Schulthess Albert W, Zhao Yusheng, Longin C Friedrich H, Reif Jochen C
Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany.
Theor Appl Genet. 2018 Mar;131(3):685-701. doi: 10.1007/s00122-017-3029-7. Epub 2017 Dec 2.
Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.
通过从单性状基因组预测转向多性状基因组预测赤霉病严重程度，与估计集相关性较低的小麦杂交种的预测能力得到了提高。培育具有改良抗赤霉病能力（FHBr）的小麦是一项非常费力且昂贵的任务。FHBr的复杂性主要归因于其高度多基因的性质，以及赤霉病严重程度（FHBs）受环境影响很大。相关性状株高和抽穗期可能提供与FHBr相关的额外信息，但在单性状基因组预测（STGP）中被忽略。我们研究的目的是利用17372个单核苷酸多态性标记以及指示性状株高和抽穗期的信息，在1604个小麦杂交种群体中，探索多性状基因组预测（MTGP）相对于目标性状FHBs的STGP在预测能力方面的优势。FHBs的加性遗传使得利用双亲的一般配合力或平均表现信息就能准确预测杂交种表现，而无需标记。分子标记和指示性状的信息提高了与估计集相关性较低的杂交种的FHBs预测能力。必须在预测个体上观察指示性状才能从MTGP中受益。遗传和表型相关性的大小以及预测能力的提高使得株高成为比抽穗期更好的FHBs指示性状。因此，仅以株高作为指示性状的MTGP已经使FHBs预测能力最大化。如果有良好的指示性状，MTGP可以减少基因型 - 环境[公式：见原文]互作对与估计集相关性较低的杂交种STGP的影响。
