Postgrado en Recursos Genéticos y Productividad-Genética, Colegio de Postgraduados, Campus Montecillo, Texcoco 56264, Estado de México, Mexico.
International Maize and Wheat Improvement Center (CIMMYT), Km 35 Carretera México-Veracruz, Texcoco 56237, Estado de México, Mexico.
Int J Mol Sci. 2023 Jun 22;24(13):10506. doi: 10.3390/ijms241310506.
Genomic prediction combines molecular and phenotypic data in a training population to predict the breeding values of individuals that have only been genotyped. The use of genomic information in breeding programs helps to increase the frequency of favorable alleles in the populations of interest. This study evaluated the performance of BLUP (Best Linear Unbiased Prediction) in predicting resistance to tan spot, spot blotch and Septoria nodorum blotch in synthetic hexaploid wheat. BLUP was implemented in single-trait and multi-trait models with three variations: (1) the pedigree relationship matrix (A-BLUP), (2) the genomic relationship matrix (G-BLUP), and (3) a combination of the two matrices (A+G BLUP). In all three diseases, the A-BLUP model had a lower performance, and the G-BLUP and A+G BLUP were statistically similar ( ≥ 0.05). The prediction accuracy with the single trait was statistically similar ( ≥ 0.05) to the multi-trait accuracy, possibly due to the low correlation of severity between the diseases.
基因组预测将分子和表型数据结合在一个训练群体中，以预测仅进行基因分型的个体的育种值。在育种计划中使用基因组信息有助于增加目标群体中有利等位基因的频率。本研究评估了 BLUP（最佳线性无偏预测）在预测普通小麦合成六倍体对叶斑病、条斑病和叶枯病抗性中的表现。BLUP 分别在单性状和多性状模型中实施了三种变化：（1）系谱关系矩阵（A-BLUP），（2）基因组关系矩阵（G-BLUP），（3）两种矩阵的组合（A+G BLUP）。在所有三种疾病中，A-BLUP 模型的性能较低，而 G-BLUP 和 A+G BLUP 在统计学上相似（≥0.05）。单性状的预测准确性与多性状准确性在统计学上相似（≥0.05），这可能是由于疾病之间严重程度的相关性较低。
