Genomic selection strategies for clonally propagated crops

For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. H...

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Main Authors: Werner, Christian R., Gaynor, Robert Chris, Sargent, Daniel J., Lillo, Alessandra, Gorjanc, Gregor, Hickey, John M.
Format: Journal Article
Language:Inglés
Published: Springer 2023
Subjects:
Online Access:https://hdl.handle.net/10568/132712
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author Werner, Christian R.
Gaynor, Robert Chris
Sargent, Daniel J.
Lillo, Alessandra
Gorjanc, Gregor
Hickey, John M.
author_browse Gaynor, Robert Chris
Gorjanc, Gregor
Hickey, John M.
Lillo, Alessandra
Sargent, Daniel J.
Werner, Christian R.
author_facet Werner, Christian R.
Gaynor, Robert Chris
Sargent, Daniel J.
Lillo, Alessandra
Gorjanc, Gregor
Hickey, John M.
author_sort Werner, Christian R.
collection Repository of Agricultural Research Outputs (CGSpace)
description For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops.
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spelling CGSpace1327122025-10-26T12:52:10Z Genomic selection strategies for clonally propagated crops Werner, Christian R. Gaynor, Robert Chris Sargent, Daniel J. Lillo, Alessandra Gorjanc, Gregor Hickey, John M. marker-assisted selection breeding programmes genetic engineering crops For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops. 2023-04 2023-11-03T15:58:15Z 2023-11-03T15:58:15Z Journal Article https://hdl.handle.net/10568/132712 en Open Access application/pdf Springer Werner, C. R., Gaynor, R. C., Sargent, D. J., Lillo, A., Gorjanc, G., & Hickey, J. M. (2023). Genomic selection strategies for clonally propagated crops. Theoretical and Applied Genetics, 136(4), 74.
spellingShingle marker-assisted selection
breeding programmes
genetic engineering
crops
Werner, Christian R.
Gaynor, Robert Chris
Sargent, Daniel J.
Lillo, Alessandra
Gorjanc, Gregor
Hickey, John M.
Genomic selection strategies for clonally propagated crops
title Genomic selection strategies for clonally propagated crops
title_full Genomic selection strategies for clonally propagated crops
title_fullStr Genomic selection strategies for clonally propagated crops
title_full_unstemmed Genomic selection strategies for clonally propagated crops
title_short Genomic selection strategies for clonally propagated crops
title_sort genomic selection strategies for clonally propagated crops
topic marker-assisted selection
breeding programmes
genetic engineering
crops
url https://hdl.handle.net/10568/132712
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