Kokko/Keaney
Scientific Background
Adaptation is the process by which organisms in a population evolve to fit the environment in which they reside. The ‘fuel’ of adaptation is generally considered to be genetic variation, produced by mutation in the genetic code. However, epigenetic changes to genetic structure, such as the addition of a methyl group to the DNA molecule, may, in some cases, provide an alternative fuel source for adaptation to occur. For example, in Arabidopsis thaliana these ‘epimutations’ have been shown to contribute to phenotypic variation, to persist for multiple generations and to accumulate several orders of magnitude faster than conventional genetic mutations (Cortijo et al. 2014, Yao et al. 2023). Drawing from these observations, it has been hypothesised that epimutations offer a complementary path to traverse fitness landscapes towards local phenotypic optima.
Models of epigenetic adaptive walks typically consider adaptation to occur in one dimension, where epimutations affect a single trait that is subject to selection (Kronholm and Collins, 2016 present a notable exception). However, it has long been known that pleiotropy and linkage disequilibrium produce genetic correlations between traits, and that these correlations are a considerable hinderance to adaptation (Fisher, 1930). Models of epigenetic adaptation should therefore also consider that epimutations are likely subject to the same constraints.
Project description
In this project, you will utilise Fisher’s geometric model of adaptation (Fisher, 1930; Fisher is famously opaque in his writing, so we recommend Orr 2005 for a nice review) to theoretically model the evolutionary process when both genetic and epigenetic mutations affect fitness. Fisher’s model captures the basic biological details of adaptation in a complex organism: mutations cause random changes to the phenotype in multi-dimensional trait space, those mutations that move the phenotype closer to the optimal phenotypic value are favoured by selection, and a population moves towards the phenotypic optimum by fixing beneficial mutations in a step-wise manner.
With this framework in place, you will generate predictions for how epimutations are likely to affect the rate of adaptation.
The project can then be extended based upon the interests of the student. For example, one could choose to focus on epigenetics, adaptive walks or applying and refining the geometric model to explore other evolutionary problems.
What you will learn
Our group has expertise in a broad range of modelling techniques that apply to evolutionary and ecological questions (and everything in between), providing a great environment for a developing theoretician. The GenEvo program also contains multiple empirical groups working on epigenetic mechanisms (a quick browse through the other offered projects shall reveal this), with whom there will be abundant collaborative opportunities.
Your qualifications
An enthusiasm for evolutionary ecology and a master’s degree in a relevant topic (evolutionary biology, ecology, mathematics). Coding ability (R, python, matlab) is very desirable but not required (training will be provided).
Publications relevant to this project
Yao N, Zhang Z, Yu L, Hazarika R, Yu C, Jang H, Smith LM et al. (2023) An evolutionary epigenetic clock in plants. Science 381:1440–1445. https://doi.org/10.1126/science.adh9443
Kronholm I and Collins S (2016) Epigenetic mutations can both help and hinder adaptive evolution. Molecular Ecology 25:1856–1868. https://doi.org/10.1111/mec.13296
Leimar O and McNamara JM (2015) The evolution of transgenerational integration of information in heterogeneous environments. The American Naturalist 185:E55-69. https://doi.org/10.1086/679575
Day T and Bonduriansky R (2011) A unified approach to the evolutionary consequences of genetic and nongenetic inheritance. The American Naturalist 178 (2):E18–E36. https://doi.org/10.1086/660911
Orr HA (2005) The genetic theory of adaptation: a brief history. Nature Reviews Genetics 6:119–127. https://doi.org/10.1038/nrg1523