当前位置: X-MOL 学术Plant Genome › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Genomic Prediction of Pumpkin Hybrid Performance.
The Plant Genome ( IF 4.219 ) Pub Date : 2019-06-01 , DOI: 10.3835/plantgenome2018.10.0082
Po-Ya Wu , Chih-Wei Tung , Chieh-Ying Lee , Chen-Tuo Liao

Genomic prediction has become an increasingly popular tool for hybrid performance evaluation in plant breeding mainly because that it can reduce cost and accelerate a breeding program. In this study, we propose a systematic procedure to predict hybrid performance using a genomic selection (GS) model that takes both additive and dominance marker effects into account. We first demonstrate the advantage of the additive–dominance effects model over the only additive effects model through a simulation study. Based on the additive–dominance model, we predict genomic estimated breeding values (GEBVs) for individual hybrid combinations and their parental lines. The GEBV‐based specific combining ability (SCA) for each hybrid and general combining ability (GCA) for its parental lines are then derived to quantify the degree of midparent heterosis (MPH) or better‐parent heterosis (BPH) of the hybrid. Finally, we estimate the variance components resulting from additive and dominance gene action effects and heritability using a genomic best linear unbiased predictor (g‐BLUP) model. These estimates are used to justify the results of the genomic prediction study. A pumpkin (Cucurbita spp.) data set is given to illustrate the provided procedure. The data set consists of 320 parental lines with 61,179 collected single nucleotide polymorphism (SNP) markers; 119, 120, and 120 phenotypic values of hybrids on three quantitative traits within C.maxima Duchesne; and 89, 111, and 90 phenotypic values of hybrids on the same three quantitative traits within C. moshata Dechesne.

中文翻译:

南瓜杂种表现的基因组预测。

基因组预测已成为植物育种中杂交表现评估的一种越来越流行的工具,主要是因为它可以降低成本并加快育种程序。在这项研究中,我们提出了使用基因组选择(GS)模型预测杂种性能的系统程序,该模型同时考虑了加性和优势标记效应。我们首先通过模拟研究证明了加性-主导效应模型优于唯一的加性效应模型的优势。基于加性优势模型,我们预测了单个杂种组合及其亲本的基因组估计育种值(GEBV)。然后,得出每个杂种的基于GEBV的特异结合能力(SCA)和其亲本系的一般结合能力(GCA),以量化该杂种的中父母杂种优势(MPH)或更好父母杂种优势(BPH)的程度。最后,我们使用基因组最佳线性无偏预测因子(g-BLUP)模型估算由加性和优势基因作用效应和遗传性产生的方差分量。这些估计用于证明基因组预测研究的结果合理。一个南瓜 (给出了南瓜属(Cucurbita spp。)数据集以说明所提供的过程。数据集由320个亲本系组成,具有61,179个收集到的单核苷酸多态性(SNP)标记;119,120和120上在三个数量性状的杂种表型值Ç .maxima杜申; 在C. moshata Dechesne内,相同的三个数量性状上的杂种的表型值分别为89、111和90 。
更新日期:2019-06-01
down
wechat
bug