# 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: data/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: data/images/brennan_paul.png
titles:
  Professor of Medicinal Chemistry, Head of Chemistry – Alzheimer’s Research UK Oxford Drug Discovery Institute, Group Leader


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


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


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


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


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


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


id: knight_julian
name: Professor Julian Knight
location: Wellcome Centre for Human Genetics
department: Nuffield Department of Medicine
group: Knight group
url: https://www.well.ox.ac.uk/people/julian-knight
email: julian.knight@well.ox.ac.uk
image: data/images/knight_julian.png
titles:
  Professor of Genomic Medicine, 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: data/images/mccullagh_james.jpeg
titles:
  Director of the Mass Spectrometry Research Facility and group leader, Associate Professor of Analytical Chemistry


id: taylor_jenny
name: 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: data/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: data/images/udalova_irina.jpeg
titles:
  Professor of Molecular immunology. Associate Director of the Kennedy Institute of Rheumatology in Data Science. Head of Laboratory of Genomics of Inflammation, Group Leader / PI, Member of congregation


# research

pi_id: ansari_azim
themes: 1,3,5
overview:
  We investigate infectious diseases and the role of host and pathogen genetic variation on the outcome of infection. Genome-wide association studies (GWAS) aim to identify the genetic basis of phenotypic traits using the variation that exists within natural populations. Uniquely for infectious diseases, the inter-individual heterogeneity in disease phenotype is linked to both host and pathogen genetic variation. Traditionally, genetic studies of infectious diseases have sought to explain between-individual variation in disease phenotypes by assessing genetic factors separately in humans or pathogens, under the assumption that these factors are independent. We integrate host and pathogen genomic data from the same patients to better understand pathogenesis and between-individual heterogeneity in disease outcomes. Using paired host-pathogen data we aim to identify (a) host polymorphisms linked with pathogen sequence variation, (b) pathogen sites under strong host genetic selective pressures, (c) host and virus genetic factors independently contributing to disease phenotypes and (d) host-virus genetic interactions contributing to disease phenotypes. The findings have the potential to: (I) revolutionize our understanding of host-pathogen interactions and human biology; (II) aid in development of more effective vaccines, drug targets and immunotherapies; and (III) permit better use of therapies through patient stratification. 
  Our work focuses on viral infections of hepatitis B and C viruses (HBV and HCV), human immunodeficiency virus (HIV) and SARS-CoV-2. The datasets available for this project include host and virus genomic data from large cohorts of HCV infected individuals (5000 from the UK, 2000 from Pakistan and 1000 from Vietnam) where we have collected extensive clinical information; host and virus genomic data on a cohort of 5000 individuals with HBV infection (from China) with extensive clinical information and host and virus genomic data on a cohort of 2000 individuals with SARS-CoV-2 infection with treatment outcome and viral load measurements. 
  In the age of “Big Data” and “Personalised Medicine”, analysis of paired host-pathogen genomic data will become increasingly important to uncover the mechanisms driving pathogen adaptations and heterogeneity of infection outcomes.
  We are a cross‐disciplinary group, based both at the Peter Medawar Building for Pathogen Research and the 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: band_gavin
themes: 1,3,5
overview:
  Our group is focussed on host-pathogen interactions, with a particular focus on the malaria parasite Plasmodium falciparum. We are taking a range of experimental and computational approaches to try to understand the interactions that have been discovered so far (described in <a href="https://doi.org/10.1038/s41586-021-04288-3">Band et al Nature 2021</a> and <a href="https://doi.org/10.1101/2023.09.14.557461">Hamilton et al bioRxiv 2023</a>), and are building data and methods to search for currently unknown interactions.
  Genomic interactions form a rich area of study. One reason is that any interaction that affects the success of parasites to transmit (or that affects the ability of humans to survive their infections) places selective pressure on the populations. Rapid genome evolution is often a result. Because of this we are interested in complex regions of the parasite and human genomes, and in methods and technologies that can resolve structural variants and other complex variation. To this end we have been developing methods to use long-read sequencing to assemble genomes and resolve variation in some of the most complex genome regions - including those encoding the immune system (e.g. as described in <a href="https://doi.org/10.1371/journal.pcbi.1009254">Zhang et al 2021</a>).
  Project areas: Malaria genomics, host-pathogen coevolution, long read methods and genome assembly, structural variation and complex genome regions, population genetics and genome-wide association studies.
  Specific project proposals:
  -- Resolve T cell receptor diversity using long-read sequencing!


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
themes: 6
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: gill_deborah
overview:
  The manipulation of nucleic acids for therapeutic purposes (gene therapy, gene editing, etc) is generating success in the clinic. A key challenge, however, is to understand and control the delivery and expression of genes in target tissues. My research focuses on the development of genetic treatments for respiratory conditions with a large unmet clinical need. We have substantial expertise in the development of novel non-viral and viral gene delivery systems; we developed a CpG-free plasmid DNA/cationic liposome formulation for the treatment of cystic fibrosis (CF) lung disease that successfully completed a Phase IIb clinical study in 136 CF patients, which showed for the first time that gene therapy could halt the inexorable decline of lung function that leads ultimately to the premature death of CF patients. In the viral vector space, we are developing novel, lung-targeted lentiviral and AAV vectors for a range of lung disorders and applications. 
  In particular, there is an urgent need for treatments for childhood Interstitial Lung Diseases (ILD), affecting the interstitium - the tissue in and around the alveoli (air sacs) of the lungs. In adults, ILD often occurs after a lung injury triggers an abnormal healing response causing thickened, fibrotic alveolar tissue, leading to poor lung function. In children, ILD is more typically caused by genetic conditions, several of which can be lethal at birth. There are very few interventions/treatments available for these rare genetic diseases, with life expectancy typically measured in weeks or months. For example, genes involved in lung surfactant production are essential for establishing a healthy lung in newborns and studies in transgenic mouse models have provided proof of principle for therapeutic gene therapy/gene editing approaches. We are therefore developing a genetic treatment for a range of childhood ILDs, including deficiencies in surfactant protein B, surfactant protein C, and adenosine triphosphate-binding cassette transporter A3 (ABCA3).
  Project areas: Gene editing, gene therapy, transgenic mouse models, human lung culture models.
  Please contact directly for further information.


