Covariance functions for body weight from birth to maturity in Nellore cows

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

Development of an index that decreases birth weight, promotes postnatal growth and yet minimizes selection intensity in beef cattle

OBJECTIVE

The main goal of our current study was to improve the growth curve of meat animals by decreasing the birth weight while achieving a finishing weight that is the same as that before selection but at younger age.

METHODS

Random regression model was developed to derive various selection indices to achieve desired gains in body weight at target time points throughout the fattening process. We considered absolute and proportional gains at specific ages (in weeks) and for various stages (i.e., early, middle, late) during the fattening process.

RESULTS

The point gain index was particularly easy to use because breeders can assign a specific age (in weeks) as a time point and model either the actual weight gain desired or a scaled percentage gain in body weight.

CONCLUSION

The point gain index we developed can achieve the desired weight gain at any given postnatal week of the growing process and is an easy-to-use and practical option for improving the growth curve.

Longitudinal genetic dynamics of weaning index and implications for cow-calf production efficiency

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.

Genotype by Prenatal Environment Interaction for Postnatal Growth of Nelore Beef Cattle Raised under Tropical Grazing Conditions

The prenatal environment is recognized as crucial for the postnatal performance in cattle. In tropical regions, pregnant beef cows commonly experience nutritional restriction during the second half of the gestation period. Thus, the present study was designed to analyze the genotype by prenatal environment interaction (G × Epn) and to identify genomic regions associated with the level and response in growth and reproduction-related traits of beef cattle to changes in the prenatal environment. A reaction norm model was applied to data from two Nelore herds using the solutions of contemporary groups for birth weight as a descriptor variable of the gestational environment quality. A better gestational environment favored weights until weaning, scrotal circumference at yearling, and days to first calving of the offspring. The G × Epn was strong enough to result in heterogeneity of variance components and genetic parameters in addition to reranking of estimated breeding values and SNPs effects. Several genomic regions associated with the level of performance and specific responses of the animals to variations in the gestational environment were revealed, which harbor QTLs and can be exploited for selection purposes. Therefore, genetic evaluation models considering G × Epn and special management and nutrition care for pregnant cows are recommended.

Trace minerals source in calf starters interacts with birth weights to affect growth performance

The present study was conducted to investigate the effects of partial replacement of inorganic minerals (IM) with trace minerals in advance chelate components form in starter diets for calves of different birth weights on performance, health, and behavior of Holstein calves. Fifty-two calves were assigned to 1 of 4 treatments in a 2 × 2 factorial arrangement with two mineral sources (IM or advanced chelated minerals (ACMS)) and two birth weights (low or normal birth weight; LBW or NBW). Calves were weaned on d 56 and remained until d 71 of the study. Results showed that NBW calves had higher feed intake, withers and hip height, larger heart girth and lower fecal score than LBW calves throughout the study. Calves receiving ACMS tended to have higher feed intake, larger hip width, lower eye and nose scores, and lower rectal temperature throughout the study than IM calves. In addition, ACMS calves had larger abdominal girths at d 56 of the study compared to IM calves. Interactions between birth weights and mineral sources for preweaning average daily gain (ADG) and weaning and final BW showed that ACMS supplementation improved ADG and BW in LBW calves. Non-nutritive oral behavior was lower in ACMS calves compared to IM calves during all periods. Overall, ACMS feeding decreased non-nutritive oral behavior and improved calf health status during the study. In addition, feeding ACMS to dairy calves with LBW increased their ADG to a similar extent as to NBW calves, suggesting an improvement in their efficiency.

Selection effect for growth traits on energy requirements in beef Nelore steers

Growth data of 77,372 Nelore steers were used to estimate the selection effect on energy requirements considering two beef production systems: cow-calf and slaughter cycles. All the animals had measures from 120 days to 7 years old. The parameters necessary to evaluate the selection effect on energy requirements were obtained by random regression analysis using Legendre polynomials. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered random covariables. The coefficients from the model M3353_5 were used to calculate the genetic gains necessary to predict the increase in phenotypes. The selection was simulated for body weight (BW) and weight gain (WG) at different ages and energy requirements were calculated using NRC equations. The cost of feed was calculated for a cow-calf and slaughter cycle of production considering a system of Brachiaria decumbens pasture without supplementation. In slaughter system, the selection for weight of 365 days of age is the best option. In cow-calf systems, the selection W120 is the best choice.

