Abstract
The fatty acid profile of beef is a complex trait that can benefit from gene-interaction network analysis to understand relationships among loci that contribute to phenotypic variation. Phenotypic measures of fatty acid profile from triacylglycerol and phospholipid fractions of longissimus muscle, pedigree information, and Illumina 54 k bovine SNP genotypes were utilized to derive an annotated gene network associated with fatty acid composition in 1,833 Angus beef cattle. The Bayes-B statistical model was utilized to perform a genome wide association study to estimate associations between 54 k SNP genotypes and 39 individual fatty acid phenotypes within each fraction. Posterior means of the effects were estimated for each of the 54 k SNP and for the collective effects of all the SNP in every 1-Mb genomic window in terms of the proportion of genetic variance explained by the window. Windows that explained the largest proportions of genetic variance for individual lipids were found in the triacylglycerol fraction. There was almost no overlap in the genomic regions explaining variance between the triacylglycerol and phospholipid fractions. Partial correlations were used to identify correlated regions of the genome for the set of largest 1 Mb windows that explained up to 35% genetic variation in either fatty acid fraction. SNP were allocated to windows based on the bovine UMD3.1 assembly. Gene network clusters were generated utilizing a partial correlation and information theory algorithm. Results were used in conjunction with network scoring and visualization software to analyze correlated SNP across 39 fatty acid phenotypes to identify SNP of significance. Significant pathways implicated in fatty acid metabolism through GO term enrichment analysis included homeostasis of number of cells, homeostatic process, coenzyme/cofactor activity, and immunoglobulin. These results suggest different metabolic pathways regulate the development of different types of lipids found in bovine muscle tissues. Network analysis using partial correlations and annotation of significant SNPs can yield information about the genetic architecture of complex traits.
Highlights
Beef is a nutritious source of protein, fat, vitamins, and minerals when appropriately included in the human diet
The genomic window on chromosome 19 at Mb 51 appears to describe a large proportion of the genetic variance across multiple fatty acids in the triacylglycerol fraction, including 14:0, 16:0, 16:1, 18:0, 18:1, saturated fatty acids (SFA), and monounsaturated fatty acids (MUFA)
This region harbors the candidate gene fatty acid synthase (FASN), which is known to be associated with primary lipid synthesis in adipose tissue (Zhang et al, 2008; Abe et al, 2009)
Summary
Beef is a nutritious source of protein, fat, vitamins, and minerals when appropriately included in the human diet. Considerable ongoing effort has been devoted to identification of genomic regions as well as candidate genes for fatty acid profile and adipose synthesis in various breeds of beef cattle, including Angus, Nellore, Brahman, Santa Gertrudis, Hereford, and Shorthorn (Barendse, 2011; Cesar et al, 2014; Kelly et al, 2014). The usefulness of these loci in DNA based beef cattle selection schemes will increase with knowledge of the genomic regions contributing to the development fat deposition (Saatchi et al, 2013). Given the increasing availability of SNP data, there has been an interest in developing computational methods that utilize GWAS results from multiple traits along with principles of co-association to identify clusters of SNP that likely regulate the underlying metabolic pathways (Reverter and Chan, 2008; Fortes et al, 2011; Reverter and Fortes, 2013)
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