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FACCE ERA-NET+ GrassLandscape (Project Leader: Jean-Paul Sampoux, INRA, France)

FACCE ERA-NET GrassLandscape（项目负责人：Jean-Paul Sampoux，INRA，法国）

基本信息

批准号：
BB/M018393/1
负责人：
Matthew Hegarty
金额：
$ 31.31万
依托单位：
Aberystwyth University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FM018393%2F1
关键词：
FACCE ERA NET+GrassLandscape Project

项目摘要

Our project aims to implement an innovative methodological frame to screen the natural diversity of agrassland species in order to discover genetic variability involved in environmental adaptation, and morespecifically in climatic adaptation (Sampoux et al., 2013). We will consider the use of results delivered by thisapproach to plan strategies to restore permanent grasslands degraded by climatic shifts and disruptions. Ourproject will focus on perennial ryegrass (Lolium perenne L.), which is a major grass species naturallydistributed over the whole European continent as well as in Northern Africa and Near East (Humphreys et al.,2010). This species is a major component of many natural grassland communities. It is a resource capturestrategy species (Martin et al., 2009) which is especially prevalent in grasslands grazed by cattle. It is also themain grass species sown in Europe to create temporary meadows and it has therefore received extensivebreeding effort during the last four decades (Sampoux et al., 2011). Recent developments in a new area ofecological sciences (landscape genomics) have paved the way to the discovery of genomic markers ofadaptive diversity from genome-wide genotyping data. They are based on the implementation of methodscorrelating genomic polymorphisms and environmental variations at sites of origin of genotypes combinedwith tests of signature of selection (Manel et al., 2010). We will implement this methodological frame to detectgenomic markers of climatic adaptation in the natural diversity of perennial ryegrass. We will use a genotypingmethod based on massively parallel sequencing technology applied to a high number of populations obtainedfrom genebanks of plant breeding research institutes or collected in situ across Europe. We will furthermoretake advantage of know-how and facilities of plant breeding research institutes participating in the project tophenotype these populations in fields and in controlled environment to record agronomic and ecophysiologicaltraits. These phenotypic data will be used to model associations between phenotypic variabilityand genomic polymorphisms. Association models between genomic polymorphisms and environmental variations will be used to mapthe spatial distribution of genomic markers linked to adaptive diversity in present climatic conditions and toforesee possible shifts in the spatial range fitting these markers in the context of several climate changescenarios based on the four Representative Concentration Pathways (RCP) of IPCC AR5 (Moss et al., 2010).On the basis of these results, we will define allelic profiles of perennial ryegrass expected to provide climaticadaptation at regional scale over Europe under the future climatic conditions foreseen by climate models. Wewill consider combining climatic adaptation and value for services (forage production and climate mitigation)by the recombination of alleles providing climatic adaptation and value for services. We will design severalgenetic pools mixing different natural populations for breeding regionally adapted populations to restorepermanent grasslands degraded climatic disruptions. Breeding and releasing improved genetic material willbe out of the scope of the project but will be discussed with stakeholders at the end of the project during adhoc meetings for implementation in further collaborative projects.

我们的项目旨在实施一种创新的方法框架来筛选草地物种的自然多样性，以发现与环境适应有关的遗传变异，尤其是与气候适应有关的遗传变异（Sampoux等，2013）。我们将考虑利用这种方法提供的结果来规划战略，以恢复因气候变化和破坏而退化的永久草原。我们的项目将重点关注多年生黑麦草（Lolium perenne L.），这是一种自然分布在整个欧洲大陆以及北非和近东的主要草种（Humphreys et al.,2010）。本种是许多天然草地群落的主要组成部分。它是一种资源捕获策略物种（Martin et al., 2009），在牛放牧的草原上特别普遍。它也是欧洲种植的主要草种，用于创建临时草地，因此在过去四十年中得到了广泛的育种努力（Sampoux等人，2011）。生态科学新领域（景观基因组学）的最新发展为从全基因组基因分型数据中发现适应性多样性的基因组标记铺平了道路。它们是基于将基因型起源地点的基因组多态性和环境变化联系起来的方法，并结合选择特征测试（Manel等人，2010年）。我们将实施这一方法框架来检测多年生黑麦草自然多样性中气候适应的基因组标记。我们将使用一种基于大规模平行测序技术的基因分型方法，该技术应用于从植物育种研究所基因库获得的大量种群或在欧洲各地就地收集的种群。我们将进一步利用参与项目的植物育种研究所的专业知识和设备，在田间和受控环境下对这些群体进行表型分析，记录农艺和生态生理性状。这些表型数据将用于建立表型变异和基因组多态性之间的关联模型。基因组多态性与环境变化之间的关联模型将用于绘制当前气候条件下与适应性多样性相关的基因组标记的空间分布，并基于IPCC AR5的四个代表性浓度路径（RCP），预测在几种气候变化情景下拟合这些标记的空间范围可能发生的变化（Moss等，2010）。在这些结果的基础上，我们将定义多年生黑麦草的等位基因分布，以期在气候模式预测的未来气候条件下在欧洲区域尺度上提供气候适应。我们将考虑通过重组提供气候适应和服务价值的等位基因，将气候适应和服务价值（饲料生产和气候减缓）结合起来。我们将设计多个混合不同自然种群的基因库，培育适应区域的种群，以恢复退化的永久性草原。育种和释放改良的遗传物质将不在项目范围之内，但将在项目结束时的特别会议上与利益相关者讨论，以便在进一步的合作项目中实施。