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小规模繁育计划中高级最优贡献选择的实施:Vorderwald 牛的前景和挑战。

Implementation of advanced Optimum Contribution Selection in small-scale breeding schemes: prospects and challenges in Vorderwald cattle.

机构信息

University of Hohenheim, Animal Genetics and Breeding (460g), Garbenstr. 17, Stuttgart 70599, Baden-Württemberg, Germany.

State Agency for Spatial Information and Rural Development Baden-Württemberg, Breeding Value Estimation Team, Stuttgarter Str. 161, Kornwestheim 70806, Baden-Württemberg, Germany.

出版信息

Animal. 2020 Mar;14(3):452-463. doi: 10.1017/S1751731119002295. Epub 2019 Oct 10.

DOI:10.1017/S1751731119002295
PMID:31597583
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7026723/
Abstract

Vorderwald cattle are a regional cattle breed from the Black Forest in south western Germany. In recent decades, commercial breeds have been introgressed to upgrade the breed in performance traits. On one hand, native genetic diversity of the breed should be conserved. On the other hand, moderate rates of genetic gain are needed to satisfy breeders to keep the breed. These goals are antagonistic, since the native proportion of the gene pool is negatively correlated to performance traits and the carriers of introgressed alleles are less related to the population. Thus, a standard Optimum Contribution Selection (OCS) approach would lead to reinforced selection on migrant contributions (MC). Our objective was the development of strategies for practical implementation of an OCS approach to manage the MC and native genetic diversity of regional breeds. Additionally, we examined the organisational efforts and the financial impacts on the breeding scheme of Vorderwald cattle. We chose the advanced Optimum Contribution Selection (aOCS) to manage the breed in stochastic simulations based on real pedigree data. In addition to standard OCS approaches, aOCS facilitates the management of the MC and the rate of inbreeding at native alleles. We examined two aOCS strategies. Both strategies maximised genetic gain, while strategy (I) conserved the MC in the breeding population and strategy (II) reduced the MC at a predefined annual rate. These two approaches were combined with one of three flows of replacement of sires (FoR strategies). Additionally, we compared breeding costs to clarify about the financial impact of implementing aOCS in a young sire breeding scheme. According to our results, conserving the MC in the population led to significantly (P < 0.01) higher genetic gain (1.16 ± 0.13 points/year) than reducing the MC (0.88 ± 0.10 points/year). In simulation scenarios that conserved the MC, the final value of MC was 57.6% ± 0.004, while being constraint to 58.2%. However, reducing the MC is only partially feasible based on pedigree data. Additionally, this study proves that the classical rate of inbreeding can be managed by constraining only the rate of inbreeding at native alleles within the aOCS approach. The financial comparison of the different breeding schemes proved the feasibility of implementing aOCS in Vorderwald cattle. Implementing the modelled breeding scheme would reduce costs by 1.1% compared with the actual scheme. Reduced costs were underpinned by additional genetic gain in superior simulation scenarios compared to expected genetic gain in reality (+4.85%).

摘要

前瓦尔登牛是德国西南部黑森林地区的一种地方牛种。近几十年来,商业品种被引入以提高品种的性能特征。一方面,应该保护该品种的本地遗传多样性。另一方面,需要适度的遗传增益来满足饲养者保留该品种的需求。这些目标是相互矛盾的,因为基因库的本地比例与性能特征呈负相关,并且携带导入等位基因的个体与群体的亲缘关系较低。因此,标准最优贡献选择(OCS)方法会导致对移徙贡献(MC)的选择加强。我们的目标是制定策略,以便在实际实施 OCS 方法来管理区域品种的 MC 和本地遗传多样性。此外,我们还研究了组织工作和对前瓦尔登牛育种计划的财务影响。我们选择了先进的最优贡献选择(aOCS)来基于真实系谱数据在随机模拟中管理该品种。除了标准 OCS 方法外,aOCS 还可以方便地管理 MC 和本地等位基因的近交率。我们检查了两种 aOCS 策略。这两种策略都最大化了遗传增益,而策略(I)在育种群体中保留了 MC,策略(II)则以预定的年度速度降低了 MC。这两种方法与三种 sire 替换流(FoR 策略)之一相结合。此外,我们比较了繁殖成本,以明确在年轻 sire 繁殖计划中实施 aOCS 的财务影响。根据我们的研究结果,在种群中保留 MC 可导致显著(P < 0.01)更高的遗传增益(1.16 ± 0.13 点/年),而降低 MC 只能导致 0.88 ± 0.10 点/年的遗传增益。在保留 MC 的模拟场景中,MC 的最终值为 57.6% ± 0.004,而限制在 58.2%。然而,基于系谱数据,降低 MC 只是部分可行的。此外,这项研究证明,在 aOCS 方法中仅通过限制本地等位基因的近交率就可以管理经典的近交率。不同繁殖计划的财务比较证明了在前瓦尔登牛中实施 aOCS 的可行性。与实际计划相比,实施模拟繁殖计划将降低 1.1%的成本。与现实中预期的遗传增益相比,在优越的模拟场景中增加的遗传增益支撑了降低成本(+4.85%)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/987623958f98/S1751731119002295_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/5b212fe8f80d/S1751731119002295_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/78dabf6691d1/S1751731119002295_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/ce64d26d7e72/S1751731119002295_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/987623958f98/S1751731119002295_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/5b212fe8f80d/S1751731119002295_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/78dabf6691d1/S1751731119002295_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/ce64d26d7e72/S1751731119002295_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/863f/7026723/987623958f98/S1751731119002295_fig4.jpg

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