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Made available in DSpace on 2018-12-11T17:08:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The aim of this study was to determine the extent (r2) of linkage disequilibrium (LD) in the genome of Nellore cattle, and to examine associations between single nucleotide polymorphisms (SNP) and age at first calving (AFC) and early pregnancy (EP) using a panel of high-density SNPs and data from 1182 Nellore females. A total of 13 contemporary groups (CG) were used consisting of farm, season, and year of birth. For genome-wide association analysis, SNPs with a minor allele frequency (MAF)

Made available in DSpace on 2019-10-06T17:03:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-02-20 Background: Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. Results: Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. Conclusions: There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance. Animal Science Department School of Agricultural and Veterinary Sciences São Paulo State University (Unesp) Animal Science Department São Paulo State University (Unesp), Dracena Animal Science Department School of Agricultural and Veterinary Sciences São Paulo State University (Unesp) Animal Science Department São Paulo State University (Unesp), Dracena

Made available in DSpace on 2019-10-05T08:00:48Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) 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, BAYESC pi, 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. BAYESC pi showed higher predictive ability to estimate SNP effects and GEBV for all traits. (C) 2018 Elsevier Inc. All rights reserved. Sao Paulo State Univ, Via Acesso Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, Brazil Univ Fed Bahia, Ave Adhemar de Barros 500, BR-40170110 Salvador, BA, Brazil Sao Paulo State Univ, Via Acesso Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, Brazil FAPESP: :2009/16118-5

Made available in DSpace on 2018-12-11T17:16:07Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-07-01 The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth. Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Escola de Medicina Veterinária e Zootecnia Universidade Federal da Bahia (UFBA) Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias

Made available in DSpace on 2018-12-11T17:35:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Reproductive traits are of the utmost importance for any livestock farming, but are difficult to measure and to interpret since they are influenced by various factors. The objective of this study was to detect associations between known polymorphisms in candidate genes related to sexual precocity in Nellore heifers, which could be used in breeding programs. Records of 1,689 precocious and non-precocious heifers from farms participating in the Conexão Delta G breeding program were analyzed. A subset of single nucleotide polymorphisms (SNP) located in the region of the candidate genes at a distance of up to 5 kb from the boundaries of each gene, were selected from the panel of 777,000 SNPs of the High-Density Bovine SNP BeadChip. Linear mixed models were used for statistical analysis of early heifer pregnancy, relating the trait with isolated SNPs or with haplotype groups. The model included the contemporary group (year and month of birth) as fixed effect and parent of the animal (sire effect) as random effect. The fastPHASE® and GenomeStudio® were used for reconstruction of the haplotypes and for analysis of linkage disequilibrium based on r2 statistics. A total of 125 candidate genes and 2,024 SNPs forming haplotypes were analyzed. Statistical analysis after Bonferroni correction showed that nine haplotypes exerted a significant effect (p

Made available in DSpace on 2018-12-11T17:32:48Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-06-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Stayability, which can be defined as the probability of a cow calving at a certain age when given the opportunity, is an important reproductive trait in beef cattle because it is directly related to herd profitability. The objective of this study was to estimate genetic parameters and to identify possible genomic regions associated with the phenotypic expression of stayability in Nellore cows. The variance components were estimated by Bayesian inference using a threshold animal model that included the systematic effects of contemporary group and sexual precocity and the random effects of animal and residual. The SNP effects were estimated by the single-step genomic BLUP method using information of 2,838 animals (2,020 females and 930 sires) genotyped with the Illumina High-Density BeadChip Array (San Diego, CA, USA). The variance explained by windows formed by 200 consecutive SNPs was used to identify genomic regions of largest effect on the expression of stayability. The heritability was 0.11 ± 0.01 when A matrix (pedigree) was used and 0.14 ± 0.01 when H matrix (relationship matrix that combines pedigree information and SNP data) was used. A total of 147 candidate genes for stayability were identified on chromosomes 1, 2, 5, 6, 9 and 20 and on the X chromosome. New candidate regions for stayability were detected, most of them related to reproductive, immunological and central nervous system functions. Faculdade de Ciências Agrárias e Veterinárias UNESP Escola de Medicina Veterinária e Zootecnia UFBA CNPq Fellowship Faculdade de Ciências Agrárias e Veterinárias UNESP

