospective and a prospective cohort. For both groups, a number of measurements are collected at different time-points: ultrasound imaging, protein biomarkers, metabolomics data from the blood, and cell-free DNA methylation.
  If you choose this project for a rotation, you will first work on the cell-free DNA data. We will try to determine liver-cancer specific features in the methylation patterns and the read-density from cancer and control patients. We will also search for known liver-cancer mutations in the cfDNA.
  If you continue on to a DPhil, the aim will be to fully develop the cell-free DNA analysis into an assay. This will involve developing a robust classifier, quantifying the accuracy and variability of the classifier, estimating the positive predictive value, and determining the minimal set of genomic regions that are informative, in order to reduce the sequencing cost. The next step will be to integrate the predictions from cell-free DNA with the information from the other measurements, to determine whether the accuracy of the test can be further improved by incorporating other data.

training:
  This project would suit a statistically minded person who would like to work on a real-world problem using genomic data. You would learn basic computational genomics techniques and get expose to biomarker discovery and evaluation in the setting of a large collaborative project.

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).
  -- <a href="https://www.oxcode.ox.ac.uk/research-showcase/liver-cancer">https://www.oxcode.ox.ac.uk/research-showcase/liver-cancer</a>
  -- Siejka-Zielińska, P. et al. Cell-free DNA TAPS provides multimodal information for early cancer detection. Sci Adv 7, eabh0534 (2021).


pi_id: schuster-böckler_benjamin
title: The epigenetic landscape of the human body
supervisors: Benjamin Schuster-Böckler, Chunxiao Song
mix: 100% dry lab
description:
  DNA methylation is an important determinator of cell fate by “switching off” certain genes that are not needed in more differentiated cells. Methylation - and its further modified form of “hydroxymethylation” - also impact on the activity of retroviruses, transposable elements and non-coding RNA, they are involved in DNA repair processes, and might affect a range of other biological processes, some of which are not yet fully understood.
  The Song lab developed methods to measure methylation and hydroxymethylation using much milder chemistry compared to existing approaches. They now created an atlas of cell- or tissue-type specific methylation and hydroxymethylation from dozens of different sites in the body, as well as various cancer types. This unique resource of nearly 200 whole-genome epigenetic maps can be used to address a whole range of biological questions regarding the function and impact of DNA modifications.
  For the rotation phase of the project, you would investigate basic covariates in the data, such as the relationship between epigenetic patterns within the same tissue depending on age or gender of the donor, and whether there are tissue independent features that consistently change with age or gender.
  For the continuation into a DPhil, you could  e.g. investigate tissue-dependent methylation and hydroxymethylation patterns inside and outside of regulatory elements, to deepen our understanding of the biological role of these marks. We would also aim to use these maps to explore the relationship between methylation and chromatin structure and develop ways to apply this knowledge for early disease detection, for example using cell-free DNA or other biopsies.

training:
  This project would suit anyone with an interest in genome biology who is keen to perform statistical analysis on large data. You would learn basic computational genomics techniques and gain a lot of knowledge on the role and function of epigenetic regulation in health and disease.
  Background Reading/References
  -- Greenberg, M. V. C. & Bourc’his, D. The diverse roles of DNA methylation in mammalian development and disease. Nat Rev Mol Cell Biol 20, 590-607 (2019).
  -- Liu, Y. et al. Bisulfite-free direct detection of 5-methylcytosine and 5-hydroxymethylcytosine at base resolution. Nat Biotech 37, 424-429 (2019).
  -- Liu, Y. et al. Subtraction-free and bisulfite-free specific sequencing of 5-methylcytosine and its oxidized derivatives at base resolution. Nat Commun 12, 618 (2021).


pi_id: schuster-böckler_benjamin
title: What drives trophoblastic tumours?
supervisors: Benjamin Schuster-Böckler, Máire Ní Leathlobhair, Yang Shi
mix: 50% dry lab, 50% wet lab
description:
  Gestational trophoblastic disease (GTD) describes a group of rare pregnancy-related tumours arising from the abnormal development of trophoblast, the cells that form the placenta. Globally, 18,000 women per year develop GTD and disease has a distinct pattern of geographical distribution, with higher incidence in the developing world. These tumours are unconventional biological entities - they are the only example of a human tumour that develops from the cells of another individual, the fetus.
  To date there has been relatively little work examining the potential role of genetic and epigenetic changes in the pathogenesis of gestational tumours. Limited sequencing data suggests that tumours have an extremely low mutation rate and harbour very few recurrent genetic events similar to many paediatric malignancies. Moreover, recent data suggests that that the malignant phenotype is more likely to be based on epigenetic rather than genetic changes. We recently managed to get access to a large number of GTD samples which are ready to be processed, providing a unique resource to study the biology of this disease and the mechanisms that underpin early development.
  The focus of the rotation project would be to characterize DNA patterns across a ‘discovery cohort’ of GTD tumours, as well as normal placenta at different stages of development, and to apply clustering approaches to identify distinct disease subgroups. You would then further characterize and validate the most predictive genomic regions in a large cohort of GTD tumours.
  The next stage of this project, if you continue on to a PhD, would be to work with laser-capture microscopy to excise and sequence clusters of trophoblast cell subtypes from different GTDs. By applying RNA and DNA methylation sequencing to samples, the aim is to identify the specific alterations that define their proliferative phenotype, to determine whether these differ between trophoblast clones, and to compare this to similar data from normal placental samples.
  The placenta plays a crucial role as the interface between mother and child during pregnancy and placenta-related complications of pregnancy, including GTD, are a major challenge for maternal health. This research has the potential to inform our understanding of the early stages of placental development and, in particular, the processes controlling proliferation and how these can go awry.

