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Made available in DSpace on 2019-10-06T16:51:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-11-01 Principal component analysis (PCA) is used to summarize important information from multivariate data in sets of new variables named principal components (PCs). In animal breeding, these new composite variables can be used to study the associations among multiple traits using the magnitude and direction of the PCA coefficients (in the eigenvectors) for each trait. Phenotypic data from 355 524 Nellore animals were used to estimate genetic parameters and explore the relationship among growth (weaning and post-weaning weight gain), visual score (weaning and yearling conformation, finishing precocity and muscling) and reproductive (scrotal circumference) traits using PCA. Genetic parameters were estimated by multi-trait analysis using a mixed linear animal model. The eigen-decomposition of the additive genetic (co)variance matrix (AT matrix) obtained using multi-trait analysis were used to calculate the PCs. In addition, PCA using the (co)variance matrix of the breeding values (EBVs) from single- and multi-trait analyses were investigated for comparison purposes. The direct heritability estimates for the weaning and yearling traits ranged from 0.17 (birth-to-weaning weight gain and conformation) to 0.21 (finishing precocity) and from 0.18 (weaning-to-yearling weight gain) to 0.46 (scrotal circumference), respectively. Genetic correlations estimated among all analyzed traits were positive (favorable) ranging from 0.15 (conformation at weaning and scrotal circumference) to 0.96 (finishing precocity and muscling at weaning). The first three PCs from multi-trait analysis using the eigen-decomposition of the AT matrix, explained 87.11% of the total additive genetic variance for the traits. The first PC (PC1) had negative and relatively similar coefficients for all traits, the second PC (PC2) contrasted the animals with early or late biotype, and the third PC (PC3) characterized a contrast between weaning and yearling traits. Our findings suggest that the PCA could be explored in breeding programs to select Nellore cattle to tailor selection towards specific PC, targeting, for instance, faster growth and precocious biotype. Department of Animal Science School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane Centre for Genetic Improvement of Livestock Department of Animal Biosciences University of Guelph, 50 Stone Road East GenSys Associated Consultants Department of Exact Sciences School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane National Council for Science and Technological Development Department of Animal Science Universidade Federal de Pelotas Department of Animal Science School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane Department of Exact Sciences School of Agricultural and Veterinarian Sciences Sao Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0-0.86) and the heritability of residual variance is low (median = 0.01; range 0-0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.

Background In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv ≠ 0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv = 0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\upsigma}_{\widehat{\mathrm{e}}}^2 $$\end{document}σe^2). Results The dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor > 20) with dEBVv and ln_\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\upsigma}_{\widehat{\mathrm{e}}}^2 $$\end{document}σe^2, respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation. Conclusions It is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it. Electronic supplementary material The online version of this article (10.1186/s12864-018-5003-4) contains supplementary material, which is available to authorized users.

Made available in DSpace on 2018-12-11T17:20:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-06-05 Background: Due to the advancement in high throughput technology, single nucleotide polymorphism (SNP) is routinely being incorporated along with phenotypic information into genetic evaluation. However, this approach often cannot achieve high accuracy for some complex traits. It is possible that SNP markers are not sufficient to predict these traits due to the missing heritability caused by other genetic variations such as microsatellite and copy number variation (CNV), which have been shown to affect disease and complex traits in humans and other species. Results: In this study, CNVs were included in a SNP based genomic selection framework. A Nellore cattle dataset consisting of 2230 animals genotyped on BovineHD SNP array was used, and 9 weight and carcass traits were analyzed. A total of six models were implemented and compared based on their prediction accuracy. For comparison, three models including only SNPs were implemented: 1) BayesA model, 2) Bayesian mixture model (BayesB), and 3) a GBLUP model without polygenic effects. The other three models incorporating both SNP and CNV included 4) a Bayesian model similar to BayesA (BayesA+CNV), 5) a Bayesian mixture model (BayesB+CNV), and 6) GBLUP with CNVs modeled as a covariable (GBLUP+CNV). Prediction accuracies were assessed based on Pearson's correlation between de-regressed EBVs (dEBVs) and direct genomic values (DGVs) in the validation dataset. For BayesA, BayesB and GBLUP, accuracy ranged from 0.12 to 0.62 across the nine traits. A minimal increase in prediction accuracy for some traits was noticed when including CNVs in the model (BayesA+CNV, BayesB+CNV, GBLUP+CNV). Conclusions: This study presents the first genomic prediction study integrating CNVs and SNPs in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some traits in Nellore cattle. Fort Keogh Livestock and Range Research Laboratory USDA Agricultural Research Service UNESP - Univ Estadual Paulista Departamento de Medicina Veterinária Preventiva e Reprodução Animal Faculdade de Ciências Agrárias e Veterinárias Chinese Academy of Agricultural Science Institute of Animal Science Northwest A and F University Shaanxi Key Laboratory of Agricultural Molecular Biology College of Animal Science and Technology Faculdade de Ciências Agrárias e Veterinárias UNESP - Univ Estadual Paulista Departamento de Zootecnia Animal Genomics and Improvement Laboratory BARC USDA-ARS University of Maryland Department of Animal and Avian Sciences Faculdade de Medicina Veterinária de Araçatuba UNESP - Univ Estadual Paulista Departamento de Apoio Produção e Saúde Animal UNESP - Univ Estadual Paulista Departamento de Medicina Veterinária Preventiva e Reprodução Animal Faculdade de Ciências Agrárias e Veterinárias Faculdade de Ciências Agrárias e Veterinárias UNESP - Univ Estadual Paulista Departamento de Zootecnia Faculdade de Medicina Veterinária de Araçatuba UNESP - Univ Estadual Paulista Departamento de Apoio Produção e Saúde Animal

Made available in DSpace on 2018-12-11T17:19:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-05-04 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Feet and leg conformation is evaluated as a subset of conformational structure traits in dairy and beef cattle and is related to the feet and leg quality that can compromise the animals’ productive performance and longevity. The aim of this study was to perform a genome-wide association study (GWAS) of two traits related to feet and leg conformation in Nellore cattle to identify chromosomal regions related to the expression of these traits. Phenotypic and pedigree data from 104,725 animals and genotypes from 1,435 animals and 407,730 SNPs were used. Feet and leg structure was evaluated as a binary trait (FL1) to identify yearling animals with feet and leg problems or as categorical score (FL2) to assess the overall quality of their feet and leg. The top ten 1-Mb windows that explained the largest proportion of the total genetic variance were identified and functional enrichment analyses were performed. The 10 windows with large effects obtained for FL1 are located on chromosomes 1, 2, 6, 7, 8, 10, and 14, and together explained 8.96% of the additive genetic variance. For FL2, these windows are located on chromosomes 1, 7, 10, 11, 18, 20, 22, 28, and 29, explaining 8.98% of the additive genetic variance. Several candidate genes were identified, including DLX2 which is associated with osteogenic differentiation, IL-1β and IL-1A associated with some properties of articular cartilage, PiT1 which plays an important role in bone physiology, and CTSL associated with rheumatoid arthritis. The results presented here should contribute to a better understanding of the genetic and physiologic mechanisms regulating both traits, and identifies candidate genes for future investigation of causal mutations. Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Câmpus de Jaboticabal Gensys Associated Consultants Departamento de Zootecnista Universidade Federal da Bahia (UFBA) Departamento de Ciências Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Câmpus de Jaboticabal Conselho Nacional de Desenvolvimento Científico e Tecnológico Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Câmpus de Jaboticabal Departamento de Ciências Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Câmpus de Jaboticabal FAPESP: 2013/25312-5 CAPES: 303606/2009-6

Made available in DSpace on 2018-12-11T17:15:54Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS. Departamento de Zootecnia School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane s/n GenSys Consultores Associados S/S Ltda., Rua Guilherme Alves, 170. Cj 304 Departamento de Zootecnia School of Agricultural and Veterinarian Sciences (FCAV) São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane s/n FAPESP: 2010/06185-4 CNPq: 307440/2013-3 CNPq: 308636/2014-7

