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Made available in DSpace on 2020-12-12T02:06:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 The aim of this study was to identify differentially expressed genes (DEG) in the Longissimus thoracis muscle of Nelore cattle related to fatty acid (FA) profile through RNA sequencing and principal component analysis (PCA). Two groups of 10 animals each were selected containing PC1 and PC2 extreme DEG values (HIGH × LOW) for each FA group. The intramuscular fat (IMF) was compared between cluster groups by ANOVA, and only the sum of monounsaturated FA (MUFA) and ω3 showed significant differences (p

Made available in DSpace on 2020-12-12T01:51:04Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-09-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The aim of this study was to evaluate the genomic predictions using the single-step genomic best linear unbiased predictor (ssGBLUP) method based on SNPs and haplotype markers associated with beef fatty acids (FAs) profile in Nelore cattle. The data set contained records from 963 Nelore bulls finished in feedlot (±90 days) and slaughtered with approximately 24 months of age. Meat samples from the Longissimus dorsi muscle were taken for FAs profile measurement. FAs were quantified by gas chromatography using a SP-2560 capillary column. Animals were genotyped with the high-density SNP panel (BovineHD BeadChip assay) containing 777,962 markers. SNPs with a minor allele frequency and a call rate lower than 0.05 and 0.90, respectively, monomorphic, located on sex chromosomes, and with unknown position were removed from the data set. After genomic quality control, a total of 469,981 SNPs and 892 samples were available for subsequent analyses. Missing genotypes were imputed and phased using the FImpute software. Haplotype blocks were defined based on linkage disequilibrium using the Haploview software. The model to estimate variance components and genetic parameters and to predict the genomic values included the random genetic additive effects, fixed effects of the contemporary group and the age at slaughter as a linear covariate. Accuracies using the haplotype-based approach ranged from 0.07 to 0.31, and those SNP-based ranged from 0.06 to 0.33. Regression coefficients ranged from 0.07 to 0.74 and from 0.08 to 1.45 using the haplotype- and SNP-based approaches, respectively. Despite the low to moderate accuracies for the genomic values, it is possible to obtain genetic progress trough selection using genomic information based either on SNPs or haplotype markers. The SNP-based approach allows less biased genomic evaluations, and it is more feasible when taking into account the computational and operational cost underlying the haplotypes inference. Faculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia Universidade Estadual Paulista Júlio de Mesquita Filho UNESP Faculdade de Zootecnia e Engenharia de Alimentos Departamento de Nutrição e Produção Animal Universidade de São Paulo Zoetis Department of Animal Sciences Purdue University Faculdade de Zootecnia e Engenharia de Alimentos Departamento de Medicina Veterinária Universidade de São Paulo Faculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia Universidade Estadual Paulista Júlio de Mesquita Filho UNESP FAPESP: 2009/16118-5 FAPESP: 2015/25304-8 FAPESP: 2016/24085-3

Background Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus mykiss) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population. Methods Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method. Results Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations. Conclusions Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations. Electronic supplementary material The online version of this article (10.1186/s12711-019-0484-4) contains supplementary material, which is available to authorized users.

Made available in DSpace on 2022-04-29T08:31:48Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-09-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The multiple sire system (MSS) is a common mating scheme in extensive beef production systems. However, MSS does not allow paternity identification and lead to inaccurate genetic predictions. The objective of this study was to investigate the implementation of single-step genomic BLUP (ssGBLUP) in different scenarios of uncertain paternity in the evaluation for 450-day adjusted liveweight (W450) and age at first calving (AFC) in a Nellore cattle population. To estimate the variance components using BLUP and ssGBLUP, the relationship matrix (A) with different proportions of animals with missing sires (MS) (scenarios 0, 25, 50, 75, and 100% of MS) was created. The genotyped animals with MS were randomly chosen, and ten replicates were performed for each scenario and trait. Five groups of animals were evaluated in each scenario: PHE, all animals with phenotypic records in the population; SIR, proven sires; GEN, genotyped animals; YNG, young animals without phenotypes and progeny; and YNGEN, young genotyped animals. The additive genetic variance decreased for both traits as the proportion of MS increased in the population when using the regular REML. When using the ssGBLUP, accuracies ranged from 0.13 to 0.47 for W450 and from 0.10 to 0.25 for AFC. For both traits, the prediction ability of the direct genomic value (DGV) decreased as the percentage of MS increased. These results emphasize that indirect prediction via DGV of young animals is more accurate when the SNP effects are derived from ssGBLUP with a reference population with known sires. The ssGBLUP could be applied in situations of uncertain paternity, especially when selecting young animals. This methodology is shown to be accurate, mainly in scenarios with a high percentage of MS. Grupo de Melhoramento Animal Faculdade de Ciências Agrárias E Veterinárias Universidade Estadual Paulista Júlio de Mesquita Filho Zoetis Faculdade de Medicina Veterinária E Zootecnia Universidade de São Paulo Associação Nacional de Criadores E Pesquisadores (ANCP) Instituto Nacional de Pesquisa Agropecuária (INIA) University of Georgia Grupo de Melhoramento Animal Faculdade de Ciências Agrárias E Veterinárias Universidade Estadual Paulista Júlio de Mesquita Filho FAPESP: 2013/25910-0

Made available in DSpace on 2019-10-06T16:51:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The objective of this study was to present heritability estimates and accuracy of genomic prediction using different methods for meat quality traits in Nelore cattle. Approximately 5000 animals with phenotypes and genotypes of 412,000 SNPs, were divided into two groups: (1) training population: animals born from 2008 to 2013 and (2) validation population: animals born in 2014. A single-trait animal model was used to estimate heritability and to adjust the phenotype. The methods of GBLUP, Improved Bayesian Lasso and Bayes Cπ were performed to estimate the SNP effects. Accuracy of genomic prediction was calculated using Pearson's correlations between direct genomic values and adjusted phenotypes, divided by the square root of heritability of each trait (0.03–0.19). The accuracies varied from 0.23 to 0.73, with the lowest accuracies estimated for traits associated with fat content and the greatest accuracies observed for traits of meat color and tenderness. There were small differences in genomic prediction accuracy between methods. São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences Centre for Genetic Improvement of Livestock University of Guelph BRF Company Federal University of Pelotas (UFPel) São Paulo State University (Unesp) College of Veterinary and Animal Science São Paulo State University (Unesp) School of Agricultural and Veterinarian Sciences São Paulo State University (Unesp) College of Veterinary and Animal Science