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


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


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

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

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


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


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


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


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


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


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


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


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


pi_id: 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: 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:
  -- Genomic landscape of neutrophil states in inflammation: morphology, behaviour, function, and interactions
  -- Granulopoiesis: chromatin topology and associated functions
  Please contact directly for further information.


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


pi_id: whiffin_nicola
themes: 3,4,5
overview:
  Although individually rare (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: Detecting and dissecting host-pathogen genetic interactions
supervisors: Dr. Azim Ansari and Dr. Gavin Band
mix: 0% wet lab, 100% dry lab
description:
  The outcome of infections depends on a complex interplay of interactions between host cells and the pathogens that invade and replicate inside them.  Underlying this is natural genetic variation, but little is known about the mutations involved, their biological function or how they interact.  In this project, you will work with Dr. Azim Ansari (Medawar) and Dr. Gavin Band (Wellcome Centre for Human Genetics) to develop and apply statistical genetic methods that will improve our understanding of this.  There are several key challenges to overcome which could form the source of a rotation project, including
  -- Population genetics and natural selection: infections are a major source of natural selection on the human genome, and human resistance alleles provide a strong selective force on pathogens.  But how this plays out at the level of populations is mostly unknown.  It could involve stable interactions between segregating mutations, but also selective sweeps or development of complex genetic diversity through diversifying or balancing selection.  Understanding this is important because it shapes attempts to discover genetic interactions and, ultimately, to discover new aspects of infection biology.  A key way to gain a better understanding of this will be to conduct population-genetic simulations, potentially incorporating host-pathogen interactions, spatial aspects, recombination and mutation, between-pathogen competition and potentially epistasis, to generate realistic population-genetic outcomes.  You will then compare that to real population datasets.
  -- Robust methods for genotyping complex variation in human and pathogen genomes are needed.  Both Dr. Ansari and Dr. Band are engaged in projects to leverage new developments in long-read sequencing.  There is an opportunity for you to contribute by developing targeted assays for genomic regions of interest, apply long-read methods such as Oxford Nanopore Technologies MinION, and conduct in silico work to call and analyse the resulting data, and apply results to existing datasets.
  -- An important feature of infections is that they are often mixed – that is, they consist of more than one genetic type of pathogen at the same time.  Current analysis methods deal with this in limited and ad hoc ways, such as simply taking a ‘majority’ or arbitrary genotype call at each locus, but as a result they can lose power.  You will develop better methods to handle this in the context of host-pathogen analyses, either by exploiting genome-wide data or panels of known sequences to estimate and exploit the mixture composition of infections, from genome-wide sequence data.
  This work will be carried out using large datasets on Hepatitis B and C, HIV and malaria infections.

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

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


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

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

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


pi_id: band_gavin
title: Resolve T cell receptor diversity using long-read sequencing!
supervisors: Dr. Gavin Band, Prof. Julian Knight and Prof. John Todd
mix: 0% wet lab, 100% dry lab
description:
  Some of the most complex, diverse and important parts of the human genome are those that encode for adaptive immunity.  Among these, the immunoglobulin regions (which code for antibody diversity) and the T cell receptor regions are particularly important, but also particularly hard to study using traditional methods.  In this project you will develop new computational methods to try to resolve T cell receptor diversity using long-read sequencing data.
  image://data/images/band_gavin_01.png
  <b>Figure 1</b>: a schematic of the T cell receptor alpha / delta locus
  This approach exploits a key feature of T cell development: the T cell receptor regions undergo somatic recombination (so called 'VJ' or 'V(D)J' recombination) to generate a large number of different haplotypes carried by different T cells.  These recombinations splice together different gene components to make the functional receptor genes.  This is one of nature's most complex and beautiful mechanisms of generating genetic diversity, and is a core component of what makes immunity 'adaptive' in the first place.
  We recently worked with Pacific Biosciences (PacBio) and with Oxford Nanopore Technologies (ONT) to generated high-coverage long-read sequencing data for a healthy volunteer codenamed 'HV31'.  Crucially, because this is long-read data, sequencing reads from recombinant T cells are easily visible because they don't align in one piece to the genome.  In other words, the reads capture both the germline structure of the genome and somatically rearranged DNA from T cells.
  Your mission (if you choose to accept) it is to:
  -- Learn to analyse long-read sequencing data from PacBio and ONT.
  -- Find a way to extract out reads in the T cell receptor regions, that come from the somatic recombinant T cells.
  -- Use the reads to estimate the proportion of T cells in the sample.
  -- Estimate the proportion of αβ versus γδ T cells in the sample (which can be distinguished as they undergo different recombination processes).
  -- Identify and determine the different T cell recombinant haplotypes - for example by clustering the reads and aligning them to each other - and predict gene content.
  -- Analyse the T cell receptor diversity in HV31, at least at a broad scale.
  -- Analyse patterns of methylation on these recombinant haplotypes.
  The work is part of a larger project to assemble and align functional data to the HV31 genome, and there are many opportunities to pursue it further.