Feet and leg conformation scores are important traits in beef cattle because they encompass a wide range of locomotion disorders that can lead to productive and reproductive losses. Thus, the study of feet and legs in beef cattle is essential for evaluating possible responses to selection focusing on minimizing economic losses caused by the occurrence of feet and leg problems. The aim of this study was to estimate variance components for feet and leg conformation traits in Nelore cattle. The data set contained records of approximately 300,000 animals that were born between 2000 and 2013. These animals belonged to the commercial beef cattle breeding program of the CRV Lagoa (). Feet and legs were evaluated by assigning visual scores at 2 different time points: feet and leg evaluated as a binary trait (FL1), measured at yearling (about 550 d of age) to identify whether (or not) an animal has feet and leg defects, and feet and leg score (FL2), ranging from 1 (less desirable) to 5 (more desirable) was assigned to the top 20% of animals according to the selection index adopted by the beef cattle breeding program, which was measured 2 to 5 mo after the yearling evaluation. The FL1 and FL2 traits were analyzed together with yearling weight (YW). The (co)variance components and breeding values were estimated by Bayesian inference using 2-trait animal models. The posterior means (standard errors) of the heritabilities for FL1, FL2, and YW were 0.18 (0.04), 0.39 (0.07), and 0.47 (0.01), respectively. The results indicate that the incidence of feet and leg problems in this population might be reduced by selection. The genetic correlation between FL1 and FL2 (-0.47) was moderate and negative as expected because the classification score that holds up each trait has opposite numerical values. The genetic trends estimated for FL1 and FL2 (-0.042 and 0.021 genetic standard deviations per year, respectively) were favorable and they indicate that the independent culling strategy for feet and leg problems promotes favorable changes and contributes to the genetic progress of these traits in the population under study.

Made available in DSpace on 2018-11-26T15:44:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-04-01 There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 +/- 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (

Made available in DSpace on 2019-10-06T17:01:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Reproductive performance is a key indicator of the long-term sustainability of any livestock production system. Testicular hypoplasia (TH) is a morphological and functional reproductive disorder that affects bulls around the world and consequently causes major economic losses due to reduced fertility rates. Despite the improvements in management practices to enhance performance of affected animals, the use of hypoplastic animals for reproduction might contribute to expand the prevalence of this disorder. The aim of this study was to identify genomic regions that are associated with TH in Nellore cattle by performing a genome-wide association study (GWAS) and functional analyses. Phenotypic and pedigree data from 47,563 animals and genotypes (500,689 Single Nucleotide Polymorphism, SNPs) from 265 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. The estimated breeding values (EBVs) were calculated by fitting a single-trait threshold animal model using a Bayesian approach. The SNP effects were estimated using the Bayes C method and de-regressed EBVs for TH as the response variable (pseudo-phenotype). The top-15 ranking windows (5-adjacent SNPs) that explained the highest proportion of variance were identified for further functional and biological network analyses. The posterior mean (95% highest posterior density) of the heritability for TH was 0.16 (0.08; 0.23). The most important genomic windows were located on BTA1, BTA3, BTA4, BTA5, BTA9, BTA22, BTA23, and BTA25. These windows explained together 22.69% of the total additive genetic variance for TH. Strong candidate genes associated with metabolism and synthesis of steroids, cell survival, spermatogenesis process and sperm motility were identified, which might play an important role in the expression of TH. Our findings contribute to a better biological understanding of TH and future characterization of causal variants might enable improved genomic prediction of this trait in beef cattle. GenSys Associated Consultants Department of Animal Sciences School of Agricultural and Veterinary Sciences São Paulo State University (UNESP) Department of Animal Sciences Purdue University Centre for Genetic Improvement of Livestock (CGIL) Department of Animal Biosciences University of Guelph National Council for Science and Technological Development (Cnpq) Department of Animal Sciences School of Agricultural and Veterinary Sciences São Paulo State University (UNESP)

Made available in DSpace on 2020-12-12T01:34:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-11-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Several methods have been used to perform genome wide association (GWA) studies, aiming to map quantitative trait loci (QTL) and candidate variants. The single-step genomic best linear unbiased prediction (ssGBLUP) method is one alternative to perform GWA, which allows the simultaneous use of genotypic, pedigree and phenotypic information. Bayesian multiple regression models have also been used to perform GWA, allowing specifying different priori distribution for the molecular marker effects. The aim of the present study was to evaluate, through simulation, the performance of different methods in the identification of QTLs for polygenic and major gene traits, under different heritabilities when only relatively few animals were genotyped. We also investigated the consequence of considering the agreement among results from different methods as a strategy to decrease errors associated with false positives in QTL mapping. For polygenic scenarios, results showed low power to detect QTL, irrespective of the method, and the use of phenotypes from non-genotyped animals slightly helped QTL detection of ssGBLUP and weighted ssGBLUP (wssGBLUP). For scenarios with major gene effects, there was greater power in QTL detection, with a slight superiority of Bayes C over the other methods. The inclusion of additional phenotypic information (from non-genotyped animals) harmed the performance of wssGBLUP in the presence of major QTL. When only consensus regions identified by different methods were considered as evidence of QTL, the percentage of top windows containing a true QTL tended to increase with the number of methods that identified a top window, for all scenarios. However, an important proportion of true QTL were identified only by a single or few methods. Despite the small differences among methods in the QTL detection, for polygenic traits, the ssGBLUP and wssGBLUP methods seemed to show better results in comparison to the other methods mainly in the low heritability scenario. For traits with major gene effects, the Bayes C method is expected to present better results, compared to the other methods evaluated, given a limited number of genotyped animals. The strategy to use agreement of GWA results among methods to map QTL helps to reduce false positives but comes at a cost of missing important QTL, irrespective of the genetic structure of the trait. Department of Animal Science School of Agricultural and Veterinary Sciences São Paulo State University (UNESP) Via de Acesso Prof. Paulo Donato Castellane GenSys Consultores Associados S/C Ltda National Council for Science and Technological Development Department of Animal Science School of Agricultural and Veterinary Sciences São Paulo State University (UNESP) Via de Acesso Prof. Paulo Donato Castellane CAPES: 2013

Made available in DSpace on 2020-12-12T02:34:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 Universidade Estadual Paulista Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The search for candidate genes underlying the expression of principal components (PCs) for different traits is a useful tool that allows exploring biological mechanisms associated with the traits of interest. The aim of this study was to identify genomic regions associated with PCs for growth, visual score and reproductive traits in Nellore cattle by performing a genome-wide association study (GWAS). Phenotypic and pedigree data from 355,524 animals and genotypes from 3,519 animals, were used in this investigation. The estimated breeding values (EBV) were obtained from a multi-trait analysis using a mixed linear animal model. The eigen-decomposition of the additive genetic (co)variance matrix among traits was used to calculate the EBVs for the main PCs. The SNP effects were estimated using the weighted single-step GBLUP and the BayesC method. The top-10 ranking windows that explained the highest proportion of variance were identified for further functional analyses. The most important genomic regions were identified on BTA7 and BTA24 for PC1, BTA8 for PC2, and BTA3 and BTA10 for PC3. The functional analyses contributed to unravel biological interpretation of PCs by identifying genes potentially associated with growth, carcass traits, conformation, and fatty acid composition traits. These findings are of relevance to the biological understanding of the PCs and their related biotypes in Nellore cattle, potentially allowing for genetic selection for more specific breeding goals. Department of Animal Science School of Agricultural and Veterinary Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane Centre for Genetic Improvement of Livestock Department of Animal Biosciences University of Guelph, 50 Stone Road East Department of Animal Sciences Purdue University, 610 Purdue Mall GenSys Associated Consultants National Council for Science and Technological Development Department of Exact Sciences School of Agricultural and Veterinary Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane Department of Animal Science School of Agricultural and Veterinary Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane Department of Exact Sciences School of Agricultural and Veterinary Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castellane FAPESP: #2009/16118-5 FAPESP: #2015/25449-6 FAPESP: #2017/03331-9

