Almost all traits of importance in agriculture, medicine and evolution are complex and influenced by the actions and interactions of many genes and environmental factors. One of the major challenges in biology is to understand the genetic control of these complex traits. Advances in genomic technologies, especially in the development of high-density genotyping arrays have made it possible to begin to dissect the genetic variation and characterise the genetic architecture of traits in many, including non-model, species.
This project aims to investigate the genetic architecture of morphometric, fitness and health related traits in the Soay sheep (Ovis aries), using new analytical methods and data collected as part of a long-term study on the St. Kilda archipelago (Scotland) that is one of the largest projects encompassing genomic data and high quality phenotypes in a wild population (http://soaysheep.biology.ed.ac.uk). The data consist of over 6,500 individuals that have been genotyped for around 39K polymorphic loci (SNPs), and, in addition, a subset of 188 that have been genotyped with a high-density SNP chip containing 450K polymorphic SNPs in Soays. By applying cutting edge quantitative genomic methodologies to this population, we will be able to explore strategies that could be used in other populations, including livestock, as the data become available.
The project will have three main stages. The first will involve imputing SNP genotypes for all 450K SNPs for all 6500 individuals, taking advantage of the well-resolved pedigree available for the population. Once complete the next stages will investigate different approaches to dissecting the genetic variation underpinning a range of traits. The second will work at the whole genome level, asking what proportion of the genetic variance is associated with common genetic variants (SNPs) and whether we can quantify the effects of other genetic variants not captured by the SNP array, such as rare variants. The third stage will investigate the contribution from regions across the genome using, among other approaches, a new ‘regional heritability’ method based on haplotypes. The analyses will contribute to the development of the methodology and combining the results will give new insights into the genetic control of a range of traits in this sheep population.
This project will provide training and experience in key areas of genomics combined with statistics and computation relevant to all species as well as field data collection. In particular, experience will be gained in state-of-the-art analytical methods and software being used in the analysis of human data. Training in genetics, genomics and statistics is available through our MSc programme in Quantitative Genetics and Genome Analysis (http://qgen.bio.ed.ac.uk). Additionally training is offered in generic transferable and professional skills.
The project is relevant to students with a background in statistics or computational sciences and a keen interest in genetics as well as those with a training in quantitative or population genetics and related subjects. Experience in programming would be beneficial.
Bérénos C, Ellis PA, Pilkington JG, Lee SH, Gratten J and Pemberton JM (2015) Heterogeneity of genetic architecture of body size traits in a free‐living population. Molecular Ecology, 24, 1810-1830.
Xia C, Amador C, Huffman J, Trochet H, Campbell A, Porteous D, Generation Scotland, Hastie N, Hayward C, Vitart V, Navarro P and Haley C (2016) Pedigree- and SNP-Associated Genetics and Recent Environment are the Major Contributors to Anthropometric and Cardiometabolic Trait Variation. PLoS Genetics, 12 (2), e1005804
Shirali M, Knott S, Pong-Wong R, Navarro P and Haley C (2018) Haplotype Heritability Mapping Method Uncovers Missing Heritability of Complex Traits. Scientific Reports, 8, 4982
If you wish to apply for this project, please go to this link.