RESUMO
In beef cattle, the selection for higher weights at young ages has been questioned with the argument that this criterion may increase the adult weight of cows, resulting in higher costs. Therefore, selection criteria should be employed to increase weights at young ages with minimal impact on the adult weight of cows. Additionally, the relationship between measures of cow production efficiency and other well-established selection criteria in breeding programs remains poorly understood. The objective of this study was to longitudinally evaluate the relationship between the weaning index (WIndex) as a measure of efficiency and growth traits of the cows. Possible changes over time in WIndex due to selection applied for yearling weight (YW) were also investigated. The WIndex was proposed to maximize genetic response in the weaning weight of the calf while maintaining genetic gain in BW of the cow at zero. A random regression model was adopted to estimate correlations between WIndex, BW, hip height (HH), and body condition score (BCS) using records of Nelore cows from three lines. Genetic trends were calculated for the control line (NeC) and lines selected for greater YW (NeS and NeT). The age of 3 years was the most critical for the weaning efficiency of the cows. At this stage, young cows are still growing and wean lighter calves than their adult counterparts. The genetic correlation estimates between WIndex and BW (-0.58 to 0.04), HH (-0.05 to -0.34), and BCS (-0.51 to -0.17) were close to zero or negative. BW and HH were strongly correlated genetically across all ages (0.73-0.76). In general, HH exhibited a weak and negative genetic relationship with BCS. The genetic correlation between BW and BCS was stronger for advanced ages (0.45-0.68). In lines selected for YW, important increases in WIndex were observed. However, NeS has been selected since the 1980s until the present for YW, and thus, it showed a more pronounced trend of increasing BW and, consequently, a more modest trend of increasing WIndex compared to NeT. In contrast, WIndex exhibited a trend close to zero for NeC. In this context, monitoring HH and BCS can be useful to avoid losses in the weaning efficiency of cows. Furthermore, we suggest that one way to mitigate efficiency losses in calf production could involve stabilizing the BW of cows and increasing the weaning weight of calves using the WIndex.
Assuntos
Desmame , Feminino , Bovinos/genética , Animais , Peso Corporal/genética , FenótipoRESUMO
This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5-fold cross-validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome-enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait-dependent, thus, a fine-tuning for this hyper-parameter in the training phase is crucial.
Assuntos
Bovinos/genética , Aprendizado de Máquina , Modelos Genéticos , Reprodução/genética , Animais , Brasil , Feminino , Genômica , Fenótipo , Polimorfismo de Nucleotídeo Único , GravidezRESUMO
Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer's early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal's sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme-dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme-low EC (-3.0 and -1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28-0.56 for SC and 0.26-0.49 for HP, using RNM_H, and 0.26-0.52 for SC and 0.22-0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (-3.0) and favorable (3.0) EC levels were 0.30 for HP and -0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals' genetic merit and re-ranking of animals on different environmental conditions. SNP marker-environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.
Assuntos
Bovinos/fisiologia , Interação Gene-Ambiente , Genoma , Comportamento Sexual Animal , Maturidade Sexual/genética , Animais , Brasil , Bovinos/genética , Feminino , Genômica , Masculino , Modelos GenéticosRESUMO
When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.
Assuntos
Bovinos/genética , Interação Gene-Ambiente , Variação Genética , Genômica , Modelos Genéticos , Animais , Peso Corporal/genética , Cruzamento , Bovinos/crescimento & desenvolvimento , Feminino , Genótipo , Masculino , Linhagem , FenótipoRESUMO
The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth.
Assuntos
Cruzamento , Bovinos , Estudo de Associação Genômica Ampla , Animais , Peso Corporal , Bovinos/genética , Bovinos/crescimento & desenvolvimento , Feminino , Fenótipo , Polimorfismo de Nucleotídeo Único , Desmame , Aumento de PesoRESUMO
We performed a genome-wide association study to detect markers associated with growth traits in Atlantic salmon. The analyzed traits included body weight at tagging (BWT) and body weight at 25 months (BW25M). Genotypes of 4662 animals were imputed from the 50K SNP chip to the 200K SNP chip using fimpute software. The markers were simultaneously modeled using Bayes C to identify genomic regions associated with the traits. We identified windows explaining a maximum of 3.71% and 3.61% of the genetic variance for BWT and BW25M respectively. We found potential candidate genes located within the top ten 1-Mb windows for BWT and BW25M. For instance, the vitronectin (VTN) gene, which has been previously reported to be associated with cell growth, was found within one of the top ten 1-Mb windows for BWT. In addition, the WNT1-inducible-signaling pathway protein 3, melanocortin 2 receptor accessory protein 2, myosin light chain kinase, transforming growth factor beta receptor type 3 and myosin light chain 1 genes, which have been reported to be associated with skeletal growth in humans, growth stimulation during the larval stage in zebrafish, body weight in pigs, feed conversion in chickens and growth rate of sheep skeletal muscle respectively, were found within some of the top ten 1-Mb windows for BW25M. These results indicate that growth traits are most likely controlled by many variants with relatively small effects in Atlantic salmon. The genomic regions associated with the traits studied here may provide further insight into the functional regions underlying growth traits in this species.
