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.

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Fitness consequences of IGEs on parental investment
The knowledge of how interactions among conspecifics feedback into individual behaviour is crucial to understanding how phenotypic and genotypic variance is maintained, to understand how selection can act, and how behaviours evolve. Interacting individuals can influence each other’s phenotypes and even fitness where the variation of an interacting phenotype in a population depends on the social environment – through indirect genetic effects (IGEs). This concept is similar to the idea of an extended phenotype, where social interactions rather than abiotic factors influence phenotypes. We recently found in a wild bird population, that parental care is partly determined by the genetics of the social partner. This is especially interesting in a trait with mutual consequences for the interacting partners, since not only will an individual pass on its genes to its offspring, but the genes of the mating partner will also be passed on to the offspring. IGEs in social traits between mating partners may therefore be responsible for the maintenance of genetic variance in traits that affect their mutual fitness. This might be one reason for why we fail to find a clear response to selection in wild populations. This PhD will test recent hypotheses on IGEs in the context of fitness to fully understand how parental care can evolve. We have evidence for heritable variation in fitness in the same population, therefore, some of the recently developed theory will be testable in this study system, as a first, in a wild system. Moore, A., Brodie, E. & Wolf, J. Interacting phenotypes and the evolutionary process. 1. Direct and indirect genetic effects of social interactions. Evolution 51, 1352–1362 (1997). Schroeder J, Dugdale H, Nakagawa S, Sparks A, Burke T. Sex specific social genetic effects contribute to the total heritable variance in parental care. EcoEvoRxiv doi: 10.32942/ Schroeder J, Burke T, Dawson DA, Mannarelli ME, Nakagawa S (2012) Maternal effects and the heritability of annual productivity. J. Evol. Biol. 25, 149–156. Wolf, J., Brodie, E., III, Cheverud, J. & Moore, A. Evolutionary consequences of indirect genetic effects. Trends Ecol. Evol. 13, 64–69 (1998).
Julia Schroeder
Jinliang Wang
Prof Terry Burke, University of Sheffield,
Development of mathematical theory, Computing, Quantitative data analysis, Evolutionary observations / data collection
Julia Schroeder
- Advanced statistics (variance/covariance analysis) - Computer programming - Theory of fitness, some theory development - Managing large dataset Both supervisors are responsible for quantitative aspects - Schroeder for statistical modelling, Wang for theory
This project will be part of the development of new theories about evolution when indirect genetic effects take place. We know that IGEs can majorly affect evolutionary trajectories but we have very few empirical data to support this. Novel theories of how such IGEs can affect fitness are currently being developed.
- Theory of fitness - Quantitative genetics
- For agricultural breeding - Big data
- This project has the potential to be transformative to the field, as its accounting for IGEs will uncover a wealth of quantitative genetic architecture and explain missing heritability that may otherwise remain undetected. IGEs thus may contribute to the maintenance of variance and evolution of life-history traits.
This project is multidisciplinary as it crosses evolutionary theory, statistics and basic ecology. Students will learn excellent data analysis skills, and evolutionary theory. Students will tackle theory using both, analytical and simulation approaches., thus computing is also relevant. Students will also learn to model and analyse big data.
Population genetics and evolution, Ecological/Evolutionary tools, technology & methods
- Quantitative genetic analyses (stats) - Mathematical analysis and theory development - Computer programming
Silwood, ZSL
2019-05-17 11:10:32