Genomics of Adaptation in European Pines (GAP)

欧洲松树适应基因组学 (GAP)

• 批准号: NE/H003959/1
• 负责人: Stephen Cavers
• 金额: $ 43.78万
• 依托单位: NERC CEH (Up to 30.11.2019)
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FH003959%2F1
• 关键词: Genomics; Adaptation; European; Pines; GAP

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.

自然选择是一种地理上的可变力，部分由局部环境条件决定。由于表型是基因型及其环境的产物，并且表型决定了适应性，因此空间环境变异性应产生不同的适应种群，并且对当地条件进行了优化的表型。这种发散选择的过程是维持物种内遗传多样性的重要机制，对于长寿的久坐生物（如树木）尤其重要，因为树木适应了当地条件至关重要，因为它们将在一个终生中，而终身可能长达几个世纪。如果我们要对环境变化对树种的可能影响进行合理的预测，那么我们必须开始了解基因组水平上局部适应的过程，并鉴定基因和这些基因中的突变，这些突变与树木表型的控制有关。然而，几种进化力是针对分歧选择的作用，其中基因流是最重要的，人口统计学过程（例如灭绝和再持续化）可能会混淆局部适应性。因此，成功检测局部适应的分子特征需要平行评估进化过程和人口统计学过程，因为两者都塑造了自然种群的遗传变异。该项目将将从基因到表型的数据集成到人群量表，并将其应用于特殊选择的欧洲树种，其中存在明显的自适应差异，并且后冰期的定植动力学发挥了强烈的作用。该项目将利用大量的新基因组资源来研究与环境应激，物候和木材形成有关的核基因中表型变异与核苷酸多态性之间的联系，以及在四种松树物种的天然种群中的线粒体基因组中的联系。该物种包括通才，Pinus Sylvestris（Scots Pine），以及来自P. Mugo Complex的三个栖息地专家，即P. Mugo（Dwarf Mountain Pine），P。Uncinata（Mountain Pine）（山松木）和P. uliginosa（Peat-Bog Pine）。该物种构成了由于系统发育关系紧密而导致的中性和适应性变化的绝佳系统，但在地理分布，生物学和生态学方面存在强烈的对比。从根本上讲，该项目将整合基因组和表型数据和统计数据，从而为发展中的生物多样性研究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仍处于起步阶段，该项目将对科学做出两个主要的贡献：自然松树种群中基因组数据的最大分析，并在最近的进化历史上放置了独特的实验设计，从而实现了独特的实验设计。此外，该项目在自适应基因座上产生的信息将直接应用于基因保护和育种计划。这将增强森林遗传资源和树木生产质量的管理，特别是在当前影响大多数森林树种适应性最佳的气候变化方案下。项目输出也将直接应用于基于科学的保护中，例如，在苏格兰残留的苏格兰森林碎片中保存遗传资源。 CEH与负责管理英国森林资源管理的法定机构的牢固联系，并在将科学产出传达给最终用户方面的经验将有助于有效地提供结果。总而言之，该项目是一个即时优势新基因组数据，现成的收集以及高素质和经验丰富的研究人员的技能的绝佳机会。所有这些关键的项目组件都已经到位，现在可用，因此该项目有望对低风险产生很大的影响，并具有巨大的下游研究潜力。

项目成果

Genetic variation for needle traits in Scots pine (Pinus sylvestris L.)

• DOI: 10.1007/s11295-016-1000-4
• 发表时间: 2016-06-01
• 期刊: TREE GENETICS & GENOMES
• 影响因子: 2.4
• 作者: Donnelly, Kevin;Cavers, Stephen;Ennos, Richard A.
• 通讯作者: Ennos, Richard A.

Identifying and testing marker-trait associations for growth and phenology in three pine species: Implications for genomic prediction.

• DOI: 10.1111/eva.13345
• 发表时间: 2022-03
• 期刊: Evolutionary applications
• 影响因子: 4.1
• 作者: Perry A;Wachowiak W;Beaton J;Iason G;Cottrell J;Cavers S
• 通讯作者: Cavers S

Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research.

• DOI: 10.1111/tpj.15628
• 发表时间: 2022-03
• 期刊: PLANT JOURNAL
• 影响因子: 7.2
• 作者: Kastally, Chedly;Niskanen, Alina K.;Perry, Annika;Kujala, Sonja T.;Avia, Komlan;Cervantes, Sandra;Haapanen, Matti;Kesalahti, Robert;Kumpula, Timo A.;Mattila, Tiina M.;Ojeda, Dario, I;Tyrmi, Jaakko S.;Wachowiak, Witold;Cavers, Stephen;Karkkainen, Katri;Savolainen, Outi;Pyhajarvi, Tanja
• 通讯作者: Pyhajarvi, Tanja

Development of a single nucleotide polymorphism array for population genomic studies in four European pine species.

开发用于四种欧洲松树种群基因组研究的单核苷酸多态性阵列。

• DOI: 10.1111/1755-0998.13223
• 发表时间: 2020
• 期刊: Molecular ecology resources
• 影响因子: 7.7
• 作者: Perry A

Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research

• DOI: 10.1101/2021.06.29.450162
• 发表时间: 2021-06
• 期刊: The Plant Journal
• 作者: Chedly Kastally;Alina K. Niskanen;A. Perry;S. Kujala;K. Avia;Sandra Cervantes;M. Haapanen;Robert Kesälahti;T. Kumpula;Tiina M. Mattila;D. I. Ojeda;J. Tyrmi;W. Wachowiak;S. Cavers;K. Kärkkäinen;O. Savolainen;T. Pyhäjärvi