Gensys Consultores Associados S C Ltda

Jaboticabal, Brazil

Gensys Consultores Associados S C Ltda

Jaboticabal, Brazil
Time filter
Source Type

Santana M.H.A.,University of Sao Paulo | Ventura R.V.,University of Sao Paulo | Ventura R.V.,University of Guelph | Utsunomiya Y.T.,São Paulo State University | And 12 more authors.
Journal of Animal Breeding and Genetics | Year: 2015

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations. © 2015 Blackwell Verlag GmbH.

Lucena C.R.S.,São Paulo State University | Neves H.H.R.,Gensys Consultores Associados S C Ltda | Carvalheiro R.,São Paulo State University | Oliveira J.A.,São Paulo State University | Queiroz S.A.,São Paulo State University
Animal | Year: 2014

Temperament is an important trait for the management and welfare of animals and for reducing accidents involving people who work with cattle. The present study aimed to estimate the genetic parameters related to the temperament score (T) and weaning weight (WW) of Nellore cattle, reared in a beef cattle breeding program in Brazil. Data were analyzed using two different two-trait statistical models, both considering WW and T: (1) a linear-linear model in which variance components (VCs) were estimated using restricted maximum likelihood; and (2) a linear-threshold model in which VCs were estimated via Bayesian inference. WW was included in the analyses of T to minimize any possible effects of sequential selection and to allow for estimation of the genetic correlation between these two traits. The heritability estimates for T were 0.21±0.003 (model 1) and 0.26 (model 2, with a 95% credibility interval (95% CI) of 0.21 to 0.32). The estimated genetic correlations between WW and T were of a moderate magnitude (-0.33±0.01 (model 1) and -0.34 (95% CI: -0.40, -0.28, model 2). The genetic correlations between the estimated breeding values (EBVs) obtained for the animals based on the two models were high (>0.92). The use of different models had little influence on the classification of animals based on EBVs or the accuracy of the EBVs. © The Animal Consortium 2014.

Santana M.H.A.,Pirassununga | Gomes R.C.,EMBRAPA - Empresa Brasileira de Pesquisa Agropecuária | Utsunomiya Y.T.,São Paulo State University | Neves H.H.R.,São Paulo State University | And 9 more authors.
Genetics and Molecular Research | Year: 2015

Weight gain is a key performance trait for beef cattle; however, attention should be given to the production costs for better profitability. Therefore, a feed efficiency trait based on performance can be an interesting approach to improve performance without increasing food costs. To identify candidate genes and genomic regions associated with residual body weight gain (RWG), we conducted a genome-wide association study (GWAS) with 720 Nellore cattle using the GRAMMAR-Gamma association test. We identified 30 significant single nucleotide polymorphisms (SNPs), especially on chromosomes 2, 8, 12, and 17. Several genes and quantitative train loci (QTLs) present in the regions identified were appointed; we highlight DMRT2 (doublesex and mab-3 related transcription factor 2), IFFO2 (intermediate filament family orphan 2), LNX2 (ligand of numb-protein X 2), MTIF3 (mitochondrial translational initiation factor 3), and TRNAG-CCC (transfer RNA glycine anticodon CCC). The metabolic pathways that can explain part of the phenotypic variation in RWG are related to oxidative stress and muscle control. ©FUNPEC-RP.

Queiroz S.A.,São Paulo State University | Oliveira J.A.,São Paulo State University | Costa G.Z.,Animal Breeding Consultant | Fries L.A.,GenSys Consultores Associados S C Ltda
Animal | Year: 2011