Milk production potential and reproductive performance of Egyptian buffalo cows

Limited data are available on the phenotypic factors related to the productive and reproductive performance of Egyptian buffalo cows, based on a large sample size. This study aims to estimate the effect of phenotypic factors on productive and reproductive traits of Egyptian buffaloes. Data were collected from five dairy buffalo stations and include 3787 lactation records. For the analysis of variance, four seasons were considered in each year, and the parity included seven classes. Dry periods were divided into three intervals (< 90, 90-170, and > 170 d). Birth weight was divided into four categories (<25, 25-30, 31-35, and >35 kg). The results indicated that winter-calving buffaloes had the highest total milk yield (TMY) of the whole lactation, with the shortest (p<0.001) lactation length (LL), days open (DO), and calving interval (CI). Both, total milk TMY/kg and LL/days were increased (p<0.001), but the CI was linearly decreased (p<0.001). Overall, buffaloes with age at first mating (AFM<25month), age at first calving (AFC<35 month), and a dry period (DP<90days), produced the highest TMY (p<0.001) and maintained the longest LL (p<0.001). By increasing the body weight at birth (BWB), milk production level significantly increased. Buffaloes of BWB<25kg had the shortest DO (p<0.004; 168.10±3.598 days) and CI (p<0.006; 17.01±.135 months). In conclusion, body weight at birth, season, parity, DO, CI, AFM, AFC, and DP could be used as predictors to improve reproductive and productive traits in buffalo breeding programs. The wide range in milk yield and reproductive traits indicated significant potential in increasing the productive and reproductive performances of Egyptian buffalo cows.

Genetic parameters for weights from birth to 10 years of age in different beef cow breeds

Context Most Brazilian beef breeding programs perform selection for young bodyweight, which will inevitably increase mature weight due to the genetic correlation among weights at different ages. Aims The objective of the present study was to estimate genetic parameters for bodyweight from birth to maturity in Gir, Guzerat, Nelore and Caracu cows born between 1981 and 2014 at Centro APTA Bovinos de Corte, Instituto de Zootecnia, Sertãozinho, São Paulo, Brazil. Methods The model included the fixed effects of contemporary group (herd and year of birth), month of birth and previous reproductive status (calved = 1, or not calved = 0), the linear and quadratic effects of animal and cow age as covariates, and direct additive genetic, maternal genetic and maternal permanent environmental effects as random effects. The genetic parameters were estimated by univariate analysis of weights adjusted at birth, and at 120, 210, 378, 450 and 550 days of age, and annually from 2 to 10 years. In addition, multivariate analysis was performed considering weights at birth, and at 210 and 550 days, and at 5 years of age for all breeds. Key results For the different breeds, the heritability estimates ranged from 0.28 to 0.49 for birthweight, from 0.11 to 0.31 for weaning weight, from 0.25 to 0.43 for yearling weight, and from 0.25 to 0.69 for weights from 2 to 10 years of age. The genetic correlations were high and positive, indicating that selection at any age will affect weights at the other ages. Conclusions The results suggest the possibility of genetic progress for weights at different ages and the use of the young weights to monitor the mature weight of the animals. Implications As the trait most strongly correlated with mature weight was yearling weight, already used as the selection criteria for females in the breeding program of the Instituto de Zootecnia, selection indexes should be derived to keep the mature cow weight constant, since heavier cows could be undesirable for pasture-based Brazilian production systems.

