<br>肉牛体况评分和成年牛体重的遗传参数、杂种优势和品种效应,Journal of Animal Science

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肉牛体况评分和成年牛体重的遗传参数、杂种优势和品种效应
Journal of Animal Science ( IF 2.7 ) Pub Date : 2022-01-19 , DOI: 10.1093/jas/skac017
André Mauric F Ribeiro _{1,

2} , Leticia P Sanglard ₁ , Warren M Snelling ₃ , R Mark Thallman ₃ , Larry A Kuehn ₃ , Matthew L Spangler ₁

Affiliation

了解成熟奶牛体重 (MWT) 和身体状况评分 (BCS) 之间的遗传关系有助于实施以奶牛效率为重点的选择计划。本研究的目的是估计 MWT 和 BCS 的遗传参数、杂种优势和品种效应。总共有 25,035 条重叠记录和 24,522 条重叠记录分别来自美国肉类动物研究中心的杂交牛肉群体种质评估计划，分别针对 6,138 头和 6,131 头奶牛进行了 MWT 和 BCS。共有 48,013 个人拥有血统书。使用单变量动物模型通过胎次来估计每个性状的遗传力。双变量动物模型用于估计性状内胎次之间以及胎次内性状之间的遗传相关性。双变量重复性动物模型用于估计不同胎次性状之间的遗传相关性。不同胎次的遗传力估计值范围为：MWT 为 0.43 ± 0.05 至 0.55 ± 0.07，BCS 为 0.12 ± 0.03 至 0.25 ± 0.04，而 MWT 和 BCS 的重复性模型则较低，分别为 0.40 ± 0.02 和 0.11 ± 0.01。 MWT 的重复性估计值较高 (0.67 ± 0.005)，而 BCS 的重复性估计值较低 (0.22 ± 0.006)。一般来说，胎次之间 MWT 和 BCS 的遗传相关性估计较高，尤其是连续胎次之间。 MWT 和 BCS 之间的遗传相关性估计为正且中等，范围为 0.32 ± 0.09 至 0.68 ± 0.14。 MWT 的直接杂种优势估计为 21.56 ± 3.53 kg (P ≤ 0.001)，BCS 的直接杂种优势估计为 0.095 ± 0.034 (P ≤ 0.001)。按 MWT 递减排序，这些品种依次为 Brahman、Charolais、Angus、Simmental、Salers、Hereford、Santa Gertrudis、Chiangus、Brangus、Red Angus、Shorhorn、Maine-Anjou、Gelbvieh、Beefmaster、Limousin 和 Braunvieh。按 BCS 降序排列，这些品种依次为：婆罗门 (Brahman)、红安格斯 (Red Angus)、夏洛莱 (Charolais)、安格斯 (Angus)、赫里福德 (Hereford)、布朗格斯 (Brangus)、Beefmaster、Chiangus、Salers、西门塔尔 (Simmental)、缅因安茹 (Maine-Anjou)、利木赞 (Limousin)、圣格特鲁迪 (Santa Gertrudis)、短角 (Shorthhorn)、盖尔布维 (Gelbvieh) 和布劳恩 (Braunvieh)。 MWT 的品种差异估计也针对 BCS (AMWT) 进行了调整，一般来说，AMWT 通过某种程度的重新排名描述了品种之间较小的差异 (r = 0.59)。这些结果表明 MWT 和 BCS 至少具有中等程度的遗传相关性，并且它们会对选择做出有利的反应。品种差异和杂种优势效应的估计可用于对奶牛维持能量需求指标的多品种遗传评估进行参数化。

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Genetic parameters, heterosis, and breed effects for body condition score and mature cow weight in beef cattle

Understanding the genetic relationship between mature cow weight (MWT) and body condition score (BCS) is useful to implement selection programs focused on cow efficiency. The objectives of this study were to estimate genetic parameters, heterosis, and breed effects for MWT and BCS. In total, 25,035 and 24,522 overlapping records were available for MWT and BCS on 6,138 and 6,131 cows, respectively, from the Germplasm Evaluation program, a crossbred beef population at the U.S. Meat Animal Research Center. Pedigree was available for 48,013 individuals. Univariate animal models were used to estimate heritabilities for each trait by parity. Bivariate animal models were used to estimate genetic correlations between parities within a trait and between traits within parities. Bivariate repeatability animal models were used to estimate genetic correlations between traits across parities. Estimates of heritability for different parities ranged from 0.43 ± 0.05 to 0.55 ± 0.07 for MWT and from 0.12 ± 0.03 to 0.25 ± 0.04 for BCS and were lower with the repeatability model at 0.40 ± 0.02 and 0.11 ± 0.01 for MWT and BCS, respectively. Estimates of repeatability were high for MWT (0.67 ± 0.005) and low for BCS (0.22 ± 0.006). Estimates of genetic correlation for MWT and BCS between parities were, in general, high, especially between consecutive parities. Estimates of genetic correlation between MWT and BCS were positive and moderate, ranging from 0.32 ± 0.09 to 0.68 ± 0.14. The direct heterosis estimates were 21.56 ± 3.53 kg (P ≤ 0.001) for MWT and 0.095 ± 0.034 (P ≤ 0.001) for BCS. Ordered by decreasing MWT, the breeds ranked Brahman, Charolais, Angus, Simmental, Salers, Hereford, Santa Gertrudis, Chiangus, Brangus, Red Angus, Shorthorn, Maine-Anjou, Gelbvieh, Beefmaster, Limousin, and Braunvieh. Ordered by decreasing BCS, the breeds ranked Brahman, Red Angus, Charolais, Angus, Hereford, Brangus, Beefmaster, Chiangus, Salers, Simmental, Maine-Anjou, Limousin, Santa Gertrudis, Shorthorn, Gelbvieh, and Braunvieh. Estimates of breed differences for MWT were also adjusted for BCS (AMWT), and in general, AMWT depicted smaller differences between breeds with some degree of re-ranking (r = 0.59). These results suggest that MWT and BCS are at least moderately genetically correlated and that they would respond favorably to selection. Estimates of breed differences and heterotic effects could be used to parameterize multibreed genetic evaluations for indicators of cow maintenance energy requirements.

更新日期：2022-01-19

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