CREA Research Center for Cereals and Industrial Crops, via di Corticella 133-40128 Bologna, Italy.
Crop, Soil, and Microbial Sciences Department, Michigan State University, 1066 Bogue St, East Lansing, MI 42824, USA.
Genes (Basel). 2019 Oct 24;10(11):841. doi: 10.3390/genes10110841.
The purpose of this work was to assess the performance of four genomic selection (GS) models (GBLUP, BRR, Bayesian LASSO and BayesB) in 4 sorghum grain antioxidant traits (phenols, flavonoids, total antioxidant capacity and condensed tannins) using whole-genome SNP markers in a novel diversity panel of lines and landraces and recombinant inbred lines. One key breeding problem modelled was predicting the performance in the antioxidant production of new and unphenotyped sorghum genotypes (validation set). The population was weakly structured (analysis of molecular variance, AMOVA R = 9%), showed a significant genetic diversity and expressed antioxidant traits with a good level of variability and high correlation. The lines outperformed populations for all the antioxidants. The four GS models implemented in this work performed comparably across traits, with accuracy ranging from 0.49 to 0.58, and are considered high enough to sustain sorghum breeding for antioxidants production and allow important genetic gains per unit of time and cost. The results presented in this work are expected to contribute to GS implementation and the genetic improvement of sorghum grain antioxidants for different purposes, including the manufacture of health-promoting and specialty foods.
这项工作的目的是评估 4 种基因组选择（GS）模型（GBLUP、BRR、贝叶斯 LASSO 和 BayesB）在一个新的多样性 个品系和地方品种和重组自交系的全基因组 SNP 标记下，对 4 个高粱籽粒抗氧化特性（酚类、类黄酮、总抗氧化能力和缩合单宁）的表现。模拟的一个关键育种问题是预测新的和未经表型高粱基因型（验证集）在抗氧化生产中的表现。该群体结构较弱（分子方差分析，AMOVA R = 9%），表现出显著的遗传多样性，并表现出具有良好变异性和高度相关性的抗氧化特性。与所有抗氧化剂相比， 品系表现优于 群体。本工作中实施的 4 种 GS 模型在各性状上的表现相当，准确性在 0.49 到 0.58 之间，被认为足以维持高粱抗氧化剂生产的育种，并允许在单位时间和成本内获得重要的遗传增益。本工作中提出的结果有望为 GS 的实施和高粱籽粒抗氧化剂的遗传改良提供参考，以用于不同的目的，包括生产促进健康和特色食品。
