The QMEE CDT Project proposal database

Welcome to the QMEE CDT Project proposal database. This is a live list of projects proposals put forward by PIs across the CDT partner institutions

PIs/Supervisors will continue to add projects to this list over the next few months, so do keep checking back! You can search the projects using the box below: simply enter some text and press Search to do a text search across all the database fields. If you want to search more finely, the search tool also allows you to search on particular details of the project descriptions: you will see these finer search options appear if you click on the search box.

Click on the view button next to a project to get the full proposal description. If you want to download project details, either for all projects, or for a subset you have searched for, then click on the 'Download details' button.

Biomonitoring and controlling amphibian-killing fungi using worldwide genomic data
The chytrid fungus Batrachochytrium dendrobatidis (Bd) is responsible for the dramatic decline of amphibians worldwide, causing one of the largest losses of biodiversity in recent times (Fisher et al. Nature 2012). Despite much interest, the genetic mechanisms that underpin Bd’s virulence are not yet known. For this reason, appropriate computational methods are in dire need to gain meaningful insights from the vast amount of data that are being generated by our global surveillance of this pathogen. The use of high-throughput DNA and RNA sequencing technologies machines is at the forefront of cutting-edge discoveries in ecology and evolutionary biology. The ability to obtain and analyse genomic data from previously neglected species is allowing researchers to understand which demographic and adaptive factors characterised species’ evolution. For instance, measurements of population genetic differentiation are an effective predictor of functional genes which can be associated with important virulence-related phenotypes. In Bd’s case, comparing the genomic landscape of lineages that show different phenotypes, such as virulence, is a promising approach to pinpoint candidate genes to be further explored. Statistical methods that take sequencing data uncertainty into account have been proposed to accurately estimate population genetic differentiation from high-throughput sequencing data (Fumagalli et al. Genetics 2013). While promising, a framework that capture the complexity of genomes with mixed ploidy is still missing. This is particular relevant for Bd (as well as other emerging pathogenic fungi), as high chromosomal plasticity has been suggested to play a role in its virulence (Farrer et al. Plos Genet 2013). In this project, the analysis of large-scale genomic data from worldwide isolates will provides us with the unprecedented opportunity to address how virulent Bd genotypes spread around the globe. Specifically, this project will encompass three main aims: (1) Improvement of statistical methods for the inference of ploidy and copy-number-variation from high-throughput sequencing data. The student will build the theory behind the estimation of population genetics parameters from these mixed-ploidy genomes. (2) Bioinformatics analysis of whole-genome sequencing data for almost 300 samples distributed worldwide. The student will develop a pipeline to process large-scale genomic data for estimating genomic diversity in Bd and will associate variation against distinct geographical lineages. The student will have the opportunity to participate at field-work activities (Pyrenees, Asia, Africa) for the collection of further samples. (3) Functional assessment of candidate loci through in vitro/vivo experiments. The student will assess changes in gene expression directly linked to increased virulence, and plan in vivo studies on animal models. The geographic origins and the timing of Bd’s spread are yet to be fully unravelled, making this one of the most controversial problems in disease ecology (Fisher Nature 2017). Understanding the genetic mechanisms underlying Bd’s virulence is a fundamental goal to plan molecular monitoring and develop our holy-grail, effective methods of control using our genetic insights.
Matteo Fumagalli
Matthew Fisher
Dr Richard Everitt, University of Reading, Department of Mathematics and Statistics, r.g.everitt@reading.ac.uk; Dr Trenton W J Garner, Institute of Zoology, Zoological Society of London, trent.garner@ioz.ac.uk
Computing, Quantitative data analysis, Ecological observations / data collection
Matteo Fumagalli
The student will gain an extensive expertise in big data management, mathematical modelling, theoretical population genetics and computational algorithms. Bioinformatic and population modelling skills acquired during this project will be highly transferable.
This proposal will open novel research themes by developing a new computational approach to analyse genomics data from mixed-ploidy species. It will also demonstrate the utility of an evolutionary genetics approach to predict virulence-associated loci to plan molecular monitoring and to design cutting edge control-methods using nucleic acids (eg. RNA interference).
New theory for genomic data analysis is in dire need to extract biological information from large scale DNA data. Understanding the evolutionary mechanisms underlying pathogens’ virulence is essential to design effective molecular monitoring. This project will meet CDT aims by training a student with valuable cross-disciplinary skills in quantitative genomics and evolution.
The integration of big data analysis with integrative statistical modelling is key for extracting meaningful information from eco-genomics data. Unveiling the genetic mechanisms underlying Bd’s virulence is vital to design effective biomonitoring and control using nucleic-acid approaches (eg. RNA interference). The framework developed here could be potentially extended to further panzootics.
Bd is responsible for over a hundred cases of species extinction. By identifying the molecular mechanisms underpinning its virulence, it is possible to plan and adopt effective monitoring strategies for the emergence of novel virulent genotypes in order to reinforce biosecurity and to develop novel methods of control.
This project will combine statistical modelling, bioinformatics, ecology and molecular biology. The student will be part of an excellent multidisciplinary environment. Dr Fumagalli is a biomedical engineer with extensive expertise in bioinformatics. Professor Fisher is a world leading expert in ecology and evolution of chytrid fungi.
Population ecology, Population genetics and evolution, Ecological/Evolutionary tools, technology & methods
Computing (R, python, C++) and modelling (Bayesian statistics) training will provided at Silwood Park. The student will receive training in functional ecology and molecular genomics techniques at new Royal Society laboratories at St Mary’s campus. Further training will be given by attending the A(S)PA and NC3Rs workshops on amphibian welfare.
Imperial College London, Reading, ZSL
No
2017-09-29 15:40:17