The aim of this study was to estimate genetic parameters and identify genomic regions associated with carcass traits obtained by ultrasound and visual scores in Nellore cattle. Data from ~66,000 animals from the National Association of Breeders and Researchers (ANCP) were used. The variance components for backfat thickness, rump fat thickness and Longissimus muscle area (LMA) were estimated considering a linear model whereas a threshold model for body structure (BS), finishing precocity (FP) and musculature (MS) traits. The SNP solutions were estimated using the ssGBLUP approach by considering windows of 10 consecutive SNPs. Regions that accounted for more than 1.0% of the additive genetic variance were used. Genes identified within the significant windows, such as FOXA3, AP2S1, FKRP, NPASI and ATP6V1G1, were found to be related with MS, while OMA1 and FFGY with BS and FP traits. The PLTP, TNNC2 and GPAT2 genes were found in the regions associated with LMA, as well as TKT, FNDC5 and CHRND can strongly be related with fat deposition. Gene enrichment analysis revealed processes that might be directly influenced the organism growth and development. These results should help to better understand the genetic and physiological mechanisms regulating growth and body composition, muscle tissue development and subcutaneous fat expression, and this information might be useful for future genomic studies in Nellore cattle.

Previously accurate genomic predictions for Bacterial cold water disease (BCWD) resistance in rainbow trout were obtained using a medium-density single nucleotide polymorphism (SNP) array. Here, the impact of lower-density SNP panels on the accuracy of genomic predictions was investigated in a commercial rainbow trout breeding population. Using progeny performance data, the accuracy of genomic breeding values (GEBV) using 35K, 10K, 3K, 1K, 500, 300 and 200 SNP panels as well as a panel with 70 quantitative trait loci (QTL)-flanking SNP was compared. The GEBVs were estimated using the Bayesian method BayesB, single-step GBLUP (ssGBLUP) and weighted ssGBLUP (wssGBLUP). The accuracy of GEBVs remained high despite the sharp reductions in SNP density, and even with 500 SNP accuracy was higher than the pedigree-based prediction (0.50-0.56 versus 0.36). Furthermore, the prediction accuracy with the 70 QTL-flanking SNP (0.65-0.72) was similar to the panel with 35K SNP (0.65-0.71). Genomewide linkage disequilibrium (LD) analysis revealed strong LD (r2 ≥ 0.25) spanning on average over 1 Mb across the rainbow trout genome. This long-range LD likely contributed to the accurate genomic predictions with the low-density SNP panels. Population structure analysis supported the hypothesis that long-range LD in this population may be caused by admixture. Results suggest that lower-cost, low-density SNP panels can be used for implementing genomic selection for BCWD resistance in rainbow trout breeding programs.

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. Previously, we reported high genomic prediction accuracy of 0.72 for BCWD resistance in rainbow trout using the 57 K Axiom SNP array. Due to the high cost of phenotyping and genotyping in rainbow trout breeding programs, it is paramount to know if acceptable genomic prediction accuracy can be obtained in the subsequent generation without retraining the prediction model. In the current study, we found that the accuracy of genomic prediction without model retraining in the subsequent generation was reduced from 0.65 and 0.61 to 0.56 and 0.53 using a lower density array of 10 K SNPs and a panel of 49 QTL-linked SNPs, respectively. Although markedly lower than the genomic prediction with model retraining, the prediction accuracy without retraining was better than the pedigree-based model (PBLUP) with retraining (0.48) and substantially higher than the PBLUP model accuracy without retraining (0.22). We conclude that genomic selection provides better prediction accuracy than the traditional PBLUP model even when ‘skipping’ one generation of model retraining. The weighted single-step GBLUP (wssGBLUP) and single-step Bayesian multiple regression BayesB (ssBMR-BayesB) had higher genomic prediction accuracy than single-step GBLUP (ssGBLUP), which is consistent with the oligogenic inheritance of BCWD resistance in this population. Imputation from the 10 K array genotypes back to the 57 K array genotypes did not improve the accuracy of genomic prediction, likely due to the high linkage disequilibrium in rainbow trout aquaculture breeding populations and the oligogenic architecture of BCWD resistance.

Made available in DSpace on 2018-12-11T17:10:03Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-04-15 The focus of this work is inspecting the synthesis and comparison of the activities of a catalyst supported on two silicate materials in the epoxidation of 1-octene. The two new catalyst materials were characterized by infrared spectroscopy, elemental analysis, solid-state 29Si and 13C nuclear magnetic resonance, scanning electronic microscope (SEM) and analysis of nitrogen. Lastly, the two new catalysts, Silsesq-TCA-[(W(CO)3I2)3] and Silica-TCA-[W(CO)3I2] were tested as catalysts in reactions of epoxidation of 1-octene and compared with their analogue not supported [W(CO)3I2(thiocarbamide)]. After an extensive literature search, we verified that our work is the first that has reported the immobilization process of [W(CO)3I2(NCCH3)2] on silsesquioxane and silica gel functionalized with propyl-thiocarbamide groups and their applications as catalysts of reactions of catalytic epoxidation of 1-octene. Departamento de Física e Química Unesp-Univ Estadual Paulista, Av. Brasil, 56-Centro, Caixa Postal 31 Universidade do Extremo Sul Catarinense, Av. Universitaria, 1105, CP 3167 Departamento de Fitotecnia Tecnologia de Alimentos e Sócio Economia Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista Departamento de Física e Química Unesp-Univ Estadual Paulista, Av. Brasil, 56-Centro, Caixa Postal 31 Departamento de Fitotecnia Tecnologia de Alimentos e Sócio Economia Faculdade de Engenharia de Ilha Solteira Universidade Estadual Paulista