Made available in DSpace on 2018-12-11T17:16:50Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 The recent evolution of cattle is marked by fluctuations in body size. Height in the Bos taurus lineage was reduced by a factor of ∼1.5 from the Neolithic to the Middle Ages, and increased again only during the Early Modern Ages. Using haplotype analysis, we found evidence that the bovine PLAG1 mutation (Q) with major effects on body size, weight and reproduction is a >1,000 years old derived allele that increased rapidly in frequency in Northwestern European B. taurus between the 16th and 18th centuries. Towards the 19th and 20th centuries, Q was introgressed into non-European B. taurus and Bos indicus breeds. These data implicate a major role of Q in recent changes in body size in modern cattle, and represent one of the first examples of a genomic sweep in livestock that was driven by selection on a complex trait. São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences Jaboticabal Department of Preventive Veterinary Medicine and Animal Reproduction International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics Istituto di Zootecnica BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico Università Cattolica del Sacro Cuore São Paulo State University (Unesp) School of Veterinary Medicine Araçatuba Department of Support Production and Animal Health Recombinetics Inc. UFPI - Universidade Federal do Piauí Animal Genomics and Improvement Laboratory Agricultural Research Service USDA Escola de Veterinária e Zootecnia (EVZ) Universidade Federal de Goiás - UFG Campus Samambaia São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences Jaboticabal Department of Animal Science GenSys Consultores Associados Centro Universitário Católico Salesiano Department of Anthropology University of Maryland Dipartimento di Storia Archeologia e Storia dell'Arte Facoltà di Lettere e Filosofia Università Cattolica del Sacro Cuore Società Friulana di Archeologia Istituto di Genomica Applicata Dipartamento di Scienze Agrarie ed Ambientali Università di Udine BOKU University of Natural Resources and Life Sciences Department of Sustainable Agricultural Systems Division of Livestock Sciences São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences Jaboticabal Department of Preventive Veterinary Medicine and Animal Reproduction São Paulo State University (Unesp) School of Veterinary Medicine Araçatuba Department of Support Production and Animal Health São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences Jaboticabal Department of Animal Science

Genotype imputation is widely used as a cost-effective strategy in genomic evaluation of cattle. Key determinants of imputation accuracies, such as linkage disequilibrium patterns, marker densities, and ascertainment bias, differ between Bos indicus and Bos taurus breeds. Consequently, there is a need to investigate effectiveness of genotype imputation in indicine breeds. Thus, the objective of the study was to investigate strategies and factors affecting the accuracy of genotype imputation in Gyr (Bos indicus) dairy cattle. Four imputation scenarios were studied using 471 sires and 1,644 dams genotyped on Illumina BovineHD (HD-777K; San Diego, CA) and BovineSNP50 (50K) chips, respectively. Scenarios were based on which reference high-density single nucleotide polymorphism (SNP) panel (HDP) should be adopted [HD-777K, 50K, and GeneSeek GGP-75Ki (Lincoln, NE)]. Depending on the scenario, validation animals had their genotypes masked for one of the lower-density panels: Illumina (3K, 7K, and 50K) and GeneSeek (SGGP-20Ki and GGP-75Ki). We randomly selected 171 sires as reference and 300 as validation for all the scenarios. Additionally, all sires were used as reference and the 1,644 dams were imputed for validation. Genotypes of 98 individuals with 4 and more offspring were completely masked and imputed. Imputation algorithms FImpute and Beagle v3.3 and v4 were used. Imputation accuracies were measured using the correlation and allelic correct rate. FImpute resulted in highest accuracies, whereas Beagle 3.3 gave the least-accurate imputations. Accuracies evaluated as correlation (allelic correct rate) ranged from 0.910 (0.942) to 0.961 (0.974) using 50K as HDP and with 3K (7K) as low-density panels. With GGP-75Ki as HDP, accuracies were moderate for 3K, 7K, and 50K, but high for SGGP-20Ki. The use of HD-777K as HDP resulted in accuracies of 0.888 (3K), 0.941 (7K), 0.980 (SGGP-20Ki), 0.982 (50K), and 0.993 (GGP-75Ki). Ungenotyped individuals were imputed with an average accuracy of 0.970. The average top 5 kinship coefficients between reference and imputed individuals was a strong predictor of imputation accuracy. FImpute was faster and used less memory than Beagle v4. Beagle v4 outperformed Beagle v3.3 in accuracy and speed of computation. A genotyping strategy that uses the HD-777K SNP chip as a reference panel and SGGP-20Ki as the lower-density SNP panel should be adopted as accuracy was high and similar to that of the 50K. However, the effect of using imputed HD-777K genotypes from the SGGP-20Ki on genomic evaluation is yet to be studied.

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.

In order to achieve improvements in production efficiency in livestock, herds of high sexual precocity and good fertility are needed. These traits increase the availability of animals in herd, either for sale or selection, allowing both greater selective intensity and greater genetic progress. This study aimed at estimating genetic parameters for reproductive traits measured directly in females in order to verify whether they could be used as selection criteria for genetic improvement in Nellore cows, as well as estimating the genetic relationship among these traits and scrotal circumference (SC), the traditional selection criterion for sexual precocity in cattle. In addition to SC, stayability (STAY), number of calvings at 53 months (NC53) and heifers rebreeding (HR) were studied. The (co)variances and genetic parameters were estimated using Bayesian inference. STAY, NC53 and HR were analyzed assuming a threshold model, whereas SC was analyzed with a linear model. Heritability estimated for NC53 was 0.22, and this trait was strongly and positively correlated with STAY, meaning selection for NC53 would improve productive longevity of Nellore cows. Correlations estimated between HR and STAY (≈0.97) and between HR and NC53 (≈0.99) allow an improvement on HR rates if selection was applied to traits related to longevity. Genetic correlations among SC and female reproductive traits were positive but weak, suggesting the need to use reproductive traits directly measured in females in order to obtain greater improvements in sexual precocity and longevity.

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.

Despite the economic importance of beef cattle production in Brazil, female reproductive performance, which is strongly associated with production efficiency, is not included in the selection index of most breeding programmes due to low heritability and difficulty in measure. The body condition score (BCS) could be used as an indicator of these traits. However, so far little is known about the feasibility of using BCS as a selection tool for reproductive performance in beef cattle. In this study, we investigated the sources of variation in the BCS of Nellore beef cows, quantified its association with reproductive and maternal traits and estimated its heritability. BCS was analysed using a logistic model that included the following effects: contemporary group at weaning, cow weight and hip height, calving order, reconception together with the weight and scores of conformation and early finishing assigned to calves at weaning. In the genetic analysis, variance components of BCS were estimated through Bayesian inference by fitting an animal model that also included the aforementioned effects. The results showed that BCS was significantly associated with all of the reproductive and maternal variables analysed. The estimated posterior mean of heritability of BCS was 0.24 (highest posterior density interval at 95%: 0.093 to 0.385), indicating an involvement of additive gene action in its determination. The present findings show that BCS can be used as a selection criterion for Nellore females.