training:
  This project involves both experimental and computational work. You would have a chance to delve into computational genomics techniques as well as learning to perform DNA methylation experiments using the novel TAPS assay, single-cell RNA-seq and low-volume DNA-seq experiments.
  Background Reading/References
  -- Savage, P. et al. A case of intraplacental gestational choriocarcinoma; characterised by the methylation pattern of the early placenta and an absence of driver mutations. BMC Cancer 19, 744 (2019).
  -- Seckl, M. J. et al., Gestational trophoblastic disease. The Lancet 376, 9742 (2010).
  -- Coorens, T.H.H. et al. Inherent mosaicism and extensive mutation of human placentas. Nature 592, 80–85 (2021).


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: Transcriptional blueprint of neutrophil development during homeostasis and disease
supervisors: Professor Irina Udalova, Dr Abhinandan Devaprasad. Prof Julia Knight
mix: 30% wet lab, 70% dry lab
description:
  Neutrophils exert anti-microbial activity through several mechanisms including release of cytotoxic products, reactive oxygen species (ROS), neutrophil extracellular traps (NETs) and pore-forming molecules. The presence of immature neutrophil subsets with abnormal functions are consistently associated with inflammation-driven pathologies, including vasculitis, sepsis and severe Covid19. The molecular control of pathogenic neutrophil responses is largely unknown. We have recently developed a state-of-the-art genomic platform to reveal transcriptional circuits that control neutrophil function and identified novel putative regulators. The identified transcriptional regulators were functionally validated using genetic CRISPR-Cas9 mediated ablation ex vivo. We assessed the ability of genetically modified neutrophils to control the production of inflammatory mediators and ROS, form NETs etc and highlighted the regulators that were essential for neutrophil development and/or activation. We are currently developing new mouse models for neutrophil-specific deletion of the identified key regulators.
  image://images/udalova_irina_01.png
  Figure: Model of transcriptional regulation of neutrophils during inflammation. 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 Nature Immunology 2021).
  The goal of this project is to generate the regulatory blueprint of neutrophil states during development and in a signal-driven microenvironment based on the already identified and functionally validated novel neutrophil regulators. This will be done by using a combination of advanced genomic, epigenomic, immunological techniques, including cutting edge single cell technologies. The multi-scale computational analysis and modelling will be used for quantitative analysis and interpretation of resulting experimental data. The work will also inform understanding of the mechanistic basis of genetic drivers of individual variation in neutrophil gene function arising from expression quantitative trait mapping, for example allele-specific differences involving key transcriptional regulators. There is also the opportunity to extend the approach to work with primary neutrophils from patients with severe infection through established local studies to understand context-specific effects.
  The outcome of this study is expected to progress fundamental biology of neutrophils, increase our understanding of neutrophil activated subsets in disease and aid the development of new targets for therapeutic interventions in inflammatory disorders.

training:
  Training will be provided in techniques in a wide range of functional genomics approaches (RNA-Seq, ATAC-Seq, ChIP-Seq), immunological (cell isolation, tissue culture, FACS), and imaging (immunofluorescence on tissue sections) approaches, as well as cutting edge single cell platforms (10x, CyTOF) and computational pipelines. Recently developed novel in vivo models of inflammatory diseases will be extensively used and new models will be generated. Students will attend weekly seminars within the department and those relevant in the wider University and receive training in scientific writing and communication through oral presentations to the scientific community at international conferences. Students will also have the opportunity to work closely with members of the Oxford Covid19 immunology network, as well as Novonordisk Immunometabolism consortium (Oxford/Karolinska Institute/University of Copenhagen).

background_reading:
  -- Ai Z, Udalova IA. Transcriptional Regulation of Neutrophil Differentiation and Function During Inflammation. Journal of Leukocyte Biology 2020 Mar;107(3):419-430.
  -- 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.
  -- 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.
  -- Kwok  A, Allcock A, Ferreira R, Smee M, Cano-Gamez E, Burnham KL, Zurke YX, Oxford acute medicine/ED research, McKechnie S, Monaco C, Udalova IA, Hinds CE, Davenport EE, Todd JA and Knight JC. Identification of deleterious neutrophil states and altered granulopoiesis in sepsis. medRxiv 2022.03.22.22272723.


