RESUMO
BACKGROUNDING: Stayability, which may be defined as the probability of a cow remaining in the herd until a reference age or at a specific number of calvings, is usually measured late in the animal's life. Thus, if used as selection criteria, it will increase the generation interval and consequently might decrease the annual genetic gain. Measuring stayability at an earlier age could be a reasonable strategy to avoid this problem. In this sense, a better understanding of the genetic architecture of this trait at different ages and/or at different calvings is important. This study was conducted to identify possible regions with major effects on stayability measured considering different numbers of calvings in Nellore cattle as well as pathways that can be involved in its expression throughout the female's productive life. RESULTS: The top 10 most important SNP windows explained, on average, 17.60% of the genetic additive variance for stayability, varying between 13.70% (at the eighth calving) and 21% (at the fifth calving). These SNP windows were located on 17 chromosomes (1, 2, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 20, 27, and 28), and they harbored a total of 176 annotated genes. The functional analyses of these genes, in general, indicate that the expression of stayability from the second to the sixth calving is mainly affected by genetic factors related to reproductive performance, and nervous and immune systems. At the seventh and eighth calvings, genes and pathways related to animal health, such as density bone and cancer, might be more relevant. CONCLUSION: Our results indicate that part of the target genomic regions in selecting for stayability at earlier ages (from the 2th to the 6th calving) would be different than selecting for this trait at later ages (7th and 8th calvings). While the expression of stayability at earlier ages appeared to be more influenced by genetic factors linked to reproductive performance together with an overall health/immunity, at later ages genetic factors related to an overall animal health gain relevance. These results support that selecting for stayability at earlier ages (perhaps at the second calving) could be applied, having practical implications in breeding programs since it could drastically reduce the generation interval, accelerating the genetic progress.
Assuntos
Estudo de Associação Genômica Ampla , Genômica , Feminino , Animais , Bovinos/genética , Fenótipo , Probabilidade , Reprodução/genéticaRESUMO
BACKGROUND: Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population). RESULTS: The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle. CONCLUSIONS: Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches.
Assuntos
Ingestão de Alimentos , Estudo de Associação Genômica Ampla , Ração Animal/análise , Animais , Bovinos/genética , Ingestão de Alimentos/genética , Metabolismo Energético/genética , Genômica , FenótipoRESUMO
Despite several studies on genetic markers and differentially expressed genes related to ribeye area (REA) and tenderness traits in beef cattle, there is divergence in the results regarding the genes associated with these traits. Thirteen genes associated with or exhibiting biological functions that might influence such phenotypes were included in this study. A total of five genes for REA (IGF-1, IGF-2, MSTN, NEDD4, and UBE4A) and eight genes for meat tenderness (CAPN1, CAPN2, CAST, HSPB1, DNAJA1, FABP4, SCD, and PRKAG3) were selected from previous studies on beef cattle. Genes and their respective proteins expression were validated in a commercial population of Nellore cattle using quantitative real-time PCR (RT-qPCR) and advanced mass spectrometry (LC/MS-MS) techniques, respectively. The MSTN gene was upregulated in animals with low REA. The CAPN1, CAPN2, CAST, HSPB1, and DNAJA1 genes were upregulated in animals with tough meat. The proteins translated by these genes were not differentially expressed. Our results confirm the potential of some of the studied genes as biomarkers for carcass and meat quality traits in Nellore cattle.
