Genomic prediction ability for feed efficiency traits using different models and pseudo-phenotypes under several validation strategies in Nelore cattle.

There is a growing interest to improve feed efficiency (FE) traits in cattle. The genomic selection was proposed to improve these traits since they are difficult and expensive to measure. Up to date, there are scarce studies about the implementation of genomic selection for FE traits in indicine cattle under different scenarios of pseudo-phenotypes, models, and validation strategies on a commercial large scale. Thus, the aim was to evaluate the feasibility of genomic selection implementation for FE traits in Nelore cattle applying different models and pseudo-phenotypes under validation strategies. Phenotypic and genotypic information from 4 329 and 3 467 animals were used, respectively, which were tested for residual feed intake, DM intake, feed efficiency, feed conversion ratio, residual BW gain, and residual intake and BW gain. Six prediction methods were used: single-step genomic best linear unbiased prediction, Bayes A, Bayes B, Bayes Cπ, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayes R. Phenotypes adjusted for fixed effects (Y*), estimated breeding value (EBV), and EBV deregressed (DEBV) were used as pseudo-phenotypes. The validation approaches used were: (1) random: the data was randomly divided into ten subsets and the validation was done in each subset at a time; (2) age: the partition into training and testing sets was based on year of birth and testing animals were born after 2016; and (3) EBV accuracy: the data was split into two groups, being animals with accuracy above 0.45 the training set; and below 0.45 the validation set. In the analyses that used the Y* as pseudo-phenotype, prediction ability (PA) was obtained by dividing the correlation between pseudo-phenotype and genomic EBV (GEBV) by the square root of the heritability of the trait. When EBV and DEBV were used as the pseudo-phenotype, the simple correlation of this quantity with the GEBV was considered as PA. The prediction methods show similar results for PA and bias. The random cross-validation presented higher PA (0.17) than EBV accuracy (0.14) and age (0.13). The PA was higher for Y* than for EBV and DEBV (30.0 and 34.3%, respectively). Random validation presented the highest PA, being indicated for use in populations composed mainly of young animals and traits with few generations of data recording. For high heritability traits, the validation can be done by age, enabling the prediction of the next-generation genetic merit. These results would support breeders to identify genomic approaches that are more viable for genomic prediction for FE-related traits.

Genome-enabled prediction of meat and carcass traits using Bayesian regression, single-step genomic best linear unbiased prediction and blending methods in Nelore cattle.

Several methods have been used for genome-enabled prediction (or genomic selection) of complex traits, for example, multiple regression models describing a target trait with a linear function of a set of genetic markers. Genomic selection studies have been focused mostly on single-trait analyses. However, most profitability traits are genetically correlated, and an increase in prediction accuracy of genomic breeding values for genetically correlated traits is expected when using multiple-trait models. Thus, this study was carried out to assess the accuracy of genomic prediction for carcass and meat quality traits in Nelore cattle, using single- and multiple-trait approaches. The study considered 15 780, 15 784, 15 742 and 526 records of rib eye area (REA, cm2), back fat thickness (BF, mm), rump fat (RF, mm) and Warner-Bratzler shear force (WBSF, kg), respectively, in Nelore cattle, from the Nelore Brazil Breeding Program. Animals were genotyped with a low-density single nucleotide polymorphism (SNP) panel and subsequently imputed to arrays with 54 and 777 k SNPs. Four Bayesian specifications of genomic regression models, namely, Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression; blending methods, BLUP; and single-step genomic best linear unbiased prediction (ssGBLUP) methods were compared in terms of prediction accuracy using a fivefold cross-validation. Estimates of heritability ranged from 0.20 to 0.35 and from 0.21 to 0.46 for RF and WBSF on single- and multiple-trait analyses, respectively. Prediction accuracies for REA, BF, RF and WBSF were all similar using the different specifications of regression models. In addition, this study has shown the impact of genomic information upon genetic evaluations in beef cattle using the multiple-trait model, which was also advantageous compared to the single-trait model because it accounted for the selection process using multiple traits at the same time. The advantage of multi-trait analyses is attributed to the consideration of correlations and genetic influences between the traits, in addition to the non-random association of alleles.