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

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


pi_id: band_gavin
title: An atlas of long-range LD in the malaria parasite genome
supervisors: Dr. Gavin Band
mix: 0% wet lab, 100% dry lab
description:
  Our recent work turned up an extremely puzzling feature of the malaria parasite genome: the presence of long-range linkage disequilbrium (LD) in African parasite genomes.  In other words - we found pairs of mutations that are almost always observed together in the same parasites, even though they lie very far apart in the genome (<a href="https://doi.org/10.1038/s41586-021-04288-3">Band et al Nature 2021</a>).
  image://data/images/band_gavin_02.png
  <b>Figure 1</b>: regions of outlying LD in the malaria parasite genome.
  This was surprising because malaria parasites undergo meiosis and recombination during transmission through the mosquito - an obligate part of the lifecycle.  If long-range LD is present, it suggests selective forces - possibly epistasis - must be operating to maintain it.  But right now we don't know the full extent of the loci that are involved or the forces involved.
  In this project you will shine light on this by exploiting the largest set of malaria parasite genome sequences currently available (<a href="https://www.malariagen.net/apps/pf7/">the MalariaGEN Pf7 dataset</a>) to estimate long-range LD in global parasite populations, using tools developed by the group.  The output will be an 'atlas of long-range LD'.  You will aim to replicate previous findings,identify possible new signals of LD that we don't know about yet, and compare LD between populations.

training:
  You'll learn to work with large-scale genotyping datasets, and to build computational pipelines that can make this tractable.  You'll develop new methods and visualisations to describe signals of LD across populations, and you'll start to think about the complicated population genetics that must underlie these signals.

background_reading:
  -- Band et al.,  "Malaria protection due to sickle haemoglobin depends on parasite genotype" Nature (2021) <a href="https://doi.org/10.1038/s41586-021-04288-3">https://doi.org/10.1038/s41586-021-04288-3</a>


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

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

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


pi_id: beagrie_robert
title: Tissue-specific regulation of chromatin proteins in neural development
supervisors: Dr. Robert Beagrie
mix: 20% wet lab, 80% dry lab
description:
  Mutations chromatin organising genes cause a group of human syndromes called “chromatinopathies”. Loss of function mutations in these chromatin genes are frequently associated with some degree of impaired neural development. Some of these same genes are also more highly expressed in the brain than they are in other organs. These kinds of tissue-specific gene expression patterns are usually driven by regulatory DNA regions called enhancers. Common genetic variants that are associated with small changes in susceptibility to human disease can affect enhancers. Rare loss of function variants in the genes driven by these enhancers are often associated with a much higher risk of similar diseases. We therefore hypothesise that common human sequence variants affecting neural enhancers of chromatin genes might contribute to common neurological diseases (e.g. mental health issues)
  The aim of this rotation project would be to identify potential neural enhancers driving brain-specific upregulation of chromatin genes in normal development. This would be done by exploring published datasets of open chromatin regions (bulk and single-cell ATAC-seq), histone modifications (ChIP-seq, single-cell CUT&TAG) and gene expression (bulk and single-cell RNA-seq) for various neural lineages. If we can identify possible enhancers, we would then ask whether any of these regions contain known sequence variants linked to common human disease (e.g. variants identified in Genome Wide Association Studies for mental health conditions).
  There would also be the opportunity to validate brain specific expression patterns of the genes in question if the student particularly wanted to gain some wet-lab experience as part of this project.

training:
  Students would be trained in analysis and mining of ATAC-seq, ChIP-seq, CUT&TAG, single-cell RNA-seq and Hi-C datasets. Computational analyses and training can be conducted in either R or Python according to the student’s preference. The student could also learn RNA extraction, qPCR and immunofluorescence as wet-lab techniques.

background_reading:
  -- Valencia AM and Pașca SP (2022). Chromatin Dynamics in Human Brain Development and Disease. Trends in Cell Biology. Available at: <a href="https://doi.org/10.1016/j.tcb.2021.09.001">https://doi.org/10.1016/j.tcb.2021.09.001</a>
  -- Ummi C and van Bokhoven H (2020). The Phenomenal Epigenome in Neurodevelopmental Disorders. Human Molecular Genetics. Available at: <a href="https://doi.org/10.1093/hmg/ddaa175">https://doi.org/10.1093/hmg/ddaa175</a>
  -- Ziffra RS et al. (2021). Single-Cell Epigenomics Reveals Mechanisms of Human Cortical Development. Nature. Available at: <a href="https://doi.org/10.1038/s41586-021-03209-8">https://doi.org/10.1038/s41586-021-03209-8</a>


pi_id: beagrie_robert
title: Studying histone modifications in a mouse model of Cornelia de Lange Syndrome
supervisors: Dr. Robert Beagrie
mix: 50% wet lab, 50% dry lab
description:
  DNA loops allow enhancers to contact and activate their target genes in the 3D space of the nucleus. These loops are formed and stabilised by CTCF (a zinc-finger transcription factor) and cohesin (a ring-shaped multi-protein complex). Mutations in components of the cohesin complex cause a rare genetic disease called Cornelia de Lange Syndrome (CdLS) which affects between 1 in 10,000 and 1 in 50,000 individuals. Around 30% of CdLS patients are born with congenital heart defects. This project aims to understand the molecular mechanisms linking disrupted DNA loop formation with heart development.
  Our lab works with mice that have a conditional knockout Nipbl allele as heterozygous loss of function mutations in NIPBL are the most common cause of CdLS. These mice also suffer from heart defects at similar frequencies to human patients (around 30%). In this project you will study histone modifications in early cardiac tissue using CUT&TAG and uncover which regulatory elements (specifically enhancers and promoters) are misregulated in CdLS. The project consists of both lab work and data analysis, and is will hopefully provide new insight in to cardiac-specific gene regulation as well as the role of cohesin in development.