(Co)variance components were estimated for visual scores of conformation (CY), early finishing (PY) and muscling (MY) at 550 days of age (yearling), average daily gain from weaning to yearling (GWY), conformation (CW), early finishing (PW) and muscling (MW) scores at weaning, and average daily gain from birth to weaning (GBW) in animals forming the Brazilian Brangus breed born between 1986 and 2002 from the livestock files of GenSys Consultants Associados S/C Ltda. The data set contained 53 683; 45 136; 52 937; 56 471; 24 531; 21 166; 24 006 and 25 419 records for CW, PW, MW, GBW, CY, PY, MY and GWY, respectively. Data were analyzed by the restricted maximum likelihood method using single- and two-trait animal models. Direct heritability estimates obtained by single-trait analysis were 0.12, 0.14, 0.13 and 0.14 for CY, PY and MY scores and GWY, respectively. A positive association was observed between the same visual scores at weaning and yearling, with correlations ranging from 0.64 to 0.94. Estimated correlations between GBW and weaning and yearling scores ranged from 0.60 to 0.77. The genetic correlation between GBW and GWY was low (0.10), whereas correlations of 0.55, 0.37 and 0.47 were observed between GWY and CY, PY and MY, respectively. Moreover, GWY showed a weak correlation with CW (0.10), PW (-0.08) and MW (-0.03) scores. These results indicate that selection of the traits that was studied would result in a small response. In addition, selection based on average daily gain may have an indirect effect on visual scores as the correlations between GWY and visual scores were generally strong. © 2011 The Animal Consortium.

Neves H.H.R.,Paulista University | Carvalheiro R.,Paulista University | Carvalheiro R.,GenSys Consultores Associados S C Ltda | O'Brien A.M.P.,University of Natural Resources and Life Sciences, Vienna | And 11 more authors.
Genetics Selection Evolution | Year: 2014

Background: Nellore cattle play an important role in beef production in tropical systems and there is great interest in determining if genomic selection can contribute to accelerate genetic improvement of production and fertility in this breed. We present the first results of the implementation of genomic prediction in a Bos indicus (Nellore) population. Methods. Influential bulls were genotyped with the Illumina Bovine HD chip in order to assess genomic predictive ability for weight and carcass traits, gestation length, scrotal circumference and two selection indices. 685 samples and 320 238 single nucleotide polymorphisms (SNPs) were used in the analyses. A forward-prediction scheme was adopted to predict the genomic breeding values (DGV). In the training step, the estimated breeding values (EBV) of bulls were deregressed (dEBV) and used as pseudo-phenotypes to estimate marker effects using four methods: genomic BLUP with or without a residual polygenic effect (GBLUP20 and GBLUP0, respectively), a mixture model (Bayes C) and Bayesian LASSO (BLASSO). Empirical accuracies of the resulting genomic predictions were assessed based on the correlation between DGV and dEBV for the testing group. Results: Accuracies of genomic predictions ranged from 0.17 (navel at weaning) to 0.74 (finishing precocity). Across traits, Bayesian regression models (Bayes C and BLASSO) were more accurate than GBLUP. The average empirical accuracies were 0.39 (GBLUP0), 0.40 (GBLUP20) and 0.44 (Bayes C and BLASSO). Bayes C and BLASSO tended to produce deflated predictions (i.e. slope of the regression of dEBV on DGV greater than 1). Further analyses suggested that higher-than-expected accuracies were observed for traits for which EBV means differed significantly between two breeding subgroups that were identified in a principal component analysis based on genomic relationships. Conclusions: Bayesian regression models are of interest for future applications of genomic selection in this population, but further improvements are needed to reduce deflation of their predictions. Recurrent updates of the training population would be required to enable accurate prediction of the genetic merit of young animals. The technical feasibility of applying genomic prediction in a Bos indicus (Nellore) population was demonstrated. Further research is needed to permit cost-effective selection decisions using genomic information. © 2014 Neves et al.; licensee BioMed Central Ltd.

Carvalheiro R.,Paulista University | Boison S.A.,University of Natural Resources and Life Sciences, Vienna | Neves H.H.R.,Paulista University | Neves H.H.R.,GenSys Consultores Associados S C Ltda | And 9 more authors.
Genetics Selection Evolution | Year: 2014

