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Journal of Integrative Agriculture  2017, Vol. 16 Issue (04): 911-920    DOI: 10.1016/S2095-3119(16)61474-0
Animal Science · Veterinary Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Effects of marker density and minor allele frequency on genomic prediction for growth traits in Chinese Simmental beef cattle
ZHU Bo*, ZHANG Jing-jing*, NIU Hong, GUAN Long, GUO Peng, XU Ling-yang, CHEN Yan, ZHANG Lu-pei, GAO Hui-jiang, GAO Xue, LI Jun-ya

Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, P.R.China

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Abstract  Genomic selection has been demonstrated as a powerful technology to revolutionize animal breeding.  However, marker density and minor allele frequency can affect the predictive ability of genomic estimated breeding values (GEBVs).  To investigate the impact of marker density and minor allele frequency on predictive ability, we estimated GEBVs by constructing the different subsets of single nucleotide polymorphisms (SNPs) based on varying markers densities and minor allele frequency (MAF) for average daily gain (ADG), live weight (LW) and carcass weight (CW) in 1 059 Chinese Simmental beef cattle.  Two strategies were proposed for SNP selection to construct different marker densities: 1) select evenly-spaced SNPs (Strategy 1), and 2) select SNPs with large effects estimated from BayesB (Strategy 2).  Furthermore, predictive ability was assessed in terms of the correlation between predicted genomic values and corrected phenotypes from 10-fold cross-validation.  Predictive ability for ADG, LW and CW using autosomal SNPs were 0.13±0.002, 0.21±0.003 and 0.25±0.003, respectively.  In our study, the predictive ability increased dramatically as more SNPs were included in analysis until 200K for Strategy 1.  Under Strategy 2, we found the predictive ability slightly increased when marker densities increased from 5K to 20K, which indicated the predictive ability of 20K (3% of 770K) SNPs with large effects was equal to the predictive ability of using all SNPs.  For different MAF bins, we obtained the highest predictive ability for three traits with MAF bin 0.01–0.1.  Our result suggested that designing a low-density chip by selecting low frequency markers with large SNP effects sizes should be helpful for commercial application in Chinese Simmental cattle.
Keywords:  genomic prediction      cross-validation      Chinese Simmental beef cattle      marker density      minor allele frequency (MAF)  
Received: 18 April 2016   Accepted:

This work was supported by the National Natural Science Foundation of China (31201782, 31672384 and 31372294), the Agricultural Science and Technology Innovation Program  of Chinese Academy of Agricultural Sciences (ASTIP-IAS03), the Cattle Breeding Innovative Research Team of Chinese Academy of Agricultural Sciences (cxgc-ias-03), the Key Technology R&D Program of China during the 12th Five-Year Plan period (2011BAD28B04), the National High Technology Research and Development Program of China (863 Program 2013AA102505-4), and the Beijing Natural Science Foundation, China (6154032).

Corresponding Authors:  LI Jun-ya, E-mail:   
About author:  ZHU Bo, E-mail:; ZHANG Jing-jing, E-mail:

Cite this article: 

ZHU Bo, ZHANG Jing-jing, NIU Hong, GUAN Long, GUO Peng, XU Ling-yang, CHEN Yan, ZHANG Lu-pei, GAO Hui-jiang, GAO Xue, LI Jun-ya. 2017. Effects of marker density and minor allele frequency on genomic prediction for growth traits in Chinese Simmental beef cattle. Journal of Integrative Agriculture, 16(04): 911-920.

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