Assuntos
Peso Corporal/genética , Estudos de Associação Genética , Salmo salar/genética , Animais , Teorema de Bayes , Variação Genética , Genótipo , FenótipoRESUMO
The aim of the present study was to evaluate the prediction ability of models that cope with longevity phenotypic expression as uncensored and censored in Nellore cattle. Longevity was defined as the difference between the dates of last weaned calf and cow birth. There were information of 77 353 females, being 61 097 cows with uncensored phenotypic information and 16 256 cows with censored records. These data were analyzed considering three different models: (1) Gaussian linear model (LM), in which only uncensored records were considered; and two models that consider both uncensored and censored records: (2) Censored Gaussian linear model (CLM); and (3) Weibull frailty hazard model (WM). For the model prediction ability comparisons, the data set was randomly divided into training and validation sets, containing 80% and 20% of the records, respectively. There were considered 10 repetitions applying the following restrictions: (a) at least three animals per contemporary group in the training set; and (b) sires with more than 10 progenies with uncensored records (352 sires) should have daughters in the training and validation sets. The variance components estimated using the whole data set in each model were used as true values in the prediction of breeding values of the animals in the training set. The WM model showed the best prediction ability, providing the lowest χ 2 average and the highest number of sets in which a model had the smallest value of χ 2 statistics. The CLM and LM models showed prediction abilities 2.6% and 3.7% less efficient than WM, respectively. In addition, the accuracies of sire breeding values for LM and CLM were lower than those obtained for WM. The percentages of bulls in common, considering only 10% of sires with the highest breeding values, were around 75% and 54%, respectively, between LM-CLM and LM-WM models, considering all sires, and 75% between LM-CLM and LM-WM, when only sires with more than 10 progenies with uncensored records were taken into account. These results are indicative of reranking of animals in terms of genetic merit between LM, CLM and WM. The model in which censored records of longevity were excluded from the analysis showed the lowest prediction ability. The WM provides the best predictive performance, therefore this model would be recommended to perform genetic evaluation of longevity in this population.
Assuntos
Bovinos/fisiologia , Longevidade/genética , Longevidade/fisiologia , Animais , Cruzamento , Feminino , Modelos Lineares , Modelos Biológicos , Parto , Gravidez , Modelos de Riscos Proporcionais , Reprodução , DesmameRESUMO
Genomic selection may accelerate genetic progress in breeding programs of indicine breeds when compared with traditional selection methods. We present results of genomic predictions in Gyr (Bos indicus) dairy cattle of Brazil for milk yield (MY), fat yield (FY), protein yield (PY), and age at first calving using information from bulls and cows. Four different single nucleotide polymorphism (SNP) chips were studied. Additionally, the effect of the use of imputed data on genomic prediction accuracy was studied. A total of 474 bulls and 1,688 cows were genotyped with the Illumina BovineHD (HD; San Diego, CA) and BovineSNP50 (50K) chip, respectively. Genotypes of cows were imputed to HD using FImpute v2.2. After quality check of data, 496,606 markers remained. The HD markers present on the GeneSeek SGGP-20Ki (15,727; Lincoln, NE), 50K (22,152), and GeneSeek GGP-75Ki (65,018) were subset and used to assess the effect of lower SNP density on accuracy of prediction. Deregressed breeding values were used as pseudophenotypes for model training. Data were split into reference and validation to mimic a forward prediction scheme. The reference population consisted of animals whose birth year was ≤2004 and consisted of either only bulls (TR1) or a combination of bulls and dams (TR2), whereas the validation set consisted of younger bulls (born after 2004). Genomic BLUP was used to estimate genomic breeding values (GEBV) and reliability of GEBV (R2PEV) was based on the prediction error variance approach. Reliability of GEBV ranged from â¼0.46 (FY and PY) to 0.56 (MY) with TR1 and from 0.51 (PY) to 0.65 (MY) with TR2. When averaged across all traits, R2PEV were substantially higher (R2PEV of TR1 = 0.50 and TR2 = 0.57) compared with reliabilities of parent averages (0.35) computed from pedigree data and based on diagonals of the coefficient matrix (prediction error variance approach). Reliability was similar for all the 4 marker panels using either TR1 or TR2, except that imputed HD cow data set led to an inflation of reliability. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. A reduced panel of â¼15K markers resulted in reliabilities similar to using HD markers. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information.