Interação genótipo x ambiente sobre o desempenho ponderal de animais da raça Nelore na região Centro-Oeste / Genotype environment interaction on the weight gain of animals of the Nelore breed in the Midwest

Utilizaram-se registros de pesos corporais padronizados aos 120, 210, 365 e 450 dias de idade, provenientes de 30.481 animais da raça Nelore, progênies de 211 reprodutores acasalados com 19.229 matrizes, oriundos de rebanhos dos estados de Mato Grosso, Mato Grosso do Sul e Goiás, com o objetivo de avaliar a presença de interação genótipo x ambiente entre os estados. As estimativas de herdabilidade entre os estados variaram de 0,09 a 0,14; 0,11 a 0,17; 0,16 a 0,27 e 0,17 a 0,35, respectivamente, para os pesos 120, 210, 365 e 450 dias de idade. As estimativas de correlação genética aditiva entre a mesma característica para os diferentes estados apresentaram valores inferiores a 0,80. As correlações de Spearman entre os valores genéticos para os pesos corporais se reduziram à medida que se aumentou a intensidade de seleção sobre os reprodutores. A presença de interação genótipo x ambiente causa maior impacto sobre a avaliação genética dos reprodutores sob intensidade de seleção elevada, sendo interessante sua consideração no processo de avaliação genética. Estimativas de tendências genéticas para todos os pesos corporais apresentaram-se crescentes ao longo dos anos nos três estados.(AU)

Data of adjusted alive weights at 120, 210, 365 and 450 days of age of 30,481 records of animals of the Nellore beef cattle breed from herds of states of Mato Grosso, Mato Grosso do Sul, and Goiás were used to study the influence of environment genotype interaction on genetic evaluation of sires. Estimates of heritability between the states ranged from 0.09 to 0.14; 0.11 to 0.17; 0.16 to 0.27 and 0.17 to 0.35, respectively for live weights 120, 210, 365 and 450 days of age. The estimates of additive genetic correlation between the same characteristic for the different states presented values lower than 0.80. Spearman correlations between breeding values obtained from live weights of sires lowered as the intensity of selection on sires increased. The presence of environment genotype interaction has greater impact on the genetic evaluation of breeding under high intensity of selection, being an interesting consideration in the process of genetic evaluation. Estimates of genetic trends for all body weights have been increasing over the years in all three states.(AU)

Genetic analysis of age at first calving, accumulated productivity, stayability and mature weight of Nellore females.

The female reproductive performance, productivity and size are strongly associated with production efficiency of herds raised in a tropical environment. The age at first calving (AFC), accumulated productivity (AP), stayability (STAY) and mature weight (MW) could be used as indicators of these traits. In this study, the genetic parameters and correlations between AFC, AP, STAY and MW measured in Nellore females were estimated, in order to provide support for the beef cattle evaluation programs. In addition, the genetic changes for these traits were obtained. The (co)variance components were estimated by Gibbs sampling by four-trait multivariate analysis, using a threshold animal model for STAY and linear animal model for the other traits (AFC, AP and MW). Heritability of AFC, AP and STAY showed low values, with posterior means of 0.13 ± 0.02, 0.14 ± 0.01 and 0.19 ± 0.03, respectively. On the other hand, for MW were estimated mean heritability of 0.44 ± 0.03 and repeatability of 0.77 ± 0.03, demonstrating the importance of genetic and permanent environmental effects for the expression of beef cows' size. The AFC showed null genetic correlation with AP (-0.06 ± 0.12) and MW (0.01 ± 0.09) and low and negative with STAY (-0.15 ± 0.11). The AP showed high genetic correlation with STAY (0.86 ± 0.03) and weak with MW (0.23 ± 0.09). Positive and moderate genetic association was estimated between STAY and MW (0.66 ± 0.05). Annual direct genetic trends of 0.19 kg, 0.30 units and 0.10 kg were estimated for AP, STAY and MW, respectively, and were significant (P < 0.05) for STAY and MW. For AFC, negative and favorable annual genetic change was estimated (-0.08 months, P < 0.05). In this population, the selection of heifers for an early reproductive age should have little influence, however favorable, in the time that the cows remain in the herd. The use of AP as a selection criterion should result in smaller changes in the females' mature weight when compared to selection based on STAY.

