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Summary

Published in Heredity 124: 562–578. https://doi.org/10.1038/s41437-019-0290-3

Genomic selection (GS) has a large potential for improving the prediction accuracy of breeding values and significantly reducing the length of breeding cycles. In this context, the choice of mating designs becomes critical to improve the efficiency of breeding operations and to obtain the largest genetic gains per time unit. Polycross mating designs have been traditionally used in tree and plant breeding to perform backward selection of the female parents. The possibility to use genetic markers for paternity identification and for building genomic prediction models should allow for a broader use of polycross tests in forward selection schemes. We compared the accuracies of genomic predictions of offspring’s breeding values from a polycross and a full-sib (partial diallel) mating design with similar genetic background in white spruce (Picea glauca). Trees were phenotyped for growth and wood quality traits, and genotyped for 4092 SNPs representing as many gene loci distributed across the 12 spruce chromosomes. For the polycross progeny test, heritability estimates were smaller, but more precise using the genomic BLUP (GBLUP) model as compared with pedigree-based models accounting for the maternal pedigree or for the reconstructed full pedigree. Cross-validations showed that GBLUP predictions were 22–52% more accurate than predictions based on the maternal pedigree, and 5–7% more accurate than predictions using the reconstructed full pedigree. The accuracies of GBLUP predictions were high and in the same range for most traits between the polycross (0.61–0.70) and full-sib progeny tests (0.61–0.74). However, higher genetic gains per time unit were expected from the polycross mating design given the shorter time needed to conduct crosses. Considering the operational advantages of the polycross design in terms of easier handling of crosses and lower associated costs for test establishment, we believe that this mating scheme offers great opportunities for the development and operational application of forward GS.

Sector(s): 

Forests

Categorie(s): 

Scientific Article

Theme(s): 

Forest Genetics, Forest Tree Breeding, Forestry Research, Forests

Departmental author(s): 

Author(s)

LENZ, Patrick R. N., Simon NADEAU, Aïda AZAIEZ, Sébastien GÉRARDI, Marie DESLAURIERS, Martin PERRON, Nathalie ISABEL, Jean BEAULIEU and Jean BOUSQUET

Year of publication :

2020

Format :

PDF available upon request

ISSN

1365-2540

Keywords :

épinette blanche, sélection par la génomique, amélioration génétique, amélioration génétique des arbres, Picea glauca, polycross, article scientifique de recherche forestière, forest tree breeding, white spruce, genomic selection, tree breeding, forestry research scientific article

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