BackgroundThe objective of this study was to evaluate the accuracy of genomic predictions for rib eye area (REA), backfat thickness (BFT), and hot carcass weight (HCW) in Nellore beef cattle from Brazilian commercial herds using different prediction models.MethodsPhenotypic data from 1756 Nellore steers from ten commercial herds in Brazil were used. Animals were offspring of 294 sires and 1546 dams, reared on pasture, feedlot finished, and slaughtered at approximately 2 years of age. All animals were genotyped using a 777k Illumina Bovine HD SNP chip. Accuracy of genomic predictions of breeding values was evaluated by using a 5-fold cross-validation scheme and considering three models: Bayesian ridge regression (BRR), Bayes C (BC) and Bayesian Lasso (BL), and two types of response variables: traditional estimated breeding value (EBV), and phenotype adjusted for fixed effects (Y*).ResultsThe prediction accuracies achieved with the BRR model were equal to 0.25 (BFT), 0.33 (HCW) and 0.36 (REA) when EBV was used as response variable, and 0.21 (BFT), 0.37 (HCW) and 0.46 (REA) when using Y*. Results obtained with the BC and BL models were similar. Accuracies increased for traits with a higher heritability, and using Y* instead of EBV as response variable resulted in higher accuracy when heritability was higher.ConclusionsOur results indicate that the accuracy of genomic prediction of carcass traits in Nellore cattle is moderate to high. Prediction of genomic breeding values from adjusted phenotypes Y* was more accurate than from EBV, especially for highly heritable traits. The three models considered (BRR, BC and BL) led to similar predictive abilities and, thus, either one could be used to implement genomic prediction for carcass traits in Nellore cattle.

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.

Age at first calving (AFC) plays an important role in the economic efficiency of beef cattle production. This trait can be affected by a combination of genetic and environmental factors, leading to physiological changes in response to heifers' adaptation to a wide range of environments. Genomewide association studies through the reaction norm model were carried out to identify genomic regions associated with AFC in Nellore heifers, raised under different environmental conditions (EC). The SNP effects for AFC were estimated in three EC levels (Low, Medium, and High, corresponding to average contemporary group effects on yearling body weight equal to 159.40, 228.6 and 297.6 kg, respectively), which unraveled shared and unique genomic regions for AFC in Low, Medium, and High EC levels, that varied according to the genetic correlation between AFC in different EC levels. The significant genomic regions harbored key genes that might play an important biological role in controlling hormone signaling and metabolism. Shared genomic regions among EC levels were identified on BTA 2 and 14, harboring candidate genes associated with energy metabolism (IGFBP2, IGFBP5, SHOX, SMARCAL1, LYN, RPS20, MOS, PLAG1, CHCD7, and SDR16C6). Gene set enrichment analyses identified important biological functions related to growth, hormone levels affecting female fertility, physiological processes involved in female pregnancy, gamete generation, ovulation cycle, and age at puberty. the genomic regions highlighted differences in the physiological processes linked to AFC in different EC levels and metabolic processes that support complex interactions between the gonadotropic axes and sexual precocity in nellore heifers. open Scientific RepoRtS | (2020) 10:6481 | https://doi.org/10.1038/s41598-020-63516-4 www.nature.com/scientificreports www.nature.com/scientificreports/ pathway and gene network analyses from these results can be performed to uncover mechanisms whereby the environment can potentially affect the sexual precocity in cattle. Such knowledge regarding genomic regions and biological pathways involved with GxE interactions in Nellore heifers' sexual precocity is important to identify molecular mechanisms underlying the phenotypic responses to different environments. Hence, this study was carried out to evaluate the changes in the SNP effect estimates, as well as the biological processes associated with age at first calving in three environmental conditions, combining RN models and GWAS. Materials and Methodsethics approval. The animal procedures in this study were approved by Animal Care of the São Paulo State University (UNESP), School of Agricultural and Veterinary Science Ethical Committee (protocol number 18.340/16). All the data sampling was performed in accordance with CEUA/ FCAV-UNESP guidelines and regulations.phenotypic and genotypic data. Age at first calving (AFC) records were obtained from 185,356Nellore heifers belonging to three commercial breeding programs (DeltaGen, Paint -CRV Lagoa and Cia de Melhoramento), which are p...

Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes ( and ) involved in the cell cycle biological process which affects many aspects of animal growth and development. The and genes, both from AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (, , , , , and ) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the . There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.

The objective of this study was to compare SNP-BLUP, BayesCπ, BayesC and Bayesian Lasso methodologies to predict the direct genomic value for saturated, monounsaturated, and polyunsaturated fatty acid profile, omega 3 and 6 in the Longissimus thoracis muscle of Nellore cattle finished in feedlot. A total of 963 Nellore bulls with phenotype for fatty acid profiles, were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. The predictive ability was evaluated using cross validation. To compare the methodologies, the correlation between DGV and pseudo-phenotypes was calculated. The accuracy varied from -0.40 to 0.62. Our results indicate that none of the methods excelled in terms of accuracy, however, the SNP-BLUP method allows obtaining less biased genomic evaluations, thereby; this method is more feasible when taking into account the analyses' operating cost. Despite the lowest bias observed for EBV, the adjusted phenotype is the preferred pseudophenotype considering the genomic prediction accuracies regarding the context of the present study.

a b s t r a c tThe objective of this study was to compare gene transcription profiles in Longissimus dorsi muscle of the following four hair sheep genetic groups, Morada Nova (MO), Brazilian Somali (SO), Santa Inês (SI) and ½Dorper  ½Morada Nova (F1). These groups all display different postnatal muscle growth. The transcriptomes of the skeletal muscle of the lambs (at 200 days of age) were profiled by using oligonucleotide microarrays and reverse transcriptionquantitative real-time PCR (RT-qPCR). The microarray experiment identified 262 transcripts that were differentially expressed when transcription levels were compared between the different breeds. A total of 23 transcripts among which those involved in skeletal muscle development (MyoD1 and IGFBP4), lipogenesis and adipogenesis (C/EBPd, PPARg and PGDS) were differentially expressed in at least in one comparison. Clustering analysis showed that there is greater similarity in gene expression between the MO and SI breeds and between F1 and SO genetic groups. The SO breed has the most distinct expression pattern. The RT-qPCR results confirmed the findings from the microarray study. A positive correlation was observed between the expression of MyoD1 and the cold carcass yield. The negative correlations between the weight and yield of cold carcass with the expression of C/EBPd mean that the selection for adipogenesis could lead to a lower carcass weight. The GLUT3 and PYGL gene transcripts were negatively correlated with fat thickness, but ATP5G1 was positively correlated with this trait. Interestingly, many genes negatively correlated with PUFA were positively correlated with cold carcass yield. In conclusion, the present work demonstrated that there are breed-specific expression patterns in Brazilian hair sheep genetic groups. The differences in gene expression among genetic groups were consistent with their phenotypic differences. The positive correlation of the MyoD1 expression with the cold carcass yield suggests that this gene is important for tissue growth in sheep. The positive correlation of the C/EBPd expression with PUFA provides an opportunity to select for lipid deposition in meat animals.

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Data from a multibreed commercial flock located at Mid-West of Brazil, supported by Programa de Melhoramento Genético de Caprinos e Ovinos de Corte (GENECOC), were used to estimate genetic parameters of traits related to ewe productivity by Average Information Restricted Maximum Likelihood method applied to an animal model. The analyzed traits were litter weight at birth (LWB) and at weaning (LWW), ewe weight at weaning (EW) and ewe production efficiency, estimated by WEE = LWW / EW 0.75 . The heritabilities were 0.26± 0.05, 0.32± 0.06, 0.37± 0.03 and 0.10± 0.02 for LWB, LWW, EW and WEE, respectively. Significant effects for direct heterosis were observed for LWW and EW. Recombination losses were important for EW and WEE. Genetic correlations of LWB with LWW, EW and WEE were 0.68, 0.37 and 0.15, respectively; of LWW with EW and WEE were 0.30 and 0.34, respectively; and between EW and WEE was −0.25. Even though it is a low heritability trait, WEE can be indicated as a selection criteria for improving the ewe productivity without increasing the mature weight of animals due to its genetic correlations with LWW and other traits.