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早期的基因组预测女儿怀孕率与荷斯坦奶牛的繁殖性能提高有关。

Early genomic prediction of daughter pregnancy rate is associated with improved reproductive performance in Holstein dairy cows.

机构信息

Department of Veterinary Clinical Medicine, University of Illinois, Urbana 61802.

Zoetis Inc., Kalamazoo, MI 49007.

出版信息

J Dairy Sci. 2020 Apr;103(4):3312-3324. doi: 10.3168/jds.2019-17488. Epub 2020 Feb 20.

Abstract

The use of genomic testing for selecting replacement heifers in commercial farms has recently attracted much attention. Fertility traits are among the most complex, hard to measure, and lowly heritable traits, and hence they can benefit the most from genomic testing. The objectives of this study were to assess the relationship between early genomic prediction of daughter pregnancy rate (GDPR) and pregnancy at the first service (P1), pregnancy at the end of lactation (PEND), number of services for conception (NSFC), days from calving to first service (TP1), and days open (TPEND). Data for GDPR, milk production, and reproductive outcomes from 1,401 multiparous and 3,044 primiparous Holstein cows from 4 commercial farms with the same reproductive management were used in the analyses. All animals were genotyped and genomically evaluated as heifers before first breeding, so no phenotypic data were available for predicting genomic merits. In addition, all animals were genotyped and evaluated as heifers before first breeding, so no phenotypic data were available for prediction. Data for GDPR and milk production were categorized in quartiles. The statistical models included GDPR, farm-year-season of the first insemination, milk yield, breeding code (estrus detection or timed artificial insemination), and the interaction terms as potential predictors for the different reproductive outcomes evaluated. Data were analyzed separately for primiparous and multiparous cows. The proportion of cows bred by estrus detection increased linearly from lowest to highest GDPR in primiparous cows. There were positive associations of GDPR for P1, PEND, NSFC, TP1, and TPEND in both primiparous and multiparous cows. For instance, positive GDPR effects in multiparous cows included a 15.7% higher P1 (47.6% vs. 31.9%), 11.9% higher PEND (84.9% vs. 73.0%), and 48.0-d shorter TPEND (139.8 vs. 175.7 d) for the highest quartile compared with the lowest quartile. Milk yield affected PEND in multiparous cows, and TPEND and NSFC affected PEND in primiparous cows. The only significant interaction between GDPR and milk production was detected for NSFC in primiparous cows, where high-producing cows showed a reduction in NSFC as GDPR increased, whereas low-producing cows showed no relationship between GDPR and NSFC. Overall, our findings show that GDPR can be effectively used as a predictor of future reproductive performance, reaffirming the potential benefits of applying early genomic predictions for making accurate early selection decisions.

摘要

基因组检测在商业农场中选择替代后备牛的应用最近引起了广泛关注。繁殖力性状是最复杂、难以测量和遗传力较低的性状之一,因此它们最能受益于基因组检测。本研究的目的是评估早期基因组预测女儿妊娠率(GDPR)与第一次配种妊娠(P1)、泌乳期末妊娠(PEND)、配种次数(NSFC)、产后第一次配种天数(TP1)和产后天数(TPEND)之间的关系。本研究使用了来自 4 个具有相同繁殖管理的商业农场的 1401 头经产和 3044 头初产荷斯坦奶牛的 GDPR、产奶量和繁殖结果数据。所有动物在第一次配种前都被作为后备牛进行了基因分型和基因组评估,因此没有表型数据可用于预测基因组优势。此外,所有动物在第一次配种前都被作为后备牛进行了基因分型和评估,因此没有表型数据可用于预测。GDPR 和产奶量数据被分为四等份。统计模型包括 GDPR、第一次输精的农场-年份-季节、产奶量、配种代码(发情检测或定时人工授精)以及不同繁殖结果的互作项,这些都是评估的潜在预测因子。根据初产和经产牛的数据分别进行分析。在初产牛中,通过发情检测配种的牛的比例从最低到最高的 GDPR 呈线性增加。在初产和经产牛中,GDPR 与 P1、PEND、NSFC、TP1 和 TPEND 呈正相关。例如,在经产牛中,GDPR 对 P1、PEND、NSFC、TP1 和 TPEND 的正向效应包括:最高四分位组的 P1 比最低四分位组高 15.7%(47.6%对 31.9%),PEND 高 11.9%(84.9%对 73.0%),TPEND 短 48.0 天(139.8 对 175.7 天);在初产牛中,产奶量影响 PEND,TPEND 和 NSFC 影响 PEND。在初产牛中,仅检测到 GDPR 与产奶量之间的显著互作,高生产牛的 NSFC 随着 GDPR 的增加而减少,而低生产牛的 GDPR 与 NSFC 之间没有关系。总的来说,我们的研究结果表明,GDPR 可以有效地作为未来繁殖性能的预测因子,这再次证实了应用早期基因组预测进行准确早期选择决策的潜在益处。

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