Deriving Gene Networks from SNP Associated with Triacylglycerol and Phospholipid Fatty Acid Fractions from Ribeyes of Angus Cattle.

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.

Genome-wide association and prediction of direct genomic breeding values for composition of fatty acids in Angus beef cattle.

BACKGROUND: As consumers continue to request food products that have health advantages, it will be important for the livestock industry to supply a product that meet these demands. One such nutrient is fatty acids, which have been implicated as playing a role in cardiovascular disease. Therefore, the objective of this study was to determine the extent to which molecular markers could account for variation in fatty acid composition of skeletal muscle and identify genomic regions that harbor genetic variation. RESULTS: Subsets of markers on the Illumina 54K bovine SNPchip were able to account for up to 57% of the variance observed in fatty acid composition. In addition, these markers could be used to calculate a direct genomic breeding values (DGV) for a given fatty acids with an accuracy (measured as simple correlations between DGV and phenotype) ranging from -0.06 to 0.57. Furthermore, 57 1-Mb regions were identified that were associated with at least one fatty acid with a posterior probability of inclusion greater than 0.90. 1-Mb regions on BTA19, BTA26 and BTA29, which harbored fatty acid synthase, Sterol-CoA desaturase and thyroid hormone responsive candidate genes, respectively, explained a high percentage of genetic variance in more than one fatty acid. It was also observed that the correlation between DGV for different fatty acids at a given 1-Mb window ranged from almost 1 to -1. CONCLUSIONS: Further investigations are needed to identify the causal variants harbored within the identified 1-Mb windows. For the first time, Angus breeders have a tool whereby they could select for altered fatty acid composition. Furthermore, these reported results could improve our understanding of the biology of fatty acid metabolism and deposition.

Assessment of ruminal hydrogen sulfide or urine thiosulfate as diagnostic tools for sulfur induced polioencephalomalacia in cattle.

To determine if ruminal hydrogen sulfide, urine thiosulfate, or blood sulfhemoglobin could be used as diagnostic indicators for sulfur-induced polioencephalomalacia, 16 steers (8 cannulated, 368 ± 12 kg; 8 unmodified, 388 ± 10 kg; mean ± standard error) were fed 1 of 2 dietary treatments. Diets consisted of a low sulfate (0.24% S; control) wheat midd-based pellet or the control pellet with sodium sulfate added to achieve a high-sulfate (0.68% S) pellet. As designed, intake did not differ (P = 0.80) between treatments. At 8 hr postfeeding, ruminal hydrogen sulfide was not affected by cannulation (P = 0.35) but was greater (P < 0.01) in high S (6,005 ± 475 mg/l) than control (1,639 ± 472 mg/l) steers. Time of day of sampling affected (P = 0.01) ruminal hydrogen sulfide, with peak concentrations occurring 4-12 hr after feeding. Urine was collected prefeeding (AM) and 7-9 hr postfeeding (PM). Urine thiosulfate concentrations of high S steers sampled in the PM were greater (P > 0.01) than in the AM. However, there was no difference due to time of sampling for control. In both the AM and PM, urine thiosulfate concentrations of high S were greater (P > 0.01) than control. Although hydrogen sulfide and thiosulfate were elevated by increased dietary S intake, a concentration at which polioencephalomalacia is likely to occur could not be determined. Sampling urine for thiosulfate or rumen gas for hydrogen sulfide of nonsymptomatic pen mates 4-8 hr after feeding may be useful to assess sulfur exposure and differentiate between causes of polioencephalomalacia.