Made available in DSpace on 2020-12-12T01:00:19Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-01-01 This study aimed to identify genomic regions influencing growth traits in Nellore cattle and evaluate the predictive ability of each trait based on results obtained from single-step genome-wide association analyzes (ssGWAS) considering different single nucleotide polymorphims (SNP) densities of markers. The National Association of Breeders and Researchers provided the dataset, from eighteen Nellore herds participating of the Nellore Brazilian breeding program. The traits birth weight (BW), adjusted weight at 210 (W210) and at 450 (W450) days of age and adult cow weight (ACW) were considered. A total of 963 animals, genotyped using the Illumina BovineHD BeadChip, were used as a reference population to impute genotypes of 7,689 animals, genotyped in low-density panel. Genotype imputation was performed using the FImpute 2.2 software. The ssGWAS was used to identify genomic regions associated to growth traits. Several genes in enrichment analysis were related to muscle and adipose tissue development and metabolism, feed efficiency, milk composition and maternal behavior. The predictive ability varied from low (0.10) to moderate (0.68). The predictive ability and bias for both panels were similar for all traits. The results found in this study should improve the understanding of genetic and physiologic mechanism associated with growth traits. However, the association of these results with other approaches, like system biologic and other omics information should improve the identification of causative genetic variants in growth traits in indicine cattle. Departament of Veterinary Medicine College of Animal Science and Food Engineer University of São Paulo (USP), 225 Duque de Caxias Norte Avenue Departament of Animal Science College of Agricultural and Veterinarian Sciences São Paulo State University (UNESP), Access Road Professor Paulo Donato Castellane s/n Zoetis, 1240 Dr. Chucri Zaidan Street, Edifício Morumbi Corporate, Diamond Tower, 4th floor National Institute of Agricultural Research (INIA) Nacional Association of Breeders and Researchers (ANCP), 463 João Godoy Street Departament of Animal Science College of Agricultural and Veterinarian Sciences São Paulo State University (UNESP), Access Road Professor Paulo Donato Castellane s/n

Made available in DSpace on 2020-12-12T01:42:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Selection for bulls that would reach puberty early reduces the generation interval and increases fertility and herd productivity. Despite its economic importance, there are few QTL associated with age at puberty described in the literature. In this study, a weighted single-step genome-wide association study was performed to detect genomic regions and putative candidate genes related to age at puberty in young Nelore bulls. Several protein-coding genes related to spermatogenesis functions were identified within the genomic regions that explain more than 0.5% of the additive genetic variance for age at puberty in Nelore bulls, such as ADAM11, BRCA1, CSNK2A, CREBBP, MEIOC, NDRG2, NECTIN3, PARP2, PARP9, PRSS21, RAD51C, RNASE4, SLX4, SPA17, TEX14, TIMP2 and TRIP13 gene. Enrichment analysis by DAVID also revealed several GO terms related to spermatogenesis such as DNA replication (GO:0006260), male meiosis I (GO:0007141), double-strand break repair (GO:0006302), base excision repair (GO:0006284), apoptotic process (GO:0006915), cell–cell adhesion (GO: 0098609) and focal adhesion (GO:0005925). The heritability for age at puberty shows that this trait can be improved based on traditional EBV selection. Adding genomic information to the system helps to elucidate genes and molecular mechanisms controlling the sexual precocity and could help to predict sexual precocity in Nelore bulls with greater accuracy at younger age, which would speed up the breeding programme for this breed. Centro de Pesquisa em Bovinos de Corte Instituto de Zootecnia (IZ) Laboratório de Reprodução Animal Faculdade de Medicina Veterinária e Zootecnia (FAMEZ) Universidade Federal de Mato Grosso do Sul (UFMS) Zoetis Edifício Morumbi Corporate - Diamond Tower PROCRIAR Assistência Veterinária Associação Nacional dos Criadores e Pesquisadores (ANCP) Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias (FCAV) Universidade Estadual Paulista Julio de Mesquita Filho (UNESP) Departamento de Zootecnia Faculdade de Ciências Agrárias e Veterinárias (FCAV) Universidade Estadual Paulista Julio de Mesquita Filho (UNESP) FAPESP: #2019/10438-0

Animal feeding is the most important economic component of beef production systems. Selection for feed efficiency has not been effective mainly due to difficult and high costs to obtain the phenotypes. The application of genomic selection using SNP can decrease the cost of animal evaluation as well as the generation interval. The objective of this study was to compare methods for genomic evaluation of feed efficiency traits using different cross-validation layouts in an experimental beef cattle population genotyped for a high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA). After quality control, a total of 437,197 SNP genotypes were available for 761 Nelore animals from the Institute of Animal Science, Sertaozinho, Sao Paulo, Brazil. The studied traits were residual feed intake, feed conversion ratio, ADG, and DMI. Methods of analysis were traditional BLUP, single-step genomic BLUP (ssGBLUP), genomic BLUP (GBLUP), and a Bayesian regression method (BayesCπ). Direct genomic values (DGV) from the last 2 methods were compared directly or in an index that combines DGV with parent average. Three cross-validation approaches were used to validate the models: 1) YOUNG, in which the partition into training and testing sets was based on year of birth and testing animals were born after 2010; 2) UNREL, in which the data set was split into 3 less related subsets and the validation was done in each subset a time; and 3) RANDOM, in which the data set was randomly divided into 4 subsets (considering the contemporary groups) and the validation was done in each subset at a time. On average, the RANDOM design provided the most accurate predictions. Average accuracies ranged from 0.10 to 0.58 using BLUP, from 0.09 to 0.48 using GBLUP, from 0.06 to 0.49 using BayesCπ, and from 0.22 to 0.49 using ssGBLUP. The most accurate and consistent predictions were obtained using ssGBLUP for all analyzed traits. The ssGBLUP seems to be more suitable to obtain genomic predictions for feed efficiency traits on an experimental population of genotyped animals.

