No abstract

Summary Age at first calving (AFC) measures the entry of heifers into the beef cattle production system. This trait can be used as a selection criterion for earlier reproductive performance. Using data from Nelore cattle participating in the 'Program for Genetic Improvement of the Nelore Breed' (PMGRN-Nelore Brazil), bi-trait analyses were performed using the restricted maximum likelihood method, based on an AFC animal model and the following traits: female body weight adjusted to 365 (BW365) and 450 (BW450) days of age, and male scrotal circumference adjusted to 365 (SC365), 450 (SC450), 550 (SC550) and 730 (SC730) days of age. The heritability estimates for AFC ranged from 0.02 +/- 0.02 to 0.04 +/- 0.02. The estimates of additive direct heritabilities (with standard error) for BW365, BW450, SC365, SC450, SC550 and SC730 were 0.36 +/- 0.07, 0.38 +/- 0.07, 0.48 +/- 0.07, 0.65 +/- 0.07, 0.64 +/- 0.07 and 0.42 +/- 0.07, respectively, and the genetic correlations with AFC were -0.38, -0.33, 0.10, -0.13, -0.13 and 0.06, respectively. In the herds studied, selection for SC365, SC450, SC550 or SC730 should not cause genetic changes in AFC. Selection based on BW365 or BW450 would favor smaller AFC breeding values. However, the low magnitude of direct heritability estimates for AFC in these farms indicates that changes in phenotypical expression depend mostly on non-genetic factors.

ABSTRACT:The aim of this study was to verify the importance of genotype-environment interaction (GEI) for age at first calving (AFC), scrotal circumference (SC) and yearling weight (YW) in Nellore cattle, using reaction norms in multi-trait random regression models and analyze the efficiency of selection for AFC based on SC and YW in different environments. The research was conducted using 28,871, 41,386 and 89,152 records for AFC, SC and YW, respectively. Environmental groups (EGs) were defined based on farm and year of birth and management group (at birth, weaning and yearling) for all traits. For YW sex of animal was added to EGs. Average post-weaning weight gain was used to assess environmental conditions. Models for SC and YW included contemporary group and the covariate, age of animal at evaluation, as fixed effects, and the residual and direct additive genetic effects as random effects. The same model was used for AFC, excluding age of animal effects. The (co)variance components were estimated using Wombat software. The additive genetic and phenotypic variances estimates for AFC, SC and YW increased as the environmental conditions improved, with a greater intensity for AFC. The heritability estimates for all traits increased as the environment became more favorable and ranged from low to medium for AFC (0.04 to 0.48), high for SC (0.51 to 0.67) and medium to high for YW (0.23 to 0.76). The genetic correlation estimates between AFC and SC, AFC and YW, YW and SC in different environments, ranged from -0.15 to -0.68, -0.18 to -0.35, -0.1 to +0.68, respectively. The efficiency of indirect selection for AFC using YW and SC ranged from 4 to 395 and from 12 to 333, respectively. There is an important GEI effect for AFC, SC and YW traits, so the expected genetic gain for these traits depend on the environment in which the animals are exploited. The SC and YW traits can be used as a selection criterion for sexual precocity in unfavorable environments.

ABSTRACT. The aim of this study was to identify single-nucleotide polymorphisms (SNPs) in buffaloes associated with milk yield and content, in addition to somatic cell scores based on the cross-species transferability of SNPs from cattle to buffalo. A total of 15,745 SNPs were analyzed, of which 1562 showed 1% significance and 4742 with 5% significance, which were associated for all traits studied. After application of Bonferroni's correction for multiple tests of the traits analyzed, we found 2 significant SNPs placed on cattle chromosomes BTA15 and BTA20, which are homologous to buffalo chromosomes BBU16 and BBU19, respectively. In this genome association study, we found several significant SNPs affecting buffalo milk production and quality. Furthermore, the use of the high-density bovine BeadChip was suitable for genomic analysis in buffaloes. Although extensive chromosome arm homology was described between cattle and buffalo, the exact chromosomal position of SNP GWAS for milk production traits in buffalo markers associated with these economically important traits in buffalo can be determined only through buffalo genome sequencing.

