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.

BackgroundEfficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle.ResultsDifferential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism.ConclusionsOur data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1464-x) contains supplementary material, which is available to authorized users.

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.

BackgroundFeed efficiency is jointly determined by productivity and feed requirements, both of which are economically relevant traits in beef cattle production systems. The objective of this study was to identify genes/QTLs associated with components of feed efficiency in Nelore cattle using Illumina BovineHD BeadChip (770 k SNP) genotypes from 593 Nelore steers. The traits analyzed included: average daily gain (ADG), dry matter intake (DMI), feed-conversion ratio (FCR), feed efficiency (FE), residual feed intake (RFI), maintenance efficiency (ME), efficiency of gain (EG), partial efficiency of growth (PEG) and relative growth rate (RGR). The Bayes B analysis was completed with Gensel software parameterized to fit fewer markers than animals. Genomic windows containing all the SNP loci in each 1 Mb that accounted for more than 1.0% of genetic variance were considered as QTL region. Candidate genes within windows that explained more than 1% of genetic variance were selected by putative function based on DAVID and Gene Ontology.ResultsThirty-six QTL (1-Mb SNP window) were identified on chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25 and 26 (UMD 3.1). The amount of genetic variance explained by individual QTL windows for feed efficiency traits ranged from 0.5% to 9.07%. Some of these QTL minimally overlapped with previously reported feed efficiency QTL for Bos taurus. The QTL regions described in this study harbor genes with biological functions related to metabolic processes, lipid and protein metabolism, generation of energy and growth. Among the positional candidate genes selected for feed efficiency are: HRH4, ALDH7A1, APOA2, LIN7C, CXADR, ADAM12 and MAP7.ConclusionsSome genomic regions and some positional candidate genes reported in this study have not been previously reported for feed efficiency traits in Bos indicus. Comparison with published results indicates that different QTLs and genes may be involved in the control of feed efficiency traits in this Nelore cattle population, as compared to Bos taurus cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-014-0100-0) contains supplementary material, which is available to authorized users.

Residual feed intake (RFI), a measure of feed efficiency (FE), is defined as the difference between the observed and the predictable feed intake considering size and growth of the animal. It is extremely important to beef production systems due to its impact on the allocation of land areas to alternative agricultural production, animal methane emissions, food demand and cost of production. Global differential gene expression analysis between high and low RFI groups (HRFI and LRFI: less and more efficient, respectively) revealed 73 differentially expressed (DE) annotated genes in Longissimus thoracis (LT) muscle of Nelore steers. These genes are involved in the overrepresented pathways Metabolism of Xenobiotics by Cytochrome P450 and Butanoate and Tryptophan Metabolism. Among the DE transcripts were several proteins related to mitochondrial function and the metabolism of lipids. Our findings indicate that observed gene expression differences are primarily related to metabolic processes underlying oxidative stress. Genes involved in the metabolism of xenobiotics and antioxidant mechanisms were primarily down-regulated, while genes responsible for lipid oxidation and ketogenesis were up-regulated in HRFI group. By using LT muscle, this study reinforces our previous findings using liver tissue and reveals new genes and likely tissue-specific regulators playing key-roles in these processes.

BackgroundIntegration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits.ResultsWe performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism.ConclusionThis study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4871-y) contains supplementary material, which is available to authorized users.

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