Weight gain is a key performance trait for beef cat- tle; however, attention should be given to the production costs for better profitability. Therefore, a feed efficiency trait based on per- formance can be an interesting approach to improve performance without increasing food costs. To identify candidate genes and ge- nomic 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)

This study aimed at imputing non(un)-genotyped sires using a stepwise imputation approach that combines identity by descent (IBD) detection methods with other imputation algorithms. We also studied the effect of using actual or imputed genotypes of non-genotyped sires in estimating genomic relationships. Simulations and real data were used for the analysis. Fifty sire families were simulated and 23 sire families were derived from 995 Brazilian Nellore cattle genotyped with Illumina ® Bovine HD (777,962 SNPs) SNP Chip. Un-genotyped sires were imputed using genotype information from progeny (5 or 10); progeny and grand offspring; a combination of progeny, mates of genotyped progeny and grand offspring; and the entire genotyped population. Stepwise imputation was done with an IBD detection method that uses simple inheritance rules (MERLIN) as a first step and subsequently with FImpute, MaCH or BEAGLE as the second step to infer genotypes that were not imputed unambiguously by MERLIN. The stepwise imputation procedure was compared to an approach that ignores the first step (MERLIN) but uses only prior pedigree information to impute non-genotyped animals. Imputation accuracy was assessed as percent of correctly called genotypes and the correlation between imputed and actual genotypes (in brackets). With real data, imputation accuracy ranged from 81.6% (0.856) to 97.4% (0.981) depending on the amount of genotyped information considered for the first step (MERLIN) and imputation algorithms used for the second step. Greater accuracies of imputing non-genotyped sires were obtained when the stepwise imputation approach was used with 10 genotyped offspring as the first step. The stepwise approach resulted in an increase of 1.2% (5 offsprings) and 4.7% (10 offsprings) in imputation accuracy. MaCH was more accurate in the second step, followed by FImpute then BEAGLE. Similar trends in imputation accuracy were observed for the simulated population. Generally, imputed genotypes were successfully used to estimate genomic relationships among close relatives but considerable bias was observed for true pairwise relationships of zero. In conclusion, high imputation accuracies can be achieved for non-genotyped animals when genotype information of 5 or 10 direct progeny is available for imputation. Performing preliminary IBD analysis and using non-ambiguous genotypes from that analysis in conventional imputation increased the imputation accuracy considerably.

The objective of a performance test station is to evaluate the performance of potential breeding bulls earlier in order to decrease the generation interval and increase genetic gain as well. This study evaluates the herd-of-origin influence on end-of-test weight (ETW), average daily weight gain during testing (ADG), average daily weight gain during the adjustment period (ADGadj), rib eye area (REA), marbling (MARB), subcutaneous fat thickness (SFT), conformation (C), early finishing (EF), muscling (M), navel (N) and temperament (T) scores, and scrotal circumference (SC) of Nellore cattle that underwent a performance test. We evaluated 664 animals that participated in the performance tests conducted at the Center for Performance CRV Lagoa between 2007 and 2012. Components of variance for each trait were estimated by an animal model (model 1), using the restricted maximum likelihood method. An alternative animal model (model 2) included, in addition to the fixed effects present in S1, the non-correlated random effect of herd-year (HY). A significant HY effect was observed on ETW, REA, SFT, ADGadj, C, and Cw (p

Number of calvings at 53 mo (NC53) was proposed as an alternative selection criterion to improve productive longevity of Nellore cows. This study was carried out to estimate variance components for NC53 by assuming different models, so that the potential for using this selection criterion to improve fertility of Nellore cows could be assessed. Genetic correlations between NC53, number of calvings at 89 mo (NC89), and 2 selection indexes used in this breed were also estimated. The NC53 trait is moderately heritable (posterior mean heritability ≈ 0.17) and selecting for this criterion could improve productive longevity of Nellore cows. Greater response to selection is expected by fitting a threshold animal model for this trait, rather than a linear animal model. Greater accuracy of prediction for this criterion could be achieved by fitting a threshold-linear model, considering this trait and a selection index composed by traits evaluated at weaning and long-yearling.

Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-27T11:27:21Z No. of bitstreams: 0 Made available in DSpace on 2014-05-27T11:27:21Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-12-01 The reproductive efficiency of Nellore females was described on the basis of sexual precocity, staying productive in the herd (NP), maternal productivity (PM) and estimated cost for maintenance (CM). The combination of these traits resulted in the bioeconomic maternal revenue index (RMat) ensures reproductive efficiency. The index estimates the return in kilograms of live weight produced per cow per year. In addition, the composition of calf weight produced was considered, adding to the PM the information on the scores of conformation, muscling and early finishing at weaning, in order to input the calf biotype. The females considered precocious had their age at first calving before 30 months. The NP was expressed by the number of calving till 53 months of age. The CM was calculated according to the estimated feed intake of dry matter. The estimated average RMat was 62.02±24.12 kg/ cow/year. Estimates of additive genetic and residual variances for RMat, using restricted maximum likelihood under a single trait animal model was equal to 195.35 and 242.96, respectively. The heritability estimated was 0.45±0.02, indicating that RMat is inheritable and can be applied in the breeding program to improve reproductive efficiency. The NP was the main component of variation for RMat. Sires selected based on RMat tended to have more efficient daughters. Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP, Jaboticabal, SP Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias UNESP, Jaboticabal, SP Gensys Consultores Associados S/S Ltda, Jaboticabal, SP Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP, Jaboticabal, SP Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias UNESP, Jaboticabal, SP

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.

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 2018-12-11T17:28:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-06-01 Background: Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). Results: We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894bp to 4,855,088bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. Conclusion: This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12. BARC USDA-ARS Animal Genomics and Improvement Laboratory, BARC-East Northwest A and F University College of Animal Science and Technology Faculdade de Ci�ncias Agr�rias e Veterin�rias UNESP - Univ Estadual Paulista Departamento de Medicina Veterin�ria Preventiva e Reprodu��o Animal Institute of Animal Science Chinese Academy of Agricultural Science College of Animal Science and Food Engineering University of S�o Paulo Department of Veterinary Medicine UNESP - Univ Estadual Paulista Departamento de Zootecnia Faculdade de Ci�ncias Agr�rias e Veterin�rias UNESP - Univ Estadual Paulista Departamento de Apoio Produ��o e Sa�de Animal Faculdade de Medicina Veterin�ria de Ara�atuba Recombinetics Inc. International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics Faculdade de Ci�ncias Agr�rias e Veterin�rias UNESP - Univ Estadual Paulista Departamento de Medicina Veterin�ria Preventiva e Reprodu��o Animal UNESP - Univ Estadual Paulista Departamento de Zootecnia Faculdade de Ci�ncias Agr�rias e Veterin�rias UNESP - Univ Estadual Paulista Departamento de Apoio Produ��o e Sa�de Animal Faculdade de Medicina Veterin�ria de Ara�atuba

Made available in DSpace on 2018-12-11T17:04:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-07-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Two complementary methods, namely Multi-Trait Meta-Analysis and Versatile Gene-Based Test for Genome-wide Association Studies (VEGAS), were used to identify putative pleiotropic genes affecting carcass traits in Bos indicus (Nellore) cattle. The genotypic data comprised over 777,000 single-nucleotide polymorphism markers scored in 995 bulls, and the phenotypic data included deregressed breeding values (dEBV) for weight measurements at birth, weaning and yearling, as well visual scores taken at weaning and yearling for carcass finishing precocity, conformation and muscling. Both analyses pointed to the pleomorphic adenoma gene 1 (PLAG1) as a major pleiotropic gene. VEGAS analysis revealed 224 additional candidates. From these, 57 participated, together with PLAG1, in a network involved in the modulation of the function and expression of IGF1 (insulin like growth factor 1), IGF2 (insulin like growth factor 2), GH1 (growth hormone 1), IGF1R (insulin like growth factor 1 receptor) and GHR (growth hormone receptor), suggesting that those pleiotropic genes operate as satellite regulators of the growth pathway. Departamento de Agroindústria Alimentos E Nutrição Escola Superior de Agricultura Luiz de Queiroz USP Departamento de Medicina Veterinária Preventiva E Reprodução Animal UNESP-Univ Estadual Paulista Faculdade de Ciências Agra Rias E Veterinárias Departamento de Apoio Produção E Saúde Animal UNESP-Univ Estadual Paulista Faculdade de Medicina Veterinária de Araçatuba International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics GenSys Consultores Associados Departamento de Zootecnia UNESP-Univ. Estadual Paulista Faculdade de Ciências Agra Rias E Veterinárias Università Cattolica del Sacro Cuore Recombinetics Inc. BOKU-University of Natural Resources and Life Sciences Department of Sustainable Agricultural Systems Division of Livestock Sciences Departamento de Medicina Veterinária Preventiva E Reprodução Animal UNESP-Univ Estadual Paulista Faculdade de Ciências Agra Rias E Veterinárias Departamento de Apoio Produção E Saúde Animal UNESP-Univ Estadual Paulista Faculdade de Medicina Veterinária de Araçatuba Departamento de Zootecnia UNESP-Univ. Estadual Paulista Faculdade de Ciências Agra Rias E Veterinárias FAPESP: 2014/01095-82013/02552-0

Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.