Bayesian analyses of genetic parameters for growth traits in Nellore cattle raised on pasture.

This study was carried out to investigate (co)variance components and genetic parameters for growth traits in beef cattle using a multi-trait model by Bayesian methods. Genetic and residual (co)variances and parameters were estimated for weights at standard ages of 120 (W120), 210 (W210), 365 (W365), and 450 days (W450), and for pre- and post-weaning daily weight gain (preWWG and postWWG) in Nellore cattle. Data were collected over 16 years (1993-2009), and all animals were raised on pasture in eight farms in the North of Brazil that participate in the National Association of Breeders and Researchers. Analyses were run by the Bayesian approach using Gibbs sampler. Additive direct heritabilities for W120, W210, W365, and W450 and for preWWG and postWWG were 0.28 ± 0.013, 0.32 ± 0.002, 0.31 ± 0.002, 0.50 ± 0.026, 0.61 ± 0.047, and 0.79 ± 0.055, respectively. The estimates of maternal heritability were 0.32 ± 0.012, 0.29 ± 0.004, 0.30 ± 0.005, 0.25 ± 0.015, 0.23 ± 0.017, and 0.22 ± 0.016, respectively, for W120, W210, W365, and W450 and for preWWG and postWWG. The estimates of genetic direct additive correlation among all traits were positive and ranged from 0.25 ± 0.03 (preWWG and postWWG) to 0.99 ± 0.00 (W210 and preWWG). The moderate to high estimates of heritability and genetic correlation for weights and daily weight gains at different ages is suggestive of genetic improvement in these traits by selection at an appropriate age. Maternal genetic effects seemed to be significant across the traits. When the focus is on direct and maternal effects, W210 seems to be a good criterium for the selection of Nellore cattle considering the importance of this breed as a major breed of beef cattle not only in Northern Brazil but all regions covered by tropical pastures. As in this study the genetic correlations among all traits were high, the selection based on weaning weight might be a good choice because at this age there are two important effects (maternal and direct genetic effects). In contrast, W120 should be preferred when the objective is improving the maternal ability of the dams. Furthermore, selection for postWWG can be used if the animals show both heavier weaning weights and high growth rate after weaning because it is possible to shorten the time between weaning and slaughter based on weaning weight, postWWG, and desired weight at the time of slaughter.

Parameter estimates for reproductive and carcass traits in Nelore beef cattle.

The aim of this study was to estimate genetic parameters for scrotal circumference at 365 (SC365) and 450 (SC450) days of age, age at first calving (AFC), ribeye area (REA), backfat (BF) thickness, and rump fat (RF) thickness, in order to provide information on potential traits for Nelore cattle breeding program. Genetic parameters were estimated using the Average Information Restricted Maximum Likelihood method in single- and multitrait analyses. Four different animal models were tested for SC365, SC450, REA, BF, and RF in single-trait analyses. For SC365 and SC450, the maternal genetic effect was statistically significant (P < 0.01) and was included for multitrait analyses. The direct heritability estimates for SC365, SC450, AFC, REA, BF, and RF were equal to 0.31, 0.38, 0.24, 0.32, 0.16, and 0.19, respectively. Maternal heritability for SC365 and SC450 was equal to 0.06 and 0.08, respectively. The highest genetic correlations were found among the scrotal circumferences. Testing for the inclusion of maternal effects in genetic parameters estimation for scrotal circumference should be evaluated in the Nelore breeding program, mostly for correctly ranking the animal's estimated breeding values. Similar heritability estimates were observed for scrotal circumference, as well as favorable genetic correlations of this trait with AFC and carcass traits. Thus, scrotal circumference measured at 365 days of age could be a target trait for consideration in the Nelore selection index in order to improve most of the traits herein analyzed.