Made available in DSpace on 2019-10-06T16:51:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-11-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The aim of the present study was to compare the predictive ability of SNP-BLUP model using different pseudo-phenotypes such as phenotype adjusted for fixed effects, estimated breeding value, and genomic estimated breeding value, using simulated and real data for beef FA profile of Nelore cattle finished in feedlot. A pedigree with phenotypes and genotypes of 10,000 animals were simulated, considering 50% of multiple sires in the pedigree. Regarding to phenotypes, two traits were simulated, one with high heritability (0.58), another with low heritability (0.13). Ten replicates were performed for each trait and results were averaged among replicates. A historical population was created from generation zero to 2020, with a constant size of 2000 animals (from generation zero to 1000) to produce different levels of linkage disequilibrium (LD). Therefore, there was a gradual reduction in the number of animals (from 2000 to 600), producing a “bottleneck effect” and consequently, genetic drift and LD starting in the generation 1001 to 2020. A total of 335,000 markers (with MAF greater or equal to 0.02) and 1000 QTL were randomly selected from the last generation of the historical population to generate genotypic data for the test population. The phenotypes were computed as the sum of the QTL effects and an error term sampled from a normal distribution with zero mean and variance equal to 0.88. For simulated data, 4000 animals of the generations 7, 8, and 9 (with genotype and phenotype) were used as training population, and 1000 animals of the last generation (10) were used as validation population. A total of 937 Nelore bulls with phenotype for fatty acid profiles (Sum of saturated, monounsaturated, omega 3, omega 6, ratio of polyunsaturated and saturated and polyunsaturated fatty acid profile) were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. To compare the accuracy and bias of direct genomic value (DGV) for different pseudo-phenotypes, the correlation between true breeding value (TBV) or DGV with pseudo-phenotypes and linear regression coefficient of the pseudo-phenotypes on TBV for simulated data or DGV for real data, respectively. For simulated data, the correlations between DGV and TBV for high heritability traits were higher than obtained with low heritability traits. For simulated and real data, the prediction ability was higher for GEBV than for Yc and EBV. For simulated data, the regression coefficient estimates (b (Yc,DGV) ), were on average lower than 1 for high and low heritability traits, being inflated. The results were more biased for Yc and EBV than for GEBV. For real data, the GEBV displayed less biased results compared to Yc and EBV for SFA, MUFA, n-3, n-6, and PUFA/SFA. Despite the less biased results for PUFA using the EBV as pseudo-phenotype, the b (Yi,DGV estimates obtained for the different pseudo-phenotypes (Yc, EBV and GEBV) were very close. Genomic information can assist in improving beef fatty acid profile in Zebu cattle, since the use of genomic information yielded genomic values for fatty acid profile with accuracies ranging from low to moderate. Considering both simulated and real data, the ssGBLUP model is an appropriate alternative to obtain more reliable and less biased GEBVs as pseudo-phenotype in situations of missing pedigree, due to high proportion of multiple sires, being more adequate than EBV and Yc to predict direct genomic value for beef fatty acid profile. Faculdade de Ciências Agrárias e Veterinárias UNESP Faculdade de Medicina Veterinária e Zootecnia USP Faculdade de Zootecnia e Engenharia de Alimentos USP Instituto Nacional de Investigación Agropecuaria Faculdade de Ciências Agrárias e Veterinárias UNESP FAPESP: 2009/16118-5 FAPESP: 2011/2141-0

Family-based selective breeding can be an effective strategy for controlling diseases in aquaculture. This study aimed to estimate (co)variance components for resistance to bacterial cold water disease (BCWD) and columnaris disease (CD) in two unrelated rainbow trout nucleus breeding populations: the USDA, ARS, National Center for Cool and Cold Water Aquaculture odd-year line (ARS-Fp-R), which has been subjected to five generations of selection for improved resistance to BCWD, and the Troutlodge, Inc., May-spawning odd-year line (TLUM), which has been selected for improved growth performance but not for disease resistance. A total of 46,805 and 27,821 pedigree records were available from both populations, respectively. Between 44 and 138 families per generation and population were evaluated under controlled BCWD and CD challenges, providing 32,311 and 17,861 phenotypic records for BCWD resistance, and 13,603 and 9,413 for CD resistance, in the ARS-Fp-R and TLUM populations, respectively. A two-trait animal threshold model assuming an underlying normal distribution for the binary survival phenotypes was used to estimate (co)variance components separately for each population. Resistance to BCWD (h(2) = 0.27 ± 0.04 and 0.43 ± 0.08) and CD (h(2) = 0.23 ± 0.07 and 0.34 ± 0.09) was moderately heritable in the ARS-Fp-R and TLUM populations, respectively. The genetic correlation between the resistance to BCWD and CD was favorably positive in the ARS-Fp-R (0.40 ± 0.17) and TLUM (0.39 ± 0.18) populations. These findings suggest that both disease resistance traits can be improved simultaneously even if genetic selection pressure is applied to only one of the two traits.

This investigation presents the syntheses of new metallodendritic catalysts from a silsesquioxane core (Silsesq-PrNH3+Cl−) via a new route. For optimization of the syntheses of the catalysts, reaction times, thermodynamic effects, and the amounts of [Mo(η3-C3H5)Br(CO)2(NCCH3)2] (1) and [Mo(CO)3Br2(NCCH3)2] (2) complexes fixed on the second-generation dendrimer (PDG2.0) were studied. After the optimization studies and with the objective of application in catalysis, the catalysts were prepared by reaction of PDG2.0 with the organometallic complexes and characterized by elemental analysis (CNH), FTIR, 13C and 29Si NMR, XRD, TGA, SEM, EDS and BET. The metallodendritic catalysts were tested in the epoxidation of olefins and shown to be a vigorous catalyst with conversion rates between 76 and 97% for PDG2.0–[(Mo(η3-C3H5)(CO)2Br)8] and 30–80% for PDG2.0–[(Mo(CO)3Br2)5], and a high selectivity in the formation of epoxides using tertbutyl hydroperoxide (TBHP) as an oxidant. The catalysts remain highly active after being used for at least 5 cycles. To the best of our knowledge, this study is the first to have reported the preparation of these new dendritic catalysts, as well as the catalytic comparison with their previous generations in the epoxidation of 1-octene, cyclooctene, (S)-limonene, cis-3-hexen-1-ol, trans-3-hexen-1-ol and styrene.