Assuntos
Carne , Carne Vermelha , Animais , Bovinos/genética , Marcadores Genéticos , Carne/análise , Fenótipo , ProteômicaRESUMO
Wearable sensors have been explored as an alternative for real-time monitoring of cattle feeding behavior in grazing systems. To evaluate the performance of predictive models such as machine learning (ML) techniques, data cross-validation (CV) approaches are often employed. However, due to data dependencies and confounding effects, poorly performed validation strategies may significantly inflate the prediction quality. In this context, our objective was to evaluate the effect of different CV strategies on the prediction of grazing activities in cattle using wearable sensor (accelerometer) data and ML algorithms. Six Nellore bulls (average live weight of 345 ± 21 kg) had their behavior visually classified as grazing or not-grazing for a period of 15 d. Elastic Net Generalized Linear Model (GLM), Random Forest (RF), and Artificial Neural Network (ANN) were employed to predict grazing activity (grazing or not-grazing) using 3-axis accelerometer data. For each analytical method, three CV strategies were evaluated: holdout, leave-one-animal-out (LOAO), and leave-one-day-out (LODO). Algorithms were trained using similar dataset sizes (holdout: n = 57,862; LOAO: n = 56,786; LODO: n = 56,672). Overall, GLM delivered the worst prediction accuracy (53%) compared with the ML techniques (65% for both RF and ANN), and ANN performed slightly better than RF for LOAO (73%) and LODO (64%) across CV strategies. The holdout yielded the highest nominal accuracy values for all three ML approaches (GLM: 59%, RF: 76%, and ANN: 74%), followed by LODO (GLM: 49%, RF: 61%, and ANN: 63%) and LOAO (GLM: 52%, RF: 57%, and ANN: 57%). With a larger dataset (i.e., more animals and grazing management scenarios), it is expected that accuracy could be increased. Most importantly, the greater prediction accuracy observed for holdout CV may simply indicate a lack of data independence and the presence of carry-over effects from animals and grazing management. Our results suggest that generalizing predictive models to unknown (not used for training) animals or grazing management may incur poor prediction quality. The results highlight the need for using management knowledge to define the validation strategy that is closer to the real-life situation, i.e., the intended application of the predictive model.
Assuntos
Aprendizado de Máquina , Dispositivos Eletrônicos Vestíveis , Algoritmos , Animais , Bovinos , Modelos Lineares , Masculino , Redes Neurais de ComputaçãoRESUMO
The objective of this study was to evaluate the accuracy of genomic predictions of growth traits in Nellore cattle. Data from 5064 animals belonging to farms that participate in the Conexão DeltaGen and PAINT breeding programs were used. Genotyping was performed with the Illumina BovineHD BeadChip (777,962 SNPs). After quality control of the genomic data, 412,993 SNPs were used. Deregressed EBVs (DEBVs) were calculated using the estimated breeding values (EBVs) and accuracies of birth weight (BW), weight gain from birth to weaning (GBW), postweaning weight gain (PWG), yearling height (YH), and cow weight (CW) provided by GenSys. Three models were used to estimate marker effects: genomic best linear unbiased prediction (GBLUP), BayesCπ, and improved Bayesian least absolute shrinkage and selection operator (IBLASSO). The prediction ability of genomic estimated breeding value (GEBVs) was estimated by the average Pearson correlation between DEBVs and GEBVs, predicted with the different methodologies in the validation populations. The regression coefficients of DEBVs on GEBVs in the validation population were calculated and used as indicators of prediction bias of GEBV. In general, the Bayesian methods provided slightly more accurate predictions of genomic breeding values than GBLUP. The BayesCπ and IBLASSO were similar for all traits (BW, GBW, PWG, and YH), except for CW. Thus, there does not seem to be a more suitable method for the estimation of SNP effects and genomic breeding values. Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions.
Assuntos
Genoma , Genômica , Animais , Teorema de Bayes , Bovinos/genética , Feminino , Genótipo , Modelos Genéticos , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
RESUMO
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populations presenting different levels of dominance effects. Simulated genome comprised 50k SNP and 300 QTL, both biallelic and randomly distributed across 29 autosomes. A total of six traits were simulated considering different values for the narrow and broad-sense heritability. In the purely additive scenario with low heritability (h2 = 0.10), the predictive ability obtained using GBLUP was slightly higher than the other methods whereas ANN provided the highest accuracies for scenarios with moderate heritability (h2 = 0.30). The accuracies of dominance deviations predictions varied from 0.180 to 0.350 in GBLUP extended for dominance effects (GBLUP-D), from 0.06 to 0.185 in RF and they were null using the ANN and SVM methods. Although RF has presented higher accuracies for total genetic effect predictions, the mean-squared error values in such a model were worse than those observed for GBLUP-D in scenarios with large additive and dominance variances. When applied to prescreen important regions, the RF approach detected QTL with high additive and/or dominance effects. Among machine learning methods, only the RF was capable to cover implicitly dominance effects without increasing the number of covariates in the model, resulting in higher accuracies for the total genetic and phenotypic values as the dominance ratio increases. Nevertheless, whether the interest is to infer directly on dominance effects, GBLUP-D could be a more suitable method.