Evaluation of body weight and visual scores for genetic improvement of Nelore cattle.

The aims of our study were to estimate genetic parameters for body weight and visual scores and to evaluate their inclusion as selection criteria in the Nelore breeding program in Brazil. The traits studied were the body weight adjusted to 210 (W210) and to 450 (W450) days of age and visual scores for body structure, finishing precocity, and muscling evaluated at weaning (BSW, FPW, and MSW) and yearling (BSY, FPY, and MSY) ages. A total of 33,242, 26,259, 23,075, and 26,057 observations were considered to analyze W210, W450, and visual scores at weaning and yearling. The significant (P < 0.05) fixed effects for all traits were farm, birth season, birth year, sex, and management group. Single-trait analyses were performed to define the most fitting model to our data using the average information restricted maximum likelihood algorithm, for weaning traits. Subsequently, these models were used in single- and two-trait analyses considering the Bayesian inference algorithm. Two-trait Bayesian analyses resulted in average direct heritability estimates for BSW, FPW, MSW, W210, BSY, FPY, MSY, and W450 of 0.28, 0.30, 0.27, 0.28, 0.40, 0.44, 0.39, and 0.50, respectively. Genetic correlations varied from 0.40 to 0.96. Benefits to animal performance can best be achieved by considering body structure, finishing precocity, and muscling as selection criteria in the Nelore breeding programs. The decision to use visual scores measured at weaning should be considered in order to decrease generation interval and assist pre-selecting individuals, expecting carcass improvements in the future progeny.

Modelos de regressão aleatória para características de crescimento de bovinos da raça Nelore do estado de Mato Grosso / Random regression models to traits of growth in the Nellore breed in Mato Grosso state

Foram utilizados 138.976 registros de informações de pesos corporais variando de 60 a 610 dias de idade, provenientes de 27.327 animais da raça Nelore, oriundos de rebanhos do estado do Mato Grosso, com o objetivo de descrever a variabilidade genética e estimar parâmetros genéticos para o peso corporal em diferentes idades, utilizando-se modelos de regressão aleatória. O modelo empregado incluiu efeitos fixos de grupo de contemporâneos e idade da vaca ao parto como covariáveis, além de efeitos aleatórios genético aditivo direto, genético materno, ambiente permanente de animal, ambiente permanente materno e efeito de ambiente temporário. O modelo de regressão aleatória mais adequado foi o que empregou função de covariância com polinômios de quarta ordem para descrição da variabilidade de todos os efeitos e duas classes de variância residual. As estimativas de variância genética aditiva direta e de ambiente permanente de animal aumentaram com a idade dos animais. As variâncias genética materna e de ambiente permanente materno exibiram comportamento semelhante, com maiores valores na fase de aleitamento. Os coeficientes de herdabilidade estimados variam de 0,25 a 0,43, com maiores valores nas idades mais avançadas na trajetória de crescimento dos animais. Esses resultados indicaram presença de variabilidade genética suficiente para obtenção de ganho genético expressivo por meio da seleção, principalmente após desmama. Os resultados encontrados para a correlação genética aditiva direta exibiram baixas correlações entre pesos nas idades iniciais e finais, porém pesos altamente correlacionados entre idades mais próximas. As correlações genéticas estimadas entre os pesos da desmama com os pesos até 610 dias de idade foram altas e positivas e indicam que os genes responsáveis por maiores pesos nesse período, em sua maioria, são os mesmos.

