Genome-wide association study provides insights into genes related with horn development in Nelore beef cattle.

The causal mutation for polledness in Nelore (Bos taurus indicus) breed seems to have appeared first in Brazil in 1957. The expression of the polled trait is known to be ruled by a few groups of alleles in taurine breeds; however, the genetic basis of this trait in indicine cattle is still unclear. The aim of this study was to identify genomic regions associated with the hornless trait in a commercial Nelore population. A total of 107,294 animals had phenotypes recorded and 2,238 were genotyped/imputed for 777k SNP. The weighted single-step approach for genome-wide association study (WssGWAS) was used to estimate the SNP effects and variances accounted for by 1 Mb sliding SNP windows. A centromeric region of chromosome 1 with 3.11 Mb size (BTA1: 878,631-3,987,104 bp) was found to be associated with hornless in the studied population. A total of 28 protein-coding genes are mapped in this region, including the taurine Polled locus and the IFNAR1, IFNAR2, IFNGR2, KRTAP11-1, MIS18A, OLIG1, OLIG2, and SOD1 genes, which expression can be related to the horn formation as described in literature. The functional enrichment analysis by DAVID tool revealed cytokine-cytokine receptor interaction, JAK-STAT signaling, natural killer cell mediated cytotoxicity, and osteoclast differentiation pathways as significant (P < 0.05). In addition, a runs of homozygosity (ROH) analysis identified a ROH island in polled animals with 2.47 Mb inside the region identified by WssGWAS. Polledness in Nelore cattle is associated with one region in the genome with 3.1 Mb size in chromosome 1. Several genes are harbored in this region, and they may act together in the determination of the polled/horned phenotype. Fine mapping the locus responsible for polled trait in Nelore breed and the identification of the molecular mechanisms regulating the horn growth deserve further investigation.

Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data.

The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty.

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle.

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.

Bayesian inference in genetic parameter estimation of visual scores in Nellore beef-cattle

The aim of this study was to estimate the components of variance and genetic parameters for the visual scores which constitute the Morphological Evaluation System (MES), such as body structure (S), precocity (P) and musculature (M) in Nellore beef-cattle at the weaning and yearling stages, by using threshold Bayesian models. The information used for this was gleaned from visual scores of 5,407 animals evaluated at the weaning and 2,649 at the yearling stages. The genetic parameters for visual score traits were estimated through two-trait analysis, using the threshold animal model, with Bayesian statistics methodology and MTGSAM (Multiple Trait Gibbs Sampler for Animal Models) threshold software. Heritability estimates for S, P and M were 0.68, 0.65 and 0.62 (at weaning) and 0.44, 0.38 and 0.32 (at the yearling stage), respectively. Heritability estimates for S, P and M were found to be high, and so it is expected that these traits should respond favorably to direct selection. The visual scores evaluated at the weaning and yearling stages might be used in the composition of new selection indexes, as they presented sufficient genetic variability to promote genetic progress in such morphological traits.

Parâmetros genéticos para idade ao primeiro parto estimados por diferentes modelos para rebanhos da raça Nelore / Genetic parameters for age at first calving estimated by different models for Nellore breed herds

Com objetivo de estimar parâmetros genéticos e estudar a utilização de diferentes efeitos em avaliações genéticas para idade ao primeiro parto (IPP) por diferentes modelos, foram utilizados registros de IPP de animais da raça Nelore, nascidos entre os anos de 1990 e 2005. Foram considerados os seguintes modelos (M): M1, incluindo o efeito fixo de GC1 (constituído pelos animais nascidos na mesma fazenda e ano), além da covariável, peso aos 365 dias de idade (efeito linear e quadrático), totalizando 24.263 registros de IPP; M2, considerando os efeitos fixos de GC1, ano e estação de parição, totalizando 59.792 registros de IPP e M3, incluindo os efeitos fixos de GC2 (agrupando os animais nascidos na mesma fazenda, ano e que conceberam no mesmo manejo reprodutivo), ano e estação de parição, totalizando 59.792 registros de IPP. As estimativas dos componentes de variância e herdabilidade e os valores genéticos (VG) foram obtidos pelo método da máxima verossimilhança restrita, com a inclusão da matriz de parentesco disponível. As diferenças esperadas na progênie (DEPs) foram obtidas dividindo os VG por dois. Após a obtenção desses resultados, foram realizadas correlações entre os VG e o ranqueamento das DEPs dos reprodutores para IPP, utilizando-se o procedimento PROC CORR (SAS, 2003). Ao se considerar o ano e a estação de parto nos modelos de análise (M2 e M3), esses produziram um maior R², indicando que tais modelos conseguiram explicar, em maior grau, as diferenças existentes entre os animais para IPP. As herdabilidades estimadas foram de baixa magnitude (0,14 e 0,15). As correlações entre os VG obtidas por diferentes modelos foram 0,73 (M1 x M2); 0,91 (M2 x M3) e 0,66 (M1 x M3).