The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty. Made available in DSpace on 2017-12-21T23:28:05Z (GMT). No. of bitstreams: 1 ApplicationofsinglestepgenomicBLUPunderdifferentuncertainpaternityscenariosusingsimulateddata..pdf: 782402 bytes, checksum: ec6960b2579b83b77b9aca6119ae98c8 (MD5) Previous issue date: 2017-12-21

Made available in DSpace on 2018-12-11T17:16:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The aim of the present study was to analyze the distribution of CNV regions (CNVRs) as well as to address hypothesis about the natural/artificial selection process in Nellore cattle. A total of 399,361 CNVs were identified, using the PennCNV algorithm, in 3794 Nellore cattle (Bos taurus indicus) genotyped with the Bovine HD BeadChip array. The default quality control was applied and 2902 samples and 195,873 CNVs remained. The medium CNV length size was 54,744 bp with a maximum of 870,000 bp and a minimum of 3000 bp. The CNVRs were generated by overlapping the 195,873 identified CNVs using the CNVRuler program. There was a higher incidence of CNVRs on BTA19 (24.26%), BTA23 (18.68%), and BTA25 (18.05%). The chromosomes that showed a lower incidence of CNVR were BTA29 (1.63%), BTA13 (9.72%), and BTA8 (9.72%). According to the type, 38.5%, 28.5% and 33.0% of the CNVRs were characterized as insertion, deletion and mixed (insertion and deletion in the same region), respectively. The 9805 CNVR estimated in the present study covered approximately 13.05% of the cattle genome (UMD_3.1, 2,649,685,063 bp) and overlapped with 5495 genes. These genes have functions described as involved in biological processes that might be related to the environmental adaptation of the subspecies to tropical areas, such as regulation of vasodilatation, immune system response, hair follicle morphogenesis, among others. This study confirms the existence of large structural variations in the Nellore cattle genome and contributes to understanding the differences between cattle subspecies. Besides, it can also work as a guideline for future studies in which structural variations are present. Department of Animal Science State University of São Paulo FCAV – UNESP, Via de acesso Prof. Paulo Donato Castellane Universidade Federal da Bahia (UFBA) Departamento de Zootecnia Department of Animal Science University of São Paulo University of São Paulo Faculdade de Medicina Veterinária e Zootecnia Department of Nutrition and Animal Production Department of Animal Science State University of São Paulo FCAV – UNESP, Via de acesso Prof. Paulo Donato Castellane FAPESP: #2009/16118-5 FAPESP: #2011/21241-0

The objective of this work was to evaluate the genetic diversity of Brahman cattle in Brazil with pedigree analysis. Genealogical records of a subpopulation were used considering all pedigree information (Pt) and the pedigree information divided into two periods (P1, from 1994 to 2004; and P2, from 2005 to 2012) or according to the raising system (Ppt, animals on pasture; or Pst, on stable). Estimates were obtained for average inbreeding coefficients, generation intervals (GI), number of equivalent known generation (CGE), number of founders (Nf), effective number of founders (fe), effective number of ancestors (fa), and founder genome equivalents (fg). The average inbreeding coefficients were 11.97, 7.79, 11.95, 11.74, and 11.31% for Pt, P1, P2, Ppt, and Pst, respectively. Average GI was 4.4 years, whereas CGE was 3.18. The fe values were similar to those of fa, which were greater than those of fg. The fe/fa and fg/fe ratios were close to 1, which indicates no genetic bottleneck and small losses by genetic drift. The genetic diversity in the Brazilian population of Brahman breed is not significantly reduced. Resumo: O objetivo deste trabalho foi avaliar a diversidade genética de bovinos da raça Brahman no Brasil com análise de pedigree. Registros genealógicos de uma subpopulação foram usados, tendo-se considerado toda a informação de pedigree (Pt) e a informação de pedigree dividida em dois períodos (P1, de 1994 a 2004; e P2, de 2005 a 2012) ou de acordo com sistema de criação (Ppt, animais a pasto; ou Pst, estabulados). Foram obtidas as estimativas de coeficientes médios de endogamia, intervalos de geração (IG), número equivalente de gerações conhecidas (EGC), número de fundadores (Nf), número efetivo de fundadores (fe), número efetivo de ancestrais (fa) e número efetivo de genomas remanescentes (fg). Os coeficientes médios de endogamia foram de 11,97, 7,79, 11,95, 11,74 e 11,31% para Pt, P1, P2, Ppt e Pst, respectivamente. O IG médio foi de 4,4 anos, enquanto o EGC médio foi de 3,18. O fe foi próximo de fa, cujos valores foram maiores que os de fg. As razões fe/fa e fg/fe foram próximas de 1, o que indica ausência de gargalo genético e pequenas perdas por deriva genética. A diversidade genética na raça Brahman no Brasil não está significativamente reduzida.

Made available in DSpace on 2018-11-26T17:44:35Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The aim of the present study was to estimate covariance components and genetic parameters for beef fatty acid (FA) composition of intramuscular fat in the longissimus thoracis muscle in Nelore bulls finished in feedlot. Twenty-two FAs were selected. The heritability estimates for individual FAs ranged from 0.01 to 0.35. The heritability estimates for myristic (0.25 +/- 0.09), palmitic (0.18 +/- 0.07), oleic (0.28 +/- 0.09), linoleic (0.16 +/- 0.06) and alpha-linolenic (0.35 +/- 0.10) FAs were moderate. Stearic, elaidic, palmitoleic, vaccenic, conjugated linoleic acid, docosahexanoic, eicosatrienoic and arachidonic FAs had heritability estimates below 0.15. The genetic-correlation estimates between the individual saturated FAs (SFAs) were low and negative between myristic and stearic FAs (-0.22 +/- 0.84), moderate between palmitic and myristic FAs (0.58 +/- 0.56) and negative between palmitic and stearic FAs (-0.69 +/- 0.45). The genetic correlations between the individual long-chain polyunsaturated FAs (PUFAs) were positive and moderate (>0.30). However, the genetic-correlation estimates between long-chain PUFAs and alpha-linolenic acid were low (

