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Direct multitrait selection realizes the highest genetic response for ratio traits

机译:直接多刻度选择实现比例性状的最高遗传响应

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摘要

For a number of traits the phenotype considered to be the goal trait is a combination of 2 or more traits, like methane (CH4) emission (CH4/kg of milk). Direct selection on CH4 emission defined as a ratio is problematic, because it is uncertain whether the improvement comes from an improvement in milk yield, a decrease in CH4 emission or both. The goal was to test different strategies on selecting for 2 antagonistic traits-improving milk yield while decreasing methane emissions. The hypothesis was that to maximize genetic gain for a ratio trait, the best approach is to select directly for the component traits rather than using a ratio trait or a trait where 1 trait is corrected for the other as the selection criteria. Stochastic simulation was used to mimic a dairy cattle population. Three scenarios were tested, which differed in selection criteria but all selecting for increased milk yield: 1) selection based on a multitrait approach using the correlation structure between the 2 traits, 2) the ratio of methane to milk and 3) gross methane phenotypically corrected for milk. Four correlation sets were tested in all scenarios, to access robustness of the results. An average genetic gain of 66 kg of milk per yr was obtained in all scenarios, but scenario 1 had the best response for decreased methane emissions, with a genetic gain of 24.8 l/yr, while scenarios 2 and 3 had genetic gains of 27.1 and 27.3 kg/yr. The results found were persistent across correlation sets. These results confirm the hypothesis that to obtain the highest genetic gain a multitrait selection is a better approach than selecting for the ratio directly. The results are exemplified for a methane and milk scenario but can be generalized to other situations where combined traits need to be improved.
机译:对于许多特征,认为是目标性状的表型是2或更多性状的组合,如甲烷(CH 4)发射(CH 4 / kg牛奶)。直接选择作为比例定义的CH4发射是有问题的,因为它不确定改善是否来自牛奶产量的提高,CH4发射减少或两者。目标是测试不同策略,用于选择2种拮抗性状,提高牛奶产量,同时降低甲烷排放。假设是为了最大化比例性状的遗传增益,最好的方法是直接为组分特征选择,而不是使用比率特征或具有1个特征的特征作为选择标准。随机仿真用于模仿奶牛群。测试了三种情况,其在选择标准中不同,但所有选择增加牛奶产量:1)基于使用2个特征,2)甲烷与3)甲烷的甲烷与3)总甲烷的相关结构的多件方法选择对于牛奶。在所有场景中测试了四个相关组,以访问结果的鲁棒性。在所有情景中获得每YR的平均遗传增益为66千克牛奶,但情况1具有降低的甲烷排放的响应,遗传增益为24.8升/年,而场景2和3具有27.1的遗传衰减27.3千克/年。相关结果跨相关组持续存在。这些结果证实了要获得最高遗传增益的假设,而多特征选择是比直接选择比率更好的方法。结果举例说明甲烷和牛奶场景,但可以推广到其他情况下需要改善组合性状的情况。

著录项

  • 来源
    《Journal of Animal Science》 |2017年第5期|共5页
  • 作者单位

    Aarhus Univ Dept Mol Biol &

    Genet Ctr Quantitat Genet &

    Genom Blichers Alle 20 DK-8830 Tjele Denmark;

    Danish Pig Res Ctr SEGES Breeding &

    Genet Axeltorv 3 DK-1609 Copenhagen V Denmark;

    Aarhus Univ Dept Mol Biol &

    Genet Ctr Quantitat Genet &

    Genom Blichers Alle 20 DK-8830 Tjele Denmark;

    Aarhus Univ Dept Mol Biol &

    Genet Ctr Quantitat Genet &

    Genom Blichers Alle 20 DK-8830 Tjele Denmark;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 动物学;
  • 关键词

    dairy cattle; methane; ratio traits; stochastic simulation;

    机译:奶牛;甲烷;比率特征;随机仿真;

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