在使用杂交猪基准种群进行基因组预测时,品种组成的影响
Euiseo Hong1, Yoonji Chung2, Phuong Thanh N Dinh3
1Department of Bio-Big Data and Precision Agriculture, Chungnam National University, Daejeon 34134, Korea.
Journal of animal science and technology
|February 20, 2025
概括
多品种基因组预测需要仔细处理种群结构. 将其建模为随机效应或根本不调整,可以获得对交叉品种猪的背脂厚度和尸体重量等特征的最高预测准确度.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 基因组预测 基因组预测
背景情况:
- 传统的基因组预测通常集中在单个品种上,通过避免人口结构调整来简化过程.
- 然而,多品种基因组预测容易受到人口结构的偏差的影响,因此需要适当的建模以获得准确的结果.
- 杂交的参考种群对基因组预测具有独特的挑战,原因是固有的种群结构.
研究的目的:
- 调查人口结构对杂交猪多品种基因组预测准确性的影响.
- 在基因组最佳线性无偏预测 (GBLUP) 模型中比较不同人口结构建模策略的有效性.
- 确定最佳方法,以提高商业杂交种群的基因组选择效率.
主要方法:
- 评估了五种GBLUP模型:没有调整,主要成分分析 (PCA) 作为固定/随机效应,基因组品种组成 (GBC) 作为固定/随机效应.
- 使用的杂交猪数据集包括Duroc × 韩国原住民,Landrace × 韩国原住民和Landrace × 约克郡 × Duroc种群.
- 在不同的人口结构建模场景下,评估了背部脂肪厚度和尸体体重的预测准确性.
主要成果:
- 没有调整人口结构的模型或使用PCA/GBC作为随机效应 (模型1,4,5) 实现了最高的预测准确度 (例如,背部脂肪厚度:0.59,尸体重量:0.50).
- 将PCA或GBC作为固定效应的模型 (模型2,3) 导致预测准确度较低 (例如,背部脂肪厚度:0.40-0.53,尸体重量:0.34-0.38).
- 人口结构建模的选择显著影响了多品种基因组预测中的预测准确性.
结论:
- 对于在杂交种群中的多品种基因组预测,最有效的是要么不调整种群结构,要么将其作为随机效应来建模.
- 对人口结构的准确核算对于强大的多品种基因组预测框架至关重要.
- 通过适当的建模策略优化预测准确度可以显著提高基因组选择效率和商业生产结果.
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