Made available in DSpace on 2018-12-11T17:22:08Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-08-01 Zebu cattle (Bos taurus indicus) are highly adapted to tropical regions. However, females reach puberty after taurine heifers, which affects the economic efficiency of beef cattle breeding in the tropical regions. The aims of this study were to establish associations between the haplotype alleles of the bovine genome and age at first calving (AFC) in the Nelore cattle, and to identify the genes and quantitative trait loci (QTL) related to this phenotype. A total of 2,273 Nelore cattle (995 males and 1,278 females) genotyped using the Illumina BovineHD BeadChip were used in the current study. The association analysis included females with valid first calving records as well as open heifers. Linkage disequilibrium (LD) analysis among the markers was performed using blocks of 5, 10, and 15 markers, which were determined by sliding windows shifting one marker at a time. Then, the haplotype block size to be used in the association study was chosen based on the highest r2 average among the SNPs in the block. The five HapAlleles most strongly associated with the trait (top five) were considered as significant associations. The results of the analysis revealed four genomic regions related to AFC, which overlapped with 20 QTL of the reproductive traits reported previously. Furthermore, there were 19 genes related to reproduction in those regions. In conclusion, the use of haplotypes allowed the detection of chromosomal regions associated with AFC in Nelore cattle, and provided the basis for elucidating the mechanisms underlying this trait. Faculdade de Ciências Biológicas e Ambientais Universidade Federal da Grande Dourados UFGD Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP Departamento de Medicina Veterinária Preventiva e Reprodução Animal Faculdade de Ciências Agrárias e Veterinárias UNESP Departamento de Apoio Produção e Saúde Animal Faculdade de Medicina Veterinária de Araçatuba UNESP GenSys Consultores Associados S/S Ltda International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias UNESP Departamento de Medicina Veterinária Preventiva e Reprodução Animal Faculdade de Ciências Agrárias e Veterinárias UNESP Departamento de Apoio Produção e Saúde Animal Faculdade de Medicina Veterinária de Araçatuba UNESP

Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2013-08-22T19:07:32Z No. of bitstreams: 1 S1516-35982009001200011.pdf: 340195 bytes, checksum: 98a79aafb82325a3d60bd0b3eaeddc7b (MD5) Made available in DSpace on 2013-08-22T19:07:32Z (GMT). No. of bitstreams: 1 S1516-35982009001200011.pdf: 340195 bytes, checksum: 98a79aafb82325a3d60bd0b3eaeddc7b (MD5) Previous issue date: 2009-12-01 Made available in DSpace on 2013-09-30T18:03:20Z (GMT). No. of bitstreams: 2 S1516-35982009001200011.pdf: 340195 bytes, checksum: 98a79aafb82325a3d60bd0b3eaeddc7b (MD5) S1516-35982009001200011.pdf.txt: 31715 bytes, checksum: 41644f4bc68390e43175aa01cbcaba55 (MD5) Previous issue date: 2009-12-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:19:07Z No. of bitstreams: 2 S1516-35982009001200011.pdf: 340195 bytes, checksum: 98a79aafb82325a3d60bd0b3eaeddc7b (MD5) S1516-35982009001200011.pdf.txt: 31715 bytes, checksum: 41644f4bc68390e43175aa01cbcaba55 (MD5) Made available in DSpace on 2014-05-20T13:19:07Z (GMT). No. of bitstreams: 2 S1516-35982009001200011.pdf: 340195 bytes, checksum: 98a79aafb82325a3d60bd0b3eaeddc7b (MD5) S1516-35982009001200011.pdf.txt: 31715 bytes, checksum: 41644f4bc68390e43175aa01cbcaba55 (MD5) Previous issue date: 2009-12-01 Desenvolveu-se um estudo de simulação estocástica com o objetivo de verificar as consequências do uso combinado de acasalamento dirigido e sêmen sexado em uma população de bovinos de corte sob seleção. Simularam-se seis gerações de seleção para três cenários de acasalamento e uso de sêmen sexado. O primeiro cenário foi caracterizado por acasalamento aleatório e uso exclusivo de sêmen convencional. O segundo cenário caracterizou-se pelo uso de acasalamento associativo positivo nas 40% melhores vacas e acasalamento associativo negativo nas demais, sem uso de sêmen sexado. O terceiro cenário seguiu o mesmo procedimento de acasalamento do segundo, combinando-o com uso de sêmen sexado nas vacas submetidas a acasalamento associativo positivo. O acasalamento associativo positivo teve maior impacto no progresso genético que o uso de sêmen sexado, apesar de ter aumentado a incidência de endogamia na população. O uso de acasalamento associativo negativo foi ineficiente em reduzir a variabilidade dos animais destinados ao abate. O uso combinado de acasalmento associativo positivo e sêmen sexado aumentou a produção de animais geneticamente superiores. Stochastic simulation was carried out to access the consequences of combined use of assortative mating and sexed semen in a beef cattle population under selection. Six generations of selection were simulated under three different scenarios of mating strategy and sexed semen use. The first was characterized by random mating and no use of sexed semen. The second was simulated using positive assortative mating (PAM) for the 40% top dams and negative assortative mating (NAM) for the remainder, with no use of sexed semen. The third followed the mating procedure of the second combined with use of sexed semen for dams under positive assortative mating. Positive assortative mating had more impact on the genetic progress than sexed semen, although it increased inbreeding incidence in the population. The combined use of negative assortative mating breeding was not efficient in reducing genetic variability of inferior offspring. The combined use of positive assortative mating and sexed semen improved production of genetically outstanding animals. Unesp FCAV Gensys Consultores Associados S/C Ltda UNESP FCAV Departamento de Zootecnia Unesp FCAV UNESP FCAV Departamento de Zootecnia