Assuntos
Genômica/normas , Técnicas de Genotipagem/veterinária , Glicolipídeos/metabolismo , Glicoproteínas/metabolismo , Leite/metabolismo , Polimorfismo de Nucleotídeo Único , Seleção Artificial/genética , Fatores Etários , Animais , Brasil , Bovinos , Indústria de Laticínios , Feminino , Marcadores Genéticos , Genótipo , Técnicas de Genotipagem/métodos , Lactação , Gotículas Lipídicas , Masculino , Análise de Sequência com Séries de Oligonucleotídeos/veterinária , Gravidez , Reprodutibilidade dos TestesRESUMO
Animal feeding is the most important economic component of beef production systems. Selection for feed efficiency has not been effective mainly due to difficult and high costs to obtain the phenotypes. The application of genomic selection using SNP can decrease the cost of animal evaluation as well as the generation interval. The objective of this study was to compare methods for genomic evaluation of feed efficiency traits using different cross-validation layouts in an experimental beef cattle population genotyped for a high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA). After quality control, a total of 437,197 SNP genotypes were available for 761 Nelore animals from the Institute of Animal Science, Sertãozinho, São Paulo, Brazil. The studied traits were residual feed intake, feed conversion ratio, ADG, and DMI. Methods of analysis were traditional BLUP, single-step genomic BLUP (ssGBLUP), genomic BLUP (GBLUP), and a Bayesian regression method (BayesCπ). Direct genomic values (DGV) from the last 2 methods were compared directly or in an index that combines DGV with parent average. Three cross-validation approaches were used to validate the models: 1) YOUNG, in which the partition into training and testing sets was based on year of birth and testing animals were born after 2010; 2) UNREL, in which the data set was split into 3 less related subsets and the validation was done in each subset a time; and 3) RANDOM, in which the data set was randomly divided into 4 subsets (considering the contemporary groups) and the validation was done in each subset at a time. On average, the RANDOM design provided the most accurate predictions. Average accuracies ranged from 0.10 to 0.58 using BLUP, from 0.09 to 0.48 using GBLUP, from 0.06 to 0.49 using BayesCπ, and from 0.22 to 0.49 using ssGBLUP. The most accurate and consistent predictions were obtained using ssGBLUP for all analyzed traits. The ssGBLUP seems to be more suitable to obtain genomic predictions for feed efficiency traits on an experimental population of genotyped animals.
Assuntos
Bovinos/genética , Genômica/métodos , Modelos Genéticos , Polimorfismo de Nucleotídeo Único , Ração Animal , Animais , Teorema de Bayes , Brasil , Cruzamento , Bovinos/metabolismo , Ingestão de Alimentos/genética , Ingestão de Alimentos/fisiologia , Genoma , Genótipo , Masculino , SoftwareRESUMO
The aim of this study was to evaluate the effect of genotype × environment interaction (G×E) on age at first calving (AFC), scrotal circumference (SC), and yearling weight (YW) and to estimate genetic correlations between these traits in Nellore cattle using reaction norms in multitrait random regression models. In this study, 28,871, 41,386, and 89,152 records of Nellore cattle for AFC, SC, and YW, respectively, were used. The data were obtained from farms located in the north, northeast, midwest, and southeast regions of Brazil that participate in the DeltaGen Breeding Program. Environmental levels were defined as a function of contemporary groups, that is, animals born in the same herd and year, from the same management group (from birth to yearling), and of the same sex. Postweaning weight gain was used as a criterion to evaluate the environmental conditions for all traits. For reaction norm analyses, residual variances were modeled with homogeneous and heterogeneous classes. The model for SC and YW included the fixed effects of contemporary group and age of the animal as a covariate as well as random direct additive genetic and residual effects. The same model, excluding the covariate age of the animal, was used for AFC. The heritability estimates were low to high for AFC (0.09 to 0.50), high for SC (0.51 to 0.67), and moderate to high for YW (0.33 to 0.71). The genetic correlations (within each trait) along the environmental levels varied from -0.27 to 1.0 for AFC, from 0.73 to 1.0 for SC, and from 0.26 to 1.0 for YW. The genetic correlations between different traits in different environments varied from -0.14 to -0.60 between AFC and SC, from -0.05 to -0.32 between AFC and YW, and from -0.05 to 0.72 between YW and SC. The genetic correlations have had different magnitudes for AFC, SC, and YW, which could indicate the presence of G×E. The present results should support researchers and farmers in defining selection criteria to improve growth traits and sexual precocity. Our results suggest that animals for breeding have to be selected in the same environment and management conditions as their progeny will be reared.
