Abstract

BackgroundIdentification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and also allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management. In this study, 81 and 83 fatty acid traits were measured in subcutaneous adipose (SQ) and longissimus lumborum muscle (LL), respectively, from 1366 purebred and crossbred beef steers and heifers that were genotyped on the Illumina BovineSNP50 Beadchip. The objective was to conduct genome-wide association studies (GWAS) for the fatty acid traits and to evaluate the accuracy of genomic prediction for fatty acid composition using genomic best linear unbiased prediction (GBLUP) and Bayesian methods.ResultsIn total, 302 and 360 significant SNPs spanning all autosomal chromosomes were identified to be associated with fatty acid composition in SQ and LL tissues, respectively. Proportions of total genetic variance explained by individual significant SNPs ranged from 0.03 to 11.06 % in SQ, and from 0.005 to 24.28 % in the LL muscle. Markers with relatively large effects were located near fatty acid synthase (FASN), stearoyl-CoA desaturase (SCD), and thyroid hormone responsive (THRSP) genes. For the majority of the fatty acid traits studied, the accuracy of genomic prediction was relatively low (<0.40). Relatively high accuracies (> = 0.50) were achieved for 10:0, 12:0, 14:0, 15:0, 16:0, 9c-14:1, 12c-16:1, 13c-18:1, and health index (HI) in LL, and for 12:0, 14:0, 15:0, 10 t,12c-18:2, and 11 t,13c + 11c,13 t-18:2 in SQ. The Bayesian method performed similarly as GBLUP for most of the traits but substantially better for traits that were affected by SNPs of large effects as identified by GWAS.ConclusionsFatty acid composition in beef is influenced by a few host genes with major effects and many genes of smaller effects. With the current training population size and marker density, genomic prediction has the potential to predict the breeding values of fatty acid composition in beef cattle at a moderate to relatively high accuracy for fatty acids that have moderate to high heritability.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0290-0) contains supplementary material, which is available to authorized users.

Highlights

  • Identification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management

  • The present study showed that single nucleotide polymorphisms (SNP) close to the stearoyl-CoA desaturase (SCD) gene were associated with many mono-unsaturated fatty acids (MUFA) and several conjugated linoleic acid (CLA) isomers but none of the saturated fatty acids (SFA), which supports the proposed role of SCD in fatty acid composition in beef

  • Fatty acid composition in beef tissues is a polygenic trait that is controlled by a few major host genes and many genes of small effects

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Summary

Introduction

Identification of genetic variants that are associated with fatty acid composition in beef will enhance our understanding of host genetic influence on the trait and allow for more effective improvement of beef fatty acid profiles through genomic selection and marker-assisted diet management. Recommendations to limit beef consumption are mainly related to its relatively high content of saturated fatty acids (SFAs) as SFA consumption is believed to have negative effects on human health [2, 3]. Diet is known to have a major influence on beef fatty acid composition [8], but the use of genomic technologies to improve beef fatty acid profiles have not been thoroughly investigated [9]

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