Dekkers J C M
Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames 50011-3150, USA.
J Anim Sci. 2007 Sep;85(9):2104-14. doi: 10.2527/jas.2006-683. Epub 2007 May 15.
Several studies have shown that selection of purebreds for increased performance of their crossbred descendants under field conditions is hampered by low genetic correlations between purebred and commercial crossbred (CC) performance. Although this can be addressed by including phenotypic data from CC relatives for selection of purebreds through combined crossbred and purebred selection (CCPS), this also increases rates of inbreeding and requires comprehensive systems for collection of phenotypic data and pedigrees at the CC level. This study shows that both these limitations can be overcome with marker-assisted selection (MAS) by using estimates of the effects of markers on CC performance. To evaluate the potential benefits of CC-MAS, a model to incorporate marker information in selection strategies was developed based on selection index theory, which allows prediction of responses and rates of inbreeding by using standard deterministic selection theory. Assuming a genetic correlation between purebred and CC performance of 0.7 for a breeding program representing a terminal sire line in pigs, CC-MAS was shown to substantially increase rates of response and reduce rates of inbreeding compared with purebred selection and CCPS, with 60 CC half sibs available for each purebred selection candidate. When the accuracy of marker-based EBV was 0.6, CC-MAS resulted in 34 and 10% greater responses in CC performance than purebred selection and CCPS. Corresponding rates of inbreeding were 1.4% per generation for CC-MAS, compared with 2.1% for purebred selection and 3.0% for CCPS. For marker-based EBV with an accuracy of 0.9, CC-MAS resulted in 75 and 43% greater responses than purebred selection and CCPS, and further reduced rates of inbreeding to 1.0% per generation. Selection on marker-based EBV derived from purebred phenotypes resulted in substantially less response in CC performance than in CC-MAS. In conclusion, effective use of MAS requires estimates of the effect on CC performance, and MAS based on such estimates enables more effective selection for CC performance without the need for extensive pedigree recording and while reducing rates of inbreeding.
多项研究表明,在田间条件下,为提高其杂交后代的性能而选择纯种时,纯种与商业杂交(CC)性能之间的低遗传相关性会阻碍这一过程。虽然可以通过纳入CC亲属的表型数据,通过杂交和纯种联合选择(CCPS)来选择纯种,但这也会增加近亲繁殖率,并且需要在CC层面建立全面的表型数据和系谱收集系统。本研究表明,通过使用标记对CC性能的效应估计,标记辅助选择(MAS)可以克服这两个局限性。为了评估CC-MAS的潜在益处,基于选择指数理论开发了一个在选择策略中纳入标记信息的模型,该模型允许使用标准确定性选择理论预测反应和近亲繁殖率。假设在一个代表猪终端父系品系的育种计划中,纯种与CC性能之间的遗传相关性为0.7,与纯种选择和CCPS相比,CC-MAS显示出能大幅提高反应率并降低近亲繁殖率,每个纯种选择候选对象有60个CC半同胞可用。当基于标记的估计育种值(EBV)的准确性为0.6时,CC-MAS导致CC性能的反应比纯种选择和CCPS分别高出34%和10%。相应的近亲繁殖率为CC-MAS每代1.4%,纯种选择为2.1%,CCPS为3.0%。对于准确性为0.9的基于标记的EBV,CC-MAS导致的反应比纯种选择和CCPS分别高出75%和43%,并进一步将近亲繁殖率降低至每代1.0%。基于纯种表型的标记EBV选择导致CC性能的反应远低于CC-MAS。总之,有效使用MAS需要对CC性能的效应进行估计,基于此类估计的MAS能够在无需广泛系谱记录的情况下,更有效地选择CC性能,同时降低近亲繁殖率。