Made available in DSpace on 2018-11-28T03:37:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-02-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The objective of this study was to estimate the genetic-quantitative relationships between the beef fatty acid profile with the carcass and meat traits of Nellore cattle. A total of 1826 bulls finished in feedlot conditions and slaughtered at 24 months of age on average were used. The following carcass and meat traits were analysed: subcutaneous fat thickness (BF), shear force (SF) and total intramuscular fat (IMF). The fatty acid (FA) profile of the Longissimus thoracis samples was determined. Twenty-five FAs (18 individuals and seven groups of FAs) were selected due to their importance for human health. The animals were genotyped with the BovineHD BeadChip and, after quality control for single nucleotide polymorphisms (SNPs), only 470,007 SNPs from 1556 samples remained. The model included the random genetic additive direct effect, the fixed effect of the contemporary group and the animal's slaughter age as a covariable. The (co)variances and genetic parameters were estimated using the REML method, considering an animal model (single-step GBLUP). A total of 25 multi-trait analyses, with four traits, were performed considering SF, BF and IMF plus each individual FA. The heritability estimates for individual saturated fatty acids (SFA) varied from 0.06 to 0.65, for monounsaturated fatty acids (MUFA) it varied from 0.02 to 0.14 and for polyunsaturated fatty acids (PUFA) it ranged from 0.05 to 0.68. The heritability estimates for Omega 3, Omega 6, SFA, MUFA and PUFA sum were low to moderate, varying from 0.09 to 0.20. The carcass and meat traits, SF (0.06) and IMF (0.07), had low heritability estimates, while BF (0.17) was moderate. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with BF were 0.04, 0.64 and -0.41, respectively. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with SF were 0.29, -0.06 and -0.04, respectively. The genetic correlation estimates between SFA sum, MUFA sum and PUFA sum with IMF were 0.24, 0.90 and -0.67, respectively. The selection to improve meat tenderness in Nellore cattle should not change the fatty acid composition in beef, so it is possible to improve this attribute without affecting the nutritional beef quality in zebu breeds. However, selection for increased deposition of subcutaneous fat thickness and especially the percentage of intramuscular fat should lead to changes in the fat composition, highlighting a genetic antagonism between meat nutritional value and acceptability by the consumer. Sao Paulo State Univ, Fac Agr & Vet Sci, Dept Anim Sci, Jaboticabal, SP, Brazil Univ Sao Paulo, Sch Vet Med & Anim Sci, Dept Anim Sci, Pirassununga, SP, Brazil Univ Sao Paulo, Fac Anim Sci & Food Engn, Dept Anim Sci, Pirassununga, SP, Brazil Univ Sao Paulo, Fac Anim Sci & Food Engn, Dept Food Engn, Pirassununga, SP, Brazil CNPq, Natl Counsel Technol & Sci Dev, Brasilia, DF, Brazil INIA, Natl Agr Res Inst, Las Brujas 90200, Uruguay Sao Paulo State Univ, Fac Agr & Vet Sci, Dept Anim Sci, Jaboticabal, SP, Brazil FAPESP: 2009/16118-5 FAPESP: 2011/21241-0 FAPESP: 2012/23979-0

Made available in DSpace on 2018-12-11T17:31:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-06-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The objective of this study was to compare SNP-BLUP, BayesCπ, BayesC and Bayesian Lasso methodologies to predict the direct genomic value for saturated, monounsaturated, and polyunsaturated fatty acid profile, omega 3 and 6 in the Longissimus thoracis muscle of Nellore cattle finished in feedlot. A total of 963 Nellore bulls with phenotype for fatty acid profiles, were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. The predictive ability was evaluated using cross validation. To compare the methodologies, the correlation between DGV and pseudo-phenotypes was calculated. The accuracy varied from − 0.40 to 0.62. Our results indicate that none of the methods excelled in terms of accuracy, however, the SNP-BLUP method allows obtaining less biased genomic evaluations, thereby; this method is more feasible when taking into account the analyses' operating cost. Despite the lowest bias observed for EBV, the adjusted phenotype is the preferred pseudophenotype considering the genomic prediction accuracies regarding the context of the present study. Faculdade de Ciências Agrárias e Veterinárias UNESP Jaboticabal Faculdade de Medicina Veterinária e Zootecnia USP Pirassununga Faculdade de Zootecnia e Engenharia de Alimentos USP Pirassununga Faculdade de Ciências Agrárias e Veterinárias UNESP Jaboticabal FAPESP: #2009/16118-5 FAPESP: (#2011/2141-0

Made available in DSpace on 2018-12-11T17:09:27Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-01-01 The purpose of this study was to identify genomic regions associated with carcass traits in an experimental Nelore cattle population. The studied data set contained 2,306 ultrasound records for longissimus muscle area (LMA), 1,832 for backfat thickness (BF), and 1,830 for rump fat thickness (RF). A high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA) was used for genotyping. After genomic data quality control, 437,197 SNPs from 761 animals were available, of which 721 had phenotypes for LMA, 669 for BF, and 718 for RF. The SNP solutions were estimated using a single-step genomic BLUP approach (ssGWAS), which calculated the variance for windows of 50 consecutive SNPs and the regions that accounted for more than 0.5% of the additive genetic variance were used to search for candidate genes. The results indicated that 12, 18, and 15 different windows were associated to LMA, BF, and RF, respectively. Confirming the polygenic nature of the studied traits, 43, 65, and 53 genes were found in those associated windows, respectively for LMA, BF, and RF. Among the candidate genes, some of them, which already had their functions associated with the expression of energy metabolism, were found associated with fat deposition in this study. In addition, ALKBH3 and HSD17B12 genes, which are related in fibroblast death and metabolism of steroids, were found associated with LMA. The results presented here should help to better understand the genetic and physiologic mechanism regulating the muscle tissue deposition and subcutaneous fat cover expression of Zebu animals. The identification of candidate genes should contribute for Zebu breeding programs in order to consider carcass traits as selection criteria in their genetic evaluation. School of Agricultural and Veterinarian Sciences FCAV/ UNESP-Sao Paulo State University Department of Animal Science University of Georgia Department of Animal and Dairy Science APTA Center of Beef Cattle Animal Science Institute Department of Animal Science Federal University of Pelotas School of Agricultural and Veterinarian Sciences FCAV/ UNESP-Sao Paulo State University Department of Animal Science

