Genomics of Adaptation in European Pines (GAP)

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Natural selection is a geographically variable force, determined in part by local environmental conditions. As phenotype is a product of a genotype and its environment, and phenotype determines fitness, then spatial environmental variability should produce differently adapted populations, with phenotypes optimised to local conditions. This process of divergent selection is an important mechanism for maintaining genetic diversity within species, and is particularly critical for long-lived sedentary organisms like trees, where adaptation to local conditions is crucial, as they will be in one place for life and that lifetime may be centuries long. If we are to form reasonable predictions of the likely impacts of environmental change on tree species, then we must begin to understand the process of local adaptation at a genomic level and identify the genes, and the mutations in those genes, that are involved in control of tree phenotype. However, several evolutionary forces act to counter divergent selection, of which gene flow is the most significant, and demographic processes such as extinction and recolonisation may confound local adaptation. Therefore, successful detection of the molecular signature of local adaptation requires parallel evaluation of evolutionary and demographic processes, as both shape genetic variation in natural populations. This project will integrate data from the gene to phenotype to population scale and apply this to a specially selected group of European tree species, in which clear adaptive divergence is present and where post-glacial colonisation dynamics have played a strong role. The project will take advantage of a large new genomic resource to study links between phenotypic variation and nucleotide polymorphism in nuclear genes related to environmental stress, phenology and wood formation, and in the mitochondrial genome in natural populations of four pine species. The species include a generalist, Pinus sylvestris (Scots pine), and three habitat specialist species from the P. mugo complex i.e. P. mugo (dwarf mountain pine), P. uncinata (mountain pine) and P. uliginosa (peat-bog pine). The species form an excellent system for study of neutral and adaptive variation due to close phylogenetic relationships but strong contrasts in geographic distribution, biology and ecology. Fundamentally, the project will integrate genomic and phenotypic data and statistics to make a unique and ground-breaking contribution to a developing field of biodiversity research. The application of genomic approaches to the study of local adaptation is in its infancy and this project will make two major new contributions to the science: the largest analysis of genomic data in natural pine populations, and deployment of a unique experimental design, placing intraspecific adaptive divergence in the context of recent evolutionary history. In addition, the information generated by the project, on adaptive loci, will be of direct application in gene conservation and breeding programs. This will enhance management of forest genetic resources and tree production quality, particularly under the climate change scenarios currently affecting adaptive optima of most forest tree species. Project outputs will also be of direct application in science-based conservation, for example, in conserving genetic resources in the remnant Scots Pine forest fragments in Scotland. CEH's strong links with statutory bodies responsible for management of the UK forest resource and experience in communicating scientific outputs to end users will facilitate effective delivery of results. In summary, the project is an excellent opportunity to take immediate advantage of new genomic data, a ready-made collection and the skills of highly qualified and experienced researchers. All of these key project components are in place and available now, so the project promises high impact for low risk and with significant potential for downstream research.