In this study 138,976 records of live weight between 60 to 610 days of age, from 27,327 Nellore cattle breed, from herds in Mato Grosso State were used in order to describe the genetic variability and to estimate genetic parameters for the live weight at different ages, using random regression models. The model included the fixed effects of contemporary group and age of cow at calving as covariate, random effects of direct additive genetic, maternal genetic, animal and maternal permanent environmental and temporary environment effect. The most appropriate random regression model employed the covariance function with fourth order polynomials to describe the variability of all effects and two residual variance classes. Estimates of direct additive genetic variance and animal permanent environment increased with the age of the animals. Maternal genetic variances and maternal permanent environment exhibited similar behavior, with higher values in pre weaning. The estimated heritability coefficients ranged from 0.25 to 0.43, with higher values at older ages in the growth trajectory of the animals. These results showed the presence of sufficient genetic variability to obtain significant genetic gain through selection, especially after weaning. The results for the direct additive genetic correlation exhibited low correlations between weights in initial and final ages, however, highly correlated weights between nearest ages. Genetic correlation estimates between weaning with weights up to 610 days of age were high and positive and indicate that most of the genes responsible for higher weights in this period are the same.

Estimates of genetic parameters and genetic trends for reproductive traits and weaning weight in Tabapuã cattle.

The Tabapuã breed is a beef cattle Brazilian breed known for its sexual precocity and desirable characteristics for tropical conditions. However, this is a newly formed breed and few studies have been conducted regarding genetic parameters and genetic trends for its reproductive traits. The objective of the present study was to estimate the genetic parameters, genetic trends, and relative selection efficiency for weaning weight adjusted to 210 d of age (W210), age at first calving (AFC), average calving interval (ACI), first calving interval (CI1), and accumulated productivity (ACP) among Tabapuã beef cattle. Pedigree data on 15,241 Tabapuã animals born between 1958 and 2011 and phenotype records from 7,340 cows born between 1970 and 2011 were supplied by the National Association of Breeders and Researchers (Associação Nacional de Criadores e Pesquisadores). Analysis through the least squares method assisted in defining the fixed effects that were considered within the models. The estimates for the genetic parameters were obtained through the REML, using a multitrait animal model. The likelihood ratio test applied for W210 was significant ( < 0.05) for the inclusion of maternal additive genetic and permanent environmental effects in the model. Genetic trends were calculated through linear regression of the EBV of the animals, according to the year of birth. The heritability estimates obtained ranged from 0.04 ± 0.03 for CI1 to 0.25 ± 0.05 for W210. The genetic correlations ranged from 0.004 ± 0.19 for W210-AFC and 0.93 ± 0.12 for ACI-CI1. The genetic trend was significant ( < 0.05) and favorable for CI1 and the maternal genetic effect of W210 and was significant ( < 0.05) and unfavorable for AFC, ACI, and ACP. The ACP could be used in the selection index to assist the breeding goal of improved productive and reproductive performance. The genetic trends indicated small and unfavorable genetic changes for AFC, ACI, and ACP in light of the recent implementation of a genetic breeding program for this breed.

Characterization of the variable cow's age at last calving as a measurement of longevity by using the Kaplan-Meier estimator and the Cox model.

