Department of Animal and Dairy Science, University of Georgia, Athens 30602-2771, USA.
J Anim Sci. 2010 Dec;88(12):3800-8. doi: 10.2527/jas.2009-2413. Epub 2010 Aug 20.
Estimates of genetic parameters for number of stillborns (NSB) in relation to litter size (LS) were obtained with random regression models (RRM). Data were collected from 4 purebred Duroc nucleus farms between 2004 and 2008. Two data sets with 6,575 litters for the first parity (P1) and 6,259 litters for the second to fifth parity (P2-5) with a total of 8,217 and 5,066 animals in the pedigree were analyzed separately. Number of stillborns was studied as a trait on sow level. Fixed effects were contemporary groups (farm-year-season) and fixed cubic regression coefficients on LS with Legendre polynomials. Models for P2-5 included the fixed effect of parity. Random effects were additive genetic effects for both data sets with permanent environmental effects included for P2-5. Random effects modeled with Legendre polynomials (RRM-L), linear splines (RRM-S), and degree 0 B-splines (RRM-BS) with regressions on LS were used. For P1, the order of polynomial, the number of knots, and the number of intervals used for respective models were quadratic, 3, and 3, respectively. For P2-5, the same parameters were linear, 2, and 2, respectively. Heterogeneous residual variances were considered in the models. For P1, estimates of heritability were 12 to 15%, 5 to 6%, and 6 to 7% in LS 5, 9, and 13, respectively. For P2-5, estimates were 15 to 17%, 4 to 5%, and 4 to 6% in LS 6, 9, and 12, respectively. For P1, average estimates of genetic correlations between LS 5 to 9, 5 to 13, and 9 to 13 were 0.53, -0.29, and 0.65, respectively. For P2-5, same estimates averaged for RRM-L and RRM-S were 0.75, -0.21, and 0.50, respectively. For RRM-BS with 2 intervals, the correlation was 0.66 between LS 5 to 7 and 8 to 13. Parameters obtained by 3 RRM revealed the nonlinear relationship between additive genetic effect of NSB and the environmental deviation of LS. The negative correlations between the 2 extreme LS might possibly indicate different genetic bases on incidence of stillbirth.
利用随机回归模型（RRM）获得了与窝产仔数（LS）相关的死产数（NSB）的遗传参数估计值。数据来自 2004 年至 2008 年间的 4 个纯种杜洛克核心场。分别分析了第一胎（P1）的 6575 窝和第二胎至第五胎（P2-5）的 6259 窝的数据，系谱中共有 8217 头和 5066 头动物。死产数作为母猪水平上的一个性状进行研究。固定效应为同期组（农场-年-季节）和 LS 的 Legendre 多项式固定三次回归系数。对于 P2-5，模型中还包括胎次的固定效应。对于两个数据集，随机效应均为加性遗传效应，同时还包括 P2-5 的永久环境效应。使用 LS 的 Legendre 多项式（RRM-L）、线性样条（RRM-S）和零阶 B 样条（RRM-BS）对随机效应进行建模。对于 P1，多项式的阶数、结的数量和各自模型的区间数量分别为二次、3 和 3。对于 P2-5，相同的参数分别为线性、2 和 2。模型中考虑了异质残差方差。对于 P1，LS 5、9 和 13 的 LS 分别为 5%至 6%和 6%至 7%时，遗传率估计值为 12%至 15%、5%至 6%和 6%至 7%。对于 P2-5，LS 分别为 6%、9%和 12%时，遗传率估计值为 15%至 17%、4%至 5%和 4%至 6%。对于 P1，LS 5 到 9、5 到 13 和 9 到 13 之间的平均遗传相关估计值分别为 0.53、-0.29 和 0.65。对于 P2-5，RRM-L 和 RRM-S 的平均估计值分别为 0.75、-0.21 和 0.50。对于具有 2 个区间的 RRM-BS，LS 5 到 7 和 8 到 13 之间的相关性为 0.66。通过 3 个 RRM 获得的参数揭示了 NSB 的加性遗传效应与 LS 的环境偏差之间的非线性关系。两个极端 LS 之间的负相关可能表明死产发生率的遗传基础不同。
