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.

The evolution of sexual behaviours: developing and testing biological models of non-reproductive sex, including homosexuality
Homosexual behaviour has often been considered a ‘Darwinian paradox’ because a focus on non-reproductive sexual behaviour to the detriment of reproductive sex should result in fewer offspring. Yet, sexual behaviour between members of the same sex (homosexuality) is commonly observed in nature, and is particularly frequent in humans and other primates. What explains this discrepancy between simple expectation and observation? How frequent is homosexual behaviour, and are there evolutionary costs or benefits associated with it? Here, we propose the first ever study quantifying the evolutionary causes and consequences of homosexuality in free-ranging social primates using behavioural data and cutting-edge genomic analyses. The results should lead to re-thinking of the prevalence, causes and consequences of sexual orientations in wild primates, with relevance to human societies. The seeming Darwinian paradox of homosexual behaviour has led to the development of several biological models to explain its prevalence. Most models fall into two broad categories: genetic and epigenetic models. Genetic models typically explain the persistence of a hypothetical homosexual gene variant (allele) through some indirect evolutionary advantage for that variant (Savolainen & Lehmann, Nature 445:158, 2007). Epigenetic models explain homosexual behaviour as a result of heritable changes in gene expression patterns due to chemical modifications that occur to the DNA of developing organisms (Rice et al., Quarterly Review of Biology 87:343, 2012). These models each make clear predictions, however, there is only limited support for any of them. Furthermore, Savolainen & Hodgson (Encyclopaedia of Evolutionary Psychology, 2017) have proposed an alternative model, the bisexual advantage model, whereby homosexuality is a quantitative trait controlled by many loci. This bisexual advantage model is perhaps the most conservative genetic explanation for the persistence of homosexual behaviour because sexuality would then follow the pattern of the vast majority of quantitative traits where intermediate phenotypes are favoured (Lande, Genetics Research 26:221, 1976). Using the rhesus macaque colony living on the 15ha island of Cayo Santiago off the coast of Puerto Rico, the student will address the following aims: 1. Quantifying the distribution and heritability of sexual behaviour. We will develop sexual behaviour profiles for each study animal to understand the distribution of the trait, including in relation to age and social ranking. To understand the genetic and environmental components of sexual behaviour, the profiles will be compared to existing pedigrees. 2. Testing for genetic associations to sexual orientation. We will collect genomic data and look for genetic associations with the sexual behaviour profiles. This will be done using a machine learning approach that is more powerful than standard genome-wide association studies. 3. Formalise mathematically the bisexual advantage model proposed above as well as models for the evolution of non-reproductive sexual behaviours depending on the ecology of species. The student will refine predictions using mathematical genetics, computer simulations and computing tools such as machine deep learning.
Vincent Savolainen
Richard Everitt
Dr Jason Hodgson; Department of Life Sciences, Imperial College London;; Professor Emeritus Russ Lande FRS; Department of Life Sciences; Imperial College London
Computing, Quantitative data analysis, Ecological observations / data collection
Richard Everitt
The project will involve both (i) developing new theory and/or quantitative methods; and (ii) developing new applications or validation for existing theory/methods. Key quantitative skills include population genetic modelling, manipulation of large genomic data, statistical and computational genetics (machine learning applications), and development of new models and modelling techniques.
Allying expertise of Life Sciences at Imperial and Mathematics at Reading, we propose the first ever study to quantify the evolutionary causes and consequences of homosexuality in free-living social primates by combining intensive behavioural data with genomic analyses and modelling.
Homosexuality has led to the development of models to explain its prevalence, however, there is only limited support for any of them. We proposed the bisexual advantage model, which predicts that sexuality is a quantitative trait where numerous genetic loci contributing to its heritability. We will formalise mathematically this latter model and confront model predictions to observations.
Homosexuality is illegal in 74 countries, punishable by death in 10. The results will lead to re-thinking of the prevalence, causes and consequences of sexual orientations in wild primates, with direct relevance to human societies.
This project can potentially drastically change minds around the world on issues of equality and diversity. It may be the case that some degree of bisexuality is actually an evolutionary optimum phenotype in many species, including humans.
This project integrates approaches from evolutionary biology, animal behaviour, genetics, mathematical biology to disentangle the evolutionary ecology of sexual behaviours. It combines expertise in evolutionary genomics (Savolainen), statistical methods for the analysis of genetic data and probabilistic predictions (Everitt), population genetics/primatology (Hodgson), and genetics theory (Lande).
Behavioural ecology
Training in genetic modelling, machine learning, and advanced statistics will be provided. The student will also need some training in high performance computing.
Mathematics at Reading, HPC at Imperial, visit to Lande in Norway for modelling elements.
2017-09-29 13:59:59