Waterhouse Lab
Modelling gene evolution - gene function interactions
through evolutionary and functional genomics in insects
​​Arthropod Genomics 

The focus of the group’s research is on computational comparative evolutionary and functional genomics of disease-vector mosquitoes and other insects: exploring the links between gene evolution and gene function through an evolutionary systems biology framework. In this regard insects and other arthropods have a lot to offer: with their countless adaptations to exploit many ecological niches they are ideal for investigating how conservation or divergence and gains or losses of functional genomic elements give rise to the splendour of animal biology.
Comparative Genomics 

This figure from the Journal of Hygiene illustrates how comparing observable features of different species has been a fundamental tool in biological research for centuries: Charles Waterhouse (no relation) notes the very different ‘attitude’ of Anopheles mosquitoes compared with Culex. As falling sequencing costs improve genomic species sampling and enrich sources of functional data, the quantities and types of ‘observable features’ are now orders of magnitude more numerous.

Herein lies the challenge: 
How do we best exploit these data to reach new levels
of depth and detail in our understanding of biology?​​

Evolutionary Genomics 

While computational methods for predicting gene functions are improving, they often fail to provide biologists with the evidence required to design and perform comprehensive experiments that probe these putative roles in detail. Addressing these challenges, the group’s principal research aim is to develop quantitative measures of gene evolutionary traits and classify genes into multiple functionally-related categories in order to build reliable predictive models of the relationships between the underlying genetics and the observable biological traits. The goal of this framework is to identify genes with similar evolutionary profiles in order to expand hypotheses on genomic functions by predicting new members of biological pathways or processes based on shared evolutionary traits.
Evolutionary-Functional Correspondences 

To build the best possible hypotheses on putative gene functions we must learn how to (i) use the accumulating data to meaningfully and quantitatively characterise the full evolutionary histories of genes and other genomic elements, and (ii) relate these evolutionary histories to assayable functions and thereby pave the way to exploiting real predictive power. Achieving these goals will require substantial methodological advances: designing, implementing, iteratively testing, adapting, and integrating a comprehensive suite of analyses tools will ensure that the predictive models are dynamic, extensible, statistically rigorous, and responsive to the fast-accumulating genomic data. 
​​This will also facilitate productive exchanges with expert biologists through a collaborative analysis and visualisation environment that will allow exploration of the relations between the evolutionary features and biological functions of genomic elements linked to their favourite study systems. In this way, exploiting genomic evolutionary signatures will enhance the understanding of putative functions of thousands of currently uncharacterised genes from hundreds of organisms.
Characterisation, Control, & Conservation 

The incredible diversity of insects makes them fascinating to study, as models for processes like ageing and sociality, and because of their roles in human, livestock, and crop health as disease vectors, in agriculture as pests, pollinators, or bio-control agents, and more generally in ecology and environmental conservation. In striving towards our goals of building an evolutionary systems biology framework that accelerates the discovery of novel insect biology, the results of our research will provide biologists with the tools they need to apply this knowledge to the characterisation of animal biology, the control of disease vectors and pests, and the conservation of threatened insects and their ecosystems. 
Doctoral & Postdoctoral Positions     *** Applications Are Now Closed  ***

With my appointment as a Swiss National Science Foundation (SNSF) Professeur Boursier at the Department of Ecology and Evolution of the University of Lausanne , I am seeking to recruit talented and enthusiastic members to join my research group in a department with a strong track record of excellence in research and teaching. As this research is funded by the SNSF, rights and responsibilities, including employment conditions, holidays, and salaries, of the research team members are governed by the SNSF rules and regulations ( funding regulations and guidelines ) in line with those of the University of Lausanne ( human resources administrative information ).

•   The doctoral student will work very closely with the postdoctoral student to implement the core research project goals in line with the aims of the doctoral thesis. In particular, designing and developing cross-species comparisons to quantify patterns of evolutionary change and exploring strengths and interdependencies of correlations amongst evolutionary metrics and global functional properties to confirm and refine our understanding evolutionary-functional correspondences. Confidence with statistics will help with the detailed resolution of the complex relations amongst evolutionarily defined modules and the different hierarchies of biological functions, and is thus desirable.

•  The postdoctoral student will work very closely with the PhD student and will be responsible for implementing the core research project goals, particularly with respect to the development of computational infrastructures to ensure that predictive model building is dynamic, extensible, and responsive to the fast-accumulating genomics data, as well as helping to design and build collaborative analysis and visualisation tools. Skills in handling large datasets, statistical modelling, automated collating of different data types from disparate resources, knowledge of database design and management for efficient data integration and quality control, are therefore desirable.