Probabilities of gene origin computed from the genomic kinships matrix can accurately identify key ancestors of modern germplasms 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.