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利用基因组模型研究不同生产阶段猪的存活率。

Investigating pig survival in different production phases using genomic models.

机构信息

Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.

Topigs Norsvin Research Center, Beuningen, GE 6641 SZ, The Netherlands.

出版信息

J Anim Sci. 2021 Aug 1;99(8). doi: 10.1093/jas/skab217.

Abstract

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.

摘要

猪的存活率是一个具有重要经济意义的性状,与相关的社会福利有关,因此成为当前养猪系统的一个重要选择标准。我们旨在估计杂种猪群在不同生产阶段的存活率(协)方差分量,以及通过单步基因组最佳线性无偏预测(ssGBLUP)在预测存活率性状方面相对于传统 BLUP 结果的准确性上纳入基因组信息的益处。在两个多性状门限模型下,最多对 64894 头杂交仔猪的个体存活记录进行了评估。第一个模型包括产仔、哺乳期和断奶后综合存活率,而第二个模型包括保育和育肥存活率。使用 BLUP 和 ssGBLUP 方法估计直接和母本育种值。此外,使用线性回归验证方法评估预测准确性、偏差和离散度。所有研究阶段的存活率直接遗传力估计值均较低(0.02 至 0.08)。在哺乳期和哺乳期,存活率由母畜和仔猪的加性遗传效应控制,尽管母畜的影响更大。断奶后阶段(保育、育肥和两者的组合)与哺乳期阶段相比具有相同或更高的直接遗传力。哺乳期和断奶后阶段之间的存活率性状的遗传相关性是有利的和强的,但哺乳期和断奶后阶段之间的相关性是中等的。尽管通过 ssGBLUP 纳入基因组信息可以提高存活率性状的预测准确性,但存活率性状的预测准确性仍然较低。BLUP 下的直接和母本育种值同样准确,但直接育种值从基因组信息中受益更多。总体而言,当纳入基因组信息时,观察到偏倚略有增加,而育种值的离散度大大降低。断奶后综合存活率比哺乳期阶段具有更高的直接遗传力,并且在所有评估的生产阶段中具有最高的预测准确性,因此是提高存活率的候选性状。存活率是一个低遗传力的复杂性状;然而,特别是在基因组预测框架下,仍可以获得重要的遗传增益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19bf/8404463/b2072b6f94bb/skab217f0001.jpg

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