The objective of this study was to identify genomic regions and metabolic pathways associated with dry matter intake, average daily gain, feed efficiency and residual feed intake in an experimental Nellore cattle population. The high-density SNP chip (Illumina High-Density Bovine BeadChip, 777k) was used to genotype the animals. The SNP markers effects and their variances were estimated using the single-step genome wide association method. The (co)variance components were estimated by Bayesian inference. The chromosome segments that are responsible for more than 1.0% of additive genetic variance were selected to explore and determine possible quantitative trait loci. The bovine genome Map Viewer was used to identify genes. In total, 51 genomic regions were identified for all analyzed traits. The heritability estimated for feed efficiency was low magnitude (0.13±0.06). For average daily gain, dry matter intake and residual feed intake, heritability was moderate to high (0.43±0.05; 0.47±0.05, 0.18±0.05, respectively). A total of 8, 17, 14 and 12 windows that are responsible for more than 1% of the additive genetic variance for dry matter intake, average daily gain, feed efficiency and residual feed intake, respectively, were identified. Candidate genes GOLIM4, RFX6, CACNG7, CACNG6, CAPN8, CAPN2, AKT2, GPRC6A, and GPR45 were associated with feed efficiency traits. It was expected that the response to selection would be higher for residual feed intake than for feed efficiency. Genomic regions harboring possible QTL for feed efficiency indicator traits were identified. Candidate genes identified are involved in energy use, metabolism protein, ion transport, transmembrane transport, the olfactory system, the immune system, secretion and cellular activity. The identification of these regions and their respective candidate genes should contribute to the formation of a genetic basis in Nellore cattle for feed efficiency indicator traits, and these results would support the selection for these traits.

The objectives of this study were to estimate genetic parameters for indicator traits of feed efficiency and to recommend traits that would result in better responses to selection for increased weaning weight (weaning weight adjusted to 210 d of age [W210]), ADG, and metabolic BW (BW(0.75)) and lower DMI. Records of W210 from 8,004 Nellore animals born between 1978 and 2011 and postweaning performance test records from 678 males and females born between 2004 and 2011 were used. The following feed efficiency traits were evaluated: G:F, partial efficiency of growth (PEG), relative growth rate (RGR), Kleiber's ratio (KR), residual feed intake (RFI), residual weight gain (RWG), and residual intake and gain (RIG). Covariance and variance components were estimated by the restricted maximum likelihood method using multitrait analysis under an animal model. Estimates of genetic gain and correlated responses were obtained considering single-stage and 2-stage selection. Heritability estimates were 0.22 ± 0.03 (W210), 0.60 ± 0.08 (DMI), 0.42 ± 0.08 (ADG), 0.56 ± 0.06 (BW(0.75)), 0.19 ± 0.07 (G:F), 0.25 ± 0.09 (PEG), 0.19 ± 0.07 (RGR), 0.22 ± 0.07 (KR), 0.33 ± 0.10 (RFI), 0.13 ± 0.07 (RWG), and 0.19 ± 0.08 (RIG). The genetic correlations of DMI with W210 (0.64 ± 0.10), ADG (0.87 ± 0.06), and BW(0.75) (0.84 ± 0.05) were high. The only efficiency traits showing favorable responses to selection for lower DMI were G:F, PEG, RFI, and RIG. However, the use of G:F, PEG, or RFI as a selection criterion results in unfavorable correlated responses in some growth traits. The linear combination of RFI and RWG through RIG is the best selection criterion to obtain favorable responses in postweaning growth and feed intake of Nellore cattle in single-stage selection. Genetic gains in feed efficiency are expected even after preselection for W210 and subsequent feed efficiency testing of the preselected animals.

