The selection of beef cattle for feed efficiency (FE) traits is very important not only for productive and economic efficiency but also for reduced environmental impact of livestock. Considering that FE is multifactorial and expensive to measure, the aim of this study was to identify biological functions and regulatory genes associated with this phenotype. Eight genes were differentially expressed between high and low feed efficient animals (HFE and LFE, respectively). Co-expression analyses identified 34 gene modules of which 4 were strongly associated with FE traits. They were mainly enriched for inflammatory response or inflammation-related terms. We also identified 463 differentially co-expressed genes which were functionally enriched for immune response and lipid metabolism. A total of 8 key regulators of gene expression profiles affecting FE were found. The LFE animals had higher feed intake and increased subcutaneous and visceral fat deposition. In addition, LFE animals showed higher levels of serum cholesterol and liver injury biomarker GGT. Histopathology of the liver showed higher percentage of periportal inflammation with mononuclear infiltrate. Liver transcriptomic network analysis coupled with other results demonstrated that LFE animals present altered lipid metabolism and increased hepatic periportal lesions associated with an inflammatory response composed mainly by mononuclear cells. We are now focusing to identify the causes of increased liver lesions in LFE animals.

Feed intake plays an important economic role in beef cattle, and is related with feed efficiency, weight gain and carcass traits. However, the phenotypes collected for dry matter intake and feed efficiency are scarce when compared with other measures such as weight gain and carcass traits. The use of genomic information can improve the power of inference of studies on these measures, identifying genomic regions that affect these phenotypes. This work performed the genome-wide association study (GWAS) for dry matter intake (DMI) and residual feed intake (RFI) of 720 Nellore cattle (Bos taurus indicus).

Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.

Ruminants play a great role in sustainable livestock since they transform pastures, silage, and crop residues into high-quality human food (i.e. milk and beef). Animals with better ability to convert food into animal protein, measured as a trait called feed efficiency (FE), also produce less manure and greenhouse gas per kilogram of produced meat. Thus, the identification of high feed efficiency cattle is important for sustainable nutritional management. Our aim was to evaluate the potential of serum metabolites to identify FE of beef cattle before they enter the feedlot. A total of 3598 and 4210 m/z features was detected in negative and positive ionization modes via liquid chromatography-mass spectrometry. A single feature was different between high and low FE groups. Network analysis (WGCNA) yielded the detection of 19 and 20 network modules of highly correlated features in negative and positive mode respectively, and 1 module of each acquisition mode was associated with RFI (r = 0.55, P < 0.05). Pathway enrichment analysis (Mummichog) yielded the Retinol metabolism pathway associated with feed efficiency in beef cattle in our conditions. Altogether, these findings demonstrate the existence of a serum-based metabolomic signature associated with feed efficiency in beef cattle before they enter the feedlot. We are now working to validate the use of metabolites for identification of feed efficient animals for sustainable nutritional management.

Improving nutrient utilization efficiency is essential for livestock, given the current scenario of increasing demand for animal protein and sustainable resource use. In this context, understanding the biology of feed efficiency (FE) in beef cattle allows the development of markers for identification and selection of best animals for animal production. Thus, 98 young Nellore bulls were evaluated for FE and at the end of the experiment liver samples from six High Feed Efficient (HFE) and six Low Feed Efficient (LFE) animals were collected for protein extraction, digestion and analysis by HPLC-MS/MS. Data were analyzed for differential abundant proteins (DAPs), protein networks, and functional enrichment. Serum endotoxin was also quantified. We found 42 DAPs and 3 protein networks significantly related to FE. The main pathways associated with FE were: microbial metabolism; biosynthesis of fatty acids, amino acids and vitamins; glycolysis/gluconeogenesis; xenobiotic metabolism and; antigen processing and presentation. Serum endotoxins were significantly higher in LFE animals supporting the results. Therefore, the findings presented here confirmed the altered hepatic metabolism and pronounced hepatic inflammation in LFE animals supporting that the increased bacterial load is at least in part responsible for the hepatic lesions and inflammation in LFE animals.

Summary: The aim of this study was to identify candidate genes and genomic regions associated with ultrasound‐derived measurements of the rib‐eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.