Department of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.
Biomolecules. 2023 Oct 3;13(10):1478. doi: 10.3390/biom13101478.
The accuracy of predicting seven human phenotypes of 3657-7564 individuals using global epistasis effects was evaluated and compared to the accuracy of haplotype genomic prediction using 380,705 SNPs and 10-fold cross-validation studies. The seven human phenotypes were the normality transformed high density lipoproteins (HDL), low density lipoproteins (LDL), total cholesterol (TC), triglycerides (TG), weight (WT), and the original phenotypic observations of height (HTo) and body mass index (BMIo). Fourth-order epistasis effects virtually had no contribution to the phenotypic variances, and third-order epistasis effects did not affect the prediction accuracy. Without haplotype effects in the prediction model, pairwise epistasis effects improved the prediction accuracy over the SNP models for six traits, with accuracy increases of 2.41%, 3.85%, 0.70%, 0.97%, 0.62% and 0.93% for HDL, LDL, TC, HTo, WT and BMIo respectively. However, none of the epistasis models had higher prediction accuracy than the haplotype models we previously reported. The epistasis model for TG decreased the prediction accuracy by 2.35% relative to the accuracy of the SNP model. The integrated models with epistasis and haplotype effects had slightly higher prediction accuracy than the haplotype models for two traits, HDL and BMIo. These two traits were the only traits where additive × dominance effects increased the prediction accuracy. These results indicated that haplotype effects containing local high-order epistasis effects had a tendency to be more important than global pairwise epistasis effects for the seven human phenotypes, and that the genetic mechanism of HDL and BMIo was more complex than that of the other traits.
使用全局上位效应预测 3657-7564 个人的 7 个人类表型的准确性，并与使用 380705 个 SNP 和 10 倍交叉验证研究的单倍型基因组预测的准确性进行比较。这七个人类表型是经过正态化处理的高密度脂蛋白（HDL）、低密度脂蛋白（LDL）、总胆固醇（TC）、甘油三酯（TG）、体重（WT），以及原始表型观察值身高（HTo）和体重指数（BMIo）。四阶上位效应实际上对表型方差没有贡献，三阶上位效应也不影响预测准确性。在预测模型中没有单倍型效应的情况下，成对上位效应提高了六个特征的预测准确性，相对于 SNP 模型，HDL、LDL、TC、HTo、WT 和 BMIo 的准确性分别提高了 2.41%、3.85%、0.70%、0.97%、0.62%和 0.93%。然而，没有一个上位效应模型的预测准确性高于我们之前报道的单倍型模型。TG 的上位效应模型相对于 SNP 模型的准确性降低了 2.35%。与单倍型模型相比，包含上位效应和单倍型效应的综合模型在两个特征（HDL 和 BMIo）上的预测准确性略高。这两个特征是唯一的，加性×显性效应增加了预测准确性。这些结果表明，对于七个人类表型，包含局部高阶上位效应的单倍型效应比全局成对上位效应更重要，而 HDL 和 BMIo 的遗传机制比其他特征更复杂。