training:
  Students would be trained in preparation of material for CUT&TAG and in analysis of CUT&TAG datasets. There may also be opportunities to incorporate other techniques.

background_reading:
  -- Santos R et al. (2016). Conditional Creation and Rescue of Nipbl-Deficiency in Mice Reveals Multiple Determinants of Risk for Congenital Heart Defects. PLOS Biology. Available at: <a href="https://doi.org/10.1371/journal.pbio.2000197">https://doi.org/10.1371/journal.pbio.2000197</a>
  -- Kawauchi S et al. (2009). Multiple Organ System Defects and Transcriptional Dysregulation in the Nipbl+/− Mouse, a Model of Cornelia de Lange Syndrome. PLoS Genetics. Available at: <a href="https://doi.org/10.1371/journal.pgen.1000650">https://doi.org/10.1371/journal.pgen.1000650</a>
  -- Bartosovic M et al. (2021). Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nature Biotechnology. <a href="https://doi.org/10.1038/s41587-021-00869-9">https://doi.org/10.1038/s41587-021-00869-9</a>


pi_id: bhattacharya_shoumo
supervisors: Shoumo Bhattacharya, Graham Davies
mix: 70% wet lab, 30% dry lab
title:
  Identifying the molecular basis of chemokine:receptor binding using phage-display and application to peptide theranostic development’

description:
  The 24 chemokine receptors are GPCRs that either cause leucocyte migration or act as ‘sumps’ to neutralize chemokines (3). The molecular basis of these interactions will be decoded by screening a receptor phage-display library with matrix attached chemokines and analysed by NGS. SLiM-peptides identified will be studied for biochemical (e.g., binding to target by fluorescent polarisation, protein-interaction disruption using bead-capture assays) and biological activity (e.g., receptor dimerization using proximity-ligation assay, cell migration assays).

training:
  Molecular biology, cloning, protein interactions, phage-display, analysis of NGS datasets, R scripting, network analysis, cell biology, chemotaxis, flow cytometry.

background_reading:
  1.  Ivarsson, Y., and Jemth, P. (2019). Affinity and specificity of motif-based protein-protein interactions. Curr Opin Struct Biol 54,26-33, 10.1016/j.sbi.2018.09.009
  2.  Mclaughlin, M.E., and Sidhu, S.S. (2013). Engineering and analysis of peptide-recognition domain specificities by phage display and deep sequencing. Methods Enzymol 523, 327-349, 10.1016/B978-0-12-394292-0.00015-1
  3.  Kufareva, I., Gustavsson, M., Zheng, Y., et al. (2017). What Do Structures Tell Us About Chemokine Receptor Function and Antagonism? Annu Rev Biophys 46, 175-198, 10.1146/annurev-biophys-051013-022942
  4.  Bhusal, R.P., Eaton, J.R.O., Chowdhury, S.T., et al. (2020). Evasins: Tick Salivary Proteins that Inhibit Mammalian Chemokines. Trends Biochem Sci 45, 108-122, 10.1016/j.tibs.2019.10.003
  5.  Darlot, B., Eaton, J.R.O., Geis-Asteggiante, L., et al. (2020). Engineered anti-inflammatory peptides inspired by mapping an evasin-chemokine interaction. J Biol Chem 295, 10926-10939, 10.1074/jbc.RA120.014103
  6.  Von Hundelshausen, P., Agten, S.M., Eckardt, V., et al. (2017). Chemokine interactome mapping enables tailored intervention in acute and chronic inflammation. Sci Transl Med 9, 10.1126/scitranslmed.aah6650


pi_id: bhattacharya_shoumo
supervisors: Shoumo Bhattacharya, Graham Davies
mix: 70% wet lab, 30% dry lab
title:
  Identifying the molecular basis of chemokine oligomerization using phage-display and application to peptide theranostic development’

description:
  Chemokine oligomerization is critical for function (6). The molecular basis of these interactions will be decoded by screening a chemokine phage-display library with matrix attached chemokines and analysed by NGS.  SLiM-peptides identified will be studied for biochemical (e.g. binding to target by fluorescent polarisation, protein-interaction disruption using bead-capture assays) and biological activity (e.g. receptor dimerization using proximity-ligation assay, cell migration assays).

training:
  Molecular biology, cloning, protein interactions, phage-display, analysis of NGS datasets, R scripting, network analysis, cell biology, chemotaxis, flow cytometry.

