EASTBIO: Tracing the fitness effects of new mutations across evolutionary timescales

About the Project

Mutations are the raw material of evolution: they generate the variation on which natural selection acts. Understanding their fate is therefore key to a fundamental question in evolutionary biology: how do species adapt to ever-changing environments? Mutations can be deleterious, advantageous, or neutral, depending on whether they decrease, increase, or have no effect on fitness (Moutinho 2020). While most genetic variation is thought to result from nearly neutral mutations (Kimura 1968; Ohta 1973), debate continues about the relative importance of selection and drift in shaping genome diversity (Kern 2018; Jensen 2018).

A powerful way to address this question is through the distribution of fitness effects (DFE), which quantifies the probabilities of different fitness outcomes for new mutations (Eyre-Walker 2007). Despite abundant genomic data, estimating the DFE remains challenging: confounding demographic factors can mimic selection (Galtier 2009), strongly beneficial and deleterious mutations are rarely observed (Keightley 2010), and evolutionary processes vary across timescales (Tataru 2017).

This project will develop new theory and statistical methods to estimate the DFE and overcome these challenges. We will build a model of fitness effects that integrates population and phylogenetic timescales of evolution based on Borges (2019, 2025) and Kotari (2024) and infer the DFE using extreme value theory and Bayesian inference. These models will be implemented in the RevBayes software (Höhna 2014; 2016) and applied to microbial genomic datasets, including bacterial and viral systems of epidemiological and medical importance. Comparing DFE estimates across taxa will allow us to explore key evolutionary questions: How conserved is the DFE among microbes? Do species or clades exhibit distinctive DFE patterns? How much variation reflects shared evolutionary history versus independent adaptation?

This research will contribute to a deeper understanding of how selection, drift, and mutation jointly shape genome evolution (Hoffmann 2011; Borges 2025).

The PhD student will join an interdisciplinary environment at the University of St Andrews, benefiting from the GRADskills programme, which supports postgraduate researchers in developing transferable and research skills for careers within and beyond academia. The student will be co-supervised by Dr. Rui Borges at the School of Mathematics and Statistics and Dr. Carolin Kosiol at the School of Biology, gaining comprehensive training in mathematical and computational biology, inferential statistics, and genomic data analysis. Ongoing collaborations with Dr Sebastian Höhna (LMU Munich; phylogenetic inference and RevBayes) and Dr Joseph Hughes (University of Glasgow; microbial genomics and host-pathogen evolution) will provide complementary expertise.

HOW TO APPLY

Application instructions can be found on the EASTBIO website: How to Apply | EastBio Doctoral Training Partnership | Biology

1) Download and complete the Equality, Diversity and Inclusion survey.

2) Download and complete the EASTBIO Application Form.

3) Please complete an application on our online portal: How to apply - Study at St Andrews - University of St Andrews

4) Select the course ‘PhD with internship’

5) Your online application must include the following documents:

• Completed EASTBIO application form
• Academic Qualifications
• English Language Qualification (if applicable)
• 2 References: this must be completed on the EASTBIO Reference Form, also found on the EASTBIO website.

Please download the EASTBIO reference form and send it to your referees. They can either upload it directly to the portal using the automated email they will receive, or they can email it to Robbie Mill at rgmm1@st-andrews.ac.uk

CONTACT

Queries on the project can be directed to the project supervisor.

Queries on the application process can be directed to Robbie Mill at rgmm1@st-andrews.ac.uk.

Funding Notes

This 4-year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership.

This opportunity is open to UK and International students and provides funding to cover stipend at UKRI standard rate and UK level tuition fees. The University of St Andrews will cover the Home-International fee difference.