Genetic analysis of live weight of local kids to promote genetic evaluations in the arid areas of Tunisia

Goat meat production, a widely extended activity in the more arid areas of Tunisia, relies on local breeds. These breeds are well adapted to produce under harsh conditions but have a very small size and low productivity. The aim of this study was to establish the basis for future genetic evaluations to improve growth potential of this local stock. A total of 13,095 body weights and pedigree of 945 kids in the caprine herd of the Arid Areas Institute of Médenine were used. Random regression (RR) and multiple trait (MT) models were analyzed and compared. All models included effects of age and weight of dam, age, sex and type of birth of the kid, and year × month of recording, plus random direct and maternal additive genetic and permanent environmental effects. RR and MT models behave similarly, with RR showing slightly better goodness of fit. Heritability estimates for direct (ranging from 0.15 to 0.4) and maternal (0.05 to 0.3) effects showed that efficient selection for weight is feasible in this population. Estimated correlations between ages were high (> 0.8) for direct effects across all ages and low (down to 0.2) for weights taken at distant ages for maternal effects. Estimated genetic correlations between direct and maternal components revealed an antagonistic relationship, especially at early ages. Recording of at least one weight in the first month of age of the kids to evaluate the maternal capacity and a later weight to evaluate direct effects on weight is recommended for genetic evaluations under field conditions.

Quantitative study of genetic gain for growth, carcass, and morphological traits of Nelore cattle

The aim of this study was to evaluate the genetic variability, genetic and phenotypic associations, and genetic gains of birth (BW), weaning (WW), and yearling (YW) weights, loin muscle area (LMA), backfat thickness (BF), rump fat thickness (RF), scores of body structure (BS), finishing precocity (FS), and muscling (MS) in Nelore cattle. Genetic parameters were obtained through Bayesian inference using BLUPF90 programs. All studied traits showed genetic variability, with heritability ranging from 0.29 to 0.47. In all studied ages, weights presented positive genetic correlations with LMA (ranging from 0.13 to 0.53), being generally stronger in comparison with the other carcass traits analyzed (BF and RF). Similarly, weights were higher genetic associated with BS (0.47–0.92) than with FS (0.18–0.62) and MS (0.22–0.65), respectively. The BF and RF showed positive and moderate genetic associations with FS and MS (0.31–0.36). Genetic trends were significant (P < 0.05) and favorable for WW, YW, and visual scores. Selection for increasing BW, WW, YW, and LMA will result in modest or no change in BF and RF (correlated response ranging from −0.04 to 0.07 mm per generation). In this population, carcass traits must be included in the selection indexes to obtain genetic gains in carcass quality, if desired.

Genetic trends and trade-offs between growth and reproductive traits in a Nellore herd

The knowledge of genetic trends and trade-offs between growth and reproductive traits might be useful to understand the evolution of these traits in livestock and natural populations of animals. We estimated the genetic trends and trade-offs between pre-weaning growth and calving intervals of Nellore animals from a commercial farm. Two-trait animal models were used to estimate covariance components and breeding values (EBV) for direct and maternal genetic effects of pre-weaning growth and direct genetic effects of calving intervals. Regression analyses were performed to examine the relationship between direct and maternal EBV of pre-weaning growth and direct EBV of calving intervals (dependent variables) and the coefficient of generation of each animal (independent variable). We also performed regression analyses to examine the relationship between direct EBV of calving intervals (dependent variables) and direct and maternal EBV of pre-weaning growth (independent variables). The genetic trends for direct and maternal genetic effect for pre-weaning growth were significant and presented genetic evolution in the studied Nellore herd. The genetic trends for the reproductive traits were also significant but indicated genetic changes in an unfavorable way. The genetic correlations between direct effects of pre-weaning growth and calving intervals traits and the genetic correlations between maternal effects of pre-weaning growth traits and direct effects of calving interval traits were not different from zero. The presence of trade-offs between the direct effects of growth and reproductive traits were confirmed through regression from direct EBV of calving intervals over EBV of pre-weaning growth traits. In addition, regression analyses showed that selection to increase pre-weaning growth also increased calving intervals. Our results showed that pre-weaning growth and calving intervals are increasing over generations and that trade-offs occurred between those traits in the studied Nellore herd.