Phenotypic data from female Canchim beef cattle were used to obtain estimates of genetic parameters for reproduction and growth traits using a linear animal mixed model. In addition, relationships among animal estimated breeding values (EBVs) for these traits were explored using principal component analysis. The traits studied in female Canchim cattle were age at first calving (AFC), age at second calving (ASC), calving interval (CI), and bodyweight at 420 days of age (BW420). The heritability estimates for AFC, ASC, CI and BW420 were 0.03±0.01, 0.07±0.01, 0.06±0.02, and 0.24±0.02, respectively. The genetic correlations for AFC with ASC, AFC with CI, AFC with BW420, ASC with CI, ASC with BW420, and CI with BW420 were 0.87±0.07, 0.23±0.02, -0.15±0.01, 0.67±0.13, -0.07±0.13, and 0.02±0.14, respectively. Standardised EBVs for AFC, ASC and CI exhibited a high association with the first principal component, whereas the standardised EBV for BW420 was closely associated with the second principal component. The heritability estimates for AFC, ASC and CI suggest that these traits would respond slowly to selection. However, selection response could be enhanced by constructing selection indices based on the principal components.

ABSTRACT. The objective of this study was to estimate the genetic and environmental parameters for carcass, carcass part, and organ weights in a paternal strain of broiler chickens that was selected mainly for body weight at 42 days of age (BW42) to provide support for poultry genetic improvement programs. A total of 1448 chickens were used that resulted from the expansion of a pure paternal strain named TT, which was developed by Embrapa Suínos e Aves. The following weights were evaluated: BW42, chilled carcass, wing, drumstick meat, thigh meat, breast meat, breast fillet, back, liver, heart (HRT), and gizzard (GIZ). The variance component was estimated by the restricted maximum likelihood method using a multi-trait animal model. The general model included the additive genetic and residual random effects and the fixed effect of the sex-hatch group (10 levels). The heritability estimates ranged from 0.27 ± 0.06 for HRT to 0.44 ± 0.08 for GIZ. These results indicated that all the traits have enough additive genetic variability to respond to selection. The genetic correlation estimates between BW42 and the carcass and carcass part weights were high and positive. However, the genetic correlation estimates between BW42 and organ weights were Genetic parameters of economic traits in broiler chickens low. In this population, the carcass traits might respond indirectly to selection applied to BW42. It can be concluded that selection to increase BW42 is not effective in improving broiler organ weight. Therefore, to obtain suitable genetic improvement for these traits, the selection indexes for broilers should include organ weight-based criteria.

The objectives of this study were to estimate genetic parameters for accumulated egg production over 3-wk periods and for total egg production over 54 wk of egg-laying, and using principal component analysis (PCA), to explore the relationships among the breeding values of these traits to identify the possible genetic relationships present among them and hence to observe which of them could be used as selection criteria for improving egg production. Egg production was measured among 1,512 females of a line of White Leghorn laying hens. The traits analyzed were the number of eggs produced over partial periods of 3 wk, thus totaling 18 partial periods (P1 to P18), and the total number of eggs produced over the period between the 17 and 70 wk of age (PTOT), thus totaling 54 wk of egg production. Estimates of genetic parameters were obtained by means of the restricted maximum likelihood method, using 2-trait animal models. The PCA was done using the breeding values of partial and total egg production. The heritability estimates ranged from 0.05 ± 0.03 (P1 and P8) to 0.27 ± 0.06 (P4) in the 2-trait analysis. The genetic correlations between PTOT and partial periods ranged from 0.19 ± 0.31 (P1) to 1.00 ± 0.05 (P10, P11, and P12). Despite the high genetic correlation, selection of birds based on P10, P11, and P12 did not result in an increase in PTOT because of the low heritability estimates for these periods (0.06 ± 0.03, 0.12 ± 0.04, and 0.10 ± 0.04, respectively). The PCA showed that egg production can be divided genetically into 4 periods, and that P1 and P2 are independent and have little genetic association with the other periods.

Identification of genotype–environment interaction in beef cattle may help the artificial selection process and increase the efficiency of genetic evaluation on sires submitted to different environments. Post-weaning traits are economically important and are more influenced by the effects of genotype–environment interactions than pre-weaning traits. Thus, the aim of this study was to investigate whether this interaction has any effect on bodyweight at 365, 450, and 550 days of age in Nellore cattle reared in Brazil. Analyses considered the states of Goiás, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Pará, and São Paulo. Genetic parameters were estimated for each trait, per state, using the restricted maximum likelihood method, in two-trait analysis under an animal model. Genetic correlations regarding the same trait in two different states were used to evaluate the effect of the genotype–environment interaction on the traits studied. Genetic correlation estimates smaller than 0.80 between observations for the same trait in different states were taken to be indicative of genotype–environment interaction. It was observed that there is evidence of genotype–environment interaction in some of the states studied, and they tend to increase when the weight measurements are made at later ages. From this, it was concluded that selection conducted using data from one state might be different from selection based on data from another state. Summaries of bulls that consider different environments could contribute greatly to the genetic improvement of livestock.