*EASTBIO* Genomic signals of selection and evolution in red deer (Cervus elaphus)

A central goal in evolutionary biology is to identify genes that are involved in natural selection (Stinchcombe & Hoekstra 2007). Advances in genomic technologies now allow unprecedented opportunities to investigate selection and evolution at the genomic level in non-model systems. Almost all studies to date in natural populations have focussed on identifying loci underlying phenotypes that are associated with fitness using techniques such as QTL analyses and genome-wide association studies (GWAS). These approaches can explain the evolution in some traits, but for the majority of quantitative traits, heritable variation cannot be attributed to particular loci (i.e. “missing heritability”). Another problem is that phenotype-based approaches alone will fail to identify loci under selection in traits that have not been measured. Therefore, there is a need for new, additional approaches to detect selection to determine the broader picture of how populations are evolving over time. One solution is to examine how selection operates directly at the level of the genome through changes in allele frequency (over shorter evolutionary timescales) and molecular signatures of selection (over longer evolutionary timescales; Nielsen et al 2005). This PhD project will integrate quantitative and population genetic approaches to examine how selection is operating at the genomic level at different evolutionary timescales in a natural population of red deer.

Study system: This project will use genome-wide data from a pedigreed population of red deer on the island of Rum, Scotland that has been intensively studied since 1972 (http://rumdeer.biology.ed.ac.uk/). Genome wide SNP data for ~2,500 individuals across ~12 generations from this population is available (Huisman et al 2016). A red deer genome project is currently underway and is expected to be completed by summer 2017.

Key research objectives:

Aid the development of simulations predicting allele frequency change under drift and selection in pedigreed populations;
Quantify changes in genome-wide allele frequencies over short evolutionary timescales and determine if changes are likely to be due to drift and/or selection;
Conduct whole genome sequencing and variant calling to identify regions of the genome showing molecular signals of directional/balancing selection at the sequence level over longer evolutionary timescales;
Examine functional enrichment in candidate regions using information from the deer genome annotation and from related species (cattle, sheep) to identify likely phenotypes that are under selection within the population.

Research Training: The project will be strongly computational with scope for developing theoretical models of selection in contemporary populations, and will suit students with strong analytical potential. The supervisors will provide cutting-edge training in quantitative genetics, evolutionary genomics and statistics (see below). The lead supervisor, Susan Johnston, has extensive experience in quantitative and evolutionary genomics in wild systems, and has developed inference methods to model transmission of genomic regions through complex pedigrees. Co-supervisor 1, Josephine Pemberton develops and manages several genomic datasets in large mammals and is currently overseeing the assembly of the deer genome project. Co-supervisor 2 John Hickey runs a large computational genetics programme for the genetic improvement and biological understanding of a range of species.

The first year will include an intensive one-semester course on theoretical population genetics, quantitative genetics and statistics at the Institute of Evolutionary Biology which will provide a basis for theoretical and statistical work. Further training will be provided by EASTBIO workshops/symposia and Edinburgh Genomics coding and bioinformatics courses. The student will also be able to take advantage of national and international collaborative links of the supervisors and of the larger red deer project community.

Fieldwork: The student will be strongly encouraged to contribute to fieldwork to collect DNA samples for whole genome sequencing and aid the field team to learn about the ecology of the system.

Lab work: The student will be expected to carry out small amounts of lab work to prepare DNA for sequencing and genotyping. Experience in molecular ecology lab techniques is desirable but not necessary as training will be provided.