Genomic clues of the evolutionary history of Bos indicus cattle.

Together with their sister subspecies Bos taurus, zebu cattle (Bos indicus) have contributed to important socioeconomic changes that have shaped modern civilizations. Zebu cattle were domesticated in the Indus Valley 8000 years before present (YBP). From the domestication site, they expanded to Africa, East Asia, southwestern Asia and Europe between 4000 and 1300 YBP, intercrossing with B. taurus to form clinal variations of zebu ancestry across the landmass of Afro-Eurasia. In the past 150 years, zebu cattle reached the Americas and Oceania, where they have contributed to the prosperity of emerging economies. The zebu genome is characterized by two mitochondrial haplogroups (I1 and I2), one Y chromosome haplogroup (Y3) and three major autosomal ancestral groups (Indian-Pakistani, African and Chinese). Phenotypically, zebu animals are recognized by their hump, large ears and excess skin. They are rustic, resilient to parasites and capable of bearing the hot and humid climates of the tropics. Many resources are available to study the zebu genome, including commercial arrays of SNP, reference assemblies and publicly available genotypes and whole-genome sequences. Nevertheless, many of these resources were initially developed to support research and subsidize industrial applications in B. taurus, and therefore they can produce bias in data analysis. The combination of genomics with precision agriculture holds great promise for the identification of genetic variants affecting economically important traits such as tick resistance and heat tolerance, which were naturally selected for millennia and played a major role in the evolution of B. indicus cattle.

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.

Performance, carcass and meat characteristics of two cattle categories finished on pasture during the dry season with supplementation in different forage allowance / Desempenho, características da carcaça e carne de duas categorias de bovinos de corte terminados em pastagem durante a estação seca com suplementação em diferentes ofertas de forragem

The objective this paper was to evaluate the effect of two categories of beef finished in pasture with supplementation with two herbage allowance on performance, carcass and meat characteristics. Thirty-six Guzera cattle were used, 18 steers and 18 heifers with an initial age of 20 months. There was significant difference in daily weight gain for animal category and the herbage allowance, which were higher in males and animals submitted to high herbage allowance. Steers showed higher final weight, carcass weight and forequarter yield compared with the heifers, although the hindquarter yield was higher in the heifers, however the herbage allowance did not influence these characteristics. There were not statistical differences for carcass yield, ribeye area, backfat thickness and marbling score for the animal categories and herbage allowance. The meat chemical composition of the steers did not differ of the heifers, however, the animals submitted to high herbage allowance was increase in ether extract and pH, decrease in protein percentage. It was concluded that the animal category and the herbage allowance changed the animal performance, improving performance in males and cattle submitted to high herbage allowance.(AU)

O objetivo do presente trabalho foi avaliar o efeito de duas categorias de bovinos terminados em pastagem com suplementação em duas ofertas de forragem no desempenho, na qualidade da carcaça e da carne. Foram utilizados 36 bovinos Guzerá, 18 novilhos e 18 novilhas, com idade inicial de 20 meses de idade. Observou-se diferença significativa no ganho de peso diário para categoria animal e ofertas de forragem, que foram superiores nos machos e nos animais submetidos à oferta alta de forragem. Os novilhos apresentaram maior peso final, peso de carcaça e rendimento de dianteiro em comparação com as novilhas, embora o rendimento do traseiro tenha sido maior para as novilhas, entretanto as ofertas de forragem não influenciaram essas características. Não houve diferenças estatísticas para rendimento de carcaça, área de olho de lombo, espessura de gordura subcutânea e marmorização para categorias de animais e ofertas de forragem. Quanto à composição química, a carne de novilhos não diferiu das novilhas. Os animais submetidos à alta oferta de forragem tiveram aumento no extrato etéreo e pH, redução na porcentagem de proteína. Conclui-se que a categoria animal e os níveis de forragem alteram o desempenho animal, melhorando, assim, o desempenho nos machos e nos bovinos submetidos à alta oferta de forragem.(AU)

Estimativas de parâmetros genéticos para características de crescimento em ovinos da raça Suffolk no Brasil / Estimates of genetic parameters for growth traits in Suffolk sheep in Brazil

O objetivo do trabalho foi estimar os parâmetros genéticos das características de crescimento da raça Suffolk, a fim de fornecer subsídio para a definição de estratégias de seleção para programas de melhoramento genético. Os dados analisados, coletados entre os anos de 2007 a 2009, são referentes a ovinos da raça Suffolk oriundos de uma propriedade localizada no Estado de São Paulo, Brasil, participante do programa de melhoramento genético Ovigol, conduzido pela empresa Aries Reprodução e Melhoramento Genético Ovino Ltda. em parceria com a empresa AbacusBio Limited, da Nova Zelândia. As características avaliadas foram: peso ao nascer (PN), ganho de peso pré-desmame (GPP) e peso ao desmame (PD), com número de registro de 1.039, 636 e 649 animais, respectivamente. Para análise estatística, utilizou-se o procedimento GLM do programa computacional SAS; para a consistência do pedigree e para as estimativas dos parâmetros genéticos, os programas computacionais utilizados foram Relax2: pedigree analysis program e o WOMBAT, respectivamente. O modelo linear geral incluiu sexo, grupo de contemporâneos (tipo de parto e ano de nascimento), covariável idade ao desmame (GPP e PD) com efeito quadrático, efeito genético aditivo direto, efeito de ambiente permanente materno e efeito residual. As herdabilidades para PN, GPP e PD foram 0,06, 0,42 e 0,37, respectivamente. As correlações genéticas entre PN e GPP, PN e PD e GPP e PD foram -0,10, -0,03 e 0,97, respectivamente. Na população estudada, as características GPP e PD, apresentam altas respostas à seleção, ao contrário do PN. As características PN e GPP são suficientes para compor um índice de seleção, sendo aconselhável o monitoramento do PN na fase inicial do programa.

