Institute of Crop Science, National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8518, Japan.
Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Maebashi, 371-0121, Japan.
Genet Sel Evol. 2019 May 2;51(1):19. doi: 10.1186/s12711-019-0461-y.
Growth curves have been widely used in genetic analyses to gain insights into the growth characteristics of both animals and plants. However, several questions remain unanswered, including how the initial phenotypes affect growth and what is the duration of any such impact. For beef cattle production in Japan, calves are procured from farms that specialize in reproduction and then moved to other farms where they are fattened to achieve their market/purchase value. However, the causal effect of growth, while calves are on the reproductive farms, on their growth during fattening remains unclear. To investigate this, we developed a model that combines a structural equation with a growth curve model. The causal effect was modeled with B-splines, which allows inference of the effect as a curve. We fitted the proposed structural growth curve model to repeated measures of body weight from a Japanese beef cattle population (n = 3831) to estimate the curve of the causal effect of the calves' initial weight on their trajectory of growth when they are on fattening farms.
Maternal and reproduction farm effects explained 26% of the phenotypic variance of initial weight at fattening farms. The structural growth curve model was fitted to remove the effects of these factors in growth curve analysis at fattening farms. The estimated curve of causal effects remained at approximately 0.8 for 200 d after the calves entered the fattening farms, which means that 64% of the phenotypic variance was explained by the initial weight. Then, the effect decreased linearly and disappeared approximately 620 d after entering the fattening farms, which corresponded to an average age of 871.5 d.
The proposed model is expected to provide more accurate estimates of genetic values for growth patterns because the confounding causal factors such as maternal and reproduction farm effects are removed. Moreover, examination of the inferred curve of the causal effect enabled us to estimate the effect of a calf's initial weight at arbitrary times during growth, which could provide suitable information for decision-making when shifting the time of slaughter, building models for genetic evaluation, and selecting calves for market.
生长曲线已广泛应用于遗传分析,以深入了解动植物的生长特征。然而,仍有几个问题尚未得到解答,包括初始表型如何影响生长以及这种影响持续的时间。在日本的肉牛生产中,小牛从专门从事繁殖的农场采购,然后转移到其他农场育肥,以达到其市场/购买价值。然而,在育肥农场期间,小牛的生长与在繁殖农场时的生长之间的因果关系仍不清楚。为了研究这一点,我们开发了一种将结构方程与生长曲线模型相结合的模型。使用 B 样条对因果效应进行建模,这允许对作为曲线的效应进行推断。我们将所提出的结构生长曲线模型拟合到日本肉牛群体的体重重复测量数据(n=3831)中,以估计小牛初始体重对其在育肥农场的生长轨迹的因果效应曲线。
母体和繁殖农场效应解释了育肥农场初始体重表型变异的 26%。结构生长曲线模型用于在育肥农场的生长曲线分析中消除这些因素的影响。在小牛进入育肥农场后的大约 200 天,估计的因果效应曲线保持在 0.8 左右,这意味着初始体重解释了 64%的表型变异。然后,该效应呈线性下降,并在大约 620 天进入育肥农场后消失,这对应于平均年龄为 871.5 天。
该模型有望提供更准确的生长模式遗传值估计,因为消除了母体和繁殖农场等混杂的因果因素。此外,推断因果效应的曲线使我们能够估计小牛在生长过程中任意时间的初始体重的影响,这可为改变屠宰时间、构建遗传评估模型和选择用于市场的小牛提供合适的信息。