Detailed phenotyping identifies genes with pleiotropic effects on body composition

被引:50
作者
Bolormaa, Sunduimijid [1 ,2 ]
Hayes, Ben J. [1 ,2 ,3 ]
van der Werf, Julius H. J. [2 ,4 ]
Pethick, David [2 ,5 ]
Goddard, Michael E. [1 ,6 ]
Daetwyler, Hans D. [1 ,2 ,3 ]
机构
[1] AgriBio, Ctr AgriBiosci, Dept Econ Dev Jobs Transport & Resources, Bundoora, Vic 3083, Australia
[2] Cooperat Res Ctr Sheep Ind Innovat, Armidale, NSW 2351, Australia
[3] La Trobe Univ, Sch Appl Syst Biol, Bundoora, Vic 3083, Australia
[4] Univ New England, Sch Environm & Rural Sci, Armidale, NSW 2351, Australia
[5] Murdoch Univ, Sch Vet & Life Sci, Murdoch, WA 6150, Australia
[6] Univ Melbourne, Sch Land & Environm, Parkville, Vic 3010, Australia
来源
BMC GENOMICS | 2016年 / 17卷
关键词
GWAS; Multi-trait; Meta-analysis; Pleiotropy; Genes; Body composition; Sheep; Human; GENOME-WIDE ASSOCIATION; MEAT QUALITY TRAITS; BREEDING VALUES; BOS-INDICUS; MUSCLE; PARAMETERS; ACCURACY; CARCASS; YIELD; ARCHITECTURE;
D O I
10.1186/s12864-016-2538-0
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Genetic variation in both the composition and distribution of fat and muscle in the body is important to human health as well as the healthiness and value of meat from cattle and sheep. Here we use detailed phenotyping and a multi-trait approach to identify genes explaining variation in body composition traits. Results: A multi-trait genome wide association analysis of 56 carcass composition traits measured on 10,613 sheep with imputed and real genotypes on 510,174 SNPs was performed. We clustered 71 significant SNPs into five groups based on their pleiotropic effects across the 56 traits. Among these 71 significant SNPs, one group of 11 SNPs affected the fatty acid profile of the muscle and were close to 8 genes involved in fatty acid or triglyceride synthesis. Another group of 23 SNPs had an effect on mature size, based on their pattern of effects across traits, but the genes near this group of SNPs did not share any obvious function. Many of the likely candidate genes near SNPs with significant pleiotropic effects on the 56 traits are involved in intra-cellular signalling pathways. Among the significant SNPs were some with a convincing candidate gene due to the function of the gene (e.g. glycogen synthase affecting glycogen concentration) or because the same gene was associated with similar traits in other species. Conclusions: Using a multi-trait analysis increased the power to detect associations between SNP and body composition traits compared with the single trait analyses. Detailed phenotypic information helped to identify a convincing candidate in some cases as did information from other species.
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页数:21
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