Made available in DSpace on 2015-10-22T06:27:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-04-17. Added 1 bitstream(s) on 2015-10-22T09:46:06Z : No. of bitstreams: 1 WOS000353019200003.pdf: 724955 bytes, checksum: 346f3a63b246310159756ccd797c7561 (MD5) European Science Foundation Advances in Farm Animal Genomic Resources project USDA-ARS Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Background: Nelore and Gir are the two most important indicine cattle breeds for production of beef and milk in Brazil. Historical records state that these breeds were introduced in Brazil from the Indian subcontinent, crossed to local taurine cattle in order to quickly increase the population size, and then backcrossed to the original breeds to recover indicine adaptive and productive traits. Previous investigations based on sparse DNA markers detected taurine admixture in these breeds. High-density genome-wide analyses can provide high-resolution information on the genetic composition of current Nelore and Gir populations, estimate more precisely the levels and nature of taurine introgression, and shed light on their history and the strategies that were used to expand these breeds.Results: We used the high-density Illumina BovineHD BeadChip with more than 777 K single nucleotide polymorphisms (SNPs) that were reduced to 697 115 after quality control filtering to investigate the structure of Nelore and Gir populations and seven other worldwide populations for comparison. Multidimensional scaling and model-based ancestry estimation clearly separated the indicine, European taurine and African taurine ancestries. The average level of taurine introgression in the autosomal genome of Nelore and Gir breeds was less than 1% but was 9% for the Brahman breed. Analyses based on the mitochondrial SNPs present in the Illumina BovineHD BeadChip did not clearly differentiate taurine and indicine haplotype groupings.Conclusions: The low level of taurine ancestry observed for both Nelore and Gir breeds confirms the historical records of crossbreeding and supports a strong directional selection against taurine haplotypes via backcrossing. Random sampling in production herds across the country and subsequent genotyping would be useful for a more complete view of the admixture levels in the commercial Nelore and Gir populations. Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria Università Cattolica del Sacro Cuore di Piacenza, Institute of Zootechnica and Biodiversity and Ancient DNA Research Center - BioDNA, Piacenza, Italy Empresa Brasileira de Pesquisa Agropecuária - Embrapa Gado de Leite, Juiz de Fora, MG, Brazil United States Department of Agriculture - Agricultural Research Service, Bovine Functional Genomics Laboratory, Beltsville, MD, USA Universidade Estadual Paulista (UNESP), Faculdade de Ciências Agrária e Veterinárias, Jaboticabal, SP, Brazil Universidade Estadual Paulista (UNESP) - Faculdade de Medicina Veterinária de Araçatuba, Araçatuba, SP, Brazil USDA-ARS: 1265-31000-104-00D CNPq: 560922/2010-8 CNPq: 483590/2010-0 FAPESP: 2014/01095-8 FAPESP: 2010/52030-2

Made available in DSpace on 2015-11-03T18:06:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-10-01. Added 1 bitstream(s) on 2015-11-04T10:13:26Z : No. of bitstreams: 1 S1984-29612014000400449.pdf: 606896 bytes, checksum: 2830ee8c635055ec093a3730b2f6fb16 (MD5) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) O presente estudo teve como objetivo investigar a ocorrência de anticorpos anti-Toxoplasma gondii, Leishmania infantum e Neospora caninum, em 151 gatos, por meio da Reação de Imunofluorescência Indireta (RIFI). Entre os meses de janeiro e abril de 2013, amostras de soro foram coletadas de 151 gatos domésticos (65 gatos errantes e 86 gatos domiciliados; 55 machos e 96 fêmeas), de Campo Grande, Mato Grosso do Sul, Brasil. Anticorpos IgG anti-T. gondii, anti-L. infantum e anti-N. caninum foram encontrados em 49 (32,5%), 34 (22,5%) e 10 (6,6%) gatos amostrados, respectivamente. Verificou-se uma associação estatisticamente significativa entre as infecções por T. gondii e N. caninum, T. gondii e L. infantum e N. caninum e Leishmania infantum (p

Made available in DSpace on 2014-12-03T13:07:04Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-02-27Bitstream added on 2014-12-03T13:24:34Z : No. of bitstreams: 1 WOS000333517900001.pdf: 714400 bytes, checksum: f20924817f39417f4b53ef96b660a911 (MD5) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (BFGL) from the USDA Agricultural Research Service 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. Univ Estadual Paulista, UNESP, Fac Ciencias Agr & Vet, BR-14884900 Sao Paulo, Brazil GenSys Consultores Assoc SC Ltda, BR-90680000 Porto Alegre, RS, Brazil Univ Nat Resources & Life Sci, Div Livestock Sci, Dept Sustainable Agr Syst BOKU, A-1180 Vienna, Austria Univ Guelph, Ctr Genet Improvement Livestock, Guelph, ON N1G 2W1, Canada AgResearch, Ctr Reprod & Genom, Invermay, Mosgiel, New Zealand ARS, USDA, Bovine Funct Genom Lab, Beltsville, MD 20705 USA ARS, Anim Improvement Programs Lab, USDA, Beltsville, MD 20705 USA Embrapa DairyCattle, Bioinformat & Anim Genom Lab, Juiz De Fora, MG, Brazil Univ Estadual Paulista, UNESP, Fac Med Vet Aracatuba, BR-16050680 Sao Paulo, Brazil Univ Estadual Paulista, UNESP, Fac Ciencias Agr & Vet, BR-14884900 Sao Paulo, Brazil Univ Estadual Paulista, UNESP, Fac Med Vet Aracatuba, BR-16050680 Sao Paulo, Brazil CNPq: 560922/2010-8 CNPq: 483590/2010-0 FAPESP: 10/06185-4 FAPESP: 11/16643-2 FAPESP: 10/52030-2 (BFGL) from the USDA Agricultural Research Service1265-31000-104D

Made available in DSpace on 2014-12-03T13:10:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-02-18Bitstream added on 2014-12-03T13:23:06Z : No. of bitstreams: 1 WOS000331706700046.pdf: 768241 bytes, checksum: 11420f7b9cd27bddac99662dee91b196 (MD5) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The reproductive performance of bulls has a high impact on the beef cattle industry. Scrotal circumference (SC) is the most recorded reproductive trait in beef herds, and is used as a major selection criterion to improve precocity and fertility. The characterization of genomic regions affecting SC can contribute to the identification of diagnostic markers for reproductive performance and uncover molecular mechanisms underlying complex aspects of bovine reproductive biology. In this paper, we report a genome-wide scan for chromosome segments explaining differences in SC, using data of 861 Nellore bulls (Bos indicus) genotyped for over 777,000 single nucleotide polymorphisms. Loci that excel from the genome background were identified on chromosomes 4, 6, 7, 10, 14, 18 and 21. The majority of these regions were previously found to be associated with reproductive and body size traits in cattle. The signal on chromosome 14 replicates the pleiotropic quantitative trait locus encompassing PLAG1 that affects male fertility in cattle and stature in several species. Based on intensive literature mining, SP4, MAGEL2, SH3RF2, PDE5A and SNAI2 are proposed as novel candidate genes for SC, as they affect growth and testicular size in other animal models. These findings contribute to linking reproductive phenotypes to gene functions, and may offer new insights on the molecular biology of male fertility. UNESP Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Med Vet Prevent & Reprod Anim, Sao Paulo, Brazil UNESP Univ Estadual Paulista, Dept Zootecnia, Sao Paulo, Brazil GenSys Consultores Associados, Porto Alegre, RS, Brazil UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, Dept Apoio Saude & Prod Anim, Sao Paulo, Brazil BOKU Univ Nat Resources & Life Sci, Div Livestock Sci, Dept Sustainable Agr Syst, Vienna, Austria CSIRO Commonwealth Sci & Ind Res Org, Food Futures Flagship, Brisbane, Qld, Australia Univ Guelph, Ctr Genet Improvement Livestock, Guelph, ON N1G 2W1, Canada AgResearch, Ctr Reprod & Genom, Mosgiel, Otago, New Zealand ARS, Anim Improvement Programs Lab, USDA, Beltsville, MD USA Embrapa Dairy Cattle, Bioinformat & Anim Genom Lab, Juiz De Fora, MG, Brazil ARS, Bovine Funct Genom Lab, USDA, Beltsville, MD USA UNESP Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Med Vet Prevent & Reprod Anim, Sao Paulo, Brazil UNESP Univ Estadual Paulista, Dept Zootecnia, Sao Paulo, Brazil UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, Dept Apoio Saude & Prod Anim, Sao Paulo, Brazil CNPq: 560922/2010-8 CNPq: 483590/2010-0 FAPESP: 11/16643-2 FAPESP: 10/52030-2

