Morales Laura, Akdemir Deniz, Girard Anne-Laure, Neumayer Anton, Reddy Nannuru Vinay Kumar, Shahinnia Fahimeh, Stadlmeier Melanie, Hartl Lorenz, Holzapfel Josef, Isidro-Sánchez Julio, Kempf Hubert, Lillemo Morten, Löschenberger Franziska, Michel Sebastian, Buerstmayr Hermann
Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden.
Institute of Biotechnology in Plant Production, Department of Agrobiotechnology, University of Natural Resources and Life Sciences Vienna, Tulln an der Donau, Austria.
Front Plant Sci. 2024 Oct 4;15:1454473. doi: 10.3389/fpls.2024.1454473. eCollection 2024.
Fusarium head blight (FHB) is a devastating disease of wheat, causing yield losses, reduced grain quality, and mycotoxin contamination. Breeding can mitigate the severity of FHB epidemics, especially with genomics-assisted methods. The mechanisms underlying resistance to FHB in wheat have been extensively studied, including phenological traits and genome-wide markers associated with FHB severity. Here, we aimed to improve genomic prediction for FHB resistance across breeding programs by incorporating FHB-correlated traits and FHB-associated loci as model covariates. We combined phenotypic data on FHB severity, anthesis date, and plant height with genome-wide marker data from five Central European winter wheat breeding programs for genome-wide association studies (GWAS) and genomic prediction. Within all populations, FHB was correlated with anthesis date and/or plant height, and a marker linked to the semi-dwarfing locus was detected with GWAS for FHB. Including the marker, anthesis date, and/or plant height as covariates in genomic prediction modeling improved prediction accuracy not only within populations but also in cross-population scenarios.
小麦赤霉病（FHB）是一种毁灭性的小麦病害，会导致产量损失、谷物品质下降和霉菌毒素污染。育种可以减轻小麦赤霉病流行的严重程度，特别是通过基因组辅助方法。小麦对赤霉病抗性的潜在机制已得到广泛研究，包括与赤霉病严重程度相关的物候性状和全基因组标记。在这里，我们旨在通过将与赤霉病相关的性状和与赤霉病相关的基因座作为模型协变量纳入，来改进不同育种计划中对赤霉病抗性的基因组预测。我们将赤霉病严重程度、开花日期和株高的表型数据与来自五个中欧冬小麦育种计划的全基因组标记数据相结合，用于全基因组关联研究（GWAS）和基因组预测。在所有群体中，赤霉病与开花日期和/或株高相关，并且通过赤霉病的GWAS检测到一个与半矮化基因座连锁的标记。在基因组预测模型中，将该标记、开花日期和/或株高作为协变量纳入，不仅提高了群体内的预测准确性，而且在跨群体情况下也提高了预测准确性。
