基因组选择技术在农业动物育种中的应用

谈成, 边成, 杨达, 李宁, 吴珍芳, 胡晓湘,

doi:10.16288/j.yczz.17-286

遗传 >

2017 , Vol. 39 >Issue 11: 1033 - 1045

DOI: https://doi.org/10.16288/j.yczz.17-286

综述

基因组选择技术在农业动物育种中的应用

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1. 中国农业大学,农业生物技术国家重点实验室,北京 100193
2. 华南农业大学动物科学学院,国家生猪种业工程技术研究中心,广州 510642
3. 广东温氏食品集团股份有限公司,云浮 527400
4. 明尼苏达大学动物科学系,圣保罗 MN55108

谈成,博士,研究方向：动物分子数量遗传学。E-mail: tancheng200508@163.com|吴珍芳，教授，博士生导师，研究方向：动物遗传育种与繁殖。E-mail: wzfemail@163.com|胡晓湘，教授，博士生导师，研究方向：生物化学与分子生物学。E-mail: huxx@cau.edu.cn

收稿日期: 2017-08-29

修回日期: 2017-10-20

网络出版日期: 2017-12-20

基金资助

农业部948项目(2012-G1(4));国家高技术研究发展计划(863计划)项目(2011AA100301)

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Application of genomic selection in farm animal breeding

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1. State Key Laboratory of Agricultural Biotechnology, China Agricultural University, Beijing 100193, China
2. National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou 510642, China
3. Guangdong Wens Foodstuff Group Co., Ltd., Yunfu 527400, China
4. Department of Animal Science, University of Minnesota, Saint Paul MN 55108, USA

Received date: 2017-08-29

Revised date: 2017-10-20

Online published: 2017-12-20

Supported by

the 948 Program of the Ministry of Agriculture of China(2012-G1(4));the National High-Tech Research and Development Program of China (863 Program)(2011AA100301)

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摘要

基因组选择(genomic selection, GS)是畜禽经济性状遗传改良的重要方法。随着高密度SNP芯片和二代测序价格的下降,GS技术越来越多被应用于奶牛、猪、鸡等农业动物育种中。然而,降低全基因组SNP分型成本、提高基因组育种值(genomic estimated breeding value,GEBV)估计准确性仍然是GS研究的主要难题。本文从全基因组SNP分型策略和GEBV估计模型两个方面进行了综述,并对目前GS技术在主要畜禽品种中的应用现状进行了介绍,以期为GS在农业动物育种中的深入开展提供借鉴和参考。

关键词： 基因组选择; 动物育种; 基因分型; 二代测序

本文引用格式

谈成, 边成, 杨达, 李宁, 吴珍芳, 胡晓湘, . 基因组选择技术在农业动物育种中的应用[J]. 遗传, 2017 , 39(11) : 1033 -1045 . DOI: 10.16288/j.yczz.17-286

Abstract

Genomic selection (GS) has become a widely accepted method in animal breeding to genetically improve economic traits. With the declining costs of high-density SNP chips and next-generation sequencing, GS has been applied in dairy cattle, swine, poultry and other animals and gained varying degrees of success. Currently, major challenges in GS studies include further reducing the cost of genome-wide SNP genotyping and improving the predictive accuracy of genomic estimated breeding value (GEBV). In this review, we summarize various methods for genome-wide SNP genotyping and GEBV prediction, and give a brief introduction of GS in livestock and poultry breeding. This review will provide a reference for further implementation of GS in farm animal breeding.

Key words： genome selection; animal breeding; genotyping; next-generation sequencing

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