Assuntos
Genoma/genética , Genômica , Aprendizado de Máquina , Herança Multifatorial , Animais , Cruzamento , Simulação por Computador , Feminino , Genes Dominantes , Genótipo , Masculino , FenótipoRESUMO
Highlighting genomic profiles for geographically distinct subpopulations of the same breed may provide insights into adaptation mechanisms to different environments, reveal genomic regions divergently selected, and offer initial guidance to joint genomic analysis. Here, we characterized similarities and differences between the genomic patterns of Angus subpopulations, born and raised in Canada (N = 382) and Brazil (N = 566). Furthermore, we systematically scanned for selection signatures based on the detection of autozygosity islands common between the two subpopulations, and signals of divergent selection, via FST and varLD tests. The principal component analysis revealed a sub-structure with a close connection between the two subpopulations. The averages of genomic relationships, inbreeding coefficients, and linkage disequilibrium at varying genomic distances were rather similar across them, suggesting non-accentuated differences in overall genomic diversity. Autozygosity islands revealed selection signatures common to both subpopulations at chromosomes 13 (63.77-65.25 Mb) and 14 (22.81-23.57 Mb), which are notably known regions affecting growth traits. Nevertheless, further autozygosity islands along with FST and varLD tests unravel particular sites with accentuated population subdivision at BTAs 7 and 18 overlapping with known QTL and candidate genes of reproductive performance, thermoregulation, and resistance to infectious diseases. Our findings indicate overall genomic similarity between Angus subpopulations, with noticeable signals of divergent selection in genomic regions associated with the adaptation in different environments.
Assuntos
Bovinos/genética , Genoma , Animais , Regulação da Temperatura Corporal/genética , Brasil , Cruzamento , Canadá , Bovinos/classificação , Resistência à Doença/genética , Marcadores Genéticos , Desequilíbrio de Ligação , Reprodução/genética , Especificidade da EspécieRESUMO
BACKGROUND: Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. RESULTS: Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. CONCLUSIONS: There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance.
Assuntos
Estudo de Associação Genômica Ampla , Genômica , Fenótipo , Animais , Cruzamento , Bovinos , Feminino , Variação Genética , Genômica/métodos , Genótipo , Masculino , Polimorfismo de Nucleotídeo Único , Locos de Características QuantitativasRESUMO
BACKGROUND: Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness. RESULTS: The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes. CONCLUSIONS: GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.
Assuntos
Haplótipos , Carne , Polimorfismo de Nucleotídeo Único , Animais , Bovinos , Redes Reguladoras de Genes , Estudo de Associação Genômica Ampla , Genótipo , FenótipoRESUMO
Multitrait meta-analyses are a strategy to produce more accurate genome-wide association studies, especially for complex phenotypes. We carried out a meta-analysis study for traits related to sexual precocity in tropical beef cattle (Nellore and Brahman) aiming to identify important genomic regions affecting these traits. The traits included in the analyses were age at first calving (AFC), early pregnancy (EP), age at first corpus luteum (AGECL), first postpartum anoestrus interval (PPAI), and scrotal circumference (SC). The traits AFC, EP, and SCN were measured in Nellore cattle, while AGECL, PPAI, and SCB were measured in Brahman cattle. Meta-analysis resulted in 108 significant single-nucleotide polymorphisms (SNPs), at an empirical threshold P-value of 1.39 × 10-5 (false discovery rate [FDR] < 0.05). Within 0.5 Mb of the significant SNP, candidate genes were annotated and analyzed for functional enrichment. Most of the closest genes to the SNP with higher significance in each chromosome have been associated with important roles in reproductive function. They are TSC22D2, KLF7, ARHGAP29, 7SK, MAP3K5, TLE3, WDR5, TAF3, TMEM68, PPP1R15B, NR2F2, GALR1, SUFU, and KCNU1. We did not observe any significant SNP in BTA5, BTA12, BTA17, BTA18, BTA19, BTA20, BTA22, BTA23, BTA25, and BTA28. Although the majority of significant SNPs are in BTA14, it was identified significant associations in multiple chromosomes (19 out of 29 autosomes), which is consistent with the postulation that reproductive traits are complex polygenic phenotypes. Five proposed association regions harbor the majority of the significant SNP (76%) and were distributed over four chromosomes (P < 1.39 × 10-5, FDR < 0.05): BTA2 (5.55%) from 95 to 96 Mb, BTA4 (5.55%) from 94.1 to 94.8 Mb, BTA14 (59.26%) from 24 to 25 Mb and 29 to 30 Mb, and BTA21 (5.55%) from 6.7 Mb to 11.4 Mb. These regions harbored key genes related to reproductive function. Moreover, these genes were enriched for functional groups associated with immune response, maternal-fetal tolerance, pregnancy maintenance, embryo development, fertility, and response to stress. Further studies including other breeds and precocity traits could confirm the importance of these regions and identify new candidate regions for sexual precocity in beef cattle.
