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BackgroundGenotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R2).ResultsThe highest imputation accuracy scenario consisted of a reference population with males and females and a target population with young females. Among the SNP panels in the tested scenarios, from the 50K, GGP75Ki and GGP80K were the most adequate to impute to HD in Canchim cattle. FImpute reduced computation run-time to impute genotypes from 20 to 100 times when compared to BEAGLE.ConclusionThe genotyping panels possessing at least 50 thousands markers are suitable for genotype imputation to HD with acceptable accuracy. The FImpute algorithm demonstrated a higher efficiency of imputed markers, especially in lower density panels. These considerations may assist to increase genotypic information, reduce genotyping costs, and aid in genomic selection evaluations in crossbred animals.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0251-7) contains supplementary material, which is available to authorized users.

In beef cattle, growth, reproductive, and carcass traits have been studied for improving productivity and quality of meat products. The aim of this study was to estimate genetic parameters for birth (BW), weaning (WW) and yearling (YW) weights, scrotal circumferences at weaning (SCW) and yearling (SCY), age at first calving (AFC), ribeye area (REA) and back fat thickness (BFT) in order to provide support for the evaluation program of the composite Canchim breed. Data on 12 967 (BW), 7481 (WW), 5131 (YW), 1447 (SCW), 1224 (SCY), 1400 (AFC), and 2082 (REA and BFT) animals were analysed using the Average Information Restricted Maximum Likelihood method under an animal model (single and multi-trait analyses). A substantial proportion of the variation in the bodyweights, scrotal circumferences and carcass traits was associated with the additive genetic term indicating that these traits may respond to the selection process. For AFC, a low heritability estimate was observed. Genetic correlations among bodyweights varied from 0.41 to 0.93. The genetic correlation among scrotal circumferences was 0.91. Important genetic correlations among YW, SCW, and SCY with AFC were observed (–0.48, –0.61, and –0.71, respectively), indicating that indirect responses to selection for these traits would be expected in the age of which the heifers calve. Furthermore, BFT presented an interesting result with calving performance due to the genetic correlation (–0.69) with AFC. Post-weaning weights showed moderate genetic correlations with REA. Many of the traits considered in the genetic evaluation of this breed are genetically correlated in a favourable manner. Genetic improvement through selection is expected for production, reproduction, and carcass traits in Canchim beef cattle.

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.

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

-The objective of this work was to estimate genetic parameters for bird carcass and meat quality traits, as well as to explore the genetic patterns of the breeding values of this population using cluster analyses. Data from 1,846 birds were used to estimate the genetic parameters of production and quality traits using the multiple-trait animal model, and cluster analyses were performed. The heritability estimates ranged from 0.08±0.03 for meat pH measured 24 hours after slaughter to 0.85±0.09 for body weight. The genetic correlations between production traits were high and positive. The genetic correlations between meat quality traits were low and were not informative due to the high standard errors (same magnitudes as those of the genetic correlations). The genetic correlations between meat production and quality traits were negative, except between production traits and meat lightness intensity. Based on breeding values (EBVs), the evaluated population can be divided into four groups through cluster analyses, and one group is suitable for selection because the birds presented EBVs above and around the average of the population, respectively, for production and quality traits. Therefore, it is possible to obtain genetic gains for production-related traits without decreasing meat quality.Index terms: genetic correlation, heritability, meat color, White Leghorn. Estimativa de parâmetros genéticos e análises de agrupamento para características de carcaça e qualidade da carne em avesResumo -O objetivo deste trabalho foi estimar os parâmetros genéticos para características de carcaça e qualidade da carne de aves, bem como explorar o perfil dos valores genéticos desta população, com uso de análises de agrupamento. Foram utilizados dados de 1.846 aves para estimar os parâmetros genéticos de características de produção e qualidade por meio do modelo animal multicaracterística, e foram realizadas análises de agrupamento. As estimativas de herdabilidade variaram de 0,08±0,03 para o pH da carne medido 24 horas após o abate a 0,85±0,09 para o peso corporal. As correlações genéticas entre as características de produção foram altas e positivas. Já as correlações genéticas entre as características de qualidade da carne foram baixas e não foram informativas devido aos altos erros-padrão (mesmas magnitudes que as das correlações genéticas). As correlações genéticas entre as características de produção e de qualidade da carne foram negativas, exceto entre as características de produção e o teor de luminosidade da carne. Com base nos valores genéticos (VGs), a população avaliada pode ser dividida em quatro grupos por meio da análise de agrupamento, e um dos grupos é mais adequado para seleção, uma vez que as aves apresentaram VGs acima e em torno da média da população, respectivamente, para as características de produção e de qualidade da carne. Assim, é possível obter ganhos genéticos para características relacionadas à produção sem diminuir a qualidade da carne.Termos para indexação: correlação genética, herdabilidade,...