Accuracy of genomic predictions in Gyr (Bos indicus) dairy cattle.

Genomic selection may accelerate genetic progress in breeding programs of indicine breeds when compared with traditional selection methods. We present results of genomic predictions in Gyr (Bos indicus) dairy cattle of Brazil for milk yield (MY), fat yield (FY), protein yield (PY), and age at first calving using information from bulls and cows. Four different single nucleotide polymorphism (SNP) chips were studied. Additionally, the effect of the use of imputed data on genomic prediction accuracy was studied. A total of 474 bulls and 1,688 cows were genotyped with the Illumina BovineHD (HD; San Diego, CA) and BovineSNP50 (50K) chip, respectively. Genotypes of cows were imputed to HD using FImpute v2.2. After quality check of data, 496,606 markers remained. The HD markers present on the GeneSeek SGGP-20Ki (15,727; Lincoln, NE), 50K (22,152), and GeneSeek GGP-75Ki (65,018) were subset and used to assess the effect of lower SNP density on accuracy of prediction. Deregressed breeding values were used as pseudophenotypes for model training. Data were split into reference and validation to mimic a forward prediction scheme. The reference population consisted of animals whose birth year was ≤2004 and consisted of either only bulls (TR1) or a combination of bulls and dams (TR2), whereas the validation set consisted of younger bulls (born after 2004). Genomic BLUP was used to estimate genomic breeding values (GEBV) and reliability of GEBV (R2PEV) was based on the prediction error variance approach. Reliability of GEBV ranged from ∼0.46 (FY and PY) to 0.56 (MY) with TR1 and from 0.51 (PY) to 0.65 (MY) with TR2. When averaged across all traits, R2PEV were substantially higher (R2PEV of TR1 = 0.50 and TR2 = 0.57) compared with reliabilities of parent averages (0.35) computed from pedigree data and based on diagonals of the coefficient matrix (prediction error variance approach). Reliability was similar for all the 4 marker panels using either TR1 or TR2, except that imputed HD cow data set led to an inflation of reliability. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. A reduced panel of ∼15K markers resulted in reliabilities similar to using HD markers. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information.

Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips.

Genotype imputation is widely used as a cost-effective strategy in genomic evaluation of cattle. Key determinants of imputation accuracies, such as linkage disequilibrium patterns, marker densities, and ascertainment bias, differ between Bos indicus and Bos taurus breeds. Consequently, there is a need to investigate effectiveness of genotype imputation in indicine breeds. Thus, the objective of the study was to investigate strategies and factors affecting the accuracy of genotype imputation in Gyr (Bos indicus) dairy cattle. Four imputation scenarios were studied using 471 sires and 1,644 dams genotyped on Illumina BovineHD (HD-777K; San Diego, CA) and BovineSNP50 (50K) chips, respectively. Scenarios were based on which reference high-density single nucleotide polymorphism (SNP) panel (HDP) should be adopted [HD-777K, 50K, and GeneSeek GGP-75Ki (Lincoln, NE)]. Depending on the scenario, validation animals had their genotypes masked for one of the lower-density panels: Illumina (3K, 7K, and 50K) and GeneSeek (SGGP-20Ki and GGP-75Ki). We randomly selected 171 sires as reference and 300 as validation for all the scenarios. Additionally, all sires were used as reference and the 1,644 dams were imputed for validation. Genotypes of 98 individuals with 4 and more offspring were completely masked and imputed. Imputation algorithms FImpute and Beagle v3.3 and v4 were used. Imputation accuracies were measured using the correlation and allelic correct rate. FImpute resulted in highest accuracies, whereas Beagle 3.3 gave the least-accurate imputations. Accuracies evaluated as correlation (allelic correct rate) ranged from 0.910 (0.942) to 0.961 (0.974) using 50K as HDP and with 3K (7K) as low-density panels. With GGP-75Ki as HDP, accuracies were moderate for 3K, 7K, and 50K, but high for SGGP-20Ki. The use of HD-777K as HDP resulted in accuracies of 0.888 (3K), 0.941 (7K), 0.980 (SGGP-20Ki), 0.982 (50K), and 0.993 (GGP-75Ki). Ungenotyped individuals were imputed with an average accuracy of 0.970. The average top 5 kinship coefficients between reference and imputed individuals was a strong predictor of imputation accuracy. FImpute was faster and used less memory than Beagle v4. Beagle v4 outperformed Beagle v3.3 in accuracy and speed of computation. A genotyping strategy that uses the HD-777K SNP chip as a reference panel and SGGP-20Ki as the lower-density SNP panel should be adopted as accuracy was high and similar to that of the 50K. However, the effect of using imputed HD-777K genotypes from the SGGP-20Ki on genomic evaluation is yet to be studied.

