Natural Resources Institute Finland (Luke), Jokioinen, Finland.
Nordic Cattle Genetic Evaluation (NAV), Aarhus, Denmark.
Genet Sel Evol. 2022 Jun 2;54(1):38. doi: 10.1186/s12711-022-00721-x.
Genomic estimated breeding values (GEBV) by single-step genomic BLUP (ssGBLUP) are affected by the centering of marker information used. The use of a fixed effect called J factor will lead to GEBV that are unaffected by the centering used. We extended the use of a single J factor to a group of J factors.
J factor(s) are usually included in mixed model equations (MME) as regression effects but a transformation similar to that regularly used for genetic groups can be applied to obtain a simpler MME, which is sparser than the original MME and does not need computation of the J factors. When the J factor is based on the same structure as the genetic groups, then MME can be transformed such that coefficients for the genetic groups no longer include information from the genomic relationship matrix. We illustrate the use of J factors in the analysis of a Red dairy cattle data set for fertility.
The GEBV from these analyses confirmed the theoretical derivations that show that the resulting GEBV are allele coding independent when a J factor is used. Transformed MME led to faster computing time than the original regression-based MME.
单步基因组最佳线性无偏预测（ssGBLUP）的基因组估计育种值（GEBV）受到所使用的标记信息中心化的影响。使用称为 J 因子的固定效应将导致不受所使用的中心化影响的 GEBV。我们将单个 J 因子的使用扩展到一组 J 因子。
J 因子通常作为回归效应包含在混合模型方程（MME）中，但可以应用类似于通常用于遗传群体的转换来获得更简单的 MME，该 MME 比原始 MME 更稀疏，并且不需要计算 J 因子。当 J 因子基于与遗传群体相同的结构时，则可以转换 MME，使得遗传群体的系数不再包含基因组关系矩阵的信息。我们在红色奶牛数据集的生育力分析中说明了 J 因子的使用。
这些分析的 GEBV 证实了理论推导，即当使用 J 因子时，所得 GEBV 是等位基因编码独立的。转换后的 MME 比原始基于回归的 MME 计算速度更快。
