RESUMO
This study aimed to assess the impact of differential weighting in genomic regions harboring candidate causal loci on the genomic prediction accuracy and dispersion for growth and carcass-related traits in Nelore cattle. The dataset contained 168 793 phenotypic records for adjusted weight at 450 days of age (W450), 83 624 for rib eye area (REA), 24 480 for marbling (MAR) and 82 981 for subcutaneous backfat thickness (BFT) and rump fat thickness (RFT). The pedigree harbored information from 244 254 animals born between 1977 and 2016, including 6283 sires and 50 742 dams. Animals (n = 7769) were genotyped with the low-density panel (Clarifide® Nelore 3.0), and the genotypes were imputed to a panel containing 735 044 markers. A linear animal model was applied to estimate the genetic parameters and to perform the weighted single-step genome-wide association study (WssGWAS). A total of seven models for genomic prediction were evaluated combining the SNP weights obtained in the iterations of the WssGWAS and the candidate QTL. The heritability estimated for W450 (0.35) was moderate, and for carcass-related traits, the estimates were moderate for REA (0.27), MAR (0.28) and RFT (0.28), and low for BFT (0.18). The prediction accuracy for W450 incorporating reported QTL previously described in the literature along with different SNPs weights was like those described for the default ssGBLUP model. The use of the ssGWAS to weight the SNP effects displayed limited advantages for the REA prediction accuracy. Comparing the ssGBLUP with the BLUP model, a meaningful improvement in the prediction accuracy from 0.09 to 0.63 (700%) was observed for MAR. The highest prediction accuracy was obtained for BFT and RFT in all evaluated models. The application of information obtained from the WssGWAS is an alternative to reduce the genomic prediction dispersion for growth and carcass-related traits, except for MAR. Furthermore, the results obtained herein pointed out that is possible to improve the prediction accuracy and reduce the genomic prediction dispersion for growth and carcass-related traits in young animals.
Assuntos
Estudo de Associação Genômica Ampla , Modelos Genéticos , Bovinos , Animais , Genoma , Genômica/métodos , Fenótipo , Genótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
The aim of this work was to evaluate the impact of applying genomic information in pedigree uncertainty situations on genetic evaluations for growth- and cow productivity-related traits in Nelore commercial herds. Records for accumulated cow productivity (ACP) and adjusted weight at 450 days of age (W450) were used, as well as genotypes of registered and commercial herd animals, genotyped with the Clarifide Nelore 3.1 panel (~29,000 SNPs). The genetic values for commercial and registered populations were estimated using different approaches that included (ssGBLUP) or did not include genomic information (BLUP), with different pedigree structures. Different scenarios were tested, varying the proportion of young animals with unknown sires (0, 25, 50, 75, and 100%), and unknown maternal grandsires (0, 25, 50, 75, and 100%). The prediction accuracies and abilities were calculated. The estimated breeding value accuracies decreased as the proportion of unknown sires and maternal grandsires increased. The genomic estimated breeding value accuracy using the ssGBLUP was higher in scenarios with a lower proportion of known pedigree when compared to the BLUP methodology. The results obtained with the ssGBLUP showed that it is possible to obtain reliable direct and indirect predictions for young animals from commercial herds without pedigree structure.
Assuntos
Genoma , Modelos Genéticos , Feminino , Bovinos , Animais , Linhagem , Genômica/métodos , Genótipo , FenótipoRESUMO
The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n = 4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5 ± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n = 8) animal model. The heritability estimates for RFI (0.23 ± 0.02), DMI (0.31 ± 0.02), MF (0.65 ± 0.02), AMD (0.29 ± 0.02), ACM (0.24 ± 0.02), MD (0.41 ± 0.02), MC (0.48 ± 0.02), and CR (0.42 ± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73 ± 0.03), CR and AMD (-0.68 ± 0.04), and RFI and DMI (0.81 ± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77 ± 0.02), and DMI and RFI (0.77 ± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.