Genome-wide association with residual body weight gain in Bos indicus cattle.

Weight gain is a key performance trait for beef cat-tle; however, attention should be given to the production costs for better profitability. Therefore, a feed efficiency trait based on per-formance can be an interesting approach to improve performance without increasing food costs. To identify candidate genes and ge-nomic regions associated with residual body weight gain (RWG), we conducted a genome-wide association study (GWAS) with 720 Nellore cattle using the GRAMMAR-Gamma association test. We identified 30 significant single nucleotide polymorphisms (SNPs), especially on chromosomes 2, 8, 12, and 17. Several genes and quantitative train loci (QTLs) present in the regions identified were appointed; we highlight DMRT2 (doublesex and mab-3 related tran-scription factor 2), IFFO2 (intermediate filament family orphan 2), LNX2 (ligand of numb-protein X 2), MTIF3 (mitochondrial transla-tional initiation factor 3), and TRNAG-CCC (transfer RNA glycine anticodon CCC). The metabolic pathways that can explain part of the phenotypic variation in RWG are related to oxidative stress and muscle control.

A genomewide association mapping study using ultrasound-scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle.

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.

Genome-wide association study for feedlot average daily gain in Nellore cattle (Bos indicus).

The genome-wide association study (GWAS) results are presented for average daily gain (ADG) in Nellore cattle. Phenotype of 720 male Bos indicus animals with information of ADG in feedlots and 354,147 single-nucleotide polymorphisms (SNPs) obtained from a database added by information from Illumina Bovine HD (777,962 SNPs) and Illumina BovineSNP50 (54,609) by imputation were used. After quality control and imputation, 290,620 SNPs remained in the association analysis, using R package Genome-wide Rapid Association using Mixed Model and Regression method GRAMMAR-Gamma. A genomic region with six significant SNPs, at Bonferroni-corrected significance, was found on chromosome 3. The most significant SNP (rs42518459, BTA3: 85849977, p = 9.49 × 10(-8)) explained 5.62% of the phenotypic variance and had the allele substitution effect of -0.269 kg/day. Important genes such as PDE4B, LEPR, CYP2J2 and FGGY are located near this region, which is overlapped by 12 quantitative trait locus (QTLs) described for several production traits. Other regions with markers with suggestive effects were identified in BTA6 and BTA10. This study showed regions with major effects on ADG in Bos indicus in feedlots. This information may be useful to increase the efficiency of selecting this trait and to understand the physiological processes involved in its regulation.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

Genetic analysis of feet and leg conformation traits in Nelore cattle.

Feet and leg conformation scores are important traits in beef cattle because they encompass a wide range of locomotion disorders that can lead to productive and reproductive losses. Thus, the study of feet and legs in beef cattle is essential for evaluating possible responses to selection focusing on minimizing economic losses caused by the occurrence of feet and leg problems. The aim of this study was to estimate variance components for feet and leg conformation traits in Nelore cattle. The data set contained records of approximately 300,000 animals that were born between 2000 and 2013. These animals belonged to the commercial beef cattle breeding program of the CRV Lagoa (). Feet and legs were evaluated by assigning visual scores at 2 different time points: feet and leg evaluated as a binary trait (FL1), measured at yearling (about 550 d of age) to identify whether (or not) an animal has feet and leg defects, and feet and leg score (FL2), ranging from 1 (less desirable) to 5 (more desirable) was assigned to the top 20% of animals according to the selection index adopted by the beef cattle breeding program, which was measured 2 to 5 mo after the yearling evaluation. The FL1 and FL2 traits were analyzed together with yearling weight (YW). The (co)variance components and breeding values were estimated by Bayesian inference using 2-trait animal models. The posterior means (standard errors) of the heritabilities for FL1, FL2, and YW were 0.18 (0.04), 0.39 (0.07), and 0.47 (0.01), respectively. The results indicate that the incidence of feet and leg problems in this population might be reduced by selection. The genetic correlation between FL1 and FL2 (-0.47) was moderate and negative as expected because the classification score that holds up each trait has opposite numerical values. The genetic trends estimated for FL1 and FL2 (-0.042 and 0.021 genetic standard deviations per year, respectively) were favorable and they indicate that the independent culling strategy for feet and leg problems promotes favorable changes and contributes to the genetic progress of these traits in the population under study.

