Department of Plant Breeding, Swedish University of Agricultural Sciences, Sundsvagen 14, Box 101, Alnarp, SE 23053, Sweden.
Department of Plant Breeding, Swedish University of Agricultural Sciences, Sundsvagen 14, Box 101, Alnarp, SE 23053, Sweden.
Trends Plant Sci. 2014 Sep;19(9):592-601. doi: 10.1016/j.tplants.2014.05.006. Epub 2014 Jun 23.
Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy.
关联分析用于测量标记物和数量性状基因座（QTL）之间的关系。它们的估计忽略了具有触发基础数量性状的小效应的基因。相比之下，全基因组选择基于在训练群体（TP）中开发的预测模型，在目标群体中估计整个基因组上的标记物效应。全基因组预测模型估计所有基因座中所有标记物的效应，并捕获小 QTL 效应。在这里，我们根据预测准确性和遗传增益，对几种基因组选择（GS）模型进行了综述。基于全基因组预测的选择可以替代表型选择或标记辅助育种方案，在这种方案中，表型更新模型以提高预测准确性。
