Application of Genomic Random Regression Models for Genetic Parameter Estimations of Female Fertility Traits in Different Parities in German Holsteins

IF 1.9 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Journal of Animal Breeding and Genetics Pub Date : 2026-04-06 Epub Date: 2025-11-14 DOI:10.1111/jbg.70027
Sina Sakhaei-far, Tong Yin, Sven König
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引用次数: 0

Abstract

The aim of the present study was to infer genetic (co) variance components and to estimate parity-specific breeding values for the female fertility traits non-return rate after 56 days, the interval from calving to first service and days open by applying random regression models on a time-dependent parity scale. In this regard, we considered a female fertility dataset comprising 592,829 records on 190,269 German Holstein cows and heifers kept in 45 large-scale dairy contract herds. From a subset of 21,316 cattle with phenotypic records, (imputed) 50 K genotypes were available. The applied genomic random regression model considered Legendre polynomials of order 2 for the additive-genetic effects along the parity scale, and combined pedigree and genomic relationships through the H-matrix. Results were compared with genetic parameter estimates from a multiple-trait model, considering the same fertility trait in different parities as different traits. From both modelling approaches, we observed the trend of increasing genetic variances and heritabilities with increasing parity. Especially for the non-return rate, the genetic variance in heifers was substantially smaller than in all parities of cows. With regard to the random regression model, genetic correlations between the same fertility traits from adjacent parities were close to 1, but gradually declined with increasing parity distances. Small genetic correlations were also estimated between non-return rates in heifers with non-return rates in all cow parities, i.e., 0.50 with parity 1, 0.44 with parity 2, 0.41 with parity 3, 0.35 with parity 4, 0.33 with parity 5, and 0.25 with parity 6. A similar pattern for genetic correlations in the same traits across parities was confirmed from the multiple-trait model application. Estimated breeding values for all fertility traits in different parities of sires with at least 10 phenotyped daughters per trait (estimates from the random regression model) were correlated with their official breeding indexes from the national genetic evaluation. In this regard, moderate differences were observed when comparing breeding value correlations for non-return rates in heifers with respective correlations in all cow parities. From a practical breeding perspective, the most important results were the rather small genetic correlations for the same traits in different parities (e.g., 0.24 between calving to first service in parities 1 and 6), and differing breeding value correlations with other breeding indexes in different parities. These findings suggest the implementation of specific genetic evaluations for specific cow parities, as an extension to the existing separation between heifer and cow fertility traits. Parity-specific breeding value correlations from the random regression and the multiple-trait model considering the sires with at least 10 daughters were larger than 0.85, suggesting only minor re-rankings of sires from the two different modeling approaches.

Abstract Image

基因组随机回归模型在德国荷尔斯坦不同胎次雌性育性性状遗传参数估计中的应用。
本研究的目的是在时间相关的胎次尺度上应用随机回归模型,推断遗传(co)方差成分,并估计56天后雌性生育性状的不回复率、产犊至首次服务间隔和开放天数的胎次特异性育种值。在这方面,我们考虑了一个包含592,829条记录的女性生育数据集,这些记录来自45个大型奶牛合同畜群中的190,269头德国荷斯坦奶牛和小母牛。从21,316头有表型记录的牛的亚群中,(估算的)50个K基因型可用。应用基因组随机回归模型考虑了2阶勒让德多项式沿奇偶尺度的加性遗传效应,并通过h矩阵将家系和基因组关系结合起来。结果与多性状模型的遗传参数估计值进行了比较,将不同胎次的相同育性性状视为不同性状。从这两种建模方法中,我们观察到遗传变异和遗传力随着宇称的增加而增加的趋势。特别是对于不回复率,小母牛的遗传变异明显小于所有胎次的奶牛。在随机回归模型中,相邻胎次相同育性性状的遗传相关接近1,但随胎次距离的增加而逐渐降低。在所有奶牛胎次中,也估计了小母牛的不复归率与不复归率之间的小遗传相关性,即胎次1为0.50,胎次2为0.44,胎次3为0.41,胎次4为0.35,胎次5为0.33,胎次6为0.25。从多性状模型应用中证实了相同性状跨胎次的遗传相关性的类似模式。每个性状至少有10个表型子代的不同胎次的所有育性性状的育种估计值(随机回归模型估计值)与其国家遗传评价的官方育种指标相关。在这方面,当比较小母牛不还款率的育种值相关性与所有奶牛胎次的各自相关性时,观察到中度差异。从实际育种的角度来看,最重要的结果是相同性状在不同胎次之间的遗传相关性较小(如1胎次和6胎次产仔至首次服务之间的遗传相关性为0.24),以及不同胎次与其他育种指标的育种值相关性不同。这些发现建议对特定胎次的奶牛进行特定的遗传评估,作为现有小牛和奶牛生育性状分离的延伸。来自随机回归和考虑至少有10个子代的母系的多性状模型的胎次特异性育种值相关性大于0.85,这表明两种不同建模方法只对母系进行了轻微的重新排序。
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来源期刊
Journal of Animal Breeding and Genetics
Journal of Animal Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
5.20
自引率
3.80%
发文量
58
审稿时长
12-24 weeks
期刊介绍: The Journal of Animal Breeding and Genetics publishes original articles by international scientists on genomic selection, and any other topic related to breeding programmes, selection, quantitative genetic, genomics, diversity and evolution of domestic animals. Researchers, teachers, and the animal breeding industry will find the reports of interest. Book reviews appear in many issues.
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