Context A frame score prediction equation developed specifically for Nellore cattle could be an auxiliary tool to improve mating decisions on the basis of feed resources and production-system objectives. Aims Estimate genetic parameters for frame by using a prediction equation developed for Nellore cattle and genetic associations between frame score (FRAME) and growth-, reproductive-, carcass- and feed efficiency-related traits, and five bioeconomic indexes. Methods Birth weight (BW), adjusted weight at 120 (W120), 210 (W210) and 450 (W450) days of age, adult weight (AW), age at first calving (AFC), probability of precocious calving (PPC30), stayability (STAY), accumulated cow productivity (ACP), adjusted scrotal circumference at 365 (SC365) and 450 (SC450) days of age, rib eye area (REA), subcutaneous backfat thickness (BFT), rump fat thickness (RFT), intramuscular fat percentage (IMF), residual feed intake (RFI) and dry-matter intake (DMI) were included in the analyses. Frame score was calculated using the multiple linear regression (MLR) prediction method. The estimation of genetic parameters was performed using a linear animal model, except for PPC30 and STAY, which were estimated through a threshold animal model. The correlated response in FRAME considering selection for growth-, reproductive-, carcass- and feed efficiency-indicator traits were obtained in the context of single-trait selection and a multiple-trait context. Key results Heritability estimated for FRAME was moderate (0.30 ± 0.09). Frame score showed moderate genetic correlations with growth traits, BW (0.51 ± 0.08), W120 (0.41 ± 0.07), W210 (0.35 ± 0.07) and W450 (0.29 ± 0.08). The genetic correlation estimates between FRAME and RFT was high (−0.84 ± 0.02), but low with ACP (0.25 ± 0.08) and RFI (0.10 ± 0.13). In the single-trait and multi-trait contexts, there was a lower correlated gain for FRAME when the selection was applied for traits commonly measured in beef cattle breeding programs. Conclusion Selection to increase growth traits would lead to an increase in frame size and herd nutritional requirements, and it would reduce the carcass fatness level and early heifer sexual precocity. FRAME could be an alternative trait to monitor calf birth weight. Implications Selection for FRAME is feasible, and the most suitable frame score value depends on the production system objectives and feed resources.

Context Livestock feed costs have a higher impact on the profitability of beef production systems and are directly related to feed efficiency. However, these traits are hard and have high costs to measure, reducing the availability of phenotypic records and reliability of genetic evaluations. Thus, the use of genomic information can increase the robustness of genetic studies that address them. Aims The aim of the present study was to estimate genetic parameters for feed efficiency, growth, reproductive and carcass traits in Nelore cattle and the correlated response among them, using genomic information. Methods Residual feed intake (RFI), dry-matter intake, feed conversion ratio, feed efficiency (FE), residual average daily gain (RG), residual feed intake and average daily gain (RIG), birthweight, weight at 120, 240, 365 and 450 days of age, scrotal circumference at 365 and 450 days of age, rib-eye area, backfat thickness and rump fat thickness were evaluated. The genetic parameters were estimated using the single-step genomic best linear unbiased prediction approach. Key results The FE-related traits showed low to moderate heritability ranging from 0.07 to 0.23. Feed efficiency-related traits showed low genetic correlations with reproductive (–0.24 to 0.27), carcass (–0.17 to 0.27) and growth (–0.19 to 0.24) traits, except for growth with dry-matter intake (0.32–0.56) and weight at 365 days of age with FE (–0.40). Conclusions The selection to improve growth, reproductive and carcass traits would not change RFI, RG and RIG. The choice of the most adequate selection criterion depends on the production system, that is, RFI might be used for low-input beef cattle systems, and RIG would be used for more intensive and without-any-dietary-restrictions beef cattle systems. Implications The estimates of heritability and genetic correlations suggest that genetic selection for feed efficiency using RFI, RG and RIG in Nellore cattle leads to higher genetic gain than does that using FE and feed conversion ratio without affecting other profitability traits.

