Genomic selection strategies for clonally propagated crops

Area of Science:

• Plant breeding
• Quantitative genetics
• Genomic selection

Background:

• Clonal propagation is vital for many crops.
• Genomic selection (GS) offers potential for accelerating breeding.
• Optimizing GS strategies in clonal breeding programs requires careful consideration of parent selection.

Purpose of the Study:

• To compare different genomic selection (GS) strategies for clonally propagated crops.
• To evaluate the effectiveness of parent selection based on genomic estimated breeding values (GEBVs) versus genomic predicted cross-performance (GPCP).
• To assess the impact of different breeding program structures on genetic gain.

Main Methods:

• Stochastic simulation was employed to model breeding programs.
• Six combinations of three breeding program designs and two parent selection methods were evaluated.
• Strawberry was used as a model crop with diploid-like meiotic behavior.

Main Results:

• Parent selection based on GPCP consistently yielded higher genetic gain than selection based on GEBVs.
• GPCP-based selection effectively reduced inbreeding, particularly when dominance effects were significant.
• Two-part breeding programs incorporating GPCP demonstrated superior performance, especially with multiple crossing cycles per year.

Conclusions:

• Genomic predicted cross-performance (GPCP) is the optimal method for parent selection in GS for clonally propagated crops.
• Two-part breeding programs combined with GPCP offer a powerful approach for rapid genetic improvement.
• These findings have significant implications for enhancing the efficiency of breeding programs for clonally propagated species.