background_reading:
  1.  Ivarsson, Y., and Jemth, P. (2019). Affinity and specificity of motif-based protein-protein interactions. Curr Opin Struct Biol 54,26-33, 10.1016/j.sbi.2018.09.009
  2.  Mclaughlin, M.E., and Sidhu, S.S. (2013). Engineering and analysis of peptide-recognition domain specificities by phage display and deep sequencing. Methods Enzymol 523, 327-349, 10.1016/B978-0-12-394292-0.00015-1
  3.  Kufareva, I., Gustavsson, M., Zheng, Y., et al. (2017). What Do Structures Tell Us About Chemokine Receptor Function and Antagonism? Annu Rev Biophys 46, 175-198, 10.1146/annurev-biophys-051013-022942
  4.  Bhusal, R.P., Eaton, J.R.O., Chowdhury, S.T., et al. (2020). Evasins: Tick Salivary Proteins that Inhibit Mammalian Chemokines. Trends Biochem Sci 45, 108-122, 10.1016/j.tibs.2019.10.003
  5.  Darlot, B., Eaton, J.R.O., Geis-Asteggiante, L., et al. (2020). Engineered anti-inflammatory peptides inspired by mapping an evasin-chemokine interaction. J Biol Chem 295, 10926-10939, 10.1074/jbc.RA120.014103
  6.  Von Hundelshausen, P., Agten, S.M., Eckardt, V., et al. (2017). Chemokine interactome mapping enables tailored intervention in acute and chronic inflammation. Sci Transl Med 9, 10.1126/scitranslmed.aah6650


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

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

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

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


pi_id: 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


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

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

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

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


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

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

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


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

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


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

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

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


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

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

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


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

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

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

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


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

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

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

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


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

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

background_reading:
  R Hinch, P Donnelly, AG Hinch. Meiotic DNA breaks drive multifaceted mutagenesis in the human germline. Science (In press).
  AG Hinch et al. The Configuration of RPA, RAD51, and DMC1 Binding in Meiosis Reveals the Nature of Critical Recombination Intermediates. Mol Cell, 79 (4), pp. 689-701.e10.
  AG Hinch et al. Factors influencing meiotic recombination revealed by whole-genome sequencing of single sperm. Science, 363 (6433).
  B Davies et al. Re-engineering the zinc fingers of PRDM9 reverses hybrid sterility in mice. Nature, 530 (7589), pp. 171-6.
  AG Hinch et al. The landscape of recombination in African Americans. Nature, 476 (7359), pp. 170-5.


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


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

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

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


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

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

background_reading:
  -- Interaction  mapping of endoplasmic reticulum ubiquitin ligases identifies  modulators of innate immune signalling. Fenech EJ, Lari F, Charles  PD, Fischer R, Laétitia-Thézénas M, Bagola K, Paton AW, Paton JC,  Gyrd-Hansen M, Kessler BM, Christianson JC. Elife. 2020 Jul  2;9:e57306. doi: 10.7554/eLife.57306.
  -- Comprehensive  Landscape of Active Deubiquitinating Enzymes Profiled by Advanced  Chemoproteomics. Pinto-Fernández A, Davis S, Schofield AB, Scott  HC, Zhang P, Salah E, Mathea S, Charles PD, Damianou A, Bond G,  Fischer R, Kessler BM. Front Chem. 2019 Aug 29;7:592. doi:  10.3389/fchem.2019.00592.
  -- Molecular  basis of USP7 inhibition by selective small-molecule inhibitors.  Turnbull AP, Ioannidis S, Krajewski WW, Pinto-Fernandez A, Heride C,  Martin ACL, Tonkin LM, Townsend EC, Buker SM, Lancia DR, Caravella  JA, Toms AV, Charlton TM, Lahdenranta J, Wilker E, Follows BC, Evans  NJ, Stead L, Alli C, Zarayskiy VV, Talbot AC, Buckmelter AJ, Wang M,  McKinnon CL, Saab F, McGouran JF, Century H, Gersch M, Pittman MS,  Marshall CG, Raynham TM, Simcox M, Stewart LMD, McLoughlin SB,  Escobedo JA, Bair KW, Dinsmore CJ, Hammonds TR, Kim S, Urbé S,  Clague MJ, Kessler BM, Komander D. Nature. 2017 Oct  26;550(7677):481-486. doi: 10.1038/nature24451.
  image://data/images/kessler_benedikt_03.png
  1) Figure/Photo  – Cellular Ubiquitin System
  Figure 1: Cellular ubiquitin system – The turn-over of most proteins in cells are controlled by the attachment of ubiquitin, a small protein (black dots), to protein substrates. These are then recognised by the 26S proteasome complex for destruction into peptides and further degraded to amino acids (AAs). AAs are serving as building blocks for protein synthesis. The protein’s life cycle is perturbed in cancer and other human diseases, a trait that is the focus of this bioinformatics based research project.


pi_id: knight_julian
title: 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 publicly accessible data, for example from compound screens within the Library of Integrated Network-based Cellular Signatures together with existing genome-wide mutagenesis and CRISPR screens. This work is made tractable by our established collaborations with academia and industry. You will benefit from working within a supportive research group with a strong track record in graduate student training and mentoring. You will have the opportunity to regularly present your work within the group, to your peers within the Centre as well as at international conferences. Students are encouraged and supported to undertake further relevant training courses in Oxford and elsewhere depending on need.