Assuntos
Peso Corporal/fisiologia , Cruzamento/métodos , Bovinos/genética , Meio Ambiente , Genótipo , Modelos Genéticos , Escroto/crescimento & desenvolvimento , Fatores Etários , Animais , Peso Corporal/genética , Brasil , Cruzamento/normas , Bovinos/crescimento & desenvolvimento , Feminino , Masculino , Análise de RegressãoRESUMO
Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.
Assuntos
Constituição Corporal/fisiologia , Cruzamento/métodos , Bovinos/fisiologia , Carne/normas , Modelos Biológicos , Fenótipo , Seleção Genética , Animais , Teorema de Bayes , Constituição Corporal/genética , Peso Corporal/genética , Brasil , Bovinos/genética , Feminino , Reprodução/genéticaRESUMO
In order to achieve improvements in production efficiency in livestock, herds of high sexual precocity and good fertility are needed. These traits increase the availability of animals in herd, either for sale or selection, allowing both greater selective intensity and greater genetic progress. This study aimed at estimating genetic parameters for reproductive traits measured directly in females in order to verify whether they could be used as selection criteria for genetic improvement in Nellore cows, as well as estimating the genetic relationship among these traits and scrotal circumference (SC), the traditional selection criterion for sexual precocity in cattle. In addition to SC, stayability (STAY), number of calvings at 53 months (NC53) and heifers rebreeding (HR) were studied. The (co)variances and genetic parameters were estimated using Bayesian inference. STAY, NC53 and HR were analyzed assuming a threshold model, whereas SC was analyzed with a linear model. Heritability estimated for NC53 was 0.22, and this trait was strongly and positively correlated with STAY, meaning selection for NC53 would improve productive longevity of Nellore cows. Correlations estimated between HR and STAY (≈0.97) and between HR and NC53 (≈0.99) allow an improvement on HR rates if selection was applied to traits related to longevity. Genetic correlations among SC and female reproductive traits were positive but weak, suggesting the need to use reproductive traits directly measured in females in order to obtain greater improvements in sexual precocity and longevity.
Assuntos
Bovinos/genética , Bovinos/fisiologia , Reprodução/genética , Animais , Teorema de Bayes , Feminino , Fertilidade/genética , Modelos Lineares , Longevidade , Masculino , Modelos Genéticos , Fenótipo , Maturidade SexualRESUMO
Temperament is an important trait for the management and welfare of animals and for reducing accidents involving people who work with cattle. The present study aimed to estimate the genetic parameters related to the temperament score (T) and weaning weight (WW) of Nellore cattle, reared in a beef cattle breeding program in Brazil. Data were analyzed using two different two-trait statistical models, both considering WW and T: (1) a linear-linear model in which variance components (VCs) were estimated using restricted maximum likelihood; and (2) a linear-threshold model in which VCs were estimated via Bayesian inference. WW was included in the analyses of T to minimize any possible effects of sequential selection and to allow for estimation of the genetic correlation between these two traits. The heritability estimates for T were 0.21 ± 0.003 (model 1) and 0.26 (model 2, with a 95% credibility interval (95% CI) of 0.21 to 0.32). The estimated genetic correlations between WW and T were of a moderate magnitude (-0.33 ± 0.01 (model 1) and -0.34 (95% CI: -0.40, -0.28, model 2). The genetic correlations between the estimated breeding values (EBVs) obtained for the animals based on the two models were high (>0.92). The use of different models had little influence on the classification of animals based on EBVs or the accuracy of the EBVs.
