Abstract
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Probabilities of gene origin computed from the genomic kinships matrix can accurately identify key ancestors of modern germplasms
Abstract
Identifying the key ancestors of modern plant breeding populations can provide valuable insights into the history of a breeding program and provide reference genomes for next generation whole genome sequencing. In an animal breeding context, a method was developed that employs probabilities of gene origin, computed from the pedigree-based additive kinship matrix, for identifying key ancestors. Because reliable and complete pedigree information is often not available in plant breeding, we replaced the additive kinship matrix with the genomic kinship matrix. As a proof-of-concept, we applied this approach to simulated data sets with known ancestries. The relative contribution of the ancestral lines to later generations could be determined with high accuracy, with and without selection. Our method was subsequently used for identifying the key ancestors of the modern Dent germplasm of the public maize breeding program of the University of Hohenheim. We found that the modern germplasm can be traced back to six or seven key ancestors, with one or two of them having a disproportionately large contribution. These results largely corroborated conjectures based on early records of the breeding program. We conclude that probabilities of gene origin computed from the genomic kinships matrix can be used for identifying key ancestors in breeding programs and estimating the proportion of genes contributed by them.
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Acknowledgments
This research was funded by the German Federal Ministry of Education and Research within the Agro-Cluster “Synbreed—Synergistic plant and animal breeding” (grant 0315528D). We acknowledge the contributions of the late Prof. W.G. Pollmer and Dr. D. Klein in the development of the maize inbred lines analyzed in this study and grants from the University of Hohenheim for the development of the modern maize germplasm. We are indebted to Dr. Eva Bauer, Technische Universität München, for generating part of the SNP data used in this study under the “Cornfed” Project, supported by the German Federal Ministry of Education and Research (grant number 0315461). This paper is dedicated to one of the pioneers of biometrical methods in plant breeding, Prof. Dr. H. Friedrich Utz, on the occasion of his 75th anniversary.
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Communicated by Natalia de Leon.
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Technow, F., Schrag, T.A., Schipprack, W. et al. Identification of key ancestors of modern germplasm in a breeding program of maize. Theor Appl Genet 127, 2545–2553 (2014). https://doi.org/10.1007/s00122-014-2396-6
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DOI: https://doi.org/10.1007/s00122-014-2396-6