Assuntos
Bovinos/genética , Cromossomos/genética , Estudo de Associação Genômica Ampla/veterinária , Polimorfismo de Nucleotídeo Único/genética , Puberdade Precoce/genética , Reprodução/genética , Animais , Cruzamento , Bovinos/fisiologia , Feminino , Fertilidade/genética , Genótipo , Fenótipo , Gravidez , Carne VermelhaRESUMO
The objective of this study was to estimate genetic parameters for carcass and meat quality traits, as well as their genetic correlations using pedigree and genomic information. A total of 3,716; 3,702; 3,439; 3,705; and 3,714 records of 12th-13th rib LM area (LMA), backfat thickness (BF), HCW, marbling score (MARB), and Warner-Bratzler peak shear force (WBSF), respectively, were used. Animals were genotyped with BovineHD BeadChip and GeneSeek Genomic Profiler Indicus HD - GGP75Ki panel. The (co)variance components were estimated by Bayesian inference using a multitrait ssGBLUP analysis. The animal model included fixed effects of contemporary group (defined by the combination of farm and year of birth, and management group at yearling) and age of animal at slaughtering as a covariate (linear). Direct additive genetic and residual effects were fitted as random. The posterior means and SD of heritabilities for LMA, BF, HCW, MARB, and WBSF were 0.28 (0.03), 0.21 (0.04), 0.21 (0.04), 0.12 (0.04), and 0.11 (0.03), respectively. The posterior means for genetic correlations between LMA and meat quality were positive and moderate with MARB (0.38 ± 0.12) and negative with WBSF (-0.47 ± 0.12). Low genetic correlations were estimated between BF and WBSF (-0.03 ± 0.16) and between HCW and MARB (-0.04 ± 0.14), indicating that these traits are not controlled by the same set or linked genes. Carcass traits (LMA, BF, and HCW) presented moderate heritability providing quick response to the selection purpose. The estimates of heritability for meat quality traits (MARB and WBSF) were low and indicate that the rate of genetic improvement for these traits would be slow. Genetic correlations indicated that selection for carcass traits would not be strongly antagonistic for improving meat quality.
Assuntos
Carne , Animais , Teorema de Bayes , Composição Corporal/fisiologia , Bovinos , Variação Genética , Masculino , Carne/análise , Carne/normas , Músculo Esquelético/fisiologia , FenótipoRESUMO
Stayability, which can be defined as the probability of a cow calving at a certain age when given the opportunity, is an important reproductive trait in beef cattle because it is directly related to herd profitability. The objective of this study was to estimate genetic parameters and to identify possible genomic regions associated with the phenotypic expression of stayability in Nellore cows. The variance components were estimated by Bayesian inference using a threshold animal model that included the systematic effects of contemporary group and sexual precocity and the random effects of animal and residual. The SNP effects were estimated by the single-step genomic BLUP method using information of 2,838 animals (2,020 females and 930 sires) genotyped with the Illumina High-Density BeadChip Array (San Diego, CA, USA). The variance explained by windows formed by 200 consecutive SNPs was used to identify genomic regions of largest effect on the expression of stayability. The heritability was 0.11 ± 0.01 when A matrix (pedigree) was used and 0.14 ± 0.01 when H matrix (relationship matrix that combines pedigree information and SNP data) was used. A total of 147 candidate genes for stayability were identified on chromosomes 1, 2, 5, 6, 9 and 20 and on the X chromosome. New candidate regions for stayability were detected, most of them related to reproductive, immunological and central nervous system functions.
Assuntos
Cruzamento , Genoma , Modelos Genéticos , Reprodução/genética , Animais , Teorema de Bayes , Bovinos , Feminino , Genótipo , Linhagem , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , GravidezRESUMO
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.
