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首页> 美国卫生研究院文献>Scientific Reports >Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones
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Genomic prediction models for grain yield of spring bread wheat in diverse agro-ecological zones

机译：农业生态区春面包小麦籽粒产量的基因组预测模型

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Genomic and pedigree predictions for grain yield and agronomic traits were carried out using high density molecular data on a set of 803 spring wheat lines that were evaluated in 5 sites characterized by several environmental co-variables. Seven statistical models were tested using two random cross-validations schemes. Two other prediction problems were studied, namely predicting the lines’ performance at one site with another (pairwise-site) and at untested sites (leave-one-site-out). Grain yield ranged from 3.7 to 9.0 t ha−1 across sites. The best predictability was observed when genotypic and pedigree data were included in the models and their interaction with sites and the environmental co-variables. The leave-one-site-out increased average prediction accuracy over pairwise-site for all the traits, specifically from 0.27 to 0.36 for grain yield. Days to anthesis, maturity, and plant height predictions had high heritability and gave the highest accuracy for prediction models. Genomic and pedigree models coupled with environmental co-variables gave high prediction accuracy due to high genetic correlation between sites. This study provides an example of model prediction considering climate data along-with genomic and pedigree information. Such comprehensive models can be used to achieve rapid enhancement of wheat yield enhancement in current and future climate change scenario.
机译：使用高密度分子数据对一组803春小麦品系进行了基因组和谱系预测，以高密度分子数据对5个站点进行了评估，这些站点以几个环境协变量为特征。使用两个随机交叉验证方案测试了七个统计模型。研究了另外两个预测问题，即预测一个站点与另一个站点（成对站点）和未测试站点（留出一个站点）的生产线性能。不同地点的谷物产量在3.7至9.0 t ha -1 之间。当将基因型和谱系数据包括在模型中以及它们与位点和环境协变量的相互作用时，观察到最佳的可预测性。对于所有性状，留一留点法的平均预测准确度均高于成对留白，特别是谷物产量从0.27增至0.36。花期，成熟期和株高的预测天数具有很高的遗传力，并且预测模型的准确性最高。由于位点之间的高度遗传相关性，基因组和谱系模型与环境协变量相结合提供了较高的预测准确性。这项研究提供了一个考虑气候数据以及基因组和谱系信息的模型预测示例。这样的综合模型可用于在当前和未来的气候变化情景中实现小麦单产的快速提高。

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