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Genetics and genomics to improve fertility in high producing dairy cows

机译:遗传和基因组学可以提高高产奶牛的生育能力

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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.
机译:通过基因选择来提高奶牛的生育能力可能变得越来越重要,因为现在已经公认,生育率下降不仅可以通过改善管理来制止。每公斤牛奶生产的利润率正在下降,因此,农民需要降低成本并增加畜群规模。这限制了每头母牛的劳动投入和使母牛怀孕的可支配成本,而与此同时激素治疗变得越来越不可接受。这使得额外的管理干预措施不太可能在不久的将来将生育率维持在可接受的水平。遗传改良似乎是显而易见的解决方案。在大多数西方国家,都可以使用传统的育种价值估算程序获得有效的选择工具。此外,除了使用单个基因或QTL进行基因辅助选择外,高通量单核苷酸多态性(SNP)技术还可以基于来自整个基因组的信息(每只动物成千上万个SNP)进行遗传改良生育力,即进行基因组选择。仿真研究表明,与传统的育种方法相比,与仅使用少数基因或QTL信息进行的选择相比,基因组选择提高了选择幼年动物的准确性。基因组学和蛋白质组学领域的研究有望使基因选择更加有效。基因组学和蛋白质组学技术与支持基因功能和蛋白质表达解释的生物信息学工具相结合,为开发新的管理策略和改善生殖性能的工具提供了令人兴奋的起点。

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