Assuntos
Ácidos Graxos/análise , Genômica/métodos , Carne/análise , Modelos Genéticos , Proteínas Musculares/genética , Músculo Esquelético/metabolismo , Polimorfismo de Nucleotídeo Único , Animais , Animais Endogâmicos , Teorema de Bayes , Brasil , Bovinos , Ácidos Graxos/metabolismo , Ácidos Graxos Monoinsaturados/metabolismo , Ácidos Graxos Ômega-3/metabolismo , Ácidos Graxos Ômega-6/metabolismo , Estudos de Viabilidade , Humanos , Masculino , Proteínas Musculares/metabolismo , Músculo Esquelético/crescimento & desenvolvimento , Valor Nutritivo , Seleção GenéticaRESUMO
The aim of this study was to estimate (co)variance components and genetic parameters from birth to yearling weight (550 days of age) in Guzerá cattle, using random regression models. Data set from animals (male and female) born between 1993 and 2011 belonging to ten farms in seven Brazilian States were used. The best-fit model considering direct and maternal genetic effect and permanent environmental animal effect were adjusted by fourth, third, and second order, respectively, using orthogonal polynomials of Legendre. The higher estimated values of direct heritability were observed in birth (0.88) and yearling weight (0.70). The genetic correlations were moderate to high magnitude, remaining up even with the increase in the ages gap.(AU)
O objetivo do presente trabalho foi estimar componentes de (co)variâncias e parâmetros genéticos para características de pesos do nascimento ao sobreano (550 dias de idade) para bovinos da raça Guzerá, por meio de modelos de regressão aleatória. Os dados utilizados são de animais (machos e fêmeas) nascidos entre 1993 e 2011 e pertencentes a dez fazendas de sete estados brasileiros. O modelo de melhor ajuste considerou os efeitos genéticos aditivos diretos e maternos e os de ambiente permanente do animal ajustado usando polinômios ortogonais de Legendre de quarta, terceira e segunda ordem, respectivamente. As maiores estimativas de herdabilidade diretas foram observadas para os pesos ao nascimento (0,88) e ao sobreano (0,70). As correlações genéticas foram de moderada a alta magnitude, mantendo-se elevada mesmo com o aumento da distância entre as idades.(AU)
Assuntos
Animais , Bovinos , Análise de Regressão , Hereditariedade/fisiologiaRESUMO
Abstract The aim of this study was to estimate (co)variance components and genetic parameters from birth to yearling weight (550 days of age) in Guzerá cattle, using random regression models. Data set from animals (male and female) born between 1993 and 2011 belonging to ten farms in seven Brazilian States were used. The best-fit model considering direct and maternal genetic effect and permanent environmental animal effect were adjusted by fourth, third, and second order, respectively, using orthogonal polynomials of Legendre. The higher estimated values of direct heritability were observed in birth (0.88) and yearling weight (0.70). The genetic correlations were moderate to high magnitude, remaining up even with the increase in the ages gap.
Resumo O objetivo do presente trabalho foi estimar componentes de (co)variâncias e parâmetros genéticos para características de pesos do nascimento ao sobreano (550 dias de idade) para bovinos da raça Guzerá, por meio de modelos de regressão aleatória. Os dados utilizados são de animais (machos e fêmeas) nascidos entre 1993 e 2011 e pertencentes a dez fazendas de sete estados brasileiros. O modelo de melhor ajuste considerou os efeitos genéticos aditivos diretos e maternos e os de ambiente permanente do animal ajustado usando polinômios ortogonais de Legendre de quarta, terceira e segunda ordem, respectivamente. As maiores estimativas de herdabilidade diretas foram observadas para os pesos ao nascimento (0,88) e ao sobreano (0,70). As correlações genéticas foram de moderada a alta magnitude, mantendo-se elevada mesmo com o aumento da distância entre as idades.
RESUMO
The aim of this study was to estimate (co)variance components and genetic parameters from birth to yearling weight (550 days of age) in Guzerá cattle, using random regression models. Data set from animals (male and female) born between 1993 and 2011 belonging to ten farms in seven Brazilian States were used. The best-fit model considering direct and maternal genetic effect and permanent environmental animal effect were adjusted by fourth, third, and second order, respectively, using orthogonal polynomials of Legendre. The higher estimated values of direct heritability were observed in birth (0.88) and yearling weight (0.70). The genetic correlations were moderate to high magnitude, remaining up even with the increase in the ages gap.