This study evaluated phenotypic (rph) and genetic correlations (rg) between 8 feed efficiency traits and other traits of economic interest including weight at selection (WS), loin-eye area (LEA), backfat thickness (BF), and rump fat thickness (RF) in Nellore cattle. Feed efficiency traits were gain:feed, residual feed intake (RFI), residual feed intake adjusted for backfat thickness (RFIb) and for backfat and rump fat thickness (RFIsf), residual body weight gain (RG), residual intake and body weight gain (RIG), and residual intake and body weight gain using RFIb (RIGb) and RFIsf (RIGsf). The variance components were estimated by the restricted maximum likelihood method using a two-trait animal model. The heritability estimates (h2) were 0.14, 0.24, 0.20, 0.22, 0.19, 0.15, 0.11 and 0.11 for gain:feed, RFI, RFIb, RFIsf, RG, RIG, RIGb and RIGsf, respectively. All rph values between traits were close to zero, except for the correlation of feed efficiency traits with dry matter intake and average daily gain. High rg values were observed for the correlation of dry matter intake, average daily gain and metabolic weight with WS and hip height (>0.61) and low to medium values (0.15 to 0.48) with the carcass traits (LEA, BF, RF). Among the feed efficiency traits, RG showed the highest rg with WS and hip height (0.34 and 0.25) and the lowest rg with subcutaneous fat thickness (-0.17 to 0.18). The rg values of RFI, RFIb and RFIsf with WS (0.17, 0.23 and 0.22), BF (0.37, 0.33 and 0.33) and RF (0.30, 0.31 and 0.32) were unfavorable. The rg values of gain:feed, RIG, RIGb and RIGsf with WS were low and favorable (0.07 to 0.22), while medium and unfavorable (-0.22 to -0.45) correlations were observed with fat thickness. The inclusion of subcutaneous fat thickness in the models used to calculate RFI did not reduce the rg between these traits. Selecting animals for higher feed efficiency will result in little or no genetic change in growth and will decrease subcutaneous fat thickness in the carcass.

Fifty-nine Nellore bulls from low and high residual feed intake (RFI) levels were studied with the objective of evaluating meat quality traits. Animals were slaughtered when ultrasound-measured backfat thickness reached 4mm, and samples of Longissimus were collected. A mixed model including RFI as fixed effect and herd and diet as random effects was used, and least square means were compared by t-test. More efficient animals consumed 0.730 kg dry matter/day less than less efficient animals, with similar performance. No significant differences in carcass weight, prime meat cuts proportion, chemical composition, pH, sarcomere length, or color were observed between RFI groups. Shear force, myofibrillar fragmentation index and soluble collagen content were influenced by RFI, with a higher shear force and soluble collagen content and a lower fragmentation index in low RFI animals. Feedlot-finished low RFI young Nellore bulls more efficiently convert feed into meat, presenting carcasses within quality standards.

The ruminant gastrointestinal tract (GIT) microbiome plays a major role in the health, physiology and production traits of the host. In this work, we characterized the bacterial and fungal microbiota of the rumen, small intestine (SI), cecum and feces of 27 Nelore steers using next-generation sequencing and evaluated biochemical parameters within the GIT segments. We found that only the bacterial microbiota clustered according to each GIT segment. Bacterial diversity and richness as well as volatile fatty acid concentration was lowest in the SI. Taxonomic grouping of bacterial operational taxonomic units (OTUs) revealed that Lachnospiraceae (24.61 ± SD 6.58%) and Ruminococcaceae (20.87 ± SD 4.22%) were the two most abundant taxa across the GIT. For the fungi, the family Neocallismastigaceae dominated in all GIT segments, with the genus Orpinomyces being the most abundant. Twenty-eight bacterial and six fungal OTUs were shared across all GIT segments in at least 50% of the steers. We also evaluated if the fecal-associated microbiota of steers showing negative and positive residual feed intake (n-RFI and p-RFI, respectively) was associated with their feed efficiency phenotype. Diversity indices for both bacterial and fungal fecal microbiota did not vary between the two feed efficiency groups. Differences in the fecal bacterial composition between high and low feed efficiency steers were primarily assigned to OTUs belonging to the families Lachnospiraceae and Ruminococcaceae and to the genus Prevotella . The fungal OTUs shared across the GIT did not vary between feed efficiency groups, but 7 and 3 OTUs were found only in steers with positive and negative RFI, respectively. These results provide further insights into the composition of the Nelore GIT microbiota, which could have implications for improving animal health and productivity. Our findings also reveal differences in fecal-associated bacterial OTUs between steers from different feed efficiency groups, suggesting that fecal sampling may represent a non-invasive strategy to link the bovine microbiota with productivity phenotypes.