Genetic analysis of the temperament of Nellore cattle using linear and threshold models.

Temperament is an important trait for the management and welfare of animals and for reducing accidents involving people who work with cattle. The present study aimed to estimate the genetic parameters related to the temperament score (T) and weaning weight (WW) of Nellore cattle, reared in a beef cattle breeding program in Brazil. Data were analyzed using two different two-trait statistical models, both considering WW and T: (1) a linear-linear model in which variance components (VCs) were estimated using restricted maximum likelihood; and (2) a linear-threshold model in which VCs were estimated via Bayesian inference. WW was included in the analyses of T to minimize any possible effects of sequential selection and to allow for estimation of the genetic correlation between these two traits. The heritability estimates for T were 0.21 ± 0.003 (model 1) and 0.26 (model 2, with a 95% credibility interval (95% CI) of 0.21 to 0.32). The estimated genetic correlations between WW and T were of a moderate magnitude (-0.33 ± 0.01 (model 1) and -0.34 (95% CI: -0.40, -0.28, model 2). The genetic correlations between the estimated breeding values (EBVs) obtained for the animals based on the two models were high (>0.92). The use of different models had little influence on the classification of animals based on EBVs or the accuracy of the EBVs.

Body condition score of Nellore beef cows: a heritable measure to improve the selection of reproductive and maternal traits.

Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.

Genetic relationship among reproductive traits in Nellore cattle.

In order to achieve improvements in production efficiency in livestock, herds of high sexual precocity and good fertility are needed. These traits increase the availability of animals in herd, either for sale or selection, allowing both greater selective intensity and greater genetic progress. This study aimed at estimating genetic parameters for reproductive traits measured directly in females in order to verify whether they could be used as selection criteria for genetic improvement in Nellore cows, as well as estimating the genetic relationship among these traits and scrotal circumference (SC), the traditional selection criterion for sexual precocity in cattle. In addition to SC, stayability (STAY), number of calvings at 53 months (NC53) and heifers rebreeding (HR) were studied. The (co)variances and genetic parameters were estimated using Bayesian inference. STAY, NC53 and HR were analyzed assuming a threshold model, whereas SC was analyzed with a linear model. Heritability estimated for NC53 was 0.22, and this trait was strongly and positively correlated with STAY, meaning selection for NC53 would improve productive longevity of Nellore cows. Correlations estimated between HR and STAY (≈0.97) and between HR and NC53 (≈0.99) allow an improvement on HR rates if selection was applied to traits related to longevity. Genetic correlations among SC and female reproductive traits were positive but weak, suggesting the need to use reproductive traits directly measured in females in order to obtain greater improvements in sexual precocity and longevity.

Genetic parameters for an alternative criterion to improve productive longevity of Nellore cows.

Number of calvings at 53 mo (NC53) was proposed as an alternative selection criterion to improve productive longevity of Nellore cows. This study was carried out to estimate variance components for NC53 by assuming different models, so that the potential for using this selection criterion to improve fertility of Nellore cows could be assessed. Genetic correlations between NC53, number of calvings at 89 mo (NC89), and 2 selection indexes used in this breed were also estimated. The NC53 trait is moderately heritable (posterior mean heritability ≈ 0.17) and selecting for this criterion could improve productive longevity of Nellore cows. Greater response to selection is expected by fitting a threshold animal model for this trait, rather than a linear animal model. Greater accuracy of prediction for this criterion could be achieved by fitting a threshold-linear model, considering this trait and a selection index composed by traits evaluated at weaning and long-yearling.

Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle.

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.