Background: Genotype imputation from low-density (LD) to high-density single nucleotide polymorphism (SNP) chips is an important step before applying genomic selection, since denser chips tend to provide more reliable genomic predictions. Imputation methods rely partially on linkage disequilibrium between markers to infer unobserved genotypes. Bos indicus cattle (e.g. Nelore breed) are characterized, in general, by lower levels of linkage disequilibrium between genetic markers at short distances, compared to taurine breeds. Thus, it is important to evaluate the accuracy of imputation to better define which imputation method and chip are most appropriate for genomic applications in indicine breeds.Methods. Accuracy of genotype imputation in Nelore cattle was evaluated using different LD chips, imputation software and sets of animals. Twelve commercial and customized LD chips with densities ranging from 7 K to 75 K were tested. Customized LD chips were virtually designed taking into account minor allele frequency, linkage disequilibrium and distance between markers. Software programs FImpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina® BovineHD chip (HD), 793 sires composed the reference set, and the remaining 202 younger sires and all the cows composed two separate validation sets for which genotypes were masked except for the SNPs of the LD chip that were to be tested.Results: Imputation accuracy increased with the SNP density of the LD chip. However, the gain in accuracy with LD chips with more than 15 K SNPs was relatively small because accuracy was already high at this density. Commercial and customized LD chips with equivalent densities presented similar results. FImpute outperformed BEAGLE for all LD chips and validation sets. Regardless of the imputation software used, accuracy tended to increase as the relatedness between imputed and reference animals increased, especially for the 7 K chip.Conclusions: If the Illumina® BovineHD is considered as the target chip for genomic applications in the Nelore breed, cost-effectiveness can be improved by genotyping part of the animals with a chip containing around 15 K useful SNPs and imputing their high-density missing genotypes with FImpute. © 2014 Carvalheiro et al.; licensee BioMed Central Ltd.

Melo T.P.,Paulista University | Takada L.,Paulista University | Baldi F.,Paulista University | Oliveira H.N.,Paulista University | And 6 more authors.
BMC Genetics | Year: 2016

Background: QTL mapping through genome-wide association studies (GWAS) is challenging, especially in the case of low heritability complex traits and when few animals possess genotypic and phenotypic information. When most of the phenotypic information is from non-genotyped animals, GWAS can be performed using the weighted single-step GBLUP (WssGBLUP) method, which permits to combine all available information, even that of non-genotyped animals. However, it is not clear to what extent phenotypic information from non-genotyped animals increases the power of QTL detection, and whether factors such as the extent of linkage disequilibrium (LD) in the population and weighting SNPs in WssGBLUP affect the importance of using information from non-genotyped animals in GWAS. These questions were investigated in this study using real and simulated data. Results: Analysis of real data showed that the use of phenotypes of non-genotyped animals affected SNP effect estimates and, consequently, QTL mapping. Despite some coincidence, the most important genomic regions identified by the analyses, either using or ignoring phenotypes of non-genotyped animals, were not the same. The simulation results indicated that the inclusion of all available phenotypic information, even that of non-genotyped animals, tends to improve QTL detection for low heritability complex traits. For populations with low levels of LD, this trend of improvement was less pronounced. Stronger shrinkage on SNPs explaining lower variance was not necessarily associated with better QTL mapping. Conclusions: The use of phenotypic information from non-genotyped animals in GWAS may improve the ability to detect QTL for low heritability complex traits, especially in populations in which the level of LD is high. © 2016 The Author(s).

Queiroz S.A.,São Paulo State University | Oliveira J.A.,São Paulo State University | Costa G.Z.,São Paulo State University | Fries L.A.,GenSys Consultores Associados S C Ltda
Archivos de Zootecnia | Year: 2013

This research aimed at studying the effects of age of the cow at calving (IVP), age of the animal at yearling (IDS), the direct additive genetic (AD) and maternal (AM) effects and individual heterozygosity (HI) on visual scores of conformation (CS), early finishing (PS) and muscling (MS) at postweaning and average daily gain from weaning to yearling (GDS) of cattle used to originate the Brangus breed. There were analyzed records on 24 531, 21 166, 24 006 and 25 419 for CS, PS, MS and GDS, respectively, of animals born from 1986 to 2002 belonging to livestock files of Gensys Consultores Associados S/C Ltda. The analyses were performed by the least square method using mathematical models that included contemporary group as class variable and IVP, IDS, AD, AM and HI as covariates. IVP showed linear and quadratic effects (p<0.01) on GDS and linear (p<0.01) on PS, while the quadratic effect of IDS was not significant for PS and GDS. AD and AM were significant (p<0.01) only for PS and MS scores, respectively. All the traits were significantly (p<0.01) influenced by HI. The environmental and genetic effects were important sources of variation for the studied traits and should be taken into account when comparison of animals and selection were performed.

Loading Gensys Consultores Associados S C Ltda collaborators
Loading Gensys Consultores Associados S C Ltda collaborators