background_reading:
  -- Fang H, Consortium U-D, De Wolf H, Knezevic B, Burnham KL, Osgood J, Sanniti A, Lledo Lara A, Kasela S, De Cesco S, Wegner JK, Handunnetthi L, McCann FE, Chen L, Sekine T, Brennan PE, Marsden BD, Damerell D, O'Callaghan CA, Bountra C, Bowness P, Sundstrom Y, Milani L, Berg L, Gohlmann HW, Peeters PJ, Fairfax BP, Sundstrom M & Knight JC. 2019 A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat Genet 51:1082-1091
  -- Fang H, Chen L & Knight JC. 2019 From genome-wide association studies to rational drug target prioritisation in inflammatory arthritis. The Lancet Rheumatology 2, 50-62
  -- Zhang P, Amarasinghe HE, Whalley JP, Tay C, Fang H, Migliorini G, Brown AC, Allcock A, Scozzafava G, Rath P, Davies B & Knight JC. 2022 Epigenomic analysis reveals a dynamic and context-specific macrophage enhancer landscape associated with innate immune activation and tolerance. Genome Biology 23, 136


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). 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. 2017 Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia. Am J Respir Crit Care Med 196, 328-339.
  -- Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, Rautanen A, Gordon AC, Garrard C, Hill AVS, Hinds CJ & Knight JC. 2016 Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med 4, 259-271.
  -- Fairfax BP, Humburg P, Makino S, Naranbhai V, Wong D, Lau E, Jostins L, Plant K, Andrews R, McGee C & Knight JC. 2014 Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949.
  -- COMBAT Consortium. 2022 A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. Cell 185, 916-938 e958.
  -- Maslove DM, Tang B, Shankar-Hari M, Lawler PR, Angus DC, Baillie JK, Baron RM, Bauer M, Buchman TG, Calfee CS, dos Santos CC, Giamarellos-Bourboulis EJ, Gordon AC, Kellum JA, Knight JC, Leligdowicz A, McAuley DF, McLean AS, Menon DK, Meyer NJ, Moldawer LL, Reddy K, Reilly JP, Russell JA, Sevransky JE, Seymour CW, Shapiro NI, Singer M, Summers C, Sweeney TE, Thompson BT, van der Poll T, Venkatesh B, Walley KR, Walsh TS, Ware LB, Wong HR, Zador ZE and Marshall JC (2022). Redefining critical illness. Nature Medicine 28, 1141-1148.


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

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


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

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

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


pi_id: leedham_simon
title: Stem cells and adaptive molecular phenotype in colorectal cancer (STAMP-CRC)
supervisors: Professor Simon Leedham
mix: can be wet or dry lab work, or mixture depending on student preference
description:
  Tumour heterogeneity plays a key role in cancer adaption and resistance to therapies, but understanding genetic heterogeneity alone cannot paint a complete picture. The forces of natural (and therapeutic) selection act upon phenotypic characteristics, and phenotype is a function of both the genotype and the microenvironment. The capacity to measure and understand relevant cancer cell phenotypic variation is key to monitoring neoplasia evolutionary trajectory. We believe that cancer stem cell molecular phenotype is an informative readout of dynamic evolutionary change within a tumour and is an important, and currently unmeasured metric that can improve prediction of tumour response to treatments, biologically inform existing therapy scheduling and drive the development of cancer cell adaption drug targets. Here we will assess demonstrable cross-species stem cell phenotypic heterogeneity in intestinal tumours, investigate the driving co-evolutionary interaction between the mutant epithelium and surrounding stromal/immune cell compartments, and assess the spatio-temporal impact of therapeutic selective pressures.
  image://data/images/leedham_simon_04.png

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


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

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

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


pi_id: luo_yang
title: Identifying the influence of HLA genetic variation on protein expression
supervisors: Yang Luo
mix: 100% dry lab
description:
  Variations of human leukocyte antigen (HLA) genes in the major histocompatibility complex region(MHC) play a vital role in our immune system and are of great importance to many areas of medicine,from organ transplantation and disease diagnosis to cancer immunotherapy. In autoimmune diseases,for example, the HLA-DRB1 allele is highly associated with seropositive rheumatoid arthritis, whileindividuals with HLA-B*27 alleles are 100 times more likely to develop active ankylosing spondylitis.Despite considerable advances in identifying genetic associations between HLA and a vast number ofimmune-mediated traits, the underlying molecular mechanisms behind these associations remainlargely unknown. In particular, proteins have key roles in various biological processes, includingsignalling, growth, repair and defence against infection. Proteins can serve as biomarkers for diseaserisk and clinical outcomes, and represent the targets of most approved drugs. Recent advances inscalable affinity-based proteomic techniques allow us to measure thousands of protein targetssimultaneously within an individual. Thus opens the opportunity for us to improve our understandingon how HLA variations influence genome-wide protein expression level. This project will focus onidentifying statistical associations between HLA alleles and protein expression (HLA-pQTL) in large-scale cohort data, including STEpUP OA, the UK Biobank and the China Kandoori Biobanks. We will conduct a systematic investigation of how HLA variants affect protein expression, and thus identifyingimprove our interpretation of the association between HLA and diseases.

training:
  The successful candidate will be benefit from supervision by a team of scientists with key expertise instatistical genetics, immunology and clinical science. You will be based in the Kennedy Institute ofRheumatology, a world-leading centre in genomics and inflammatory biology. Training will be providedin data science techniques including statistical data analysis and visualisation with R, the writing ofcomputational pipelines with Python/Nextflow, and the use of high-performance compute clusters.The student will gain expertise in analysing cutting-edge datasets including genotyping and proteomicsequencing. The primary supervisor, Dr. Yang Luo, is an expert in statistical genetics, and her labdevelops statistical methods and computational software to better understand the geneticcontributions to immune-mediated traits. The successful candidate is expected to meet her on aminimum weekly basis. The secondary supervisor, Professor Tonia Vincent, directs the Centre for OAPathogenesis, and has led the STEpUP OA consortium, the largest international effort to date to definemolecular endotypes within osteoarthritis. The STEpUP OA consortium measures protein signatures inthe synovial fluid of more than 2000 OA patients. The successful candidate is expected to meetProfessor Tonia on a monthly basis. The Kennedy Institute is a world-renowned research centre andhas a vibrant PhD program with weekly journal club, seminars, student symposia, weekly internalinstitute presentations and training. A core curriculum of lectures will provide a solid foundation of abroad range of subjects including data analysis, statistical methods and immunology summer school.Students will also have the opportunity to work closely with both computational and experimentalscientists.

