ORCID Profile
0000-0002-3181-1223
Current Organisation
Universidade Estadual Paulista Júlio de Mesquita Filho Câmpus de Jaboticabal Faculdade de Ciências Agrárias e Veterinárias
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Publisher: Springer Science and Business Media LLC
Date: 14-01-2019
Publisher: Elsevier BV
Date: 02-2017
DOI: 10.1016/J.ANIREPROSCI.2016.12.009
Abstract: The aim of this study was to determine the extent (r
Publisher: Springer Science and Business Media LLC
Date: 19-08-2015
Publisher: Genetics and Molecular Research
Date: 2015
Publisher: Elsevier BV
Date: 2018
Publisher: Public Library of Science (PLoS)
Date: 05-08-2016
Publisher: Springer Science and Business Media LLC
Date: 17-09-2015
Publisher: Oxford University Press (OUP)
Date: 04-2015
Abstract: The aim of this study was to evaluate the effect of genotype × environment interaction (G×E) on age at first calving (AFC), scrotal circumference (SC), and yearling weight (YW) and to estimate genetic correlations between these traits in Nellore cattle using reaction norms in multitrait random regression models. In this study, 28,871, 41,386, and 89,152 records of Nellore cattle for AFC, SC, and YW, respectively, were used. The data were obtained from farms located in the north, northeast, midwest, and southeast regions of Brazil that participate in the DeltaGen Breeding Program. Environmental levels were defined as a function of contemporary groups, that is, animals born in the same herd and year, from the same management group (from birth to yearling), and of the same sex. Postweaning weight gain was used as a criterion to evaluate the environmental conditions for all traits. For reaction norm analyses, residual variances were modeled with homogeneous and heterogeneous classes. The model for SC and YW included the fixed effects of contemporary group and age of the animal as a covariate as well as random direct additive genetic and residual effects. The same model, excluding the covariate age of the animal, was used for AFC. The heritability estimates were low to high for AFC (0.09 to 0.50), high for SC (0.51 to 0.67), and moderate to high for YW (0.33 to 0.71). The genetic correlations (within each trait) along the environmental levels varied from -0.27 to 1.0 for AFC, from 0.73 to 1.0 for SC, and from 0.26 to 1.0 for YW. The genetic correlations between different traits in different environments varied from -0.14 to -0.60 between AFC and SC, from -0.05 to -0.32 between AFC and YW, and from -0.05 to 0.72 between YW and SC. The genetic correlations have had different magnitudes for AFC, SC, and YW, which could indicate the presence of G×E. The present results should support researchers and farmers in defining selection criteria to improve growth traits and sexual precocity. Our results suggest that animals for breeding have to be selected in the same environment and management conditions as their progeny will be reared.
Publisher: Springer Science and Business Media LLC
Date: 05-05-2013
Abstract: Knowledge of the linkage disequilibrium (LD) between markers is important to establish the number of markers necessary for association studies and genomic selection. The objective of this study was to evaluate the extent of LD in Nellore cattle using a high density SNP panel and 795 genotyped steers. After data editing, 446,986 SNPs were used for the estimation of LD, comprising 2508.4 Mb of the genome. The mean distance between adjacent markers was 4.90 ± 2.89 kb. The minor allele frequency (MAF) was less than 0.20 in a considerable proportion of SNPs. The overall mean LD between marker pairs measured by r 2 and |D'| was 0.17 and 0.52, respectively. The LD (r 2 ) decreased with increasing physical distance between markers from 0.34 (1 kb) to 0.11 (100 kb). In contrast to this clear decrease of LD measured by r 2 , the changes in |D'| indicated a less pronounced decline of LD. Chromosomes BTA1, BTA27, BTA28 and BTA29 showed lower levels of LD at any distance between markers. Except for these four chromosomes, the level of LD (r 2 ) was higher than 0.20 for markers separated by less than 20 kb. At distances 3 kb, the level of LD was higher than 0.30. The LD (r 2 ) between markers was higher when the MAF threshold was high (0.15), especially when the distance between markers was short. The level of LD estimated for markers separated by less than 30 kb indicates that the High Density Bovine SNP BeadChip will likely be a suitable tool for prediction of genomic breeding values in Nellore cattle.
Publisher: Oxford University Press (OUP)
Date: 14-07-2018
DOI: 10.1093/JAS/SKY284
Publisher: Elsevier BV
Date: 09-2017
Publisher: Genetics and Molecular Research
Date: 2015
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.MEATSCI.2018.09.010
Abstract: The objective of this study was to present heritability estimates and accuracy of genomic prediction using different methods for meat quality traits in Nelore cattle. Approximately 5000 animals with phenotypes and genotypes of 412,000 SNPs, were ided into two groups: (1) training population: animals born from 2008 to 2013 and (2) validation population: animals born in 2014. A single-trait animal model was used to estimate heritability and to adjust the phenotype. The methods of GBLUP, Improved Bayesian Lasso and Bayes Cπ were performed to estimate the SNP effects. Accuracy of genomic prediction was calculated using Pearson's correlations between direct genomic values and adjusted phenotypes, ided by the square root of heritability of each trait (0.03-0.19). The accuracies varied from 0.23 to 0.73, with the lowest accuracies estimated for traits associated with fat content and the greatest accuracies observed for traits of meat color and tenderness. There were small differences in genomic prediction accuracy between methods.
Publisher: Elsevier BV
Date: 2018
Publisher: Oxford University Press (OUP)
Date: 10-2016
Abstract: Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes ( and ) involved in the cell cycle biological process which affects many aspects of animal growth and development. The and genes, both from AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (, , , , , and ) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the . There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.
Publisher: Springer Science and Business Media LLC
Date: 21-06-2016
Publisher: Springer Science and Business Media LLC
Date: 09-03-2016
Publisher: Oxford University Press (OUP)
Date: 05-2016
Abstract: The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.
Publisher: Wiley
Date: 05-10-2020
DOI: 10.1111/RDA.13811
Publisher: Springer Science and Business Media LLC
Date: 25-01-2022
DOI: 10.1007/S13353-021-00680-X
Abstract: The research article was carried out with the objective of studying the genetic variation on the resilience of buffaloes to negative energy balance-NEB (measured by changes in body weight in early lactation)-as well as investigating genomic regions of interest for this trait. A model of reaction norms was used, considering milk production as the trait to be analyzed and solutions of the contemporary groups to weight changes as environmental gradient. In this methodology, the genetic value of the slope represents the measure of resilience of the animals. After the estimation step, a genome-wide association analysis was performed for the slope of the reaction norms model, to obtain a list of windows and associated genes. The heritability estimates for milk production over the resilience gradient ranged from 0.13 to 0.28, with lower values in the intermediate environmental groups. Regarding the productive resilience of dairy buffalo cows to NEB, the genomic windows with the highest contribution to the genetic variance were detected on chromosomes BBU 1, 2, 3, 4, 9, 12, 19, and 21. A functional analysis of the genes described in the selected windows indicated association with metabolic routes related to growth and immunity of the animals, with an emphasis on the STAT6 gene. The results presented indicate that there is for this trait genetic variation to be used as selection criteria, in addition to genomic regions that can increase the precision of the selection.
Publisher: FapUNIFESP (SciELO)
Date: 02-2012
DOI: 10.1590/S0100-204X2012000200019
Abstract: The objective of this work was to evaluate the effects of single-nucleotide polymorphisms (SNPs) in the genes IGF1 (AF_017143.1:g.198C T), MSTN (AF_320998.1:g.433C A), MYOD1 (NC_007313:g.1274A G) and MYF5 (NC_007303:g.1911A G) on carcass and meat traits in Nelore (Bos indicus) and Nelore x B. taurus. A total of 300 animals were genotyped and phenotyped for rib eye area (REA), backfat thickness (BT), intramuscular fat (IF), shear force (SF) and myofibrillar fragmentation index (MFI). The effects of allele substitution for each SNP were estimated by regression of the evaluated phenotypes on the number of copies of a particular allele using the general linear model. The polymorphism at IGF1 was non-informative in Nelore animals. In crossbred animals, the IGF1 C allele was associated with greater REA. However, this relation was not significant after Bonferroni correction for multiple testing. The A allele of the MSTN polymorphism was absent in Nelore cattle and was only found in two crossbred animals. The polymorphisms of MYOD1 and MYF5 were little informative in Nelore animals with G allele frequency of 0.097 and A allele frequency of 0.031, respectively. These markers show no association with the analyzed traits in the total s le of evaluated animals.
Publisher: Public Library of Science (PLoS)
Date: 02-01-2018
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.THERIOGENOLOGY.2018.10.014
Abstract: The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle. A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.
Location: Brazil
Location: Brazil
No related grants have been discovered for HENRIQUE OLIVEIRA.