Assuntos
Bovinos/genética , Bovinos/fisiologia , Temperamento , Animais , Teorema de Bayes , Comportamento Animal/fisiologia , Peso Corporal/genética , Peso Corporal/fisiologia , Cruzamento , Modelos Biológicos , Modelos EstatísticosRESUMO
Body size is directly related to the productive and reproductive performance of beef cattle raised under free-range conditions. In an attempt to better plan selection criteria, avoiding extremes in body size, this study estimated the heritabilities and genetic correlations of yearling hip height (YH) and mature hip height (MH) with selection indices obtained at weaning (WI) and yearling (YI) and mature weight (MW). Data from 102,373 Nelore animals born between 1984 and 2010, which belong to 263 farms that participate in genetic evaluation programmes of beef cattle conducted in Brazil and Paraguay, were used. The (co)variance components and genetic parameters were estimated by Bayesian inference in multi-trait analysis using an animal model. The mean heritabilities for YH, MH and MW were 0.56 ± 0.06, 0.47 ± 0.02 and 0.42 ± 0.02, respectively. The genetic correlation of YH with WI (0.13 ± 0.01) and YI (0.11 ± 0.01) was practically zero, whereas a higher correlation was observed with MW (0.22 ± 0.03). Positive genetic correlations of medium magnitude were estimated between MH and WI and YI (0.23 ± 0.01 and 0.43 ± 0.02, respectively). On the other hand, a high genetic correlation (0.68 ± 0.03) was observed between the indicator traits of mature body size (MH and MW). Considering the top 20 % of sire (896 sires) in terms of breeding values for the yearling index, the rank sire correlations between breeding values for MH and MW was 0.62. In general, the results indicate that selection based on WI and YI should not lead to important changes in YH. However, an undesired correlated response in mature cow height is expected, particularly when selection is performed using YI. Therefore, changes in the body structure of Nelore females can be obtained when MH and MW is used as a selection criterion for cows.
Assuntos
Tamanho Corporal/genética , Peso Corporal/genética , Bovinos/anatomia & histologia , Articulação do Quadril/fisiologia , Animais , Teorema de Bayes , Biometria , Cruzamento , Feminino , Masculino , Fenótipo , Fatores SexuaisRESUMO
Genetic correlations of selection indices and the traits considered in these indices with mature weight (MW) of Nelore females and correlated responses were estimated to determine whether current selection practices will result in an undesired correlated response in MW. Genetic trends for weaning and yearling indices and MW were also estimated. Data from 612,244 Nelore animals born between 1984 and 2010, belonging to different beef cattle evaluation programs from Brazil and Paraguay, were used. The following traits were studied: weaning conformation (WC), weaning precocity (WP), weaning muscling (WM), yearling conformation (YC), yearling precocity (YP), yearling muscling (YM), weaning and yearling indices, BW gain from birth to weaning (BWG), postweaning BW gain (PWG), scrotal circumference (SC), and MW. The variance and covariance components were estimated by Bayesian inference in a multitrait analysis, including all traits in the same analysis, using a nonlinear (threshold) animal model for visual scores and a linear animal model for the other traits. The mean direct heritabilities were 0.21±0.007 (WC), 0.22±0.007 (WP), 0.20±0.007 (WM), 0.43±0.005 (YC), 0.40±0.005 (YP), 0.40±0.005 (YM), 0.17±0.003 (BWG), 0.21±0.004 (PWG), 0.32±0.001 (SC), and 0.44±0.018 (MW). The genetic correlations between MW and weaning and yearling indices were positive and of medium magnitude (0.30±0.01 and 0.31±0.01, respectively). The genetic changes in weaning index, yearling index, and MW, expressed as units of genetic SD per year, were 0.26, 0.27, and 0.01, respectively. The genetic trend for MW was nonsignificant, suggesting no negative correlated response. The selection practice based on the use of sires with high final index giving preference for those better ranked for yearling precocity and muscling than for conformation generates only a minimal correlated response in MW.
Assuntos
Bovinos/crescimento & desenvolvimento , Bovinos/genética , Seleção Genética , Envelhecimento , Animais , Feminino , MasculinoRESUMO
Number of calvings at 53 mo (NC53) was proposed as an alternative selection criterion to improve productive longevity of Nellore cows. This study was carried out to estimate variance components for NC53 by assuming different models, so that the potential for using this selection criterion to improve fertility of Nellore cows could be assessed. Genetic correlations between NC53, number of calvings at 89 mo (NC89), and 2 selection indexes used in this breed were also estimated. The NC53 trait is moderately heritable (posterior mean heritability ≈ 0.17) and selecting for this criterion could improve productive longevity of Nellore cows. Greater response to selection is expected by fitting a threshold animal model for this trait, rather than a linear animal model. Greater accuracy of prediction for this criterion could be achieved by fitting a threshold-linear model, considering this trait and a selection index composed by traits evaluated at weaning and long-yearling.
Assuntos
Bovinos/genética , Bovinos/fisiologia , Longevidade/genética , Seleção Genética , Animais , Cruzamento , Feminino , Modelos Lineares , Longevidade/fisiologia , Modelos Genéticos , Reprodução/genética , Reprodução/fisiologiaRESUMO
Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore.