Parâmetros genéticos e análises de componentes principais para peso corporal e características morfológicas em bovinos de corte da raça Nelore.

Resumo: O objetivo do presente trabalho foi estudar as associações entre características de escores visuais de estrutura corporal ao sobreano (ES), precocidade ao sobreano (PS) e musculosidade ao sobreano (MS), e peso ajustado aos 455 dias de idade, por meio de análises de componentes principais, de forma a obter variáveis indicadoras de biotipo animal e estimar os parâmetros genéticos. Foram analisados 10.888 registros de bovinos de corte da raça Nelore, provenientes de um rebanho participante do Programa Nelore Brasil. As análises de componentes principais (PCA) foram realizadas por meio do software STATISTICA. Utilizando como autovetor o primeiro componente principal das análises, foram calculados valores para os animais com informações de escores visuais e pesos ajustados, que originaram as características de índices de biotipo INDs1, INDs2 e INDs3. Os componentes de (co) variância e os parâmetros genéticos foram estimados por inferência Bayesiana, utilizando modelo ui-característica pelo software AIREMLF90. As estimativas de herdabilidade para P455, ES, PS, MS, INDs1, INDs2 e INDs3 foram de 0,50, 0,33, 0,41, 0,34, 0,36, 0,44 e 0,30, respectivamente. As características estudadas apresentam variância genética aditiva suficiente para responderem satisfatoriamente a seleção. Mais estudos sobre as associações genéticas entre os índices de biotipo e características de importância econômica são necessários. Palavras?chave: bovinos de corte, componentes principais, estrutura corporal, herdabilidade, musculosidade, precocidade Abstract: The aim of this study was to assess the relationship between visual scores of body structure (BY), finishing precocity, and muscling (MY) evaluated at yearling, and weight adjusted to 455 days of age, through principal components analysis, in order to obtain indicators of animal biotype and to estimate the genetic parameters. A total of 10.888 records of Nelore beef cattle from a herd of Nelore Brasil program were analyzed. Principal components analyzes (PCA) were performed using STATISTICA software. Using as eigenvector or the first main component of the analyzes, values were calculated for the animals with information of visual scores and adjusted weights, which gave rise to the biotype indexes characteristics INDy1, INDy2, INDy3. The (co) variance components and genetic parameters were estimated by Bayesian inference, using a uni-characteristic model by AIREMLF90 software. The estimates of heritability for W455, BY, PY, MY, INDs1, INDs2 and INDs3 were 0.50, 0.33, 0.41, 0.34, 0.36, 0.44 and 0.30, respectively. As characteristics studied, they present sufficient genetic variance to satisfy the selection. More studies on genetic associations between biotype indexes and economic importance are needed

Estimativas de parâmetros genéticos para as características consideradas no índice bioeconômico (MGTe) do programa de melhoramento Nelore Brasil.

Resumo: O objetivo do presente estudo foi estimar parâmetros genéticos para características de carcaça, crescimento e reprodutivas de bovinos da raça Nelore. Foram analisadas as características de peso aos 120, 210 e 450 dias (P120, P210, P450), área do olho de lombo (AOL), perímetros escrotais aos 365 e 450 dias (PE365, PE450), idade ao primeiro parto (IPP), stayability (STAY) e probabilidade de prenhez precoce (3P). Para as características STAY e 3P foi utilizado o modelo de limiar, e para as demais características o modelo animal linear. Para a estimação dos componentes de variância e herdabildaide soi utilizado o modelo ssGBLUP. As estimativas de herdabilidade para as características P120, P210, P450, AOL, PE365, PE450, IPP, STAY e 3P foram 0,20; 0,21; 0,43; 0,33; 0,47; 0,52; 0,11; 0,12 e 0,37, respectivamente. A magnitude apresentada para as estimativas de herdabilidade foram de baixa (0,30), o que mostra que as mesmas possuem variabilidade genética suficiente para responderem a seleção. Indicando que maiores ganhos por seleção direta podem ser obtidos para as características P450, PE365, PE450, AOL e 3P, uma vez que a herdabilidade estimada destas características é superior as demais. Abstract: The aim in the present study was to estimate genetic parameters for carcass, growth and reproductive traits of Nellore cattle. The weight traits at 120, 210 and 450 days (W120, W210, W450), loin eye area (LEA), scrotal circumference at 365 (SC365) and 450 (SC450) days of age age at first calving (AFC), stayability (STAY) and probability of Precocious pregnancy (3P) with the inclusion of the genomic kinship matrix by means of the Single Step GBLUP. For the STAY and 3P traits, the threshold model was used, and for the other traits the linear animal model. Heritability estimates for traits W120, W210, W450, LEA, SP365, SP450, AFC, STAY and 3P were 0.20; 0.21; 0.43; 0.33; 0.47; 0.52; 0.11; 0.12 and 0.37, respectively. The results show that higher gains by direct selection can be obtained for the traits P450, PE365, PE450, LEA and 3P, because these traits presented heritability is higher than the others

Impacto nas acurácias dos valores genéticos para idade ao primeiro parto em diferentes cenários com paternidade incerta.

Resumo: O objetivo deste estudo foi investigar o impacto nas acurácias de predição utilizando os métodos BLUP e ssGBLUP em diferentes cenários considerando paternidade incerta utilizando dados de uma população de bovinos Nelore. Foram estudados dados de 18.526 registros de idade ao primeiro parto (IPP). Os componentes de variância foram estimados usando os métodos BLUP e ssGBLUP. A matriz de parentesco (A) foi criada com diferentes proporções de animais com pais desconhecidos (0, 25, 50, 75 e 100%). Todos os modelos incluíram grupos contemporâneos como efeitos fixos. Os valores genéticos e genômicos (EBV / GEBV) foram avaliados em cada cenário para quatro grupos: ALL = todos os animais da população, BULL = somente touros com dez ou mais progênies; GEN = animais genotipados e YOUNG = animais jovens machos e fêmeas sem fenótipos. As acurácias de predição variaram de 0,04 a 0,17 e de 0,15 a 0,29 obtidas com o método BLUP e ssGBLUP, respectivamente. A variância genética aditiva manteve-se praticamente constante à medida que a proporção de reprodutores múltiplos aumentou na população, porém as acurácias de predição diminuíram de acordo com o aumento de reprodutores múltiplos independentemente do método utilizado (BLUP e ssGBLUP). O método ssGBLUP mostrou-se acurado em situações de incerteza paternidade, especialmente para a seleção de animais jovens. Abstract: The objective of this study was to investigate the impact on prediction accuracy using BLUP and ssGBLUP methods in different scenarios of uncertain paternity using data from a Nellore cattle population. Data from 18,526 records age at first calving (AFC) were studied. The variance components were estimated using BLUP and ssGBLUP methods. The relationship matrix (A) was created with different proportions of animals with unknown sires (0, 25, 50, 75, and 100%). All models included contemporary groups as fixed effects. The accuracy of the estimated breeding value (EBV/GEBV) was evaluated in each scenario with six groups of animals: ALL = all animals in the population, BULL = only bulls with ten or more progenies; GEN = genotyped animals and YOUNG = male and female young animals without phenotypes. Prediction accuracies ranged from 0.04 to 0.17 and from 0.15 to 0.29 obtained with BLUP and ssGBLUP method respectively. The additive genetic variance remained practically constant as the proportion of multiple sires increased in the population, however, the accuracies decreased according to the increase of multiple sires in the population using BLUP and ssGBLUP. The ssGBLUP method could be applied in situations of uncertainty paternity, especially for selection of young animals

Caracterização do desequilíbrio de ligação em uma população de bovinos da raça Nelore.

Resumo: Tendo em vista a importância da estimação do desequilíbrio de ligação para a seleção genômica, o objetivo deste estudo foi estimar o desequilíbrio de ligação de uma população de bovinos da raça Nelore participantes do programa de melhoramento da ANCP. Foram utilizadas informações de 9.459 animais genotipados com um painel de alta densidade, totalizando 735.044 SNP?s, antes do controle de qualidade. A estimação do desequilíbrio de ligação foi realizada através do programa SNP1101. Os valores de LD observados para os cromossomos autossômicos variaram de 0,18 a 0,25. Para marcadores distanciados até 1 Kb a média de r² foi de 0,53 e para marcadores distanciados entre 90 e 100 Kb 0,14. Para MAF a média variou de 0,23 a 0,25, considerando MAF mínimo de 5%. Os resultados obtidos neste estudo indicam que, a densidade de marcadores utilizados foi capaz de detectar altos níveis de LD. Adicionalmente, conclui-se que marcadores distanciados até 50 Kb ainda detectam consideráveis níveis de LD. Abstract: Considering the importance of estimating linkage disequilibrium for genomic selection, the objective of this study was to estimate the linkage disequilibrium in a population of Nellore cattle participating in the ANCP breeding program. Information from 9,396 genotyped animals with a high density panel, totaling 735,044 SNP's before quality control were used. The estimation of linkage dissequilibrium (LD) was performed using the SNP1101 program. The mean LD values observed for the autosomal chromosomes ranged from 0.18 to 0.25. For markers distanced lower than 1 Kb the r² mean was 0.53, and for markers distanced between 90 and 100 Kb was 0.14. For MAF, the mean ranged from 0.23 to 0.25, a minimum MAF of 0.05 was considered. The results obtained in this study indicated that the density of markers used was able to detect high levels of LD. Additionally, for markers distanced up to 50 Kb, considerable levels of LD was detected

Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure

Abstract\ud \ud Background\ud Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method.\ud \ud \ud Results\ud The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9, C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio.\ud \ud \ud Conclusions\ud The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health.MVA Lemos, (FAPESP, Fundação de Amparo à Pesquisa do Estado de São\ud Paulo). HLJ Chiaia, MP Berton, FLB Feitosa received scholarships from the\ud Coordination Office for Advancement of University-level Personnel (CAPES;\ud Coordenação de Aperfeiçoamento de Pessoal de Nível Superior) in conjunction\ud with the Postgraduate Program on Genetics and Animal Breeding, Faculdade\ud de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista (FCAV,\ud UNESP). F Baldi (FAPESP, Fundação de Amparo à Pesquisa do Estado de São\ud Paulo grant #2011/21241-0). Lucia G. Albuquerque (FAPESP, Fundação de\ud Amparo à Pesquisa do Estado de São Paulo grant #2009/16118-5)

Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article).

ABSTRACT.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. © 2017 Tonussi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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.Made available in DSpace on 2017-12-21T23:28:05Z (GMT). No. of bitstreams: 1 ApplicationofsinglestepgenomicBLUPunderdifferentuncertainpaternityscenariosusingsimulateddata..pdf: 782402 bytes, checksum: ec6960b2579b83b77b9aca6119ae98c8 (MD5) Previous issue date: 2017-12-21bitstream/item/169502/1/Application-of-single-step-genomic-BLUP-under-different-uncertain-paternity-scenarios-using-simulated-data..pd