Meiotic recombination is a fundamental feature of sexual reproduction in nearly all multi-cellular organisms. It is advantageous from an evolutionary perspective, as it rearranges existing allelic variation to create novel haplotypes in which beneficial alleles are uncoupled from deleterious alleles. Consequently, beneficial alleles are more likely to spread through populations and deleterious alleles are less likely to accumulate, meaning that populations with higher recombination can respond to selection at a faster rate. Nevertheless, recombination may also have a cost: it is a mutagenic process that can create deleterious mutations and/or rearrangements; it may also break apart beneficial combinations of alleles previously build up by selection. These relative costs and benefits may vary within and between populations, and if recombination rate itself is heritable, then it may be subject to selection and have the potential to evolve. Therefore, understanding the genetic causes of variation in recombination rate is important in interpreting and predicting evolutionary phenomena and for understanding the potential of a population to respond to selection. This project will use genomic data from a long term ecological study of house sparrows (Passer domesticus) to investigate fine-scale variation in recombination and to determine the genetic architecture and selection on individual recombination rates in a wild system.
Study system: The pedigreed population of house sparrows in Northern Norway has been intensively studied on an individual basis since 1993. Genome-wide SNP data for 200K SNPs is currently available for ~4000 individuals, along with the recently assembled and annotated house sparrow genome. This data is provided in collaboration with Prof Henrik Jensen and Prof Bernt-Erik Sæther at NTNU, Trondheim, Norway.
Key research objectives:
Research Training: The project will be mostly computational 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 first year will include an intensive one-semester course on population genetics, quantitative genetics and statistics at the Institute of Evolutionary Biology which will provide a basis for the analytical 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 house sparrow project community.
Fieldwork: The student will be encouraged to contribute to fieldwork to collect DNA and aid the field team to learn about the ecology of the system.
Lab work: The student will be expected to carry out 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.
Further information: The lead supervisor, Susan Johnston, has extensive experience in quantitative and evolutionary genomics in wild systems, and has developed methods to quantify individual rates of recombination from complex pedigrees. Co-supervisor 1 John Hickey runs a large computational genetics programme for the genetic improvement and biological understanding of a range of species, with a strong focus on recombination. Co-supervisor 2, Michael Morrissey develops new approaches to statistical quantitative genetics, focusing on the analysis of longitudinal data from natural animal populations.
Elgvin, T. O., et al (2017). The genomic mosaicism of hybrid speciation. Science Advances, 3, e1602996.
Johnston SE, C Bérénos, J Slate, JM Pemberton (2016) Conserved genetic architecture underlying individual recombination rate variation in a wild population of Soay sheep. Genetics, 203, 583–598.