Possibility of modifying the growth trajectory in Raeini Cashmere goat

The objective of this study was to investigate the possibility of modifying the growth trajectory in Raeini Cashmere goat breed. In total, 13,193 records on live body weight collected from 4788 Raeini Cashmere goats were used. According to Akanke's information criterion (AIC), the sing-trait random regression model included fourth-order Legendre polynomial for direct and maternal genetic effect; maternal and individual permanent environmental effect was the best model for estimating (co)variance components. The matrices of eigenvectors for (co)variances between random regression coefficients of direct additive genetic were used to calculate eigenfunctions, and different eigenvector indices were also constructed. The obtained results showed that the first eigenvalue explained 79.90% of total genetic variance. Therefore, changing the body weights applying the first eigenfunction will be obtained rapidly. Selection based on the first eigenvector will cause favorable positive genetic gains for all body weight considered from birth to 12 months of age. For modifying the growth trajectory in Raeini Cashmere goat, the selection should be based on the second eigenfunction. The second eigenvalue accounted for 14.41% of total genetic variance for body weights that is low in comparison with genetic variance explained by the first eigenvalue. The complex patterns of genetic change in growth trajectory observed under the third and fourth eigenfunction and low amount of genetic variance explained by the third and fourth eigenvalues.

Weight evaluation of Tabapuã cattle raised in northeastern Brazil using random-regression models

ABSTRACT The objective of this study is to compare random-regression models used to describe changes in evaluation parameters for growth in Tabapuã bovine raised in the Northeast of Brazilian. The M4532-5 random-regression model was found to be best for estimating the variation and heritability of growth characteristics in the animals evaluated. Estimates of direct additive genetic variance increased with age, while the maternal additive genetic variance demonstrated growth from birth to up to nearly 420 days of age. The genetic correlations between the first four characteristics were positive with moderate to large ranges. The greatest genetic correlation was observed between birth weight and at 240 days of age (0.82). The phenotypic correlation between birth weight and other characteristics was low. The M4532-5 random-regression model with 39 parameters was found to be best for describing the growth curve of the animals evaluated providing improved selection for heavier animals when performed after weaning. The interpretation of genetic parameters to predict the growth curve of cattle may allow the selection of animals to accelerate slaughter procedures.

MODELOS DE REGRESSÃO ALEATÓRIA PARA CARACTERÍSTICA DE CRESCIMENTO EM BOVINOS DA RAÇA GUZERÁ

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.

Random regression models to estimate genetic parameters for weights in Murrah buffaloes

This article reports genetic analysis of the weight at different ages of Murrah water buffaloes, using random regression models (RRM). Models ranging from third to sixth order polynomial were used to describe direct genetic and animal permanent environmental effects. Contemporary group was included as a fixed effect, and a cubic polynomial was used to model the mean curve of the population. The residual was modeled considering a log-linear function. Two models were selected for study of genetic parameters. The first model included third and sixth order polynomials for direct genetic and animal permanent environmental effects (M36). The second model included sixth order polynomials for all random effects (M66). The estimates of heritability varied from 0.16 + 0.04 (44 days) to 0.38 + 0.04 (568 days) for model M36 and from 0.16 + 0.05 (33 days) to 0.42 + 0.05 (600 days) for model M66. Regarding estimates of the correlation for all effects, the magnitude tended to decline with the increase of the time span between measurements. These results indicate that the species has potential for genetic selection based on weight at different ages, since we found favorable genetic variability within the herd, with selection likely to be more efficient at ages near 600 days.

Polynomials to model the growth of young bulls in performance tests

The use of polynomial functions to describe the average growth trajectory and covariance functions of Nellore and MA (21/32 Charolais+11/32 Nellore) young bulls in performance tests was studied. The average growth trajectories and additive genetic and permanent environmental covariance functions were fit with Legendre (linear through quintic) and quadratic B-spline (with two to four intervals) polynomials. In general, the Legendre and quadratic B-spline models that included more covariance parameters provided a better fit with the data. When comparing models with the same number of parameters, the quadratic B-spline provided a better fit than the Legendre polynomials. The quadratic B-spline with four intervals provided the best fit for the Nellore and MA groups. The fitting of random regression models with different types of polynomials (Legendre polynomials or B-spline) affected neither the genetic parameters estimates nor the ranking of the Nellore young bulls. However, fitting different type of polynomials affected the genetic parameters estimates and the ranking of the MA young bulls. Parsimonious Legendre or quadratic B-spline models could be used for genetic evaluation of body weight of Nellore young bulls in performance tests, whereas these parsimonious models were less efficient for animals of the MA genetic group owing to limited data at the extreme ages.

