Strategies to improve genomic predictions for 35 duck carcass traits in an F-2 population

文献类型： 外文期刊

第一作者： Cai, Wentao

作者： Cai, Wentao;Hu, Jian;Fan, Wenlei;Tang, Jing;Xie, Ming;Zhang, Yunsheng;Guo, Zhanbao;Zhou, Zhengkui;Hou, Shuisheng;Hu, Jian;Fan, Wenlei;Xu, Yaxi

作者机构：

关键词： Bayesian model; Carcass traits; Duck; Genome prediction; Genomic relationship matrix; Mark density

期刊名称：JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY （ 影响因子：7.0； 五年影响因子：7.3 ）

ISSN： 1674-9782

年卷期： 2023 年 14 卷 1 期

页码：

收录情况： SCI

摘要： Background Carcass traits are crucial for broiler ducks, but carcass traits can only be measured postmortem. Genomic selection (GS) is an effective approach in animal breeding to improve selection and reduce costs. However, the performance of genomic prediction in duck carcass traits remains largely unknown.Results In this study, we estimated the genetic parameters, performed GS using different models and marker densities, and compared the estimation performance between GS and conventional BLUP on 35 carcass traits in an F-2 population of ducks. Most of the cut weight traits and intestine length traits were estimated to be high and moder-ate heritabilities, respectively, while the heritabilities of percentage slaughter traits were dynamic. The reliability of genome prediction using GBLUP increased by an average of 0.06 compared to the conventional BLUP method. The Permutation studies revealed that 50K markers had achieved ideal prediction reliability, while 3K markers still achieved 90.7% predictive capability would further reduce the cost for duck carcass traits. The genomic relationship matrix normalized by our true variance method instead of the widely used S2p(i)(1 - pi) could achieve an increase in prediction reliability in most traits. We detected most of the bayesian models had a better performance, especially for BayesN. Compared to GBLUP, BayesN can further improve the predictive reliability with an average of 0.06 for duck carcass traits. Conclusion This study demonstrates genomic selection for duck carcass traits is promising. The genomic prediction can be further improved by modifying the genomic relationship matrix using our proposed true variance method and several Bayesian models. Permutation study provides a theoretical basis for the fact that low-density arrays can be used to reduce genotype costs in duck genome selection.

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