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优化纯种选择,以提高杂交品种的表现.

Somayeh Barani1, Sayed Reza Miraie Ashtiani1, Ardeshir Nejati Javaremi1

  • 1Department of Animal Science, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

Frontiers in genetics
|October 9, 2024
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概括
此摘要是机器生成的。

使用纯种数据预测杂交的性能 (CP) 是至关重要的. 杂交和纯种种群之间的遗传相关性显著影响预测的准确性,最佳模型取决于这个值和数据整合策略.

关键词:
这就是SSGblup的原因.杂种的表现 杂种的表现杂种群和纯种群之间的遗传相关性.超级创始人 超级创始人 ssGBLUPUP 是一个不知名母组未知母组

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科学领域:

  • 动物育种和遗传学动物育种和遗传学
  • 定量遗传学 是一种定量遗传学.
  • 畜牧业生产 畜牧业生产

背景情况:

  • 杂交通过异构和品种互补性来提高牲畜生产.
  • 预测杂交表现 (CP) 往往依赖于纯种数据,因为杂交记录的稀缺性.
  • 准确的CP预测需要考虑非添加性遗传效应和环境因素,这些因素受到种群之间的遗传相关性 ( ) 的影响.

研究的目的:

  • 调查整合纯种和杂交数据的战略,以实现最佳的CP预测.
  • 在不同基因相关性水平下评估单步基因组最佳线性无偏预测 (ssGBLUP) 和带有元发现者 (ssGBLUP-MF) 的ssGBLUP模型.
  • 确定最有效的模型,在不同的场景中最大限度地提高CP.

主要方法:

  • 使用了一种双向杂交模拟.
  • 场景探索了来自纯种和杂交种群的基因型个体.
  • ssGBLUP和ssGBLUP-MF模型与BLUP与未知母组 (BLUP-UPG) 相比较.

主要成果:

  • 在所有场景中,预测准确性随着值的增加而增加.
  • 在将母品种和杂交品种的基因型结合起来时,ssGBLUP和ssGBLUP-MF的准确性相似,最高值为<0.5.5.
  • 在 = 0.8 时,ssGBLUP 仅使用 sire 品种基因型实现了最高的准确性 (73.2%).
  • BLUP-UPG 始终显示的精度低于 ssGBLUP 和 ssGBLUP-MF.
  • 结合杂交和纯种基因型,在较低的基因水平上改善了预测,而在较高的基因水平上,父亲基因型优越.

结论:

  • 基因相关性 ( ) 是从纯种数据预测CP的关键因素.
  • 对CP的最佳预测模型取决于影响的因素.
  • 需要进一步的研究来开发能够优化纯种选以提高CP的模型.