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

由于少数高产品种在现代活畜体系中的经济优势，地方品种经常被放弃，导致其中许多品种灭绝。基因组选择的引入进一步加速了最常见品种的遗传增益，这可能会加剧不太常见品种的种群规模的下降。此外，许多地方品种与高产品种杂交以提高生产性能，这威胁到了它们的遗传自主性。因此，濒危物种的基因库正在被非濒危物种的基因库所取代。保护濒危物种最可持续的战略是提高它们的竞争力，例如通过加快经济相关性状的遗传收益。然而，在加速遗传获得、保持遗传自主性和保护遗传多样性之间存在目标冲突。考虑这些冲突的一种方法被称为最佳贡献(OC)选择。这种方法确定了每个选择候选者的最佳后代数量。这些最优子代数量是受多个约束的优化问题的解。本研究项目的目的是开发同时考虑这三个目标(遗传自主性、遗传多样性和遗传增益)的OC选择方法，并且既适用于家系数据，也适用于全基因组标记数据。这些方法将被开发用于常规育种方案以及包括合作基因组选择计划的育种方案。用模拟数据和实际数据对方法进行了验证。真正的数据由濒临灭绝的沃德瓦尔德牛和欣特瓦尔德牛的基因数据组成。它与高产迁徙品种荷斯坦和弗莱克维的现有数据一起进行了分析。实施用户友好的软件，以便在实践中应用所开发的有机化合物选择方法，是项目的结束。

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.