BackgroundMeat from Bos taurus and Bos indicus breeds are an important source of nutrients for humans and intramuscular fat (IMF) influences its flavor, nutritional value and impacts human health. Human consumption of fat that contains high levels of monounsaturated fatty acids (MUFA) can reduce the concentration of undesirable cholesterol (LDL) in circulating blood. Different feeding practices and genetic variation within and between breeds influences the amount of IMF and fatty acid (FA) composition in meat. However, it is difficult and costly to determine fatty acid composition, which has precluded beef cattle breeding programs from selecting for a healthier fatty acid profile. In this study, we employed a high-density single nucleotide polymorphism (SNP) chip to genotype 386 Nellore steers, a Bos indicus breed and, a Bayesian approach to identify genomic regions and putative candidate genes that could be involved with deposition and composition of IMF.ResultsTwenty-three genomic regions (1-Mb SNP windows) associated with IMF deposition and FA composition that each explain ≥ 1% of the genetic variance were identified on chromosomes 2, 3, 6, 7, 8, 9, 10, 11, 12, 17, 26 and 27. Many of these regions were not previously detected in other breeds. The genes present in these regions were identified and some can help explain the genetic basis of deposition and composition of fat in cattle.ConclusionsThe genomic regions and genes identified contribute to a better understanding of the genetic control of fatty acid deposition and can lead to DNA-based selection strategies to improve meat quality for human consumption.

No abstract

Intramuscular fat (IMF) content is related to insulin resistance, which is an important prediction factor for disorders, such as cardiovascular disease, obesity and type 2 diabetes in human. At the same time, it is an economically important trait, which influences the sensorial and nutritional value of meat. The deposition of IMF is influenced by many factors such as sex, age, nutrition, and genetics. In this study Nellore steers (Bos taurus indicus subspecies) were used to better understand the molecular mechanisms involved in IMF content. This was accomplished by identifying differentially expressed genes (DEG), biological pathways and putative regulatory factors. Animals included in this study had extreme genomic estimated breeding value (GEBV) for IMF. RNA-seq analysis, gene set enrichment analysis (GSEA) and co-expression network methods, such as partial correlation coefficient with information theory (PCIT), regulatory impact factor (RIF) and phenotypic impact factor (PIF) were utilized to better understand intramuscular adipogenesis. A total of 16,101 genes were analyzed in both groups (high (H) and low (L) GEBV) and 77 DEG (FDR 10%) were identified between the two groups. Pathway Studio software identified 13 significantly over-represented pathways, functional classes and small molecule signaling pathways within the DEG list. PCIT analyses identified genes with a difference in the number of gene-gene correlations between H and L group and detected putative regulatory factors involved in IMF content. Candidate genes identified by PCIT include: ANKRD26, HOXC5 and PPAPDC2. RIF and PIF analyses identified several candidate genes: GLI2 and IGF2 (RIF1), MPC1 and UBL5 (RIF2) and a host of small RNAs, including miR-1281 (PIF). These findings contribute to a better understanding of the molecular mechanisms that underlie fat content and energy balance in muscle and provide important information for the production of healthier beef for human consumption.

BackgroundLipids are a class of molecules that play an important role in cellular structure and metabolism in all cell types. In the last few decades, it has been reported that long-chain fatty acids (FAs) are involved in several biological functions from transcriptional regulation to physiological processes. Several fatty acids have been both positively and negatively implicated in different biological processes in skeletal muscle and other tissues. To gain insight into biological processes associated with fatty acid content in skeletal muscle, the aim of the present study was to identify differentially expressed genes (DEGs) and functional pathways related to gene expression regulation associated with FA content in cattle.ResultsSkeletal muscle transcriptome analysis of 164 Nellore steers revealed no differentially expressed genes (DEGs, FDR 10%) for samples with extreme values for linoleic acid (LA) or stearic acid (SA), and only a few DEGs for eicosapentaenoic acid (EPA, 5 DEGs), docosahexaenoic acid (DHA, 4 DEGs) and palmitic acid (PA, 123 DEGs), while large numbers of DEGs were associated with oleic acid (OA, 1134 DEGs) and conjugated linoleic acid cis9 trans11 (CLA-c9t11, 872 DEGs). Functional annotation and functional enrichment from OA DEGs identified important genes, canonical pathways and upstream regulators such as SCD, PLIN5, UCP3, CPT1, CPT1B, oxidative phosphorylation mitochondrial dysfunction, PPARGC1A, and FOXO1. Two important genes associated with lipid metabolism, gene expression and cancer were identified as DEGs between animals with high and low CLA-c9t11, specifically, epidermal growth factor receptor (EGFR) and RNPS.ConclusionOnly two out of seven classes of molecules of FA studied were associated with large changes in the expression profile of skeletal muscle. OA and CLA-c9t11 content had significant effects on the expression level of genes related to important biological processes associated with oxidative phosphorylation, and cell growth, survival, and migration. These results contribute to our understanding of how some FAs modulate metabolism and may have protective health function.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3306-x) contains supplementary material, which is available to authorized users.

We used chemical composition and in vitro digestibility data from temperate and tropical forages to develop relationships between indices of lignification and forage indigestible NDF. Neutral detergent fiber indigestibility increased nonlinearly as the lignin concentration of the NDF increased. Differences in estimated indigestible NDF using equations developed for a specific forage class (C3 and C4 grasses and legumes) were small and are probably not biologically significant when compared to those estimated from a common equation. Selected equations were compared with the Cornell Net Carbohydrate and Protein System (CNCPS) for the prediction of ADG. The linear equation (2.4 times NDF lignin content) used by the CNCPS and the Beef NRC had some of the largest errors due to mean bias. A log-log model [4.37 x (lignin/NDF)(.84)] provided the best combination of low total prediction error, low mean bias, and minimal error due to regression bias when permanganate lignin was used. A similar equation based on sulfuric acid lignin [6.17 x (lignin/NDF)(.77)] also met the above criteria. These equations then were evaluated with the CNCPS model against animal growth data from diets ranging in forage quality. Regardless of the equation used for predicting unavailable fiber, the CNCPS underpredicted daily gain, with mean biases ranging from -.10 to -.22 kg/d. Regression bias ranged from .13 to .14 kg/d and the coefficients differed from unity (P = .0001). The new equations gave numerically lower energy allowable ADG by steers compared to the linear equation currently used by the CNCPS model. The estimates were lower due to a higher predicted indigestible NDF, which resulted in a lower estimated forage energy value.