Combining QTL Analysis and Genomic Predictions for Four Durum Wheat Populations Under Drought Conditions - Zaïm, Meryem; Kabbaj, Hafssa; Kehel, Zakaria; Gorjanc, Gregor; Filali-Maltouf, Abdelkarim; Belkadi, Bouchra; Nachit, Miloudi M.; Bassi, Filippo M. (Frontiers in Genetics, 2020)
Durum wheat is an important crop for the human diet and it is consumed largely in the form of traditional dishes such as pasta, couscous, unraised breads, and bourghul.Worldwide, the consumption of durum wheat is gaining popularity because of its nutritional properties. In order to ensure that durum wheat production maintains the pace with the increase in demand, it is necessary an increase in productivity of approximately 1.5% per year. To deliver this level of annual genetic gain it is necessary to support breeding with the incorporation of targeted quantitative trait loci and the deployment the use of genomic selection (GS). Here, four RILs populations were used to conduct QTL discovery for grain yield (GY) and 1,000 kernel weight (TKW). A total of 576 individuals were sown at three locations in Morocco and Lebanon. These individuals were genotyped by sequencing with 3,202 high-confidence polymorphic markers, to derive a consensus genetic map of 2,705.7 cM, which was used to impute any missing data. Six QTL were found to be associated with GY and independent from flowering time in chromosomes 2B, 4A, 5B, 7A and 7B, explaining a phenotypic variation (PV) ranging from 4.3% to 13.4%. In addition, the same populations were used to train genomic prediction models incorporating the relationship matrix, the genotype by environment interaction, and marker by environment interaction.Accuracies were also computed among full sibs and half sibs families. The QTL identified were also incorporated in the models. Our results confirm that the prediction accuracy depend on heritability of the trait, the size of the populations, the size of TP and VP and relatedness between TP and VP. Also, feeding the model with information on markers associated with significant QTLs increased the overall accuracy.3