background_reading:
  Please include references as desired.  Suggested format:
  -- [Surname] [Firstname],  [other authors]… (year in bold) . [Title]. [Journal name], [other details].  Available at: [link]


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>


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

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

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

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


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

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

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


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

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

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


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

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

background_reading:
  Please include references as desired.  Suggested format:
  -- Perez, M and Sarkies, P <a href="https://www.biorxiv.org/content/10.1101/2023.04.22.537846v1">https://www.biorxiv.org/content/10.1101/2023.04.22.537846v1</a>
  -- Findlay, L What is Cancer Metabolism? 2023 Cell, 186: 1670-1688 <a href="https://doi.org/10.1016/j.cell.2023.01.038">https://doi.org/10.1016/j.cell.2023.01.038</a>
  -- Morgan, M and Shilatifard, A Reevalulating the role of histone modifying enzymes and their associated chromatin modifications in transcription (2020) Nature Genetics, 52, 1271-1281. https://doi.org/10.1038/s41588-020-00736-4


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

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

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


pi_id: taylor_jenny
title: Identifying novel rare disease genes and variants from clinical whole genome sequencing data
supervisors: Prof. Jenny Taylor
mix: 100% dry lab
description:
  Rare genetic diseases are collectively common, even if individually rare, since they affect 1:17 people.  Reaching a genetic diagnosis for patients and their families not only resolves what is very often a lengthy diagnostic odyssey, sometimes lasting decades, but is often important in selecting the appropriate clinical management and treatment.  Historically, genetic testing encompassed targeted or exome sequencing, but the advent of affordable whole genome sequencing (WGS) has revolutionised the field and enabled genetic diagnostics to become mainstream across a range of medical specialties.
  The Genomics England 100,000 Genomes Project has sequenced the genomes from >75,000 rare disease patients and their family members and the WGS data are available to researchers in a secure Research Environment (RE). The diagnostic yield for 100,000 Genomes Project to date, based on pilot data, is 25%, which means there is a wealth of data still to interrogate.
  This project will investigate the WGS data in 100KGP to identify novel disease genes and variants. A particular focus will be on investigating structural and splice site variants using algorithms and pipelines developed by our group, including SVRare and AltSplicePredictor and GREEN-VARAN for structural, splicing and regulatory variants, respectively, as well as those available in the RE (eg SpliceAI). The focus will be on musculoskeletal and neurological disorders in 100KGP in first instance but the analysis approaches will be relevant to all rare diseases.

training:
  This project is designed to give an introduction to analysis of whole genome sequencing data using both well-established pipelines and bespoke tools developed in our lab.   Training will be with post- doc geneticists and bioinformaticians with extensive experience of these analyses. Findings can be validated using orthogonal approaches such as long read sequencing for structural variants (PacBIo, Nanopore, BioNano), RNA sequencing for splicing variants and other experimental assays for further functional validation. The group collaborates closely with a network of clinicians so there is an opportunity to understand the clinical consequences of the variants identified as well as identifying novel disease genes and variants.

background_reading:
  1) Taylor JC et al Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet. 2015;47(7):717-726. doi: 10.1038/ng.3304. PMID: 25985138;
  2) 100,000 Genomes Project Pilot Investigators et al. 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report. N Engl J Med. 2021;385(20):1868-1880. doi: 10.1056/NEJMoa2035790. PMID: 34758253;
  3) Lin YC et al;  SCUBE3 loss-of-function causes a recognizable recessive developmental disorder due to defective bone morphogenetic protein signaling. Am J Hum Genet. 2021 Jan 7;108(1):115-133. doi: 10.1016/j.ajhg.2020.11.015. PMID: 33308444;
  4) Giacopuzzi E, Popitsch N, Taylor JC. GREEN-DB: a framework for the annotation and prioritization of non-coding regulatory variants from whole-genome sequencing data. Nucleic Acids Res. 2022;50(5):2522-2535. doi: 10.1093/nar/gkac130. PMID: 35234913;
  5) Yu et al:  SVRare: discovering disease-causing structural variants in the 100K Genomes Project MedRxiv 2021; https://www.medrxiv.org/content/10.1101/2021.10.15.21265069v1


