Genetics and genomics to improve fertility in high producing dairy cows

被引:87
作者
Veerkamp, R. F. [1 ]
Beerda, B. [1 ]
机构
[1] Wageningen UR, ASG, Anim Breeding & Genom Ctr, NL-8200 AB Lelystad, Netherlands
关键词
genetic selection; fertility; high milk yield; genomic selection; dairy cows;
D O I
10.1016/j.theriogenology.2007.04.034
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Improving dairy cow fertility by means of genetic selection is likely to become increasingly important, since it is now well established that declining fertility cannot only be arrested by improved management. Profit margins per kg milk produced are decreasing, therefore farmers need to reduce cost and increase herd size. This restricts the labor input per cow and the disposable cost of getting a cow pregnant, whilst at the same time hormone treatments have become less acceptable. This makes it unlikely that additional management interventions will maintain fertility at acceptable levels in the near future. Genetic improvement seems the obvious solution. Effective selection tools are available in most Western countries using traditional breeding value estimation procedures. Also, in addition to gene assisted selection using individual genes or QTL, high throughput Single Nucleotide Polymorphism (SNP) technology allows genetic improvement of fertility based on information from the whole genome (tens of thousands SNP per animal), i.e. genomic selection. Simulation studies have shown that genomic selection improves the accuracy of selecting juvenile animals compared with traditional breeding methods and compared with selection using information from a few genes or QTL only. Research in the areas genomics and proteomics promise to make genetic selection even more effective. The genomic and proteomics technologies combined with the bioinformatics tools that support the interpretation of gene functioning and protein expression facilitate an exciting starting point for the development of new management strategies and tools for the improvement of reproductive performance. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:S266 / S273
页数:8
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