Nirea K G, Meuwissen T H E
Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway.
J Anim Breed Genet. 2017 Apr;134(2):119-128. doi: 10.1111/jbg.12250. Epub 2016 Dec 19.
We simulated a genomic selection pig breeding schemes containing nucleus and production herds to improve feed efficiency of production pigs that were cross-breed. Elite nucleus herds had access to high-quality feed, and production herds were fed low-quality feed. Feed efficiency in the nucleus herds had a heritability of 0.3 and 0.25 in the production herds. It was assumed the genetic relationships between feed efficiency in the nucleus and production were low (r = 0.2), medium (r = 0.5) and high (r = 0.8). In our alternative breeding schemes, different proportion of production animals were recorded for feed efficiency and genotyped with high-density panel of genetic markers. Genomic breeding value of the selection candidates for feed efficiency was estimated based on three different approaches. In one approach, genomic breeding value was estimated including nucleus animals in the reference population. In the second approach, the reference population was containing a mixture of nucleus and production animals. In the third approach, the reference population was only consisting of production herds. Using a mixture reference population, we generated 40-115% more genetic gain in the production environment as compared to only using nucleus reference population that were fed high-quality feed sources when the production animals were offspring of the nucleus animals. When the production animals were grand offspring of the nucleus animals, 43-104% more genetic gain was generated. Similarly, a higher genetic gain generated in the production environment when mixed reference population was used as compared to only using production animals. This was up to 19 and 14% when the production animals were offspring and grand offspring of nucleus animals, respectively. Therefore, in genomic selection pig breeding programmes, feed efficiency traits could be improved by properly designing the reference population.
我们模拟了一个包含核心群和生产群的基因组选择猪育种方案,以提高杂交生产猪的饲料效率。核心群能够获得优质饲料,而生产群则饲喂低质量饲料。核心群中饲料效率的遗传力为0.3,生产群中为0.25。假设核心群和生产群中饲料效率之间的遗传关系为低(r = 0.2)、中(r = 0.5)和高(r = 0.8)。在我们的替代育种方案中,记录了不同比例的生产动物的饲料效率,并使用高密度遗传标记面板进行基因分型。基于三种不同方法估计了饲料效率选择候选个体的基因组育种值。在一种方法中,估计基因组育种值时参考群体包括核心群动物。在第二种方法中,参考群体包含核心群和生产群动物的混合群体。在第三种方法中,参考群体仅由生产群组成。当生产动物是核心群动物的后代时,与仅使用饲喂优质饲料的核心群参考群体相比,使用混合参考群体在生产环境中产生的遗传进展增加了40 - 115%。当生产动物是核心群动物的孙代时,遗传进展增加了43 - 104%。同样,与仅使用生产群动物相比,使用混合参考群体时在生产环境中产生的遗传进展更高。当生产动物是核心群动物的后代和孙代时,分别高达19%和14%。因此,在基因组选择猪育种计划中,通过合理设计参考群体可以提高饲料效率性状。