title: Genome-wide prediction of three important traits in bread wheat.
abstract: Five genomic prediction models were applied to three wheat agronomic traits-grain yield, heading date and grain test weight-in three breeding populations, each comprising about 350 doubled haploid or recombinant inbred lines evaluated in three locations during a 3-year period. The prediction accuracy, measured as the correlation between genomic estimated breeding value and observed trait, was in the range of previously published values for yield (r= 0.2-0.5), a trait with relatively low heritability. Accuracies for heading date and test weight, with relatively high heritabilities, were about 0.70. There was no improvement of prediction accuracy when two or three breeding populations were merged into one for a larger training set (e.g., for yieldrranged between 0.11 and 0.40 in the respective populations and between 0.18 and 0.35 in the merged populations). Cross-population prediction, when one population was used as the training population set and another population was used as the validation set, resulted in no prediction accuracy. This lack of cross-population prediction accuracy cannot be explained by a lower level of relatedness between populations, as measured by a shared SNP similarity, since it was only slightly lower between than within populations. Simulation studies confirm that cross-prediction accuracy decreases as the proportion of shared QTLs decreases, which can be expected from a higher level of QTL × environment interactions.
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: Gilles
authors: G
authors: Charmet
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France ; Colorado State University, Fort Collins, CO 80523 USA.
authors: Eric
authors: E
authors: Storlie
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: François Xavier
authors: FX
authors: Oury
authors: Bioplante-Florimond Desprez, BP41, 59242 Cappelle en Pévèle, France.
authors: Valérie
authors: V
authors: Laurent
authors: Bioplante-Florimond Desprez, BP41, 59242 Cappelle en Pévèle, France.
authors: Denis
authors: D
authors: Beghin
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: Laetitia
authors: L
authors: Chevarin
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: Annie
authors: A
authors: Lapierre
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: Marie Reine
authors: MR
authors: Perretant
authors: INRA-APBV, Domaine de la Motte, BP 35327, 35653 Le Rheu Cedex, France.
authors: Bernard
authors: B
authors: Rolland
authors: INRA UE Lille, 2 chaussée Brunehaut, Estrées-Mons, BP 50136, 80203 Peronne Cedex, France.
authors: Emmanuel
authors: E
authors: Heumez
authors: Bioplante-R2n, 60 rue Léon Beauchamp, 59930 La Chapelle d'Armentières, France.
authors: Laure
authors: L
authors: Duchalais
authors: Bioplante-Florimond Desprez, BP41, 59242 Cappelle en Pévèle, France.
authors: Ellen
authors: E
authors: Goudemand
authors: UMR GDEC, INRA-Université Clermont II, 5 chemin de Beaulieu, 63039 Clermont-Ferrand Cedex, France.
authors: Jacques
authors: J
authors: Bordes
authors: Bioplante-Florimond Desprez, BP41, 59242 Cappelle en Pévèle, France.
authors: Olivier
authors: O
authors: Robert
keywords: Bayesian LASSO; Genomic selection; Plant breeding; Random Forest regression; Ridge regression; Triticum aestivum L.