Comparing the Predictive Abilities of Phenotypic and Marker-Assisted Selection Methods in a Biparental Lettuce Population
Comparing the Predictive Abilities of Phenotypic and Marker-Assisted Selection Methods in a Biparental Lettuce Population
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DOI：
10.3835/plantgenome2015.03.0014
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发表时间：
2016-03-01
期刊：
影响因子：
4.2
通讯作者：
Piepho, Hans-Peter
中科院分区：
文献类型：
--
作者：
Hadasch, Steffen;Simko, Ivan;Piepho, Hans-Peter
多基因遗传性状的育种是一项具有挑战性的任务，可以通过表型选择，标记辅助选择（MAS）或全基因组选择来完成。比较了4种选择模型对双亲莴苣（Lactucasativa L.）用95个单核苷酸多态性和205个扩增片段长度多态性标记对群体进行基因分型。这些模型是基于（i）表型选择，（ii）MAS（与数量性状基因座（QTL）连锁标记），（iii）基因组预测使用所有可用的分子标记，和（iv）基因组预测使用分子标记加QTL连锁标记作为固定的协变量。每个模型的性能进行了评估，使用数据的领域抗霜霉病（DMR，平均遗传力类似于0.71）和质量的货架寿命（SL，平均遗传力类似于0.91）的生菜在多个环境中。每个选择模型的预测能力进行了计算，根据采样基因型，环境，或两者兼而有之的交叉验证（CV）计划。对于DMR数据集，MAS模型的预测能力显著低于基因组预测模型。对于SL数据集，在三种CV方案中的两种方案下，基因组预测模型的预测能力显著低于使用QTL连锁标记的模型。我们的研究结果表明，选择模型的预测能力很大程度上取决于用于预测的CV方案和目标性状的遗传力。我们的研究还表明，分子标记可以用来预测DMR和SL的个人从这个十字架的基因型，但没有表型。
Breeding for traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, marker-assisted selection (MAS) or genome-wide selection. We comparatively evaluated the predictive abilities of four selection models on a biparental lettuce (Lactuca sativa L.) population genotyped with 95 single nucleotide polymorphisms and 205 amplified fragment length polymorphism markers. These models were based on (i) phenotypic selection, (ii) MAS (with quantitative trait locus (QTL)-linked markers), (iii) genomic prediction using all the available molecular markers, and (iv) genomic prediction using molecular markers plus QTL-linked markers as fixed covariates. Each model's performance was assessed using data on the field resistance to downy mildew (DMR, mean heritability similar to 0.71) and the quality of shelf life (SL, mean heritability similar to 0.91) of lettuce in multiple environments. The predictive ability of each selection model was computed under three cross-validation (CV) schemes based on sampling genotypes, environments, or both. For the DMR dataset, the predictive ability of the MAS model was significantly lower than that of the genomic prediction model. For the SL dataset, the predictive ability of the genomic prediction model was significantly lower than that for the model using QTL-linked markers under two of the three CV schemes. Our results show that the predictive ability of the selection models depends strongly on the CV scheme used for prediction and the heritability of the target trait. Our study also shows that molecular markers can be used to predict DMR and SL for individuals from this cross that were genotyped but not phenotyped.