Assuntos
Ingestão de Alimentos , Comportamento Alimentar , Bovinos/genética , Animais , Comportamento Alimentar/fisiologia , Ingestão de Alimentos/genética , Fenótipo , Brasil , Ração AnimalRESUMO
This study aimed to investigate the prediction ability for growth and maternal traits using different low-density customized SNP arrays selected by informativeness and distribution of markers across the genome employing single-step genomic BLUP (ssGBLUP). Phenotypic records for adjusted weight at 210 and 450 days of age were utilized. A total of 945 animals were genotyped with high-density chip, and 267 individuals born after 2008 were selected as validation population. We evaluated 11 scenarios using five customized density arrays (40 k, 20 k, 10 k, 5 k and 2 k) and the HD array was used as desirable scenario. The GEBV predictions and BIF (Beef Improvement Federation) accuracy were obtained with BLUPF90 family programs. Linear regression was used to evaluate the prediction ability, inflation, and bias of GEBV of each customized array. An overestimation of partial GEBVs in contrast with complete GEBVs and increase of BIF accuracy with the density arrays diminished were observed. For all traits, the prediction ability was higher as the array density increased and it was similar with customized arrays higher than 10 k SNPs. Level of inflation was lower as the density array increased of and was higher for MW210 effect. The bias was susceptible to overestimation of GEBVs when the density customized arrays decreased. These results revealed that the BIF accuracy is sensible to overestimation using low-density customized arrays while the prediction ability with least 10,000 informative SNPs obtained from the Illumina BovineHD BeadChip shows accurate and less biased predictions. Low-density customized arrays under ssGBLUP method could be feasible and cost-effective in genomic selection.
Assuntos
Genoma , Modelos Genéticos , Animais , Bovinos/genética , Genômica/métodos , Genótipo , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
The aim was to evaluate the association between growth, carcass and visual scores traits with precocious calving in Nellore cattle. Birth weight (BW), weight at 120, 210, 365 and 450 days of age, pre and post-weaning average daily gain, rib eye area, backfat thickness (BF), rump fat thickness and visual scores obtained at 18 months were used for the analysis. Records from 700 females born between 2009 and 2015, exposed to mating starting at 11 months of age were analyzed. Discriminant analyzes were performed with the software Statistica. BW and BF showed the highest (P>0.01) discrimination value for early heifer pregnancy (EP). Extreme intrauterine growth retardation can result in slower growth, which reflects in the worst reproductive performance, confirmed by the variation in BW between precocious and conventional heifers. The results also demonstrate that the level of body fat affects begin of puberty. Bone structure, musculature, depth, tail insertion and rump scores presented the highest discrimination value for EP. These traits can be used as selection tools to improve sexual precocity in female Nellore cattle. The results obtained in this study would support farmers to guide the heifer management and decisions in order to enhance the EP.
Assuntos
Tecido Adiposo , Reprodução , Animais , Bovinos , Feminino , Fenótipo , Gravidez , DesmameRESUMO
The aim was to conduct a weighted single-step genome-wide association study to detect genomic regions and putative candidate genes related to residual feed intake, dry matter intake, feed efficiency (FE), feed conversion ratio, residual body weight gain, residual intake and weight gain in Nellore cattle. Several protein-coding genes were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for these traits. These genes were associated with insulin, leptin, glucose, protein and lipid metabolisms; energy balance; heat and oxidative stress; bile secretion; satiety; feed behaviour; salivation; digestion; and nutrient absorption. Enrichment analysis revealed functional pathways (p-value < .05) such as neuropeptide signalling (GO:0007218), negative regulation of canonical Wingless/Int-1 (Wnt) signalling (GO:0090090), bitter taste receptor activity (GO:0033038), neuropeptide hormone activity (GO:0005184), bile secretion (bta04976), taste transduction (bta0742) and glucagon signalling pathway (bta04922). The identification of these genes, pathways and their respective functions should contribute to a better understanding of the genetic and physiological mechanisms regulating Nellore FE-related traits.
Assuntos
Ração Animal , Estudo de Associação Genômica Ampla , Animais , Bovinos , Ingestão de Alimentos , Genoma , Estudo de Associação Genômica Ampla/veterinária , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
The goal of this study was to compare the predictive performance of artificial neural networks (ANNs) with Bayesian ridge regression, Bayesian Lasso, Bayes A, Bayes B and Bayes Cπ in estimating genomic breeding values for meat tenderness in Nellore cattle. The animals were genotyped with the Illumina Bovine HD Bead Chip (HD, 777K from 90 samples) and the GeneSeek Genomic Profiler (GGP Indicus HD, 77K from 485 samples). The quality control for the genotypes was applied on each Chip and comprised removal of SNPs located on non-autosomal chromosomes, with minor allele frequency <5%, deviation from HWE (p < 10-6 ), and with linkage disequilibrium >0.8. The FImpute program was used for genotype imputation. Pedigree-based analyses indicated that meat tenderness is moderately heritable (0.35), indicating that it can be improved by direct selection. Prediction accuracies were very similar across the Bayesian regression models, ranging from 0.20 (Bayes A) to 0.22 (Bayes B) and 0.14 (Bayes Cπ) to 0.19 (Bayes A) for the additive and dominance effects, respectively. ANN achieved the highest accuracy (0.33) of genomic prediction of genetic merit. Even though deep neural networks are recognized to deliver more accurate predictions, in our study ANN with one single hidden layer, 105 neurons and rectified linear unit (ReLU) activation function was sufficient to increase the prediction of genetic merit for meat tenderness. These results indicate that an ANN with relatively simple architecture can provide superior genomic predictions for meat tenderness in Nellore cattle.