In most studies on beef cattle longevity, only the cows reaching a given number of calvings by a specific age are considered in the analyses. With the aim of evaluating all cows with productive life in herds, taking into consideration the different forms of management on each farm, it was proposed to measure cow longevity from age at last calving (ALC), that is, the most recent calving registered in the files. The objective was to characterize this trait in order to study the longevity of Nellore cattle, using the Kaplan-Meier estimators and the Cox model. The covariables and class effects considered in the models were age at first calving (AFC), year and season of birth of the cow and farm. The variable studied (ALC) was classified as presenting complete information (uncensored = 1) or incomplete information (censored = 0), using the criterion of the difference between the date of each cow's last calving and the date of the latest calving at each farm. If this difference was >36 months, the cow was considered to have failed. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The records of 11 791 animals from 22 farms within the Nellore Breed Genetic Improvement Program ('Nellore Brazil') were used. In the estimation process using the Kaplan-Meier model, the variable of AFC was classified into three age groups. In individual analyses, the log-rank test and the Wilcoxon test in the Kaplan-Meier model showed that all covariables and class effects had significant effects (P < 0.05) on ALC. In the analysis considering all covariables and class effects, using the Wald test in the Cox model, only the season of birth of the cow was not significant for ALC (P > 0.05). This analysis indicated that each month added to AFC diminished the risk of the cow's failure in the herd by 2%. Nonetheless, this does not imply that animals with younger AFC had less profitability. Cows with greater numbers of calvings were more precocious than those with fewer calvings.

Genetic association between body composition measured by ultrasound and visual scores in Brazilian Nelore cattle.

The objective of this study was to evaluate the genetic variability of body composition traits measured by ultrasound, growth traits, and visual scores as well as their genetic associations in Nelore cattle. A total of 9,765, 13,285, 13,061, 12,811, 3,484, 3,484, 3,483, and 3,303 records of weight at time of ultrasound measure (W550), 12th-13th rib LM area (LMA), backfat thickness (BF), rump fat thickness (RF), visual scores for body structure (BS), finishing precocity (FP), muscling (MS), and sheath and navel characteristics (SN), respectively, were used. The model included contemporary group (defined as year and season of birth, sex, and management group) as a fixed effect and age of dam at calving and age of the animal (linear and quadratic effects) as covariates. The direct additive genetic effect was included as a random effect. The analyses also included 46,157 observations of BW adjusted to 120 d. The (co)variance components were estimated by the restricted maximum likelihood method using a multitrait animal model. Heritability estimates for W550, LMA, BF, RF, BS, FP, MS, and SN were 0.37 ± 0.030, 0.33 ± 0.03, 0.24 ± 0.02, 0.28 ± 0.03, 0.24 ± 0.04, 0.38 ± 0.05, 0.29 ± 0.05, and 0.38 ± 0.06, respectively. The estimated genetic correlations between visual scores and LMA were moderate and positive, ranging from 0.37 to 0.44. Similar results were obtained for the estimated genetic correlations between FP and MS with fat thickness measures (BF and RF). Low genetic correlations were estimated between SN and BS and between SN and the body composition traits, indicating that selection for body composition traits and BS will not affect sheath and navel size. The estimated genetic correlations between weight adjusted to 120 d of age (W120) and W550 and BS were high (0.87 and 0.91) and moderate with LMA (0.49 and 0.55), FP (0.37 and 0.41), and MS (0.47 and 0.55). The visual scores and ultrasound-measured body composition traits have enough genetic variation for selection purposes in Nelore cattle. Selection based on visual scores for body structure, finishing precocity and muscling should lead to desired changes in body composition albeit much more slowly than direct selection on those traits measured by ultrasound. Selection for heavier BW at early ages should lead to favorable changes in yearling LM area and visual scores.

Random regression analyses using B-spline functions to model growth of Nellore cattle.

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Genetic analysis on growth and carcass traits in Nelore cattle.

In this study, the objective was to estimate genetic parameters of body weight at 210 (BW210) and 365 (BW365) days of age in relation to rib eye area (REA), subcutaneous back fat thickness (BF) and rump fat (RF), and their respective genetic trends, in Nelore beef cattle. Estimates of genetic parameters and breeding values for the studied traits were obtained using the REML method. The direct and maternal heritability estimates were respectively: 0.25±0.02 and 0.21±0.01, for BW210, and 0.29±0.02 and 0.09±0.01, for BW365. The heritability estimates for transformed REA, BF and RF were 0.29±0.03, 0.21±0.02 and 0.23±0.03, respectively. There were genetic associations between BW210 and REA, BW365 and REA, and BF and RF, while the other correlations were low. The selection process that was conducted at the farms participating in the breeding program, taking the proposed selection index into consideration, caused genetic changes to these traits.