With the objective of estimate genetic parameters and study the utilization of different effects on the genetic evolution for the age of the first calving (AFC) by different models, they were used AFC records from Nellore breed animals, born from 1990 to 2005. They were considered the following models (M): M1, including the fixed effect of the contemporary group (CG), CG1 (grouping the animals that were born at the same farm and year), besides the co variable, weight at 365 days of age (linear and quadratic effects), totalizing 24,263 records of AFC; M2, considering the effects of CG1, year and season of the calving, totalizing 59,792 records of AFC and M3, including effects CG2 (grouping the animals born at the same farm, year and submitted at the same reproductive management), year and season of calving totalizing 59,792 records of AFC. The components of variance and Genetic Value (GV) were obtained by Restricted Maximun Likelihood Method, with the inclusion for the relationship matrix. The Differences Expected on the Progeny (DEPs) were obtained by dividing the GV by two, after this they were estimated the correlations between GV and ranks of the reproductor's DEPs for AFC, utilizing the procedure CORR (SAS, 2003). While considering year and season of calving in the analysis models (M2 and M3), it was produced a bigger R², indicating that those models could explain, in a larger scale, the existing differences between the animals for AFC. The heritabilities estimated were of low magnitude (0,14 and 0,15). The correlations between the GV obtained by the different models were .73 (M1 x M2); .91 (M2 x M3) and .66 (M1 x M3).

Bayesian inference on field data for genetic parameters for some reproductive and related traits of Nellore cattle (Bos indicus)

We used Gibbs sampling in single and two-trait animal models to estimate genetic parameters for some reproductive and related traits of Nellore cattle (Bos indicus). Female traits were age at first calving (AFC), cumulative productivity (CP) and adult weight (AW). For males, scrotal circumferences at 365 and 450 days of age were analyzed. Gibbs sampling using the Multiple Trait using Gibbs Sampling under Animal Model (MTGSAM) program of Van Tassel and Van Vleck was used to estimate the (co) variance components of the traits and conduct genetic analyses. Heritabilities were AFC = 0.26, AW = 0.36 and CP = 0.25 under the single-trait animal model. The mean, mode and median estimates for genetic parameters obtained from the marginal posterior distributions were similar for all traits except AW, which presented lower values for the mode than the mean and median. However, the marginal posterior distributions for the traits studied presented a tendency toward normality. Favorable, but low, negative genetic correlations were found between male scrotal circumference and female age at first calving. The reproductive traits showed medium-magnitude heritabilities, which indicates that these traits should respond to selection and therefore should be included in genetic improvement programs.

Bayesian inference in a quantitative genetic study of growth traits in Nelore cattle (Bos indicus)

The objective of this study was to estimate (co)variance components and genetic parameters for weights (W) and scrotal circumferences (SC) at 365 and 450 days of age, of Nelore (Bos indicus) cattle, using Bayesian inference in single and multiple-trait animal models. The fitted linear models included, besides the animal and residual random effects, the contemporary group (herd-year-season-sex-management group) and age-of-dam as "fixed effects". The analyses were carried out using a Gibbs sampler implemented through the MTGSAM program. The heritabilities (in parentheses) obtained fitting single-trait models were W365 (0.49), W450 (0.52), SC365 (0.68) and SC450 (0.66). Estimates of means, modes and medians for genetic parameters obtained from marginal posterior distributions were similar for all traits. The W365 and SC365 can be considered as suitable traits to be included as selection criteria in genetic improvement programs, not only because of their relatively high heritabilities but also due to the fact that they can be measured when the animals are relatively young compared to the corresponding traits W450 and SC450. The Bayesian approach appears to be an appropriate alternative for estimating genetic parameters, and has the advantage over point estimation methods of allowing inferences on marginal posterior distributions.

Structure and genetic variability in Nellore (Bos indicus) cattle by pedigree analysis

Parameters based on the probability of gene origin were used to describe the genetic variability in strains of Nellore and polled Nellore (Bos indicus) cattle that participated in the Program for Genetic Improvement of the Nellore Breed (Programa de Melhoramento Genético da Raça Nelore). The effective number of founders was 87.2 for Nellore and 107.9 for polled Nellore, while the number of ancestors was 59.8 for Nellore and 61.5 for polled Nellore and the remaining genomes were 39.4 for Nellore and 34.5 for polled Nellore cattle. The results indicate an intense use (by artificial insemination) of some sires and the absence of subdivisions in the population. The family structure in the two breeds was mainly caused by the genetic contribution of the same sires and only mating preferences for descendants of some founders are recorded in either breed. The results suggest that genetic variability needs monitoring in order to avoid the compromise of genetic improvement in economically important traits in the breeding program.