Genome wide association study and genomic prediction for fatty acid composition in Chinese Simmental beef cattle using high density SNP array

Bo Zhu,Peng Guo,Lingyang Xu,Yong Guo,Hong Niu,Long Guan,Wengang Zhang,Xue Gao,Heming Ni,Lupei Zhang,Zezhao Wang,Huijiang Gao,Yan Chen,Junya Li,Yonghu Liang

doi:10.1186/s12864-017-3847-7

Abstract

BackgroundFatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle.ResultsUsing the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle.ConclusionsWe identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.

Highlights

Fatty acid composition of muscle is an important trait contributing to meat quality
For the eight groups of fatty acids, we found monounsaturated fatty acids (MUFA), n-6/n-3 and health index (HI) showed moderate heritabilities (0.27, 0.22 and 0.24), while the estimated heritability for saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), total of omega 3 (n-3), total of omega 6 (n-6) were 0.12, 0.16, 0.15, and 0.16, respectively
The averaged predictive accuracies across all fatty acids using Genomic best linear unbiased prediction (GBLUP) and BayesB were 0.24 and 0.29, respectively. These results suggested that genomic prediction using BayesB was slightly superior over GBLUP for fatty acids in Chinese Simmental cattle

Summary

Introduction

Fatty acid composition of muscle is an important trait contributing to meat quality. Genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. Fat content and fatty acid composition in beef products are associated with meat taste and flavor, and these are. Fatty acids are important indicators of beef meat quality, and previous studies have been conducted to examine fatty acids for various cattle breeds in different feeding environments [4]. Several studies have revealed that the level of heritability and genetic correlation theoretically allow for genetic improvement of fatty acid composition by selection of both major candidate genes and genomic. Application of molecular genetics approaches can provide an opportunity for genetic improvement for fatty acid composition of beef cattle [11,12,13]

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