Características reprodutivas e suas associações com outras características de importância econômica na raça Nelore / Reproductive traits and their associations with other economically important traits in Nelore

Objetivou-se com este trabalho estimar as herdabilidades (h²) e as correlações genéticas (r g) entre idade ao primeiro parto (IPP) e primeiro intervalo de partos (PIEP) e outras características como peso (PS) ao ano (A) e ao sobreano (S), altura do posterior (ALT) e perímetro escrotal (PE450) em animais da raça Nelore. Os parâmetros genéticos foram estimados em uma análise multicaracterística por modelo animal, utilizando-se a inferência bayesiana via algoritmo de "Gibbs Sampling". Os parâmetros genéticos estimados sugerem a existência de variabilidade genética para IPP (h² = 0,26), sendo que a seleção para a diminuição da IPP de fêmeas Nelore deve responder à seleção individual, sem causar antagonismo do valor genético dos animais para PS (r g = -0,22 (A) e -0,44 (S)) e PE450 (r g = 0,02). A seleção para a diminuição da IPP, no longo prazo, pode levar a um aumento da ALT dos animais, embora essa associação seja relativamente baixa (-0,35). A estimativa de herdabilidade a posteriori para a característica PIEP foi baixa, 0,11±0,03. As r g entre PIEP e as demais características estudadas indicam que a seleção para essas características de crescimento não afetará o PIEP.

Heritability (h²) and genetic correlations (r g) were estimated between reproductive traits such as age at first calving (AFC), first calving interval (FCI) and other economically relevant traits, i.e., weight (W) at year (Y) and at 18 months of age (S), scrotal circumference (SC), and hip height (HH) in Nelore cattle. The genetic parameters were estimated in a multiple-trait analysis, with animal models using the Bayesian inference by Gibbs Sampling algorithm. The genetic parameters estimated in this work suggest the existence of genetic variability for AFC (h² = 0.26), where the selection for the reduction of Nelore females AFC should respond to mass selection, without causing genetic antagonism in the selection of W (r g = -0,22 (Y) and -0,44 (S)), and SC (r g = 0,02). The selection for the AFC in the long term could lead to an increase in the animal's frame, although this association is relatively low (-0.35). The posteriori heritability estimate for FCI was low, 0.11±0.03. The r g between FCI and the other traits studied indicate that selection for these growth traits will not affect the FCI.

Trends of the genetic connectedness measures among Nelore beef cattle herds.

Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 1999-2003 to the 2004-2008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.

Genetic parameter estimates and response to selection for weight and testicular traits in Nelore cattle.

We estimated genetic parameters for various phases of body and testicular growth until 550 days of age in Nelore cattle, using Bayesian inference, including correlation values and error estimates. Weight and scrotal records of 54,182 Nelore animals originating from 18 farms participating in the Brazilian Nelore Breeding Program (PMGRN) were included. The following traits were measured: weight at standard ages of 120 (W120), 210 (W210), 365 (W365), 450 (W450), and 550 (W550) days; weight gain between 120/210 (WG1), 210/365 (WG2), 365/450 (WG3), 450/550 (WG4), 120/365 (WG5), 120/450 (WG6), 120/550 (WG7), 210/450 (WG8), 210/550 (WG9), and 365/550 (WG10) days of age; scrotal circumference at 365 (SC365), 450 (SC450) and 550 (SC550) days of age, and testicular growth between 365/450 (TG1), 450/550 (TG2) and 365/550 (TG3) days of age. The model included contemporary group (current farm, year and two-month period of birth, sex, and management group) and age of dam at calving, divided into classes as fixed effects. The model also included random effects for direct additive, maternal additive and maternal permanent environmental, and residual effects. The direct heritability estimates ranged from 0.23 to 0.39, 0.13 to 0.39 and 0.32 to 0.56 for weights at standard ages, weight gains and testicular measures, respectively. The genetic correlations between weights (0.69 to 0.94) and scrotal circumferences (0.91 to 0.97) measured at standard ages were higher than those between weight gain and testicular growth (0.18 to 0.97 and 0.36 to 0.77, respectively). The weights at standard ages responded more effectively to selection, and also gave strong correlations with the other traits.

