基因组育种值估计的贝叶斯方法研究进展

doi:10.3724/SP.J.1005.2014.0111

遗传 ›› 2014, Vol. 36 ›› Issue (2): 111-118.doi: 10.3724/SP.J.1005.2014.0111

基因组育种值估计的贝叶斯方法研究进展

王重龙¹,丁向东²,刘剑锋³,殷宗俊⁴,张勤³

1. 安徽省农业科学院畜牧兽医研究所
2. 中国农业大学动物科学技术学院
3. 中国农业大学动物科技学院
4. 安徽农业大学动物科技学院

收稿日期:2013-06-07 修回日期:2013-12-12 出版日期:2014-02-20 发布日期:2014-01-25
通讯作者: 张勤 E-mail:qzhang@cau.edu.cn
作者简介:王重龙, 博士, 副研究员，研究方向：猪遗传育种与健康养殖。E-mail: ahwchl@163.com
基金资助:
农业部948计划(编号：2011-G2A), 教育部博士学科点专项科研基金项目(编号：20110008110001), 国家高技术研究发展计划(863计划)项目(编号：2011AA100302), 国家自然科学基金项目(编号：31371258, 31171200, 31272418), 国家农业科技成果转化资金项目(编号：2011GB2C300017), 国家生猪产业技术体系(编号：CARS-36), 科技富民强县专项行动计划, 黎平黄牛品种资源保护与开发利用研究(编号：黔农育专字(2010)016号), 安徽省现代农业项目, 安徽省生猪产业技术体系, 安徽省农业科学院成果推广项目(编号：13E0403), 安徽省农业科学院院长杰出青年创新基金项目(编号：13B0405)和安徽省农业科学院科技创新团队建设项目(编号：13C0405)资助

Bayesian methods for genomic breeding value estimation

Chonglong Wang^1,2, Xiangdong Ding², Jianfeng Liu², Zongjun Yin³, Qin Zhang²

1. Institute of Animal Husbandry and Veterinary Medicine, Anhui Academy of Agricultural Sciences, Hefei 230031, China;
2. College of Animal Science and Technology, China Agricultural University, Beijing 100193, China;
3. College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China

Received:2013-06-07 Revised:2013-12-12 Online:2014-02-20 Published:2014-01-25

摘要/Abstract

摘要：

基因组育种值估计是基因组选择的重要环节, 基因组育种值的准确性是基因组选择成功应用的关键, 而其准确性在很大程度上取决于估计方法。目前研究和应用最多的基因组育种值估计方法是贝叶斯(Bayes)和最佳线性无偏预测(BLUP)两大类方法。文章系统介绍了目前已提出的各种Bayes方法, 并总结了该类方法的估计效果和各方面的改进。模拟数据和实际数据研究结果都表明, Bayes类方法估计基因组育种值的准确性优于BLUP类方法, 特别对于存在较大效应QTL的性状其优势更明显。由于Bayes方法的理论和计算过程相对复杂, 目前其在实际育种中的运用不如BLUP类方法普遍, 但随着快速算法的开发和计算机硬件的改进, 计算问题有望得到解决; 另外, 随着对基因组和性状遗传结构研究的深入开展, 能为Bayes方法提供更为准确的先验信息, 从而使Bayes方法估计基因组育种值准确性的优势更加突出, 应用将会更加广泛。

关键词: 基因组选择, 基因组育种值, 贝叶斯方法

Abstract:

Estimation of genomic breeding values is the key step in genomic selection. The successful application of genomic selection depends on the accuracy of genomic estimated breeding values, which is mostly determined by the estimation method. Bayes-type and BLUP-type methods are the two main methods which have been widely studied and used. Here, we systematically introduce the currently proposed Bayesian methods, and summarize their effectiveness and improvements. Results from both simulated and real data showed that the accuracies of Bayesian methods are higher than those of BLUP methods, especially for the traits which are influenced by QTL with large effect. Because the theories and computation of Bayesian methods are relatively complicated, their use in practical breeding is less common than BLUP methods. However, with the development of fast algorithms and the improvement of computer hardware, the computational problem of Bayesian methods is expected to be solved. In addition, further studies on the genetic architecture of traits will provide Bayesian methods more accurate prior information, which will make their advantage in accuracy of genomic estimated breeding values more prominent. Therefore, the application of Bayesian methods will be more extensive.

Key words: genomic selection, genomic estimated breeding values (GEBVs), Bayesian methods

王重龙, 丁向东, 刘剑锋, 殷宗俊, 张勤. 基因组育种值估计的贝叶斯方法研究进展[J]. 遗传, 2014, 36(2): 111-118.

Chonglong Wang, Xiangdong Ding, Jianfeng Liu, Zongjun Yin, Qin Zhang. Bayesian methods for genomic breeding value estimation[J]. HEREDITAS, 2014, 36(2): 111-118.

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基因组育种值估计的贝叶斯方法研究进展

Bayesian methods for genomic breeding value estimation

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