Steyn Yvette, Lawlor Thomas J, Lourenco Daniela, Misztal Ignacy
Department of Animal and Dairy Science, University of Georgia, Athens 30602.
Holstein Association USA Inc., Brattleboro, VT 05302.
JDS Commun. 2023 Apr 20;4(4):260-264. doi: 10.3168/jdsc.2022-0299. eCollection 2023 Jul.
The dairy industry is known for its extensive use of artificial insemination, which has resulted in a population where most animals can be traced back to only a few sires. Due to their relatedness to the population, old influential sires could still contribute to the accuracy of genomic predictions. The objective of the study was to identify the impact of historically influential sires on the recent population. This was tested by constructing a genomic relationship matrix using recursion with different sets of sires. Differences in prediction accuracies with different sets are indicative of how important each set is. Recursion coefficients linking young animals to those sets reveal the relative importance of specific sires to the prediction accuracy of recent animals. The data included ∼10 million scores for stature and fore udder attachment (FUA) measured from 1983. Genotypes of 569,404 animals were available. Sire sets included the 100 most popular sires born within different time periods. Computations were with single-step genomic BLUP. In general, the younger sires had higher prediction accuracies than the oldest sires, even though they generally have fewer progeny. The accuracy of evaluation for stature was increased from 0.54 with the most popular sires born before 1981 to 0.69 with sires born from 2001 to 2010, while the accuracy for FUA increased from 0.47 to 0.61. The accuracy achieved using the overall 100 most used sires was 0.66 for stature and 0.58 for FUA. All 100 sires from each period were combined in a subset to determine the importance of each sire relative to all 400 animals in the combined subset. The highest relative impact of a sire that was born within the different time sets was 1.97 for Valiant (before 1981), 1.94 for Blackstar (1981 to 1990), 4.38 for Shottle (1991 to 2000), and 3.09 for Planet (2001 to 2010). The 3 sires among the 400 with the greatest impact were Shottle, Goldwyn (3.73), and Planet. The relative impact of a sire was not strongly related to the number of progeny. For instance, the relative impact of Durham with 34K progeny was 2.29, whereas the impact of O Man with 15K progeny was 3.13. The impact of a sire is also influenced by whether it was used as a sire of sires. Results show that younger sires are more relevant to the accuracy of breeding value prediction in the recent population.
乳制品行业以广泛使用人工授精而闻名，这导致了一个群体中大多数动物都可以追溯到少数几个父系。由于它们与该群体的亲缘关系，过去有影响力的父系仍然可以提高基因组预测的准确性。本研究的目的是确定历史上有影响力的父系对当前群体的影响。通过使用不同父系集合进行递归构建基因组关系矩阵来对此进行测试。不同集合的预测准确性差异表明每个集合的重要程度。将年轻动物与这些集合联系起来的递归系数揭示了特定父系对近期动物预测准确性的相对重要性。数据包括自1983年以来测量的约1000万个体高和前乳房附着（FUA）评分。有569404只动物的基因型数据可用。父系集合包括在不同时间段出生的100个最受欢迎的父系。计算采用单步基因组最佳线性无偏预测法（BLUP）。总体而言，较年轻的父系比最老的父系具有更高的预测准确性，尽管它们的后代通常较少。体高评估的准确性从1981年以前出生的最受欢迎父系的0.54提高到2001年至2010年出生的父系的0.69，而FUA的准确性从0.47提高到0.61。使用全部100个最常用父系获得的体高准确性为0.66，FUA为0.58。将每个时期的所有100个父系组合在一个子集中，以确定每个父系相对于组合子集中所有400只动物的重要性。在不同时间段出生的父系中，影响最大的是“英勇”（1981年以前出生），相对影响为1.97；“黑星”（1981年至1990年出生）为1.94；“肖特尔”（1991年至2000年出生）为4.38；“行星”（2001年至2010年出生）为3.09。400只动物中影响最大的3个父系是“肖特尔”、“戈德温”（3.73）和“行星”。父系的相对影响与后代数量没有很强的相关性。例如，有34000个后代的“达勒姆”的相对影响为2.29，而有15000个后代的“奥曼”的影响为3.13。父系的影响还受其是否用作种公牛的影响。结果表明，较年轻的父系与近期群体中育种值预测的准确性更相关。
