The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

农业物种的自然遗传多样性是旨在改善其生态系统和生产服务的育种计划的重要遗传资源。大多数草原物种通常都有大量的自然生态型多样性。这可用于重新组合自然气候适应和农艺价值，以创造适应未来区域气候的改良草地物种种群。但是，描述自然遗传资源可能会很长且成本很高。分子标记可能会提供有用的信息来帮助完成此任务。对该机会进行了黑麦草的研究L.，使用了从该物种的自然多样性中收集的385种材料，这些材料直接在欧洲收集并由多个国家的种质库提供。对于这些人群中的每一个，基因分型提供了189,781个SNP标记的等位基因频率。GWAS已针对在三个气候相反的地点（法国，比利时，德国）记录的30多个农艺和/或推定的适应性状实施。尽管遗传背景有很强的混杂效应，但仍检测到数百种标记的显着关联。其中大多数与物候特征有关。这些性状的遗传变异性可能对环境适应和生态型分化有重要贡献。发现使用自然多样性校准的基因组预测模型对于描述几乎所有特征的自然种群以及描述某些重要特征（例如抗病性，春季生长或物候性状）的商业合成种群非常有效。这些结果无疑将是有助于利用其他物种的自然遗传资源的宝贵信息。