Context The selection of animals for sexual precocity and reproductive efficiency is a trend to reduce the production cycle, promote higher economic viability to the system, increase selection intensity and higher genetic gain, as well to promote the profitability of production systems. To include these traits as selection criterion in cattle breeding programs, estimating genetic parameters and studying the possibility of obtaining genetic gains is required. The hypothesis tested was that the indicators of sexual precocity traits present genetic variance and moderate heritability that allows these to be used as a criterion of selection to obtain improvement for sexual precocity, without negative implications for the reproductive efficiency in Nellore cattle. Aims This study was carried out to estimate the genetic parameters for reproductive traits (scrotal circumference at 365 and 450 days of age, gestation length, days open, calving interval, real fertility, cumulative productivity, calf weight:cow weight ratio) and age at first conception and first calving in a Nellore cattle herd under selection for sexual precocity. Methods Data of reproductive traits and indicators of sexual precocity traits from 4081 Nellore cattle born between 2009 and 2015 were used. The covariance components, heritabilities and correlations were estimated using the restricted maximum likelihood method, available in the BLUPF90 package, in single- and multiple-trait animal mixed models. Key results Estimates of heritability and standard errors for scrotal circumference at 365 and 450 days of age, gestation length, days open, calving interval, real fertility, cumulative productivity, calf weight:cow weight ratio, age at first conception (AFCo) and age at first calving (AFCa) were 0.33 ± 0.03, 0.33 ± 0.01, 0.23 ± 0.03, 0.34 ± 0.11, 0.23 ± 0.12, 0.21 ± 0.16, 0.23 ± 0.08, 0.25 ± 0.10, 0.21 ± 0.08 and 0.24 ± 0.08 respectively. The genetic correlations estimated between AFCo and the other reproductive traits ranged from –0.61 to 0.14 (standard error 0.1–0.21), and between AFCa and the other reproductive traits ranged from –0.60 to 0.16 (standard error 0.1–0.19), all of them in a favourable direction. Conclusions Selection for sexual precocity based on AFCo and AFCa may promote improvement in reproductive efficiency and fertility, except for the calf weight:cow weight ratio, whose correlation was close to zero. Implications The estimates of heritabilities and genetic correlations suggest that selection programs for reproductive traits and indicators of sexual precocity traits for the Nellore breed may provide genetic gain. In addition, considering the genetic correlation obtained between AFCo and AFCa (0.96), when the selection objective is to increase the sexual precocity of heifers, we could use the age of the first conception as criterion, as the measurement of this trait occurs at a lower age at first calving, which implies reducing the time required for animal evaluation and decision-making.

This study aimed to identify genomic regions influencing growth traits in Nellore cattle and evaluate the predictive ability of each trait based on results obtained from single-step genome-wide association analyzes (ssGWAS) considering different single nucleotide polymorphims (SNP) densities of markers. The National Association of Breeders and Researchers provided the dataset, from eighteen Nellore herds participating of the Nellore Brazilian breeding program. The traits birth weight (BW), adjusted weight at 210 (W210) and at 450 (W450) days of age and adult cow weight (ACW) were considered. A total of 963 animals, genotyped using the Illumina BovineHD BeadChip, were used as a reference population to impute genotypes of 7,689 animals, genotyped in low-density panel. Genotype imputation was performed using the FImpute 2.2 software. The ssGWAS was used to identify genomic regions associated to growth traits. Several genes in enrichment analysis were related to muscle and adipose tissue development and metabolism, feed efficiency, milk composition and maternal behavior. The predictive ability varied from low (0.10) to moderate (0.68). The predictive ability and bias for both panels were similar for all traits. The results found in this study should improve the understanding of genetic and physiologic mechanism associated with growth traits. However, the association of these results with other approaches, like system biologic and other omics information should improve the identification of causative genetic variants in growth traits in indicine 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.

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.

The aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). A pedigree structure containing the identification of the animal's sire and dam was used, with the relationship matrix comprising a total of 6,511 animals. Genotypic data from 1,201 animals were obtained using low-density panel (Clarifide Nelore 3.1) encompassing over 29,001 single nucleotide polymorphisms (SNP) markers. A threshold sire-maternal grandsire model (S-MGS) was used to estimate the genetic parameters, which included sire, maternal grandsire and residual effects as random effects and the fixed effects of contemporary groups (farm and year of calving, sex) and birth weight of the calf as covariable (linear effect). Genomic breeding values were estimated using an animal model with the direct and maternal genetic variances which were previously obtained by means of a S-MGS threshold model. The direct and maternal heritability estimates for CE were obtained considering the covariance of direct and maternal effects fixed as zero. Regions that accounted for more than 0.5% of the additive genetic variance were used. The direct and maternal heritability estimates for CE were low (0.18) and moderate (0.39) respectively, indicating that genetic progress for this trait is feasible, and so, it would respond favorably to direct selection. Genes identified within the significant windows, such as CA8, FAM110B, TOX, ARID1A, RBM15, HSF1 and PLAG1 were found to be related with maternal and direct effects on CE. Gene enrichment analysis revealed processes that might directly influence fetal processes involved in female pregnancy and stress response. These results should help to better understand the genetic and physiological mechanisms regulating placenta development and fetal development, and this information might be useful for future genomic studies in Nellore cattle.

