Festival of Genomics 2024

I will be talking at the Festival of Genomics on Wednesday 24 January about Identifying virulence and antimicrobial resistance genes in bacterial using genome-wide association studies. You can preview my talk here.

New paper: GenomegaMap for dN/dS in over 10,000 genomes

Published this week in Molecular Biology and Evolution, is a new paper joint with the CRyPTIC Consortium "GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes".

The d_N/d_S ratio is a popular statistic in evolutionary genetics that quantifies the relative rates of protein-altering and non-protein-altering mutations. The rate is adjusted so that under neutral evolution - i.e. when the survival and reproductive advantage of all variants is the same - it equals 1. Typically, d_N/d_S is observed to be less than 1 meaning that new mutations tend to be disfavoured, implying they are harmful to survival or reproduction. Occasionally, d_N/d_S is observed to be greater than 1 meaning that new mutations are favoured, implying they provide some survival or reproductive advantage. The aim of estimating d_N/d_S is usually to identify mutations that provide an advantage.

Theoreticians are often critical of d_N/d_S because it is more of a descriptive statistic than a process-driven model of evolution. This overlooks the problem that currently available models make simplifying assumptions such as minimal interference between adjacent mutations within genes. These assumptions are not obviously appropriate in many species, including infectious micro-organisms, that exchange genetic material infrequently.

There are many methods for measuring d_N/d_S. This new paper overcomes two common problems:

• It is fast no matter how many genomes are analysed together.
• It is robust whether there is frequent genetic exchange (which causes phylogenetic methods to report spurious signals of advantageous mutation) or infrequent genetic exchange.

The paper includes detailed simulations that establish the validity of the approach, and it goes on to demonstrate how genomegaMap can detect advantageous mutations in 10,209 genomes of Mycobacterium tuberculosis, the bacterium that causes tuberculosis. The method reproduces known signals of advantageous mutations that make the bacteria resistant to antibiotics, and it discovers a new signal of advantageous mutations in a cold-shock protein called deaD or csdA.

Software that implements genomegaMap is available on Docker Hub and the source code and documentation are available on Git Hub.

With the steady rise of more and more genome sequences, the analysis of data becomes an increasing challenge even with modern computers, so it is hoped that this new method provides a useful way to exploit the opportunities in such large datasets to gain new insights into evolution.

Prize PhD Studentships available

I am offering two PhD projects as part of the annual Nuffield Department of Medicine Prize Studentship competition:

• Real-time detection of multidrug resistant tuberculosis and transmission in England
  Joint with David Wyllie, molecular microbiologist, this project is focused on developing statistical methods for recognizing transmission clusters, integrating genomics approaches with molecular typing schemes and developing future-proof taxonomy for strain identification.
  
  
• Tracking future infection threats using genomic data and electronic health records
  Joint with David Clifton, biomedical engineer, this project aims to develop new machine learning and statistical methods to identify genomic markers of antibiotic resistance and susceptibility within various pathogens, to help track future infection threats.

These are fully-funded, four-year awards open to outstanding students of any nationality. Applicants nominate three projects, in order of preference, from the available pool. For how to apply, click here. Only applications submitted through the online system will be considered, but interested applicants are welcome to contact me informally. The deadline for applications is noon, 6th January 2017.

In addition to my projects, the Modernising Medical Microbiology project has announced the following PhD projects as part of the competition:

• Antimicrobial resistance gene/vector transmission across human, animal and environmental reservoirs
  Supervised by Nicole Stoesser, Nicola De Maio and Derrick Crook
  
  
• Healthcare big data and genomics for infectious disease threat detection
  Supervised by David Clifton, David Eyre and Tim Peto
  
  
• Prediction of Mycobacterium tuberculosis drug resistance through genome sequencing clinical samples
  Supervised by Tim Walker and Tim Peto
  
  
• Antibiotic resistance in Tuberculosis: Predicting de novo the effect of individual genetic mutations
  Supervised by Phil Fowler and Sarah Walker

Tackling and tracking TB through DNA analysis

Postdoctoral Scientist in Statistical Genomics

We are recruiting for a Postdoctoral Scientist in Statistical Genomics working on Antimicrobial Resistance (AMR) gene discovery and focused on Tuberculosis. This will be a joint position at the University of Oxford between Derrick Crook's group and mine, and part of the large international CRyPTIC consortium.

The role is for a population geneticist or statistical geneticist to develop and apply statistical methods, including genome-wide association studies, for discovering rare and common genetic variants underlying antimicrobial resistance in Mycobacterium tuberculosis.

One third of the world's population - 2.5 billion people - are thought to be infected with tuberculosis (TB). This post offers an opportunity to work with global TB experts from five continents, statistical geneticists, clinicians, medical statisticians and software engineers; integrating statistical genetics, bioinformatics and machine learning methods with the aim of uncovering all genomic variants causing at least 1% resistance to first line anti-TB drugs.

We're looking for candidates with a PhD in genomics, evolutionary biology, statistics or a related subject. The post is full-time and fixed-term for up to 3 years initially.

The deadline for applications is noon on Friday 6th May 2016.

Making the most of bacterial GWAS: new paper in Nature Microbiology

In a new paper published this week in Nature Microbiology, we report the performance of genome wide association studies (GWAS) in bacteria to identify causal mechanisms of antibiotic resistance in four major pathogens, and introduce a new method, bugwas,  to make the most of bacterial GWAS for traits under less strong selection.

