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Multi-Environmental Trials Reveal Genetic Plasticity of Oat Agronomic Traits Associated With Climate Variable Changes

机译:多环境试验揭示了与气候变化相关的燕麦农艺性状的遗传可塑性

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摘要

Although oat cultivation around the Mediterranean basin is steadily increasing, its yield in these regions lags far behind those of Northern Europe. This results mainly from the poor adaptation of current oat cultivars to Mediterranean environments. Local landraces may act as reservoirs of favorable traits that could contribute to increase oat resilience in this region. To aid selection of suitable agro-climate adapted genotypes we integrated genome-wide association approaches with analysis of field assessed phenotypes of genetic variants and of the weight of associated markers across different environmental variables. Association models accounting for oat population structure were applied on either arithmetic means or best linear unbiased prediction (BLUPs) to ensure robust identification of associations with the agronomic traits evaluated. The meta-analysis of the six joint environments (mega-environment) identified several markers associated with several agronomic traits and crown rust severity. Five of these associated markers were located within expressed genes. These associations were only mildly influenced by climatic variables indicating that these markers are good candidates to improve the genetic potential of oat under Mediterranean conditions. The models also highlighted several marker-trait associations, strongly affected by particular climatic variables including high rain pre- or post-heading dates and high temperatures, revealing strong potential for oat adaptation to specific agro-climatic conditions. These results will contribute to increase oat resilience for particular climatic conditions and facilitate breeding for plant adaptation to a wider range of climatic conditions in the current scenario of climate change.
机译:尽管地中海盆地周围的燕麦种植稳步增长,但在这些地区的燕麦产量却远远落后于北欧。这主要是由于当前燕麦品种对地中海环境的适应性差。当地的地方品种可以作为有利特性的储藏库,有助于增加该地区的燕麦弹性。为了帮助选择合适的适应农业气候的基因型,我们整合了全基因组关联方法,并分析了现场评估的遗传变异表型以及跨不同环境变量的相关标记的权重。将用于解释燕麦种群结构的关联模型应用于算术平均值或最佳线性无偏预测(BLUP),以确保可靠地识别与评估的农艺性状之间的关联。对六个关节环境(巨型环境)的荟萃分析确定了与几种农艺性状和冠锈病严重程度相关的几种标记。这些相关标记中的五个位于表达的基因内。这些关联仅受到气候变量的轻微影响,表明这些标记物是提高地中海条件下燕麦遗传潜力的良好候选者。这些模型还突出显示了几种标记-性状关联,这些关联受特定气候变量的强烈影响,包括抽穗前或抽穗后的高降雨日期和高温,显示燕麦有可能适应特定的农业气候条件。这些结果将有助于提高燕麦在特定气候条件下的适应力,并促进育种,以使植物适应当前气候变化情况下更广泛的气候条件。

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