In this paper, the aims were (a) to test the usefulness of using genomic and phenotypic information from public databases (open access) to predict genetic values for tropical maize inbred lines regarding plant and ear height; (b) to identify how the population structure, the use of optimized training sets (OTSs) and the amount of information originating from public databases affect the predictive ability. Thus, 29 training sets (TSs) were defined considering three diversity panels: the University of São Paulo (USP—validation set (VS)) and the ASSO and USDA North Central Regional Plant Introduction Station (NCRPIS) (external public panels—predictors), which were divided into four scenarios with different TS configurations. We showed that it is possible to use public datasets as a primary TS and that population structure can modify the predictive abilities of GS. In the four scenarios proposed, very large or very small sets did not provide predictive abilities over 0.53 for GS. However, OTSs composed of 250 individuals were sufficient to achieve predictive abilities over this limit.

中文翻译：

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使用公共数据库进行热带玉米品系的基因组预测

本文的目的是（a）测试使用公共数据库中的基因组和表型信息（开放获取）来预测热带玉米自交系关于植物和穗高的遗传价值的有用性；（b）确定人口结构，使用优化的训练集（OTS）和来自公共数据库的信息量如何影响预测能力。因此，定义了29个培训集（TSs），其中考虑了三个多样性小组：圣保罗大学（USP-验证集（VS））和ASSO和USDA北部中部地区植物引入站（NCRPIS）（外部公共小组-​​预测者） ，分为四个具有不同TS配置的方案。我们表明，可以将公共数据集用作主要的TS，人口结构可以修改GS的预测能力。在提出的四个方案中，非常大或非常小的集合都没有提供超过0.53的GS预测能力。但是，由250个人组成的OTS足以实现超过此限制的预测能力。