The aim of this study was to estimate genetic parameters for growth of Suffolk, in order to provide a basis for the definition of selection strategies for breeding programs. The data analyzed are for Suffolk sheep, collected between years 2007 to 2009, from a property located in the State of São Paulo - Brazil, a participant in the Ovigol breeding program conducted by the company (Aries Reproduction and Breeding Sheep Ltd.) in partnership with (AbacusBio) New Zealand Limited. The evaluated characteristics were: birth weight (PN), weight gain pre-weaning (GPP) and weaning weight (PD), with registration number 1039, 636 and 649 respectively. For statistical analysis we used the GLM procedure of SAS software, for the consistency of pedigree and genetic parameter estimates software Relax2: pedigree analysis program and WOMBAT, respectively, were used. The general linear model included sex, contemporary group (type of birth and year of birth), covariate age at weaning (GPP and PD) with a quadratic effect, direct genetic effect, maternal permanent environmental effect and residual effect. Heritability estimates for PN, PD and GPP were 0.06, 0.42 and 0.37, respectively. Genetic correlations between PN and GPP, and PN and PD and GPP were -0.10, -0.03 and 0.97, respectively. In the study population characteristics GPP and PD have a high response to selection, unlike the PN. The GPP and PN characteristics are enough to make a selection index, it is advisable to monitor the PN in the initial phase of the program.

Uso de modelos lineares mistos na avaliação genética de escores visuais: estudo de simulação / Using linear mixed models in genetic evaluation of visual scores: simulation study

Objetivou-se avaliar a aplicação da metodologia de modelos lineares mistos em características de escores visuais por meio de simulação, considerando-se duas estruturas populacionais (com e sem seleção), dois níveis de herdabilidade (0,1 e 0,4) e quatro níveis de conectabilidade (8, 20, 38 e 60 por cento). As populações com e sem seleção estavam constituídas por 6660 e 3360 animais, respectivamente, dos quais os últimos 2460 animais tinham fenótipo para o escore visual. Assumiu-se uma variável contínua adjacente ao escore visual, a partir da qual foram definidos os intervalos correspondentes a cada categoria de escore visual. O processo de simulação foi feito por meio do software R, e a estimação de parâmetros e predição de valores genéticos pelo software Wombat, sob modelo animal, considerando-se modelos com e sem efeitos fixos. Os critérios de avaliação foram: o erro quadrático médio (EQM) para a herdabilidade e as correlações de Spearman entre os valores genéticos verdadeiros e preditos. As estimativas da herdabilidade apresentaram-se próximas do valor verdadeiro nos cenários sem seleção (0,084-0,101 e 0,367-0,389), no entanto este resultado não ocorreu quando houve seleção, pois a herdabilidade apresentou-se subestimada (0,032 e 0,278). As correlações apresentaram-se maiores nos cenários sem seleção e com herdabilidade de 0,4 (0,86-0,89). Em todos os cenários simulados, a inclusão do efeito fixo no modelo melhorou as estimativas de herdabilidade e as correlações entre os valores genéticos verdadeiros e preditos. O nível de conectabilidade afetou a correção dos efeitos fixos feita pela atribuição dos escores. Em conclusão, a metodologia dos modelos lineares mistos pode ser utilizada na estimação de parâmetros e predição de valores genéticos de escores visuais em populações sem seleção, entretanto não se apresenta adequada em populações sob seleção...

This study aimed to evaluate the application of linear mixed models methodology using simulated data for trait visual scores, two population structures (with and without selection), two levels of heritability (0.1 and 0.4) and four levels of connectability (8, 20, 38 and 60 percent) were examined. Populations with and without selection consisted of 6,660 and 3,360 animals respectively, of which, the last in 2460 had score visual phenotypes. The scores were simulated with an underlying normal distribution from which intervals were defined corresponding to each category of the visual scores. The simulation process was performed in software R, to estimate genetic parameters and predict breeding values through software Wombat using animal model, considering models with and without fixed effects. The evaluation criteria were: the mean squared error (EQM) for heritability and Spearman correlations between true and predicted breeding values. Estimates of heritability showed close to the true value in scenarios without selection (0.084-0.101 and 0.367-0.389), however when selection was applied heritability was underestimated (0.032 and 0.278). Consistent with heritability, the correlations were higher for the scenarios without selection and with heritability of 0.4 (0.86-0.89). In all scenarios simulated the inclusion of fixed effects in the model improved the estimates of heritability and correlations between true and predicted breeding values. The level of connectability affected the correction of fixed effects done by allocating visual scores. The linear mixed model methodology can be used in the estimation of genetic parameters and predicted breeding values for visual scores in populations without selection, however, is not suiting in populations under selection...