Made available in DSpace on 2018-12-11T17:27:01Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-01-29 Background: The objective of this study was to evaluate the accuracy of genomic predictions for rib eye area (REA), backfat thickness (BFT), and hot carcass weight (HCW) in Nellore beef cattle from Brazilian commercial herds using different prediction models. Methods: Phenotypic data from 1756 Nellore steers from ten commercial herds in Brazil were used. Animals were offspring of 294 sires and 1546 dams, reared on pasture, feedlot finished, and slaughtered at approximately 2 years of age. All animals were genotyped using a 777k Illumina Bovine HD SNP chip. Accuracy of genomic predictions of breeding values was evaluated by using a 5-fold cross-validation scheme and considering three models: Bayesian ridge regression (BRR), Bayes C (BC) and Bayesian Lasso (BL), and two types of response variables: traditional estimated breeding value (EBV), and phenotype adjusted for fixed effects (Y∗). Results: The prediction accuracies achieved with the BRR model were equal to 0.25 (BFT), 0.33 (HCW) and 0.36 (REA) when EBV was used as response variable, and 0.21 (BFT), 0.37 (HCW) and 0.46 (REA) when using Y∗. Results obtained with the BC and BL models were similar. Accuracies increased for traits with a higher heritability, and using Y∗instead of EBV as response variable resulted in higher accuracy when heritability was higher. Conclusions: Our results indicate that the accuracy of genomic prediction of carcass traits in Nellore cattle is moderate to high. Prediction of genomic breeding values from adjusted phenotypes Y∗was more accurate than from EBV, especially for highly heritable traits. The three models considered (BRR, BC and BL) led to similar predictive abilities and, thus, either one could be used to implement genomic prediction for carcass traits in Nellore cattle. Faculdade de Ciências Agrárias e Veterinárias UNESP Department of Animal Sciences University of Wisconsin-Madison Faculdade de Medicina Veterinária e Zootecnia UNESP Faculdade de Ciências Agrárias e Veterinárias UNESP Faculdade de Medicina Veterinária e Zootecnia UNESP

Made available in DSpace on 2018-12-11T17:29:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-06-21 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. UNESP Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias GenSys Consultores Associados S/C Ltda University of Guelph Centre for Genetic Improvement of Livestock UNESP Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias

Made available in DSpace on 2022-04-28T19:03:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-06-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The objective of this study was to identify genomic regions that are associated with meat quality traits in the Nellore breed. Nellore steers were finished in feedlots and slaughtered at a commercial slaughterhouse. This analysis included 1,822 phenotypic records of tenderness and 1,873 marbling records. After quality control, 1,630 animals genotyped for tenderness, 1,633 animals genotyped for marbling, and 369,722 SNPs remained. The results are reported as the proportion of variance explained by windows of 150 adjacent SNPs. Only windows with largest effects were considered. The genomic regions were located on chromosomes 5, 15, 16 and 25 for marbling and on chromosomes 5, 7, 10, 14 and 21 for tenderness. These windows explained 3,89% and 3,80% of the additive genetic variance for marbling and tenderness, respectively. The genes associated with the traits are related to growth, muscle development and lipid metabolism. The study of these genes in Nellore cattle is the first step in the identification of causal mutations that will contribute to the genetic evaluation of the breed. Departamento de Zootecnia Faculdade de Ciências Agrarias E Veterinárias Conselho Nacional de Desenvolvimento Científico E Tecnológico - CNPq Departamento de Melhoramento E Nutrição Animal Faculdade de Medicina Veterinária E Zootecnia Universidade Tecnológica do Paraná Dois Vizinhos Departamento de Medicina Veterinária Preventiva E Produção Animal Universidade Federal DaBahia

The objective of this study was to identify associations between known polymorphisms in genes related to adipose tissue and sexual precocity in Nellore cattle. A total of 1689 precocious and non-precocious heifers belonging to farms participating in Conexao Delta G breeding program were studied. SNPs from the Illumina High-Density Bovine SNP BeadChip were used. This chip contains 777,000 SNPs located within the region of the candidate genes at a distance of up to 5 kb, considering that linkage disequilibrium (LD) exists at this distance. Linear models were used for statistical analysis. The fastPHASE and GenomeStudio programs were used for haplotype reconstruction and LD analysis based on r2 statistics. Fifty-seven candidate genes and 443 SNPs were analyzed: among the latter, 370 SNPs formed 83 haplotypes, while the remaining SNPs were studied separately. Statistical analysis showed that only three haplotypes, one haplotype consisting of two SNPs located in the FABP4 gene and two haplotypes consisting of four and two SNPs located in the PPP3CA gene, had a significant effect on sexual precocity at P < 0.05. It can be concluded that the FABP4 and PPP3CA genes influence sexual precocity and may therefore be used in selection programs designed to improve sexual precocity in Nellore cattle.