RESUMO 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.

We assessed whether single nucleotide polymorphisms (SNPs) in the genes beta 1,4galactosyltransferase (B4GALT1), luteinizing hormone receptor (LHR), follicle-stimulating hormone receptor (FSHR) and insulin-like growth factor 2 (IGF2) could be molecular markers for scrotal circumference (SC) in Nellore bulls. Animals with positive (+, n = 104) and negative (-, n = 74) expected progeny difference for scrotal circumference at 365 days (EPD SC 365) were selected and their SNPs were analyzed by restriction fragment length polymorphism (RFLP). The correlation between EPD SC 365 and expected progeny difference for age at first birth (EPD AFB) was also investigated. The SNPs in B4GALT1 and FSHR was not different between two groups analyzed. The CC genotype for LHR gene was most frequent in animals with EPD SC 365(+), whereas the TT was most frequent in the EPD SC 365(-). For IGF2 the CT and CC were the most frequent genotypes observed in animals with positive and negative EPD SC 365, respectively. The EPD SC 365 was negatively correlated with the EPD AFB (r = 0.23). We suggest that CC and TT genotypes for LHR and IGF2, respectively, could be possible molecular markers for SC selection in Nellore bulls, that can also predict for AFB.

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. (C) 2017 Elsevier Inc. All rights reserved.

Cow longevity measured by age at last calving was evaluated using a censorship criterion that consisted of the difference between the dates of age at last calving and the last calving on the farm. If this difference was greater than certain value, the cow failed, indicating that it should be discarded. Otherwise, the cow was censored indicating the possibility of future calving. The aim of this study was to estimate heritability and breeding values of bulls for longevity considering three different censorship criteria, 16, 26 and 36 months, using Weibull proportional hazard sire model. The 16-month criterion was proposed because it is the estimated average interval between births in Nellore. The 26-month criterion was proposed because it is an average value between 16 and 36 months. Lastly, the 36-month criterion was considered a long time interval for the cow have a new calving. The Spearman correlation test was used to compare the rankings of the bulls regarding the estimates of breeding values for longevity considering the different censorship criteria. The records of 21996 Nellore cows were used. The cows were the daughters of 2113 bulls from 13 farms that participate in the Nellore breeding program of the National Association of Breeders and Researchers (ANCP). Age at first calving was considered a fixed effect while the random effect was the contemporary group (season, year of birth, and herd) and sire. Heritability estimates for cow age at last calving were 0.1020, 0.1002 and 0.0871 for the 16, 26 and 36-month censorship criteria, respectively. The Spearman correlation estimates of sires’ rankings were −0.2124, 0.1348 and 0.1211 (P > 0.05) for the censorship criteria of 16–26 months, 16–36 months, and 26 and 36 months, respectively. Despite of the little genetic variance to age at last calving, this values were higher than those reported in the literature. The accuracy of the selected bulls varies depending on the criteria adopted. The Weibull proportional hazard sire model predicted the highest reliabilities for the 16-month criterion, compared to other censorship criteria studied, which can lead to increasing of reproductive and productive efficiency of cows in the herd, since the lower open days of cows and higher number of calves per cow in her productive life.

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 (BS W , FP W , and MS W ) and yearling (BS Y , FP Y , and MS Y ) 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 BS W , FP W , MS W , W210, BS Y , FP Y , MS Y , 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.

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.

