1Saxon State Stud Administration,Schlossallee 1,01468 Moritzburg,Germany.
2Institute of Agricultural and Nutritional Sciences,Martin-Luther-University Halle-Wittenberg,Theodor-Lieser-Str. 11,D-06120 Halle/Saale,Germany.
Animal. 2016 Jun;10(6):1050-60. doi: 10.1017/S1751731116000410. Epub 2016 Mar 9.
In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped. The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies. The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.
在现代奶牛养殖中，基因组育种计划有可能提高效率和遗传增益。与此同时，基因型和表型的要求和可用性带来了挑战。对于数量较少的品种，以及难以测量的性状，建立一个足够大的基因组预测参考群体存在问题。本研究的第一部分是对克服缺乏参考数据的策略的文献综述。一种解决方案是使用来自不同品种、不同国家或不同研究群体的组合参考群体。结果表明，合并群体之间的关系水平是最重要的因素。编译密切相关的群体有助于准确估计标记效应，从而导致基因组预测的准确性很高。因此，来自不同国家的同一品种的混合参考群体比组合不同品种更有前途，特别是如果这些品种的亲缘关系较远。利用雌性参考信息有可能扩大参考群体规模。对于小种群和困难性状，包括雌性是明智的，也许可以结合雌性的基因分型和对未基因分型的雌性进行推断。未基因分型个体的有效推断需要一组基因分型相关动物和精心考虑的选择策略，选择哪些动物进行基因分型和表型分析。小种群必须找到从成本高昂的基因组育种计划中获得额外优势的方法。可能的解决方案可能是利用基因组信息进行近亲繁殖控制、亲子关系验证、群体内选择、调整交配计划或保护策略。本文的第二部分讨论了在新的、困难和难以测量的性状的背景下，高质量表型的问题。建议使用合同牛群进行表型分析，因为与奶牛养殖中使用的标准性状相比，合同牛群可以在特定时间点测量附加性状。这甚至可以用于健康性状的记录，从而为健康性状形成完整的同期组。未来要记录和用于基因组育种计划的性状，至少部分将是基于广泛表型的传统选择不可能的性状。要实现足以进行基因组选择的数量的表型分析，将依赖于不同学科的科学家之间的合作，可能需要采用多学科方法。
