Development of genome-wide selection methods for genetic consolidation and improvement of local breeds with historic migration

• Applicant: Dr. Robin Wellmann
• Subject Area: Animal Breeding, Animal Nutrition, Animal Husbandry
• Term: from 2014 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 258739953

Due to economic superiority of a small number of high-yielding breeds in modern live stock systems, local breeds were frequently given up, which caused the extinction of many of them. The introduction of genomic selection is further accelerating genetic gain in the most common breeds which is likely to reinforce the decline of population size of less common breeds. Additionally, many local breeds have been crossed with high-yielding breeds to improve performance, which threatened their genetic autonomy. Consequently, the gene pool of endangered breeds is becoming replaced with the gene pool of non-endangered breeds. The most sustainable strategy for the conservation of endangered breeds is increasing their competitiveness, e.g. by accelerating genetic gain for economic relevant traits. However, there is a conflict of objectives between accelerating genetic gain, the maintenance of genetic autonomy, and the conservation of genetic diversity. An approach to account for these conflicts is termed optimum contribution (OC) selection. This approach determines the optimum number of offspring per selection candidate. These optimum numbers of offspring are solutions of an optimization problem which is subject to several constraints. The aim of this research project is the development of methods for OC selection that are taking all three objectives simultaneously into account (genetic autonomy, genetic diversity, and genetic gain) and are suitable for both pedigree data and genome-wide marker data. The methods will be developed for conventional breeding schemes as well as for breeding schemes that include a cooperative genomic selection program. Simulated data and real data are used for validation of the methods. The real data consists of genotypic data from the endangered breeds Vorderwald cattle and Hinterwald cattle. It is analyzed jointly with available data from the high-yielding migrant breeds Holstein and Fleckvieh. The implementation of user friendly software for applying the developed OC selection methods in practice forms the end of the project.

• DFG Programme: Research Grants
• Participating Person: Professor Dr. Jörn Bennewitz