Invited review: Genomic selection in dairy cattle: Progress and challenges

IF 4.4 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Journal of Dairy Science Pub Date : 2009-02-01 DOI:10.3168/jds.2008-1646
B.J. Hayes , P.J. Bowman , A.J. Chamberlain , M.E. Goddard
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引用次数: 1531

Abstract

A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.

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特邀评论:奶牛基因组选择:进展与挑战
一项被称为基因组选择的新技术正在彻底改变奶牛育种。基因组选择是指基于基因组育种值(GEBV)的选择决策。GEBV被计算为密集遗传标记或这些标记的单倍型在整个基因组中的效应总和,从而潜在地捕获导致性状变异的所有数量性状位点(QTL)。从单倍型或单个单核苷酸多态性标记推断的QTL效应首先在具有表型信息的大型参考群体中进行估计。在后续代中,计算GEBV只需要标记信息。用这种方法预测GEBV的可靠性已经在美国、新西兰、澳大利亚和荷兰的实验中得到了评估。这些实验使用了650至4500头经过后代测试的荷斯泰因-弗里西亚公牛的参考种群,对大约5万个全基因组标记进行了基因分型。参考人群中无子代检测结果的幼牛GEBV的信度在20% ~ 67%之间。所获得的信度取决于所评价性状的遗传力、参考群体中的公牛数、估计参考群体中单核苷酸多态性效应的统计方法以及计算信度的方法。3个国家(美国、新西兰和澳大利亚)的一个共同发现是,用于估计标记效应的直接BLUP方法使GEBV的可靠性几乎与更复杂的方法一样高。BLUP方法很有吸引力,因为它只需要性状的加性遗传变异的先验信息。所有国家在计算GEBV时都考虑了多基因效应(亲本平均育种值)。建议采用这种方法捕获与标记无关的遗传变异,并对标记无法捕获的低频QTL施加一定的选择压力。所获得的GEBV的信度显著大于亲本平均育种值的信度,而亲本平均育种值是目前选择公牛犊牛进入后代测试团队的标准。可靠性的提高是足够高的,至少有2家奶牛养殖公司已经开始销售基于2岁GEBV的公牛队用于商业用途。这一策略至少可以使乳制品行业的遗传增益率提高一倍。基因组选择及其实施仍然面临许多挑战,包括提高GEBV的准确性,将基因组信息整合到国家和国际遗传评估中,以及管理长期遗传收益。
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来源期刊
Journal of Dairy Science
Journal of Dairy Science 农林科学-奶制品与动物科学
CiteScore
7.90
自引率
17.10%
发文量
784
审稿时长
4.2 months
期刊介绍: The official journal of the American Dairy Science Association®, Journal of Dairy Science® (JDS) is the leading peer-reviewed general dairy research journal in the world. JDS readers represent education, industry, and government agencies in more than 70 countries with interests in biochemistry, breeding, economics, engineering, environment, food science, genetics, microbiology, nutrition, pathology, physiology, processing, public health, quality assurance, and sanitation.
期刊最新文献
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