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Asian-Australas J Anim Sci > Accepted Articles
DOI: https://doi.org/10.5713/ajas.19.0411    [Accepted] Published online October 21, 2019.
A genome-wide association study of reproduction traits in four pig populations with different genetic backgrounds
Jiang Yao1  , Tang Shao Qing2  , Xiao Wei2  , Yun Peng2  , Ding Xiang Dong1,* 
1National Engineering Laboratory for Animal Breeding, Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
2Beijing Station of Animal Husbandry, Beijing 100107, China
Correspondence:  Ding Xiang Dong, Tel: +86-15811104301, Fax: +86-01062734277, Email: xding@cau.edu.cn
Received: 26 May 2019   • Revised: 30 July 2019   • Accepted: 26 May 2019
Genome-wide association study and two meta-analysis based on GWAS performed to explore the genetic mechanism underlying variation in pig number born alive (NBA) and total number born (TNB).
Single trait GWAS and two meta-analysis (single-trait meta analysis and multi-trait meta analysis) were used in our study for NBA and TNB on 3121 Yorkshires from 4 populations, including three different American Yorkshire populations (n=2,247) and one British Yorkshire populations (n=874).
The result of single trait GWAS showed that no significant associated SNPs were identified. Using single-trait meta analysis and multi-trait meta analysis within populations, 11 significant loci were identified associated with target traits. SPIN1, VEGFA, FOXQ1, MSX1 and LHFPL3 are five functionally plausible candidate genes for NBA and TNB. Compared to the single population GWAS, single-trait Meta analysis can improve the detection power to identify SNPs by integrating information of multiple populations. The multiple-trait analysis reduced the power to detect trait-specific loci but enhanced the power to identify the common loci across traits.
In total, our findings identified novel genes to be validated as candidates for NBA and TNB in pigs. Also, it enabled us to enlarge population size by including multiple populations with different genetic backgrounds and increase the power of GWAS by using meta analysis.
Keywords: Genome-wide Association Study; Total Number Born; Number Born Alive; Meta-analysis

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