Assuntos
Cruzamento/estatística & dados numéricos , Genômica/estatística & dados numéricos , Redes Neurais de Computação , Característica Quantitativa Herdável , Animais , Teorema de Bayes , Bovinos , Cromossomos , Frequência do Gene , Genoma/genética , Genótipo , Desequilíbrio de Ligação/genética , Carne/análise , Carne/estatística & dados numéricos , Linhagem , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Selection for bulls that would reach puberty early reduces the generation interval and increases fertility and herd productivity. Despite its economic importance, there are few QTL associated with age at puberty described in the literature. In this study, a weighted single-step genome-wide association study was performed to detect genomic regions and putative candidate genes related to age at puberty in young Nelore bulls. Several protein-coding genes related to spermatogenesis functions were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for age at puberty in Nelore bulls, such as ADAM11, BRCA1, CSNK2A, CREBBP, MEIOC, NDRG2, NECTIN3, PARP2, PARP9, PRSS21, RAD51C, RNASE4, SLX4, SPA17, TEX14, TIMP2 and TRIP13 gene. Enrichment analysis by DAVID also revealed several GO terms related to spermatogenesis such as DNA replication (GO:0006260), male meiosis I (GO:0007141), double-strand break repair (GO:0006302), base excision repair (GO:0006284), apoptotic process (GO:0006915), cell-cell adhesion (GO: 0098609) and focal adhesion (GO:0005925). The heritability for age at puberty shows that this trait can be improved based on traditional EBV selection. Adding genomic information to the system helps to elucidate genes and molecular mechanisms controlling the sexual precocity and could help to predict sexual precocity in Nelore bulls with greater accuracy at younger age, which would speed up the breeding programme for this breed.
Assuntos
Bovinos/genética , Reprodução/genética , Maturidade Sexual/genética , Animais , Cruzamento , Bovinos/fisiologia , Mapeamento Cromossômico/veterinária , Variação Genética , Estudo de Associação Genômica Ampla/veterinária , Genômica , Genótipo , Masculino , Herança Multifatorial , Fenótipo , Polimorfismo de Nucleotídeo Único , Locos de Características QuantitativasRESUMO
The aim of this study was to estimate genetic parameters and identify genomic regions associated with carcass traits obtained by ultrasound and visual scores in Nellore cattle. Data from ~66,000 animals from the National Association of Breeders and Researchers (ANCP) were used. The variance components for backfat thickness, rump fat thickness and Longissimus muscle area (LMA) were estimated considering a linear model whereas a threshold model for body structure (BS), finishing precocity (FP) and musculature (MS) traits. The SNP solutions were estimated using the ssGBLUP approach by considering windows of 10 consecutive SNPs. Regions that accounted for more than 1.0% of the additive genetic variance were used. Genes identified within the significant windows, such as FOXA3, AP2S1, FKRP, NPASI and ATP6V1G1, were found to be related with MS, while OMA1 and FFGY with BS and FP traits. The PLTP, TNNC2 and GPAT2 genes were found in the regions associated with LMA, as well as TKT, FNDC5 and CHRND can strongly be related with fat deposition. Gene enrichment analysis revealed processes that might be directly influenced the organism growth and development. These results should help to better understand the genetic and physiological mechanisms regulating growth and body composition, muscle tissue development and subcutaneous fat expression, and this information might be useful for future genomic studies in Nellore cattle.
Assuntos
Composição Corporal/genética , Cruzamento , Genoma/genética , Genômica , Animais , Bovinos , Músculos Paraespinais/crescimento & desenvolvimento , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Gordura Subcutânea/crescimento & desenvolvimentoRESUMO
The aim of this study was to estimate heritability and predict breeding values for longevity among cows in herds of Nellore breed, considering the trait cow's age at last calving (ALC), by means of survival analysis methodology. The records of 11,791 animals from 22 farms were used. The variable ALC has been used by a criterion that made it possible to include cows not only at their first calving but also at their ninth calving. The criterion used was the difference between the date of each cow's last calving and the date of the last calving on each farm. If this difference was greater than 36 months, the cow was considered to have failed and uncensored. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The survival model used for the analyses was the proportional hazards model, and the base risk was given by a Weibull distribution. The heritability estimate obtained was equal to 0.25. It was found that the ALC variable had the capacity to respond to selection for the purpose of increasing the longevity of the cows in the herds.