Genomics of Adaptation in European Pines (GAP)

自然选择是一种地理上可变的力量，部分由当地的环境条件决定。由于表型是基因型及其环境的产物，而表型决定了适应度，那么空间环境变异性应该产生不同的适应种群，并根据当地条件优化表型。这种分化选择的过程是维持物种遗传多样性的重要机制，对于像树木这样长寿命的定居生物来说尤其重要，因为它们将在一个地方生活，而这种生活可能长达几个世纪。如果我们要对环境变化对树种的可能影响形成合理的预测，那么我们必须开始在基因组水平上理解局部适应的过程，并确定参与控制树木表型的基因，以及这些基因中的突变。然而，一些进化力量的作用是对抗分化选择，其中基因流是最重要的，而人口统计学过程，如灭绝和再殖民化，可能会混淆当地适应。因此，成功地检测局部适应的分子特征需要对进化和人口统计学过程进行平行评估，因为这两个过程都会影响自然种群的遗传变异。该项目将整合从基因到表型到种群规模的数据，并将其应用于一组特别选择的欧洲树种，其中存在明显的适应性差异，并且冰川后的殖民化动态发挥了重要作用。该项目将利用大量新的基因组资源来研究四种松树自然种群中与环境胁迫、物候和木材形成有关的核基因的表型变异和核苷酸多态性之间的联系，以及线粒体基因组。这些物种包括一种多面手——苏格兰松（Pinus sylvestris），以及三种来自mugo松群的栖息地专一物种，即矮山松（P. mugo）、山地松（P. uncinata）和泥炭沼泽松（P. uliginosa）。由于系统发育关系密切，但在地理分布、生物学和生态学方面存在强烈的差异，该物种形成了一个研究中性和适应性变异的良好系统。从根本上说，该项目将整合基因组和表型数据以及统计数据，为生物多样性研究的发展领域做出独特而开创性的贡献。基因组方法在局部适应研究中的应用尚处于起步阶段，该项目将为科学做出两项主要的新贡献：对天然松树种群的基因组数据进行最大规模的分析，以及部署独特的实验设计，将种内适应差异置于最近进化史的背景下。此外，该项目产生的适应性位点信息将直接应用于基因保护和育种计划。这将加强对森林遗传资源和树木生产质量的管理，特别是在目前影响大多数森林树种适应性最佳的气候变化情景下。项目产出也将直接应用于以科学为基础的保护，例如，保护苏格兰苏格兰松林残片的遗传资源。CEH与负责管理英国森林资源的法定机构的紧密联系，以及在向最终用户传达科学成果方面的经验，将有助于有效地交付成果。总之，该项目是一个极好的机会，可以立即利用新的基因组数据，现成的收集和高素质和经验丰富的研究人员的技能。所有这些关键的项目组成部分现在都已经到位并可用，因此该项目承诺低风险，高影响，并具有巨大的下游研究潜力。

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.