O objetivo do presente trabalho foi estimar componentes de (co)variâncias e parâmetros genéticos para características de pesos do nascimento ao sobreano (550 dias de idade) para bovinos da raça Guzerá, por meio de modelos de regressão aleatória. Os dados utilizados são de animais (machos e fêmeas) nascidos entre 1993 e 2011 e pertencentes a dez fazendas de sete estados brasileiros. O modelo de melhor ajuste considerou os efeitos genéticos aditivos diretos e maternos e os de ambiente permanente do animal ajustado usando polinômios ortogonais de Legendre de quarta, terceira e segunda ordem, respectivamente. As maiores estimativas de herdabilidade diretas foram observadas para os pesos ao nascimento (0,88) e ao sobreano (0,70). As correlações genéticas foram de moderada a alta magnitude, mantendo-se elevada mesmo com o aumento da distância entre as idades.
Assuntos
Animais , Bovinos , Análise de Regressão , Hereditariedade/fisiologiaRESUMO
The objective of this study was to identify genomic regions that are associated with meat quality traits in the Nellore breed. Nellore steers were finished in feedlots and slaughtered at a commercial slaughterhouse. This analysis included 1,822 phenotypic records of tenderness and 1,873 marbling records. After quality control, 1,630 animals genotyped for tenderness, 1,633 animals genotyped for marbling, and 369,722 SNPs remained. The results are reported as the proportion of variance explained by windows of 150 adjacent SNPs. Only windows with largest effects were considered. The genomic regions were located on chromosomes 5, 15, 16 and 25 for marbling and on chromosomes 5, 7, 10, 14 and 21 for tenderness. These windows explained 3,89% and 3,80% of the additive genetic variance for marbling and tenderness, respectively. The genes associated with the traits are related to growth, muscle development and lipid metabolism. The study of these genes in Nellore cattle is the first step in the identification of causal mutations that will contribute to the genetic evaluation of the breed.
Assuntos
Estudo de Associação Genômica Ampla/métodos , Locos de Características Quantitativas , Carne Vermelha , Animais , Bovinos , Feminino , Masculino , Polimorfismo de Nucleotídeo Único , Seleção ArtificialRESUMO
Current analysis estimated co-variance components and genetic parameters for growth traits by random regression models taking into consideration the cows age on the weight of calves. Genealogical data and records on weights of male and female Zebu cattle, born between 1993 and 2011, were provided by the National Association of Breeders and Researchers (ANCP). Different models were compared by Akaike and Bayesian criteria. Legendres orthogonal polynomials were used to model the direct and maternal genetic effects of maternal and animal permanent environmental effects. Joint modeling of cow age at the moment their progenies were weighed resulted in more accurate estimates of co-variance components and genetics parameters. Co-variance functions of the cow age retrieved the dam effect on real performance of the progenies, reduced biases, improved parameter estimates and predicted breeding rates.(AU)
Objetivou-se com o presente trabalho estimar componentes de (co)variância e parâmetros genéticos de características de crescimento por meio de modelos de regressão aleatória considerando a idade da vaca no momento da pesagem de sua respectiva progênie. As informações foram utilizadas de genealogia e registros de pesagem de bovinos machos e fêmeas da raça Guzerá, provenientes da Associação Nacional de Criadores e Pesquisadores (ANCP), nascidos entre 1993 e 2011. Os diferentes modelos foram comparados pelo critério de informação de Akaike e o critério de informação Bayesiano de Schwarz. Utilizaram-se polinômios ortogonais de Legendre para modelar os efeitos genéticos aditivos diretos e maternal, de ambiente permanente do animal e maternal. A modelagem conjunta do efeito da idade do animal e idade da vaca no momento em que suas progênies foram pesadas resultou em estimativas de componentes de (co)variâncias e parâmetros genéticos mais precisos. A função de (co)variâncias da idade da vaca permitiu capturar o efeito que a idade da vaca apresenta sobre o desempenho fenotípico de sua progênie, reduzindo o viés e auxiliando na estimação de parâmetros e predições de valores genéticos mais confiáveis.(AU)