Genetic analysis of growth traits in Polled Nellore cattle raised on pasture in tropical region using Bayesian approaches

Components of (co)variance and genetic parameters were estimated for adjusted weights at ages 120 (W120), 240 (W240), 365 (W365) and 450 (W450) days of Polled Nellore cattle raised on pasture and born between 1987 and 2010. Analyses were performed using an animal model, considering fixed effects: herd-year-season of birth and calf sex as contemporary groups and the age of cow as a covariate. Gibbs Samplers were used to estimate (co)variance components, genetic parameters and additive genetic effects, which accounted for great proportion of total variation in these traits. High direct heritability estimates for the growth traits were revealed and presented mean 0.43, 0.61, 0.72 and 0.67 for W120, W240, W365 and W450, respectively. Maternal heritabilities were 0.07 and 0.08 for W120 and W240, respectively. Direct additive genetic correlations between the weight at 120, 240, 365 and 450 days old were strong and positive. These estimates ranged from 0.68 to 0.98. Direct-maternal genetic correlations were negative for W120 and W240. The estimates ranged from −0.31 to −0.54. Estimates of maternal heritability ranged from 0.056 to 0.092 for W120 and from 0.064 to 0.096 for W240. This study showed that genetic progress is possible for the growth traits we studied, which is a novel and favorable indicator for an upcoming and promising Polled Zebu breed in Tropical regions. Maternal effects influenced the performance of weight at 120 and 240 days old. These effects should be taken into account in genetic analyses of growth traits by fitting them as a genetic or a permanent environmental effect, or even both. In general, due to a medium-high estimate of environmental (co)variance components, management and feeding conditions for Polled Nellore raised at pasture in tropical regions of Brazil needs improvement and growth performance can be enhanced.

The influence of animals from embryo transfer on the genetic evaluation of growth in Simmental beef cattle by using multi-trait models

The weight records from Simmental beef cattle were used in a genetic evaluation of growth with or without the inclusion of animals obtained by embryo transfer. A multi-trait model in which embryo transfer individuals were excluded (MTM1) contained 29,510 records from 10,659 animals, while another model without exclusion of these animals (MTM2) contained 62,895 weight records from 23,160 animals. The weight records were adjusted for ages of 100, 205, 365, 450, 550 and 730 days. The (co)variance components and genetic parameters were estimated by the restricted maximum likelihood method. The (co)variance components were similar in both models, except for maternal permanent environment variance. Direct heritabilities (h(2) d) in MTM1 were 0.04, 0.11, 0.20, 0.27, 0.31 and 0.42, while in MTM2 they were 0.11, 0.11, 0.17, 0.21, 0.22 and 0.26 for 100, 205, 365, 450, 550 and 730 days of age, respectively. Estimates of h(2) d in MTM1 were higher than in MTM2 for the weight at 365 days of age. Genetic correlations between weights in both models ranged from moderate to high, suggesting that these traits may be determined mainly by the same genes. Animals from embryo transfer may be included in the genetic evaluation of Simmental beef cattle in Brazil; this inclusion may provide potential gains in accuracy and genetic gains by reducing the interval between generations.