Made available in DSpace on 2015-03-18T15:55:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-10-10Bitstream added on 2015-03-18T16:28:32Z : No. of bitstreams: 1 WOS000344227600001.pdf: 1247925 bytes, checksum: 8f49a22061ba77c31fd10734d7cfc07d (MD5) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 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 Flmpute and BEAGLE were applied to impute genotypes. From 995 bulls and 1247 cows that were genotyped with the Illumina (R) 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. Flmpute 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 (R) 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 Flmpute. Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Nat Resources & Life Sci, Dept Sustainable Agr Syst BOKU, Div Livestock Sci, A-1180 Vienna, Austria GenSys Consultores Associados S C Ltda, BR-90680000 Porto Alegre, RS, Brazil Univ Guelph, Ctr Genet Improvement Livestock, Guelph, ON N1G 2W1, Canada Semex Alliance, Guelph, ON, Canada AgResearch, Ctr Reprod & Gen, Invermay, Mosgiel, New Zealand USDA ARS, Bovine Funct Genom Lab, Beltsville, MD 20705 USA Univ Estadual Paulista, Fac Med Vet Aracatuba, BR-16050680 Aracatuba, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Fac Med Vet Aracatuba, BR-16050680 Aracatuba, SP, Brazil CNPq: 560922/2010-8

The genome-wide association study (GWAS) results are presented for average daily gain (ADG) in Nellore cattle. Phenotype of 720 male Bos indicus animals with information of ADG in feedlots and 354,147 single-nucleotide polymorphisms (SNPs) obtained from a database added by information from Illumina Bovine HD (777,962 SNPs) and Illumina BovineSNP50 (54,609) by imputation were used. After quality control and imputation, 290,620 SNPs remained in the association analysis, using R package Genome-wide Rapid Association using Mixed Model and Regression method GRAMMAR-Gamma. A genomic region with six significant SNPs, at Bonferroni-corrected significance, was found on chromosome 3. The most significant SNP (rs42518459, BTA3: 85849977, p = 9.49 × 10(-8)) explained 5.62% of the phenotypic variance and had the allele substitution effect of -0.269 kg/day. Important genes such as PDE4B, LEPR, CYP2J2 and FGGY are located near this region, which is overlapped by 12 quantitative trait locus (QTLs) described for several production traits. Other regions with markers with suggestive effects were identified in BTA6 and BTA10. This study showed regions with major effects on ADG in Bos indicus in feedlots. This information may be useful to increase the efficiency of selecting this trait and to understand the physiological processes involved in its regulation.

Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-27T11:29:40Z No. of bitstreams: 0Bitstream added on 2014-05-27T14:43:13Z : No. of bitstreams: 1 2-s2.0-84878817065.pdf: 1569340 bytes, checksum: ee96ac3b330c175abd31d11721cf429e (MD5) Made available in DSpace on 2014-05-27T11:29:40Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-06-13 Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd. Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (UNESP), Jaboticabal, São Paulo 14884-900 GenSys Consultores Associados, Porto Alegre 90680-000 Department of Sustainable Agricultural Systems Division of Livestock Sciences BOKU - University of Natural Resources and Life Sciences, Vienna Centre for Reproduction and Genomics AgResearch, Invermay, Mosgiel ARS-USDA - Agricultural Research Service United States Department of Agriculture Animal Improvement Programs Laboratory, Beltsville, MD 20705 United States Department of Agriculture Agricultural Research Service Bovine Functional Genomics Laboratory, Beltsville, MD 20705 Centre for Genetic Improvement of Livestock University of Guelph, Guelph, ON N1G2W1 Bioinformatics and Animal Genomics Laboratory Embrapa Dairy Cattle, Juiz de Fora, Minas Gerais School of Veterinary Sciences University of Queensland, Gatton, Qld 4343 School of Rural and Environmental Science University of New England, Armidale, NSW 2351 Faculdade de Medicina Veterinária de Araçatuba UNESP - Univ. Estadual Paulista, Araçatuba, São Paulo 16050-680 Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (UNESP), Jaboticabal, São Paulo 14884-900 Faculdade de Medicina Veterinária de Araçatuba UNESP - Univ. Estadual Paulista, Araçatuba, São Paulo 16050-680

This review paper presents the three main approaches currently used in livestock genomic sciences where the bioinfomatics plays a critical role. They are named as Genomic Selection (GS), Genome Wide Association Study (GWAS) and Signatures of Selection (SS). The subsides for the construction of this article were generated in a current project (started in 2011), so called Zebu Genome Consortium (ZGC), which joins researchers from different institutions and countries, aiming to scientifically explore genomic information of Bos taurus indicus cattle breeds and deliver useful information to breeders and academic community, specially from the tropical regions of the world.

Made available in DSpace on 2013-09-27T14:53:34Z (GMT). No. of bitstreams: 1 WOS000297894700020.pdf: 197844 bytes, checksum: 348ff723dea12e7096083d8941c38080 (MD5) Previous issue date: 2011-12-01 Made available in DSpace on 2013-09-30T18:03:36Z (GMT). No. of bitstreams: 1 WOS000297894700020.pdf: 197844 bytes, checksum: 348ff723dea12e7096083d8941c38080 (MD5) Previous issue date: 2011-12-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:19:11Z No. of bitstreams: 1 WOS000297894700020.pdf: 197844 bytes, checksum: 348ff723dea12e7096083d8941c38080 (MD5) Made available in DSpace on 2014-05-20T13:19:11Z (GMT). No. of bitstreams: 1 WOS000297894700020.pdf: 197844 bytes, checksum: 348ff723dea12e7096083d8941c38080 (MD5) Previous issue date: 2011-12-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) This study was carried out to provide an exploratory analysis of genetic variability of residual variance of fifteen traits in Nellore beef cattle. The possibility of considering, simultaneously, additive and environmental effects on residual variance was investigated by analyzing log squared residuals associated with each observation according to an animal model. There is evidence of genetic variability for residual variance of most investigated traits, such as birth weight, weight gain from birth to weaning, weight gain from weaning to yearling, scrotal circumference and visual scores (specially in the case of scores for conformation, muscling and sheath). Results suggest that uniformity of some beef cattle traits could be improved by selecting for lower residual variance, when considering large amount of information to predict genetic merit for this criterion. Further studies are needed to confirm the results obtained under the exploratory approach of this work. (C) 2011 Elsevier B.V. All rights reserved. UNESP, FCAV, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil GenSys Consultores Associados SS Ltda, Porto Alegre, RS, Brazil UNESP, FCAV, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil

Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2013-08-22T19:07:28Z No. of bitstreams: 1 S1516-35982009000700006.pdf: 45874 bytes, checksum: cbd2cb45485c8d5558474636c57f6c9f (MD5) Made available in DSpace on 2013-08-22T19:07:28Z (GMT). No. of bitstreams: 1 S1516-35982009000700006.pdf: 45874 bytes, checksum: cbd2cb45485c8d5558474636c57f6c9f (MD5) Previous issue date: 2009-07-01 Made available in DSpace on 2013-09-30T18:02:36Z (GMT). No. of bitstreams: 2 S1516-35982009000700006.pdf: 45874 bytes, checksum: cbd2cb45485c8d5558474636c57f6c9f (MD5) S1516-35982009000700006.pdf.txt: 18010 bytes, checksum: 1adc1970d269c21c458ad9463d07b0a0 (MD5) Previous issue date: 2009-07-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:53Z No. of bitstreams: 2 S1516-35982009000700006.pdf: 45874 bytes, checksum: cbd2cb45485c8d5558474636c57f6c9f (MD5) S1516-35982009000700006.pdf.txt: 18010 bytes, checksum: 1adc1970d269c21c458ad9463d07b0a0 (MD5) Made available in DSpace on 2014-05-20T13:18:53Z (GMT). No. of bitstreams: 2 S1516-35982009000700006.pdf: 45874 bytes, checksum: cbd2cb45485c8d5558474636c57f6c9f (MD5) S1516-35982009000700006.pdf.txt: 18010 bytes, checksum: 1adc1970d269c21c458ad9463d07b0a0 (MD5) Previous issue date: 2009-07-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Por meio da utilização de um programa de acasalamento dirigido e de simulação de dados, foram avaliadas e comparadas estratégias alternativas de acasalamento para aumentar a probabilidade de produzir animais superiores e reduzir a variabilidade da progênie em bovinos. Simularam-se 50 populações, cada uma com 4.800 vacas, 160 touros e 4.800 produtos. Para cada vaca e touro simulados, gerou-se uma variável aleatória, seguindo distribuição normal, reproduzindo um índice composto por diferenças esperadas na progênie (DEP) de diferentes características a ser adotado como critério de seleção. As estratégias de acasalamento simuladas foram: AA - ao acaso; AP - associativo positivo; AN - associativo negativo; C20 - associativo positivo para as vacas 20% superiores e associativo negativo para as 80% restantes; C50 - associativo positivo para as vacas 50% superiores e associativo negativo para as 50% restantes. Os acasalamentos foram definidos com a utilização de um programa de acasalamentos dirigidos, calculando-se os índices esperados dos produtos e comparando as estratégias com base nestes índices. As estratégias de acasalamento alternativas, C20 e C50, apresentam probabilidades de produção de animais superiores tão altas quanto a do acasalamento associativo positivo e reduzem a probabilidade de produzir animais inferiores. O acasalamento associativo negativo é muito eficiente em produzir progênie uniforme. A simulation study was carried out to apply and compare an alternative mating strategy for increasing the probability of producing outstanding animals and reducing progeny variability, with other conventional strategies. Fifty populations were simulated, each containing 4,800 dams, 160 sires and 4,800 calves. For each dam and sire, a random variable from a normal distribution was generated, mimicking an index composed by several expected progeny differences (EPD). The mating strategies considered were: (1) random mating (RM); (2) positive assortative mating (PA); (3) negative assortative mating (NA); (4) combined, PA (assortative mating) for 20% top dams, and NA (negative assortative mating) for the remaining 80% (C20); (5) combined, PA (positive assortative mating) for 50% top dams, and NA (negative assortative mating) for the remaining 50% (C50). After applying the mating program, the expected progeny indexes were computed and the strategies were compared based on these indexes. The alternative mating strategies, C20 and C50, show probability of producing outstanding animals as great as the positive assortative mating, and reduce the probability of producing extremely inferior animals. The negative assortative mating is very efficient in producing uniform progeny. Unesp FCAV Gensys Consultores Associados S/C Ltda FAPESP UNESP FCAV Departamento de Zootecnia CNPq Unesp FCAV UNESP FCAV Departamento de Zootecnia

Made available in DSpace on 2013-08-28T14:10:15Z (GMT). No. of bitstreams: 1 WOS000314596300001.pdf: 1409766 bytes, checksum: 7b1a71f729d6bbc1e71717a941ae2b60 (MD5) Made available in DSpace on 2013-09-30T18:01:54Z (GMT). No. of bitstreams: 2 WOS000314596300001.pdf: 1409766 bytes, checksum: 7b1a71f729d6bbc1e71717a941ae2b60 (MD5) WOS000314596300001.pdf.txt: 70074 bytes, checksum: 7d30a6aea94cb746bc0494fa02bab61f (MD5) Previous issue date: 2012-11-08 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:40Z No. of bitstreams: 2 WOS000314596300001.pdf: 1409766 bytes, checksum: 7b1a71f729d6bbc1e71717a941ae2b60 (MD5) WOS000314596300001.pdf.txt: 70074 bytes, checksum: 7d30a6aea94cb746bc0494fa02bab61f (MD5) Made available in DSpace on 2014-05-20T13:18:40Z (GMT). No. of bitstreams: 2 WOS000314596300001.pdf: 1409766 bytes, checksum: 7b1a71f729d6bbc1e71717a941ae2b60 (MD5) WOS000314596300001.pdf.txt: 70074 bytes, checksum: 7d30a6aea94cb746bc0494fa02bab61f (MD5) Previous issue date: 2012-11-08 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Background: The availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population.Results: For the five traits analyzed (W6W: weight at six weeks, WGS: growth slope, BL: body length, %CD8+: percentage of CD8+ cells, CD4+/ CD8+: ratio between CD4+ and CD8+ cells), within-family predictions were more accurate than across-family predictions, although this superiority in accuracy varied markedly across traits. For within-family prediction, two kernel methods, Reproducing Kernel Hilbert Spaces Regression (RKHS) and Support Vector Regression (SVR), were the most accurate for W6W, while a polygenic model also had comparable performance. A form of ridge regression assuming that all markers contribute to the additive variance (RR_GBLUP) figured among the most accurate for WGS and BL, while two variable selection methods (LASSO and Random Forest, RF) had the greatest predictive abilities for % CD8+ and CD4+/ CD8+. RF, RKHS, SVR and RR_GBLUP outperformed the remainder methods in terms of bias and inflation of predictions.Conclusions: Methods with large conceptual differences reached very similar predictive abilities and a clear re-ranking of methods was observed in function of the trait analyzed. Variable selection methods were more accurate than the remainder in the case of % CD8+ and CD4+/ CD8+ and these traits are likely to be influenced by a smaller number of QTL than the remainder. Judged by their overall performance across traits and computational requirements, RR_GBLUP, RKHS and SVR are particularly appealing for application in genomic selection. UNESP, FCAV, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil GenSys Consultores Assoc SS Ltda, Porto Alegre, RS, Brazil UNESP, FCAV, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil

Made available in DSpace on 2014-12-03T13:08:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-02-11Bitstream added on 2014-12-03T13:23:24Z : No. of bitstreams: 1 WOS000334615600001.pdf: 735818 bytes, checksum: c3feed4b42d2f3260f9e792cf22e3fe6 (MD5) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Background: Feed intake plays an important economic role in beef cattle, and is related with feed efficiency, weight gain and carcass traits. However, the phenotypes collected for dry matter intake and feed efficiency are scarce when compared with other measures such as weight gain and carcass traits. The use of genomic information can improve the power of inference of studies on these measures, identifying genomic regions that affect these phenotypes. This work performed the genome-wide association study (GWAS) for dry matter intake (DMI) and residual feed intake (RFI) of 720 Nellore cattle (Bos taurus indicus).Results: In general, no genomic region extremely associated with both phenotypic traits was observed, as expected for the variables that have their regulation controlled by many genes. Three SNPs surpassed the threshold for the Bonferroni multiple test for DMI and two SNPs for RFI. These markers are located on chromosomes 4, 8, 14 and 21 in regions near genes regulating appetite and ion transport and close to important QTL as previously reported to RFI and DMI, thus corroborating the literature that points these two processes as important in the physiological regulation of intake and feed efficiency.Conclusions: This study showed the first GWAS of DMI to identify genomic regions associated with feed intake and efficiency in Nellore cattle. Some genes and QTLs previously described for DMI and RFI, in other subspecies (Bos taurus taurus), that influences these phenotypes are confirmed in this study. Fac Zootecnia & Engn Alimentos USP, BR-13635900 Sao Paulo, Brazil UNESP Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Sao Paulo, Brazil Empresa Brasileira Pesquisa Agropecuaria, CNPGC EMBRAPA, BR-79002970 Campo Grande, Matogrosso Do S, Brazil UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, BR-16050680 Sao Paulo, Brazil Univ Sao Paulo, Escola Super Agr Luiz de Queiroz, BR-13418900 Sao Paulo, Brazil UNESP Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Sao Paulo, Brazil UNESP Univ Estadual Paulista, Fac Med Vet Aracatuba, BR-16050680 Sao Paulo, Brazil FAPESP: 11/16643-2 FAPESP: 12/02039-9 FAPESP: 12/03551-5