Association between IGF2 and CYP21 gene polymorphisms and characteristics of economic interest in Nellore cattle.

We analyzed two single nucleotide polymorphisms (SNPs) of the IGF2 and CYP21 genes in Nellore cattle participating in the Brazilian Animal Breeding Program. The SNPs were found in exon 6 of the IGF2 (insulin-like growth factor 2) gene (RFLP/MboII) as well as in the promoter region of the CYP21 (steroid 21-hydroxylase) gene (RFLP/HpaII) of these animals. The TC heterozygotes were significantly more frequent than CC and TT homozygotes in the RFLP/MboII polymorphism. The T allele was significantly more frequent than the C allele in RFLP/HpaII polymorphism. This population was found to be in Hardy-Weinberg equilibrium for these SNPs. Association of these polymorphisms with expected progeny differences of reproductive and productive traits was investigated, but proved to be significant only for DP550 (expected progeny differenced for weight at 365 days - IGF2 - RFLP/MboII) and DP450 (expected progeny differenced for weight at 450 days - CYP21 - RFLP/HpaII). This is the first study on the occurrence of these two polymorphisms in this Zebu breed of cattle. A total of 147 Nellore animals participating in the Breeding Program of the Nellore Breed (PMGRN) under the management of the National Association of Breeders and Researchers (ANCP) in the city of Ribeirão Preto were analyzed.

Sexing single bovine blastomeres using TSPY gene amplification.

The testis-specific protein Y-encoded gene (TSPY) is a Y-specific gene present in variable copy number in many mammalian species, including cattle. We tested the applicability of the TSPY gene as a Y-specific marker to predict preimplantation embryo sex in Nelore (Bos indicus) cattle. Two blastomeres were removed from each embryo. A total of 36 single blastomeres and the remaining cells of their 18 matched in vitro conceived embryos were screened for TSPY amplification by nested-PCR. The results obtained from a single blastomere and the remaining cells of the same embryo were concordant in all cases. All blastomeres (16/16) from eight embryos produced with sexed sperm (specific for production of male embryos) were TSPY-positive. We conclude that TSPY is a good male-specific marker, the usefulness of which is probably enhanced by the high copy number. Other methods that are less time-consuming, such as real-time PCR, could be improved with the use of the TSPY gene sequences to generate primers and/or probes. This is the first report to demonstrate the applicability of the TSPY gene for sexing single cells in cattle.

Identification of a DNA methylation point in the promoter region of the bovine CYP21 gene.

The CYP21 (steroid 21-hydroxylase) gene is involved in the synthesis of steroid hormones. Bov-A2 is a retroposon that is common in ruminant genomes. The promoter region of bovine CYP21 contains a short interspersed nucleotide element of Bov-A2, which overlaps a putative Sp1 binding site. We looked for RFLP/HpaII polymorphism in the Bov-A2 element in bovine Zebu breeds by PCR-RFLP, and examined whether polymorphism in this element is associated with methylation. Among DNA samples from 135 Brazilian Zebu breed cattle, we identified an RFLP/HpaII polymorphism (T/C), which, based on a restriction methylation-sensitive assay employing HpaII and isoschizomer MspI enzymes (methylation-sensitive and -non-sensitive enzymes, respectively), appears to be a DNA methylation point. This is the first report of this polymorphism and on DNA methylation in the bovine CYP21 promoter region in Brazilian Zebu cattle.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.