Improvement of Genomic Prediction by Including Additive-by-Additive Epistasis. A Case of Study in Advanced Wheat-Breeding Lines

Miguel Angel Raffo, Pernille Merete Sarup (Medlem af forfattersamarbejde), Xiangyu Guo (Medlem af forfattersamarbejde), Huiming Liu (Medlem af forfattersamarbejde), Just Jensen (Medlem af forfattersamarbejde)

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Abstract

Epistasis is the principal non-additive genetic effect in wheat since dominance is negligible in inbred lines. Epistatic interactions are fixed in inbred lines and can be used by breeders to select cultivars based on total genetic-merit. A correct model definition for variance component estimation contributes to disentangle the genetic architecture of complex traits in wheat. We aimed to i) evaluate the performance of the extended genomic best linear unbiased prediction (EG-BLUP) and the natural and orthogonal interactions approach (NOIA) for variance components estimation in a commercial wheat-breeding population, and ii) investigate whether including epistasis in genomic prediction enhance the predictive ability (PA) for wheat-breeding lines. In total, 2060 F6-lines from Nordic Seed A/S Breeding-Company were phenotyped for grain yield in multiple years/locations in Denmark and genotyped using SNP15K-Illumina-BeadChip. Four models were used to estimate variance components and heritability on plot level: i) Baseline model without genomic information, ii) G-BLUP, iii) EG-BLUP including additive-by-additive epistasis, and iv) NOIA. Narrow-sense and broad-sense grain yield plot heritabilities estimated with the G-BLUP were 0.15 and 0.31, respectively. EG-BLUP and NOIA failed to achieve orthogonal partition of genetic variances. Even though NOIA removed the Hardy-Weinberg-Equilibrium assumption, both models yielded similar estimates, indicating that the lack of orthogonality can be attributed to the population linkage disequilibrium. PA of G-BLUP and EG-BLUP were studied using Leave-One-Line-Out cross-validation, and EG-BLUP increased PA (16.5%) significantly. We conclude that although the variance partition into orthogonal genetic effects was not possible, the EG-BLUP can enhance predictions of total genetic-merit contributing to better product development.
OriginalsprogEngelsk
Publikationsdato2020
StatusUdgivet - 2020
BegivenhedThe 6th International Conference of Quantitative Genetics -
Varighed: 3 nov. 2020 → …

Konference

KonferenceThe 6th International Conference of Quantitative Genetics
Periode03/11/2020 → …

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