Genomic prediction in a wild mammal

Imagine a world where a scientist could sample an animal or plant and, by DNA profiling, predict what it would look like, how long it would live, how many offspring it would have, and whether or not it would out-compete other members of its population. Although the idea seems fanciful, it has become a possibility, even for wild populations within complex ecological systems. The aim of this proposal is to develop, test and apply so called 'genomic prediction' methods for use in evolutionary ecology.

In the last decade remarkable advances in genomics methods, most notably next-generation sequencing, have revolutionised all areas of biological research. It is now possible to generate DNA profiles at hundreds of thousands of variable sites across the genome, in any organism. Many of these sites (known as single nucleotide polymorphisms, or SNPs) will reside within, or very close to, genes that cause phenotypic variation. Traditionally, the search for these genes, or quantitative trait loci (QTL), has involved testing each SNP individually and then identifying those which are statistically significant. However, this approach is problematic, in that it is biased towards finding genes of large effect, which for many phenotypes simply do not exist. If, as is more common, there are many genes of small effect then QTL will remain undetected. In animal and plant breeding, the problem has been solved by considering the phenotypic effect of all SNPs simultaneously. First a 'training population' of genotyped samples with known phenotype are used to estimate effect sizes of each SNP. Then a second sample of 'test' individuals is genotyped, and the genotypes are used to predict phenotype; i.e. perform genomic prediction. This approach underpins successful modern artificial selection programmes and is set to be used in personalised medicine. However, genomic prediction has never been applied to wild populations, despite its potential to revolutionise evolutionary ecological genetics.

We will test and apply genomic prediction in the feral population of Soay sheep on the island of Hirta (St Kilda, Scotland); one of the most intensively studied vertebrate populations in the world. Since 1985, over 95% of animals born in the Village Bay study area have been monitored over their entire lifetimes, such that detailed life histories (e.g. date of birth, date of death, sex, twin status, morphological measurements, immunological assays, parasite loads and lifetime fitness) are described for over 7000 sheep. Many traits have been measured numerous times across development. Furthermore, the sheep genome has been sequenced and most of the Soay study population has been typed at 38K SNPs discovered by the International Sheep Genomics Consortium. Additional features that make Soay sheep the ideal system for testing genomic prediction are: (i) different traits have well described and very different genetic architectures. eg. coat colour and horn type have a simple genetic basis while skeletal measurements are far more polygenic (but still highly heritable) and (ii) linkage disequilibrium extends for long distances in the genome, so that the SNPs on the chip 'tag' most of the genome. Using a 'training population' of all animals born until 2010 we will estimate the effects of individual SNPs, and then use these estimates to predict the phenotype of animals born after 2010. We will compare the predictions to observed values; the first time genomic prediction has been tested or applied in a wild population. We will also use genomic predictions to establish which traits have made an evolutionary response to natural selection.

We predict that genomic prediction will be achievable in our study population and that it will outperform traditional pedigree-based approaches to studying micro-evolution in nature.

Who will benefit, and how?
1) Academic and non-academic stakeholders.
Our project will be the first attempt to perform genomic prediction in a natural population. Therefore it should be of great interest to other researchers studying the genetic basis of phenotypic variation. Genomic prediction has enormous potential to help solve emerging ecological problems, because it can be conducted in populations that have not been the focus of painstaking longitudinal studies. For example, under a scenario similar to the 2012 ash tree (Fraxinus spp) dieback disease caused by the Chalara fraxinea fungus, it might be possible to type infected and uninfected trees as a training population and then predict the resistance of saplings in a nursery to aid the restocking of affected populations. Similarly, badgers (Meles meles) culled in an effort to reduce the incidence of bovine TB could be used as a training population to identify individuals that are genetically pre-disposed to being resistant or susceptible to TB. In plant breeding or conservation, genomic predictions for disease resistance, flood resistance, heat resistance or CO2 insensitivity could be used to identify which plants to use in breeding or translocation programs. The combination of cheap genotyping and the removal of the requirement for pedigrees/longitudinal data will mean that genomic prediction can have an enormous impact in ecology and conservation biology, in the same way that is has revolutionised animal and plant breeding.

We will ensure that any new code for carrying out genomic prediction will be made available e.g. through Dryad and appendices of published papers. Both the PI and CoI are actively involved in community-wide efforts to collaborate on 'wild genomics' projects e.g. we have used funds from our ERC projects to run a residential workshop where researchers in the field have exchanged ideas and spread best practice. These workshops are an ideal forum to encourage other researchers to attempt genomic prediction and colleagues are now planning follow-on workshops for 2014 and 2015.

2) University Teachers
Our previous work on Soay sheep genetics is widely used in teaching and textbooks. For example, our recent work on heterozygote advantage at the horns locus is already being used on several courses despite only being published in October 2013.

3) The general public
There is great public interest in both St Kilda and the Soay Sheep Project (see for example the BBC programs Bill Oddie Goes Wild and Britain's Lost World and coming soon, Coast) and more generally in ecological genetics. Our previous work has attracted considerable interest in the TV, radio and written media, because the sheep system provides many easy-to-understand examples of quite complex ecological genetic problems (e.g. the maintenance of genetic variation, sexual selection, colour polymorphisms, heterozygote advantage). We have a good track record of turning published outputs into accessible stories which will help the public to understand basic genetic and evolutionary principles. We hope that outputs from this project will spark interest in how genomic approaches can be used to tackle real-world ecological problems.

Whenever we have news-worthy outputs from the project we will liaise with the press offices at The University of Sheffield and The University of Edinburgh, who will help publicise our work. We already have good relationships with our media teams, who are familiar with our work.