Abstract
Genomic prediction, the technique whereby an individual's genetic component of their phenotype is estimated from its genome, has revolutionised animal and plant breeding and medical genetics. However, despite being first introduced nearly two decades ago, it has hardly been adopted by the evolutionary genetics community studying wild organisms. Here, genomic prediction is performed on eight traits in a wild population of Soay sheep. The population has been the focus of a >30year evolutionary ecology study and there is already considerable understanding of the genetic architecture of the focal Mendelian and quantitative traits. We show that the accuracy of genomic prediction is high for all traits, but especially those with loci of large effect segregating. Five different methods are compared, and the two methods that can accommodate zero-effect and large-effect loci in the same model tend to perform best. If the accuracy of genomic prediction is similar in other wild populations, then there is a real opportunity for pedigree-free molecular quantitative genetics research to be enabled in many more wild populations; currently the literature is dominated by studies that have required decades of field data collection to generate sufficiently deep pedigrees. Finally, some of the potential applications of genomic prediction in wild populations are discussed.
Highlights
A major aim of evolutionary quantitative genetics is to measure and understand heritable genetic variation, and to explain the maintenance of that variation in the face of natural and sexual selection and genetic drift (Walsh & Lynch, 2018)
4.1 | Conclusions and future directions. In this population the accuracy of genomic prediction was comparable to that seen in applied animal and plant breeding programs
Future work will examine whether a higher marker density (400– 500K SNPs) results in a further improvement in accuracy, we note that in livestock populations, improvements in genomic estimated breeding values (GEBVs) accuracy between 50–60 K SNP chips and whole genome sequences are often tiny (Frischknecht et al, 2018; Heidaritabar et al, 2016; Veerkamp et al, 2016)
Summary
A major aim of evolutionary quantitative genetics is to measure and understand heritable genetic variation, and to explain the maintenance of that variation in the face of natural and sexual selection and genetic drift (Walsh & Lynch, 2018). The pedigree of the population has been determined, allowing researchers to use either (i) quantitative genetics (Kruuk, 2004) and/ or (ii) gene mapping approaches (Slate et al, 2010) to study how selection and evolution have shaped diversity. Both approaches have led to genuine breakthroughs in our understanding of how genetic variation and selection have combined to shape biodiversity, but they both have limitations (especially when applied to natural populations). Proponents of both approaches are aware of these limitations, and they are actively seeking solutions (Charmantier et al, 2014)
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