As explained by Sarah Earle, joint first author with Jessie Wu and Jane Charlesworth, the problem with GWAS in bacteria is strong population structure and the consequent strong coinheritance of genetic variants throughout the genome. This phenomenon - known as genome-wide linkage disequilibrium (LD) - comes about because exchange of genes is relatively infrequent in bacteria, which reproduce clonally, compared to organisms that exchange genes every generation through sexual reproduction.

Genome-wide LD makes it difficult for GWAS to distinguish variants that causally influence a trait from other, coinherited variants that have no direct effect on the trait.

In the case of antibiotic resistance - a trait of high importance to human health - bacteria are under extraordinary selection pressures because resistance is a matter of life and death, to them as well as their human host. This helps overcome coinheritance and pinpoint causal variants because antibiotic usage selects for the independent evolution of the same resistance-causing variants in different genetic backgrounds.

Consequently, bacterial GWAS works very efficiently for antibiotic resistance: the variants most significantly associated with antibiotic resistance in 26 out of the 27 GWAS we performed were genuine resistance-conferring mutations. In the 27th we uncovered a putative novel mechanism of resistance to cefazolin in E. coli. These results for 17 antibiotics (ampicillin, cefazolin, cefuroxime, ceftriaxone, ciprofloxacin, erythromycin, ethambutol, fusidic acid, gentamicin, isoniazid, penicillin, pyrazinamide, methicillin, rifampicin, tetracycline, tobramycin and trimethoprim) across four species (E. coli, K. pneumoniae, M. tuberculosis and S. aureus) build on earlier work investigating beta-lactam resistance in S. pneumoniae, and convincingly demonstrate the potential for bacterial GWAS to discover new genes underlying important traits under strong selection.

What about traits under less strong selection, which probably includes pretty much every other bacterial trait? We show in this context that coinheritance poses a major challenge, based on detailed simulations. Often it may not be possible to use GWAS to pinpoint individual variants responsible for different traits because they are coinherited with - possibly many - other uninvolved variants.

But all is not lost. We show that even when individual locus-level effects cannot be pinpointed, there is often excellent power to characterize lineage-level differences in phenotype between strains. This is helpful for multiple reasons: (1) we often conceptualize trait variability in bacteria at the level of strain-to-strain differences (2) these differences can be highly predictive (3) we can prioritize variants for functional follow-up based on their contribution to strain-level differences.

These concepts represent a substantial departure from regular GWAS. In the human setting for instance, lineage-level differences are usually discarded as uninteresting or artefactual, and variants are almost always prioritized based on statistical evidence for involvement over-and-above any contribution to lineage-level differences. In the bacterial setting, we are forced to depart from these conventions because a large proportion of all genetic variation is strongly strain-stratified. To find out more, see the paper and try our methods.

CRyPTIC: rapid diagnosis of drug resistance in TB

The Modernising Medical Microbiology consortium has announced a new worldwide collaboration called CRyPTIC to speed up diagnosis of antibiotic resistant tuberculosis (TB).

TB infects nearly 10 million people each year and kills 1.5 million, making it one of the leading causes of death worldwide. Almost half a million people each year develop multidrug-resistant (MDR) TB, which defies common TB treatments. Time consuming tests must be run to identify MDR-TB and which drugs will work or fail. This delays diagnosis and creates uncertainty about the best drugs to prescribe to individual patients.

CRyPTIC aims to hasten the identification of MDR-TB using whole genome sequencing to identify genetic variants that give resistance to particular drugs. The project is funded by a $2.2m grant from the Bill & Melinda Gates Foundation and a £4m grant from the Wellcome Trust and MRC Newton Fund.

CRyPTIC aims to collect and analyse 100,000 TB cases from across the world, providing a database of MDR-TB that will underpin diagnosis using WGS. Samples from across Africa, Asia, Europe and the Americas will be collected by teams at more than a dozen centres They will conduct drug resistance testing and much of the genome sequencing. Read more information here.

Postdoc and PhD position available

These positions are now closed.

Advertised today in Nature and on Thursday in New Scientist are two positions in my lab. I am looking for a postdoc and a PhD student to work on the genome evolution and epidemiology of four human pathogens as part of the Modernising Medical Microbiology project. Three of the pathogens share the theme of hospital-acquired infections: they are Staphylococcus aureus (of MRSA infamy), Clostridium difficile and norovirus (aka winter vomiting disease). The fourth is Mycobacterium tuberculosis (TB) which is a re-emerging problem in developed countries.

The aim of the project is to use whole genome sequencing of many isolates (100s to 1000s) in order to reconstruct evolutionary relationships and deconstruct transmission routes. We hope to develop the technology to the stage that we can trace the spread of pathogens in real time, and uncover the epidemiological triggers for the spread of disease.

As of January I have relocated to the Nuffield Department of Clinical Medicine at the University of Oxford, and the project is a collaborative affair between people at Oxford (including Rory Bowden, Derrick Crook, Peter Donnelly and Rosalind Harding), the Wellcome Trust Sanger Institute, the NHS and the Health Protection Agency. The project is funded by the UKCRC and further details of the positions are available online for the postdoc and PhD studentship. The closing date for applications is Friday, 2 April 2010.