Abstract
Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenoty** at unreplicated field trials in 3–4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.
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Acknowledgments
This research was conducted within the Biometric and Bioinformatic Tools for Genomics based Plant Breeding project supported by the German Federal Ministry of Education and Research (BMBF) within the framework of GABI–FUTURE initiative. We greatly appreciate the helpful comments and suggestions of two anonymous reviewers.
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Communicated by A. Charcosset.
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Zhao, Y., Gowda, M., Liu, W. et al. Accuracy of genomic selection in European maize elite breeding populations. Theor Appl Genet 124, 769–776 (2012). https://doi.org/10.1007/s00122-011-1745-y
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DOI: https://doi.org/10.1007/s00122-011-1745-y