Made available in DSpace on 2018-11-26T17:12:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-11-25 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Background: Fatty acid type in beef can be detrimental to human health and has received considerable attention in recent years. The aim of this study was to identify differentially expressed genes in longissimus thoracis muscle of 48 Nellore young bulls with extreme phenotypes for fatty acid composition of intramuscular fat by RNA-seq technique. Results: Differential expression analyses between animals with extreme phenotype for fatty acid composition showed a total of 13 differentially expressed genes for myristic (C14:0), 35 for palmitic (C16:0), 187 for stearic (C18:0), 371 for oleic (C18:1, cis-9), 24 for conjugated linoleic (C18:2 cis-9, trans11, CLA), 89 for linoleic (C18:2 cis-9,12 n6), and 110 genes for a-linolenic (C18:3 n3) fatty acids. For the respective sums of the individual fatty acids, 51 differentially expressed genes for saturated fatty acids (SFA), 336 for monounsaturated (MUFA), 131 for polyunsaturated (PUFA), 92 for PUFA/SFA ratio, 55 for omega 3, 627 for omega 6, and 22 for omega 6/omega 3 ratio were identified. Functional annotation analyses identified several genes associated with fatty acid metabolism, such as those involved in intra and extra-cellular transport of fatty acid synthesis precursors in intramuscular fat of longissimus thoracis muscle. Some of them must be highlighted, such as: ACSM3 and ACSS1 genes, which work as a precursor in fatty acid synthesis; DGAT2 gene that acts in the deposition of saturated fat in the adipose tissue; GPP and LPL genes that support the synthesis of insulin, stimulating both the glucose synthesis and the amino acids entry into the cells; and the BDH1 gene, which is responsible for the synthesis and degradation of ketone bodies used in the synthesis of ATP. Conclusion: Several genes related to lipid metabolism and fatty acid composition were identified. These findings must contribute to the elucidation of the genetic basis to improve Nellore meat quality traits, with emphasis on human health. Additionally, it can also contribute to improve the knowledge of fatty acid biosynthesis and the selection of animals with better nutritional quality. Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil Conselho Nacl Desenvolvimento Cient & Tecnol, BR-71605001 Lago Sul, DF, Brazil Univ Sao Paulo, Fac Med Vet & Zootecnia, Dept Nutr & Prod Anim, BR-13635900 Pirassununga, SP, Brazil Univ Sao Paulo, Dept Zootecnia, BR-13418900 Piracicaba, SP, Brazil Univ Sao Paulo, Fac Zootecnia & Engn Alimentos, Dept Zootecnia, BR-13635900 Pirassununga, SP, Brazil Clemson Univ, Anim & Vet Sci Dept, Clemson, SC 29634 USA Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, BR-14884900 Jaboticabal, SP, Brazil FAPESP: 2011/2141-0 FAPESP: 2009/16118-5 FAPESP: 2012/15098-3

Made available in DSpace on 2018-11-26T17:07:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-10-19 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The objective of this study was to identify genomic regions and metabolic pathways associated with dry matter intake, average daily gain, feed efficiency and residual feed intake in an experimental Nellore cattle population. The high-density SNP chip (Illumina High-Density Bovine BeadChip, 777k) was used to genotype the animals. The SNP markers effects and their variances were estimated using the single-step genome wide association method. The (co)variance components were estimated by Bayesian inference. The chromosome segments that are responsible for more than 1.0% of additive genetic variance were selected to explore and determine possible quantitative trait loci. The bovine genome Map Viewer was used to identify genes. In total, 51 genomic regions were identified for all analyzed traits. The heritability estimated for feed efficiency was low magnitude (0.13 +/- 0.06). For average daily gain, dry matter intake and residual feed intake, heritability was moderate to high (0.43 +/- 0.05; 0.47 +/- 0.05, 0.18 +/- 0.05, respectively). A total of 8, 17, 14 and 12 windows that are responsible for more than 1% of the additive genetic variance for dry matter intake, average daily gain, feed efficiency and residual feed intake, respectively, were identified. Candidate genes GOLIM4, RFX6, CACNG7, CACNG6, CAPN8, CAPN2, AKT2, GPRC6A, and GPR45 were associated with feed efficiency traits. It was expected that the response to selection would be higher for residual feed intake than for feed efficiency. Genomic regions harboring possible QTL for feed efficiency indicator traits were identified. Candidate genes identified are involved in energy use, metabolism protein, ion transport, transmembrane transport, the olfactory system, the immune system, secretion and cellular activity. The identification of these regions and their respective candidate genes should contribute to the formation of a genetic basis in Nellore cattle for feed efficiency indicator traits, and these results would support the selection for these traits. Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Via Acesso Prof Paulo Donato Castellane S-No, BR-14884900 Jaboticabal, SP, Brazil Ctr Avancado Pesquisa Tecnol Agronegocio Bovinos, Inst Zootecnia, Rodovia Carlos Tonanni,Km 94, BR-14174000 Sertaozinho, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Via Acesso Prof Paulo Donato Castellane S-No, BR-14884900 Jaboticabal, SP, Brazil FAPESP: 2009/16118-5

The objective of this research was to use non-linear models to describe the growth pattern in Santa Ines sheep and to study the influence of environmental effects on curve parameters with the best-fit model. The models included the Brody, Richards, Von Bertalanffy, Gompertz, and Logistic models. We used 773 field reports on 162 animals ranging in age from 120 to 774 days, including 46 males and 116 females. The statistics used to evaluate the quality of fit included RMS (residual mean square), C % (percentage of convergence), R 2 (adjusted determination coefficient) and MAD (mean absolute deviation). Of the fixed effects studied, the only significant relationship was the effect of sex on parameter A . The Richards model was problematic during the process of convergence. Considering all studied criteria, the Logistic model presented the best fit in describing the growth pattern in Santa Ines sheep.

Sao Paulo State Univ UNESP, Sch Agr & Veterinarian Sci FCAV, Dept Anim Sci, Jaboticabal, Brazil

The objective of the present study was to estimate genetic parameters for stayability at 60 months of age (STAY60) and its association with first lactation cumulative milk yield (P305), age at first calving (AFC), and first calving interval (FCI), in order to adopt these traits as selection criteria for longevity in Gir dairy cattle. Records for 2770 cows born between 1982 and 2008 from six herds in the Brazilian states of Minas Gerais, Sao Paulo, and Paraiba were analyzed. The (co)variance components were estimated by a Bayesian approach using bivariate animal models. The heritability estimates were 0.37 ± 0.09, 0.23 ± 0.04, 0.26 ± 0.06, and 0.07 ± 0.03 for STAY60, P305, AFC, and FCI, respectively. The genetic correlations of STAY60 with P305, AFC, and FCI were moderate to high, with values of 0.61 (0.17), -0.44 (0.23), and 0.88 (0.13), respectively. STAY60, P305, and AFC exhibited additive genetic variability, and these traits should be considered in selection indices. The indirect selection for longevity through the correlated responses of early-expression traits, such as milk production at first lactation, could be used to improve the ability of animals to remain in the herd.

