Unitat de Cunicultura, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.
J Anim Sci. 2011 May;89(5):1294-303. doi: 10.2527/jas.2010-3242.
This work aimed to study the relationship between pH of the semen and fertility (Fert, defined as the success or failure of conception), which is of special interest because pH of the semen can be considered a global marker of the expression of some seminal quality traits. Different methods used to model the relationship between Fert and pH are presented here: 1) ignoring genetic and environmental correlations and including pH either as a covariate or as a cross-classified effect on fertility, 2) a bivariate mixed model, and 3) recursive bivariate mixed models. A total of 653 pH records and 6,365 Fert records after AI were used. Crossbreed does from 2 maternal lines were artificially inseminated with buck semen from a paternal line in a commercial environment. A negative, and almost linear, effect of pH on Fert was detected. The posterior median of pH and Fert heritabilities, and the highest posterior density interval at 95% (in parentheses) were approximately 0.18 (0.05, 0.29) and approximately 0.10 (0.02, 0.20) across all the models, respectively. Genetic correlations between traits were negative, but the highest posterior density interval at 95% included zero [i.e., -0.31 (-0.91, 0.33) in the bivariate mixed model and -0.17 (-0.99, 0.48) and -0.44 (-0.99, 0.10) in the recursive bivariate mixed models including pH as a covariate or as a cross-classified effect, respectively]. All models predicted Fert data reasonably well (i.e., 76 and 62% correct predictions for success and failure, respectively). No differences in the prediction of the EBV for male fertility were encountered between models, showing a good concordance in the animals ranked by their EBV (the correlation between EBV in all models was close to 1). Thus, no differences in results were obtained considering, or not considering, genetic and environmental correlations between pH and Fert and assuming, or not assuming, recursiveness between each trait. This is because the magnitude of the effect of pH on Fert was not large enough; therefore, the same results were obtained even though the models were of different complexity.
本研究旨在探讨精液 pH 值与生育力（定义为受孕的成功或失败）之间的关系，这一点特别重要，因为精液 pH 值可以被视为一些精液质量特征表达的综合标志物。本文介绍了用于建模生育力与 pH 值之间关系的三种不同方法：1）忽略遗传和环境相关性，将 pH 值作为协变量或交叉分类效应对生育力的影响纳入模型；2）双变量混合模型；3）递归双变量混合模型。总共使用了 653 个 pH 值记录和 6365 个人工授精后的生育力记录。在商业环境中，来自 2 个母系的杂交品种使用来自父系的公鹿精液进行人工授精。检测到 pH 值对生育力有负向的、近乎线性的影响。三种模型中 pH 值和生育力遗传力的后验中位数（括号内为最高后验密度区间）分别约为 0.18（0.05，0.29）和 0.10（0.02，0.20）。性状间的遗传相关性为负相关，但 95%的最高后验密度区间包含零[即在双变量混合模型中为-0.31（-0.91，0.33），在包含 pH 值作为协变量或交叉分类效应的递归双变量混合模型中分别为-0.17（-0.99，0.48）和-0.44（-0.99，0.10）]。所有模型都能较好地预测生育力数据（即成功和失败的正确预测率分别为 76%和 62%）。在不同模型之间，雄性生育力 EBV 的预测没有差异，表明根据 EBV 对动物进行排序时具有很好的一致性（所有模型的 EBV 之间的相关性接近 1）。因此，考虑或不考虑 pH 值和生育力之间的遗传和环境相关性，以及假设或不假设每个性状之间的递归性，都没有得到不同的结果。这是因为 pH 值对生育力的影响幅度不够大；因此，即使模型的复杂性不同，也会得到相同的结果。
