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Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce

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 ge...

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Autores principales: Lenz, Patrick R. N., Nadeau, Simon, Azaiez, Aïda, Gérardi, Sébastien, Deslauriers, Marie, Perron, Martin, Isabel, Nathalie, Beaulieu, Jean, Bousquet, Jean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080810/
https://www.ncbi.nlm.nih.gov/pubmed/31969718
http://dx.doi.org/10.1038/s41437-019-0290-3
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author Lenz, Patrick R. N.
Nadeau, Simon
Azaiez, Aïda
Gérardi, Sébastien
Deslauriers, Marie
Perron, Martin
Isabel, Nathalie
Beaulieu, Jean
Bousquet, Jean
author_facet Lenz, Patrick R. N.
Nadeau, Simon
Azaiez, Aïda
Gérardi, Sébastien
Deslauriers, Marie
Perron, Martin
Isabel, Nathalie
Beaulieu, Jean
Bousquet, Jean
author_sort Lenz, Patrick R. N.
collection PubMed
description 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.
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spelling pubmed-70808102020-03-19 Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce Lenz, Patrick R. N. Nadeau, Simon Azaiez, Aïda Gérardi, Sébastien Deslauriers, Marie Perron, Martin Isabel, Nathalie Beaulieu, Jean Bousquet, Jean Heredity (Edinb) Article 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. Springer International Publishing 2020-01-22 2020-04 /pmc/articles/PMC7080810/ /pubmed/31969718 http://dx.doi.org/10.1038/s41437-019-0290-3 Text en © The Author(s) 2020, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lenz, Patrick R. N.
Nadeau, Simon
Azaiez, Aïda
Gérardi, Sébastien
Deslauriers, Marie
Perron, Martin
Isabel, Nathalie
Beaulieu, Jean
Bousquet, Jean
Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title_full Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title_fullStr Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title_full_unstemmed Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title_short Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
title_sort genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080810/
https://www.ncbi.nlm.nih.gov/pubmed/31969718
http://dx.doi.org/10.1038/s41437-019-0290-3
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