SUMMARYGenetic parameters for visual assessment traits measured at 487 days of age (body structure (BS), finishing precocity (FP) and muscling (MS)), body weight at 450 days of age (W450), age at first calving (AFC), heifer pregnancy (HP) and stayability (STAY, i.e. the probability of a cow to produce at least three calves before reaching 76 months of age) were estimated in Nellore cattle, seeking to include these traits in the selection criteria for dams. The statistical models included additive genetic and residual random effects using single- and two-trait Bayesian analyses. The average heritability estimates were equal to 0·37 for BS, 0·42 for FP, 0·37 for MS and 0·48 for W450. Age at first calving had a low average heritability estimate (0·13), while HP and STAY estimates were higher (0·36 and 0·24, respectively). The genetic correlations between AFC, HP and STAY with visual assessment traits and body weight were favourable, indicating that selecting animals with higher BS, FP, MS and W450 values will result in the indirect selection of animals with lower AFC and successful scores for HP and STAY. The selection of heifers that present an early pregnancy should anticipate AFC and improve HP in the current herd. Except for AFC, the heritability and genetic correlation estimates between the studied traits justify their inclusion in the selection criteria of the Nellore breeding programme.

The objective of this study was to investigate the application of BLUP and ssGBLUP in different scenarios of uncertain paternity using data from a Nellore cattle population. The analyzed data set was provided by the National Association of Farmers and Researchers (ANCP). The data set contained information from 18 Nellore herds located in the southeast and mid-west regions of Brazil, which participate in the ANCP breeding program. A total of 60,325 records for weight adjusted at 450 days (W450) were used. The mean value ± standard deviation was 290.20 ± 50.26 kg, and the contemporary groups (CG) were defined as farm, year of birth, season of birth, sex and management group. Records with values above or below the range of 3.5 standard deviations from the CG mean were excluded, as well as CGs with less than five animals. The variance components were estimated using BLUP and ssGBLUP methods. The relationship matrix (A) was created with different proportions of animals with unknown sires (0, 25, 50, 75, and 100% of multiple sires). All models included contemporary groups as fixed effects. The breeding value (EBV/GEBV) accuracy was calculated according to BIF and evaluated in each scenario with eight groups of animals: ALL = all animals in the population, BULL = only bulls with ten or more progenies, GEN = genotyped animals, GENwithPHEN = genotyped animals with phenotypes, GENwithoutPHEN = genotyped animals without phenotypes, YOUNG = male and female young animals without phenotypes, YwithoutGEN = young animals without phenotypes and genotypes, and YwithGEN = young animals without phenotypes and with genotypes. The additive genetic variance decreases as the proportion of multiple sire increased in the population for both methods. Prediction accuracies ranged from 0.02 to 0.46 and from 0.12 to 0.48 for BLUP and ssGBLUP, respectively. In general, for all scenarios, the EBV/GEBV prediction accuracy decreased as the proportion of MS in the population increased; however, the decrease of EBV accuracy was more intense compared to GEBV accuracy, which was of 8.8%, 4.3%, 46.2%, 27.3%, 82.4%, 25.0%, 18.8%, and 87.5% for ALL, BULL, GEN, GENwithPHE, GENwithoutPHE, YOUNG, YwithoutGEN, and YwithGEN groups, respectively. The breeding values for W450 were influenced by presence of the paternity uncertainly in the pedigree. The presence of paternity uncertainly affects more intensively the breeding value of young animals. The genotyped young animals were benefited from the application of ssGBLUP, particularly in situations with missing pedigree.

This study evaluated a Tabapuã population structure and the linear relationship of the inbreeding coefficient with phenotypic values of weaning weight adjusted to 210 days of age (W210); age at first calving (AFC); first (CI1), second (CI2) and average (ACI) calving intervals; and, accumulated productivity (ACP). The phenotypic data used were from 7340 cows and the pedigree file had 15,241 animals. The average pedigree completeness of the last six generations was 47.99%. The effective numbers of founders and ancestors were 124 and 110, respectively, with a ratio of 1.13. These results suggested the absence of the genetic bottleneck effect. The inbreeding coefficient increased over generations and the average was 0.007. The effective population size became small in the last generation. The regression analysis results of phenotypic values for inbreeding coefficients were not significant (P>0.05) for W210, CI1 and ACP; and, significant (P<0.05) and favorable for AFC, ACI and CI2. The results indicated that mating between related animals and the intensive use of few breeders should be avoided. Regression analysis indicated no inbreeding depression, which can be justified by the fact that inbreeding is not yet strongly established.

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.

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.