忽视基因选择模型对离散值特征的优势遗传效应的后果
1Department of Animal Science, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran. f.ghafouri@basu.ac.ir.
Scientific reports
|August 13, 2025
概括
在基因组评估模型中忽视主导效应会显著降低准确性,并增加育种价值的偏差和错误. 占主导地位的计算对于在离散值特征中的精确基因组选择至关重要.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 基因组选择 基因组选择
背景情况:
- 基因组估计育种值 (GEBVs) 对动物育种至关重要.
- 离散的值特征在遗传评估中提出了独特的挑战.
- 占主导地位效应对GEBV准确性的影响尚未完全理解.
研究的目的:
- 在基因组评估模型中省略主导效应的后果.
- 为了比较各种基因组选择模型对离散值特征的预测性能.
- 评估对GEBVs准确度,平均平方误差,偏差和分散的影响.
主要方法:
- 模拟了一个带有SNP和定量特征位点 (QTL) 的基因组,具有添加和主导效应.
- 具有主导效应的QTL的比例 (0-100%) 和QTL效应分布有所不同.
- 使用GBLUP,贝叶斯方法,回归和机器学习模型估计的GEBV.
- 使用预测准确度,平均平方误差,偏差和分散度分析了GEBVs.
主要成果:
- 忽视主导效应将GEBV准确度降低了14%至31%.
- 平均平方误差增加了19-47%,偏差增加了20-42%,分散增加了50%.
- 对于离散值特征,GBLUP,BayesB和rrBLUPm6的预测性能比机器学习方法更好.
结论:
- 如果不考虑主导效应,就会导致不准确,偏见和分散的GEBV.
- 对离散值特征进行准确的基因组评估需要结合主导效应.
- 当优势被忽视时,基因组选择的效率就会受到损害.
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