Random regression models in the evaluation of the growth curve of Simbrasil beef cattle

Random regression models were used to estimate the types and orders of random effects of (co)variance functions in the description of the growth trajectory of the Simbrasil cattle breed. Records for 7049 animals totaling 18,677 individual weighings were submitted to 15 models from the third to the fifth order including as fixed effects sex, contemporary group, feeding regimen, and type of reproduction and as random effects additive direct genetic effect, animal permanent environment, maternal additive genetic effect, and maternal permanent environment. The best-fit model presented order five to additive direct genetic effect, animal permanent environment, and maternal additive effect, with 6 classes of residual variances, and the maternal permanent environment effect was not significant, likely owing to the low average number of calves per cow. However, the model chosen for the growth curve presents three classes of residual variances, because even not showing the best fit it is more parsimonious, in addition to promoting a more realistic estimate of heritability.

Analysis of longitudinal data of Nellore cattle from performance test at pasture using random regression model

This study was carried out to estimate (co)variance components and genetic parameters for live weight of Nellore cattle from Performance Test of Young Bulls using random regression models. Data of weights and ages of 925 weaned males was used. The animal model included the fixed effect of contemporary group, age of the animal at weighing as a covariate and as random effects it was considered the effect of additive genetic and permanent environment of the animal. The residue was modeled considering four classes of variances. The models were compared based on the Bayesian information criteria of Akaike and Schwartz. The model polynomial of fourth and sixth order for the direct additive genetic effects and permanent environment of the animal, respectively was the most appropriate to describe the changes in the variances of the weights during the period in which the animals participating in the performance test young bulls. Heritability estimates showed moderate magnitudes and indicated that direct selection will promote improvement of selection criteria adopted. Furthermore, due to high positive correlation between the estimated weights, it was suggested selecting the best animals before at 365 days of age, because it is the period in which the animals have a higher growth rate and thus you can select animals heavier and less delayed.

Evaluation of mature cow weight: genetic correlations with traits used in selection indices, correlated responses, and genetic trends in Nelore cattle

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.

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.

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.

MUC1 gene polymorphism in three Nelore lines selected for growth and its association with growth and carcass traits

The objective of this study was to describe the VNTR polymorphism of the mucin 1 gene (MUC1) in three Nelore lines selected for yearling weight to determine whether allele and genotype frequencies of this polymorphism were affected by selection for growth. In addition, the effects of the polymorphism on growth and carcass traits were evaluated. Birth, weaning and yearling weights, rump height, Longissimus muscle area, backfat thickness, and rump fat thickness, were analyzed. A total of 295 Nelore heifers from the Beef Cattle Research Center, Instituto de Zootecnia de Sertãozinho, were used, including 41 of the control line, 102 of the selection line and 152 of the traditional. The selection and traditional lines comprise animals selected for higher yearling weight, whereas control line animals are selected for yearling weight close to the average. Five alleles were identified, with allele 1 being the most frequent in the three lines, especially in the lines selected for higher means for yearling weight. Heterozygosity was significantly higher in the control line. Association analyses showed significant effects of allele 1 on birth weight and weaning weight while the allele 3 exert significant effects on yearling weight and back fat thickness. Despite these findings, application of this marker to marker-assisted selection requires more consistent results based on the genotyping of a larger number of animals in order to increase the accuracy of the statistical analyses.

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle

The objective of this work was to estimate covariance functions using random regression models on B-splines functions of animal age, for weights from birth to adult age in Canchim cattle. Data comprised 49,011 records on 2435 females. The model of analysis included fixed effects of contemporary groups, age of dam as quadratic covariable and the population mean trend taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were modelled through a step function with four classes. The direct and maternal additive genetic effects, and animal and maternal permanent environmental effects were included as random effects in the model. A total of seventeen analyses, considering linear, quadratic and cubic B-splines functions and up to seven knots, were carried out. B-spline functions of the same order were considered for all random effects. Random regression models on B-splines functions were compared to a random regression model on Legendre polynomials and with a multitrait model. Results from different models of analyses were compared using the REML form of the Akaike Information criterion and Schwarz' Bayesian Information criterion. In addition, the variance components and genetic parameters estimated for each random regression model were also used as criteria to choose the most adequate model to describe the covariance structure of the data. 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 adequate to describe the covariance structure of the data. Random regression models using B-spline functions as base functions fitted the data better than Legendre polynomials, especially at mature ages, but higher number of parameters need to be estimated with B-splines functions.