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

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


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


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


pi_id: tzima_ellie
title: 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 Helen Byrne
mix: 30% wet lab, 70% dry lab
description:
  Neutrophils represent a major arm of the innate immune defence system, with a long- held view of them being transcriptionally inactive, fast responders, mobilised in response to microbial and tissue insults. Recent developments in the field have changed this perception and firmly positioned neutrophils as transcriptionally active cells with the ability to adapt their transcriptional program. Our recent findings demonstrate that, despite limited residence times in tissues, neutrophils can tailor their properties to support organ homeostasis and mount tissue specific and transcriptionally regulated inflammatory response1,2. Importantly, in inflammation neutrophils are presented as functionally, morphologically, and behaviourally heterogeneous cells in circulation and tissue3.
  image://data/images/udalova_irina_05.png
  Figure: Model of transcriptional regulation of neutrophils during inflammation. Adopted from Chevre and Soehnlein, Nature Immunology News and Views on Ref 2, 2021. In the process of differentiation in bone marrow, lineage-determining transcriptional factors, including RUNX1, KLF6, CEBPE, and PU.1, are highly expressed and ensure gene expression programmes that promote proper neutrophil maturation. During the mobilization from the bone marrow into the blood, RFX2, RELB, IRF5 and JUNB become upregulated and transcriptionally accessible to support neutrophil cell survival and establish their effector function repertoire, whereas RUNX1 and KLF6 expression are silenced. Upon inflammation, circulating neutrophils migrate into the inflammatory sites, where they are exposed to inflammation-derived signals and become activated. Neutrophil activation leads to the activation of TFs, including RELB, IRF5 and JUNB, and subsequent TF binding to already accessible binding sites, thereby resulting in diverse TFs genomic occupancy and distinct transcriptional outputs (see Ref 2).
  The goal of this project is to reveal transcriptional circuits that control neutrophil differentiation and function in a signal-driven microenvironment. We aim to discover what transcriptional regulators control stage-specific expression of (1) cytoskeletal genes, that establish structural function and transcriptional regulation in the cell nucleus and distinct morphological features; (2) leukocyte migration and cell-cell interaction genes, responsible for distinct behaviour of neutrophils in the vasculature and tissue and (3) inflammatory response genes. This will be done by using a combination of cutting-edge imaging, genomic and spatial single cell transcriptomic approaches, as well as advanced immunological techniques2. Mathematical modelling of transcriptional circuits will be applied to understand the interaction between neutrophil development and activation. The project will also explore the spatial interactions of neutrophils with other immune cells in tissue using spatial transcriptomic and multimodal imaging data4. It will benefit from the already generated by us multiple genomic datasets and unique tools, such as genetically modified in vitro and in vivo models based on the recently discovered new key regulators2.
  The outcomes of this study are expected to progress fundamental biology of neutrophils and increase our understanding of neutrophil subsets in disease. This will ultimately lead to the development of a new class of therapeutic strategies, based on selective modulation of neutrophil biology, for therapeutic interventions in inflammatory disorders5.

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

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


pi_id: udalova_irina
title: Granulopoiesis: chromatin topology and associated functions
supervisors: Professor Irina Udalova, Dr Ananda Mukherjee, Prof Jim Hughes
mix: 50% wet lab, 50% dry lab
description:
  Granulopoiesis, the generation of new neutrophilic granulocytes, is crucial to health. During healthy neutrophil development its nucleus goes through dramatic morphological changes, from a simple round nucleus to a multi-segmented, lobulated nucleus. Indeed, the nuclear morphology is the main parameter used by pathologists to define the states of human neutrophil development. However, the molecular mechanisms controlling nuclear segmentation and the functional impacts of it are not understood.
  Chromatin architecture is what connects global nuclear shape and local regulation of gene expression. Chromatin is organized into distinct compartments within the nucleus and further segregated into spatially distinct regions. While neutrophils develop from progenitor cells to their multi-lobed form, long-range interactions are induced, leading to the chromatin contraction that may facilitate the folding of the neutrophil genome into the confined geometry of a toroid and segmented nucleus [1].
  image://data/images/udalova_irina_06.png
  Our recent work and results of others clearly demonstrate that neutrophils acquire different functions, such as production of reactive oxygen species, secretion of inflammatory molecules, formation of neutrophil extracellular traps, phagocytosis, bacterial killing etc, at different stages of their differentiation [2,3]. Moreover, we have identified and validated several key transcriptional regulators of neutrophil morphological development and/or functional responses [4]. This indicates that the transcriptional programming of morphological and functional maturation may be partially intertwined and are likely to be connected via changes in chromatin architecture.
  Here we will apply cutting edge chromatin conformation assays and gene expression analysis to correlate dynamic changes in the chromatin organization of the neutrophil genome to changes in gene expression and acquisition of specific functions during neutrophil maturation. Specific objectives:
  1.  To capture global chromatin topology changes during neutrophil differentiation using various cutting edge chromatin conformation capture (3-C) analyses of neutrophils throughout the differentiation trajectory [5]. Established computational pipelines would be used for visualization of contact maps, chromatin compartment analysis, chromatin compaction analysis, and finding differentially enriched topologically associating domains. The experimental setup would be used to assess changes to chromatin topology when key transcription factors for neutrophil development are depleted.
  2. To identify regions of local ‘topology dependent’ open and closed chromatin using ATAC-seq analysis to classify regions that show chromatinization changes (open/closed) in regions that gain/loss chromatin interactions. Single-cell ATAC-seq would be used for accessing heterogeneity in local chromatin conformation.
  3. To identify chromatin topology-dependent gene expression alterations using RNA-seq analysis to pin point genes that show topology and chromatin changes in their regulatory promoter/enhancer regions along the differentiation trajectory. The identified gene list will be checked for motifs for the previously identified key transcriptional regulators and validated in neutrophils with specific knock-out of these factors.
  The outcomes of this study are expected to unravel the regulation and functional consequences of the fundamental biological process, such as segmentation of neutrophil nucleus during the differentiation. This will lead to setting up a framework for further analysis of selective perturbations to this process during immunopathologies.

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

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


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

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

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


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

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

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

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


