Genomic-inferred cross-selection methods for multi-trait improvement in a recurrent selection breeding program.

Autor: Atanda SA; Agricultural Data Analytics Unit, North Dakota State University, Fargo, ND, 58105-6050, USA. sikiru.atanda@ndsu.edu., Bandillo N; Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108-6050, USA. Nonoy.bandillo@ndsu.edu.
Jazyk: angličtina
Zdroj: Plant methods [Plant Methods] 2024 Sep 02; Vol. 20 (1), pp. 133. Date of Electronic Publication: 2024 Sep 02.
DOI: 10.1186/s13007-024-01258-4
Abstrakt: The major drawback to the implementation of genomic selection in a breeding program lies in long-term decrease in additive genetic variance, which is a trade-off for rapid genetic improvement in short term. Balancing increase in genetic gain with retention of additive genetic variance necessitates careful optimization of this trade-off. In this study, we proposed an integrated index selection approach within the genomic inferred cross-selection (GCS) framework to maximize genetic gain across multiple traits. With this method, we identified optimal crosses that simultaneously maximize progeny performance and maintain genetic variance for multiple traits. Using a stochastic simulated recurrent breeding program over a 40-years period, we evaluated different GCS methods along with other factors, such as the number of parents, crosses, and progeny per cross, that influence genetic gain in a pulse crop breeding program. Across all breeding scenarios, the posterior mean variance consistently enhances genetic gain when compared to other methods, such as the usefulness criterion, optimal haploid value, mean genomic estimated breeding value, and mean index selection value of the superior parents. In addition, we provide a detailed strategy to optimize the number of parents, crosses, and progeny per cross that can potentially maximize short- and long-term genetic gain in a public breeding program.
(© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje