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特邀综述:奶牛的基因组选择:进展与挑战

Invited review: Genomic selection in dairy cattle: progress and challenges.

作者信息

Hayes B J, Bowman P J, Chamberlain A J, Goddard M E

机构信息

Department of Primary Industries Victoria,Biosciences Research Division, Bundoora, Australia.

出版信息

J Dairy Sci. 2009 Feb;92(2):433-43. doi: 10.3168/jds.2008-1646.

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.

摘要

一种名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)做出的选择决策。GEBV是通过计算整个基因组中密集遗传标记或这些标记的单倍型的效应总和得出的,从而有可能捕获所有影响某一性状变异的数量性状位点(QTL)。从单倍型或单个单核苷酸多态性标记推断出的QTL效应,首先在一个具有表型信息的大型参考群体中进行估计。在后续世代中,计算GEBV只需要标记信息。通过这种方式预测的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评估。这些实验使用了650至4500头经过后裔测定的荷斯坦 - 弗里生公牛作为参考群体,对大约50000个全基因组标记进行了基因分型。参考群体中没有后裔测试结果的年轻公牛的GEBV可靠性在20%至67%之间。所达到的可靠性取决于所评估性状的遗传力、参考群体中的公牛数量、用于估计参考群体中单核苷酸多态性效应的统计方法以及用于计算可靠性的方法。在美国、新西兰和澳大利亚这三个国家的一个共同发现是,一种简单的估计标记效应的BLUP方法所得到的GEBV可靠性几乎与更复杂的方法一样高。BLUP方法很有吸引力,因为所需的唯一先验信息是性状的加性遗传方差。所有国家在其GEBV计算中都纳入了多基因效应(亲本平均育种值)。建议纳入这一效应,以捕获与标记无关的任何遗传方差,并对可能未被标记捕获的低频QTL施加一定的选择压力。所实现的GEBV可靠性显著高于亲本平均育种值的可靠性,而亲本平均育种值是目前选择进入后裔测试组的公牛犊的标准。可靠性的提高足够大,以至于至少有两家奶牛育种公司已经在仅基于GEBV销售两岁的公牛组用于商业用途。这种策略应该至少使奶牛行业的遗传进展速度提高一倍。基因组选择及其实施仍然存在许多挑战,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进展。

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