期刊
LIVESTOCK SCIENCE
卷 166, 期 -, 页码 66-75出版社
ELSEVIER
DOI: 10.1016/j.livsci.2014.05.017
关键词
Dairy cattle; Genomics; SNP; Genomic selection
资金
- Embrapa - SEG [02.09.07.008.00.00]
- CNPq [PVE 407246/2013-4]
- FAPEMIG [CVZ PPM 00325/12]
- USDA Agricultural Research Service [1245-31000-101-00, 1245-31000-104-00]
- ARS [ARS-0423282, 813345] Funding Source: Federal RePORTER
Genomic selection (GS) has profoundly changed dairy cattle breeding in the last decade and can be defined as the use of genomic breeding values (GEBV) in selection programs. The GEBV is the sum of the effects of dense DNA markers across the whole genome, capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. This technology was successfully implemented in the United States, Canada, New Zealand, Australia, and several European countries with very promising results. The GEBV reliability depends on estimation procedures and models. The different methodologies to estimate SNP effects and GEBV have been extensively tested for many research groups with very promising results. Although GS is a success, many challenges still remain, including integration of GEBV into genetic evaluation programs and increasing GEBV reliability. The aim of this review is to discuss the main aspects involved with GS, including different methodologies of imputation, SNP effect estimation, and the most important impacts of GS implementation in dairy cattle. (C) 2014 Elsevier B.V. All rights reserved.
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