Made available in DSpace on 2018-11-26T16:54:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-08-05 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen (R) and Paint (R) animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations. Univ Estadual Paulista, Dept Zootecnia, Fac Ciencias Agr & Vet, Jaboticabal, SP, Brazil Univ Fed Mato Grosso, Inst Ciencias Agr & Tecnol, Grp Melhoramento Anim Mato Grosso, Rondonopolis, MG, Brazil Univ Fed Bahia, Dept Med Vet Prevent & Prod Anim, Escola Med Vet & Zootecnia, Salvador, BA, Brazil Univ Estadual Paulista, Dept Zootecnia, Fac Ciencias Agr & Vet, Jaboticabal, SP, Brazil FAPESP: 2013/00848-0 FAPESP: 2009/16118-5 CNPq: 559631/2009-0

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

Sao Paulo State Univ UNESP, Sch Agr & Veterinarian Sci FCAV, Dept Anim Sci, Jaboticabal, Brazil

Departamento de Fisica e Quimica UNESP Universidade Estadual Paulista, Av. Brasil, 56-Centro, Caixa Postal 31, 15385-000 Ilha Solteira

Made available in DSpace on 2018-11-26T16:27:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-03-09 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Postgraduate Program on Genetics and Animal Breeding, Faculdade de Ciencias Agrarias e Veterinarias, Universidade Estadual Paulista (FCAV, UNESP) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Background: Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono-and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method. Results: The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9, C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio. Conclusions: The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health. Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Via Acesso Prof Paulo Donato Castellane S-No, BR-14884900 Sao Paulo, Brazil Univ Sao Paulo, Fac Med Vet & Zootecnia, Dept Nutr & Prod Anim, Ave Duque de Caxias Norte 225, BR-13635900 Sao Paulo, Brazil Clemson Univ, Dept Anim & Vet Sci, Clemson, SC USA Natl Inst Agr Res Uruguayy, Dept Anim Breeding Montevideo, Montevideo, Uruguay Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Via Acesso Prof Paulo Donato Castellane S-No, BR-14884900 Sao Paulo, Brazil FAPESP: 2011/21241-0 FAPESP: 2009/16118-5

The growing global demand for safe and sustainable food production has motived a restructuring in the beef production sector aiming the production of better quality products without increasing the productive cost. Thus, animal breeding aims to improve economic productivity of future generations of domestic species through selection. Most of the economic important traits in livestock has a complex and quantitative expression, that is, they are influenced by a large number of genes and affected by environmental factors. However, there is no consensus among researches about the best methodology to obtain genomic prediction for each trait. There are different methods and pseudophenotypes used in genomic predictions, being necessary to determine the ideal for each trait of interest. In Chapter 2, the aim of this study was to estimate genetic parameters and identify genomic regions associated with carcass traits obtained by ultrasound and visual scores in Nellore cattle. Data from ~66,000 animals from the National Association of Breeders and Researchers (ANCP) were used. The variance components for back fat thickness (BF), rump fat thickness (RF) and Longissimus muscle area (LMA) were estimated considering a linear model whereas a threshold model were fitted for body structure (BS), finishing precocity (FP) and musculature (MS) traits were used. The SNP solutions were estimated using the ssGBLUP approach by considering windows of 10 consecutive SNPs. Regions that explained for more than 1.0% of the additive genetic variance were used. Gene enrichment analysis revealed GO biological processes that might be directly influenced the organism growth and development. In Chapter 3, the aim of this study was to compare the genomic prediction ability for carcass composition indicator traits in Nellore cattle using the Best Linear Unbiased Prediction (BLUP), Genomic BLUP (GBLUP), singlestep GBLUP (ssGBLUP), Bayesian methods (BayesA, BayesB, BayesC and BayesianLASSO) and an approach combining the pedigree matrix of genotyped animals and the genomic matrix using a Bayesian analysis. Phenotypic and genotypic information on about 66, and 21,000 animals, respectively, evaluated by ANCP were available for BF, RF, LMA, BS, FP and MS. To obtain the prediction ability, the dataset was split into training (genotyped sires and dams with progenies) and validation (genotyped young animals without progeny records and without phenotypes) subsets. In terms of prediction ability and bias, Bayesian approaches were superior for visual scores traits and the ssGBLUP for carcass traits obtained by ultrasonography, however, more biased results were obtained for BF and RF using the ssGBLUP. The ssGBLUP model showed less biased prediction for low heritability traits, such as LMA, and also it has lower computational demand and it is a straightforward method for implementing genomic selection in beef cattle. In Chapter 4, the aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). The direct and maternal heritability estimates for CE were low (0.18) and moderate (0.39) respectively, indicating that genetic progress for this trait is feasible, and so, it would respond favorably to direct selection. Gene enrichment analysis revealed processes that might directly influence fetal processes involved in female pregnancy and stress response. A crescente busca por produção alimentar sustentável tem incentivado uma reestruturação no setor de produção de carne visando obter produtos de melhor qualidade sem aumentar os custos de produção. Deste modo, o melhoramento genético animal tende a melhorar a produtividade econômica das futuras gerações de espécies de interesse econômico por meio da seleção. A maioria das características de interesse econômico na pecuária é de expressão quantitativa e complexa, ou seja, são influenciadas por vários genes e afetadas por fatores ambientais. No entanto, ainda não há consenso entre os pesquisadores sobre a melhor metodologia para a obtenção da predição genômica para cada característica. Existem diferentes métodos e pseudofenótipos utilizados em predições genômicas, sendo necessário determinar o ideal para a característica de interesse. No Capítulo 2, o objetivo deste estudo foi estimar parâmetros genéticos e identificar regiões genômicas associadas a características de carcaça obtidas por ultrassonografia e escores visuais em bovinos Nelore. Foram utilizados dados de aproximadamente 66.000 animais provenientes da Associação Nacional de Criadores e Pesquisadores (ANCP). Os componentes de variância para espessura de gordura subcutânea (EG), espessura de gordura subcutânea da garupa (EGP8) e área de olho de lombo (AOL) foram estimados considerando um modelo linear, e um modelo de limiar para as características, como estrutura corporal (E), precocidade (P) e musculosidade (M). As soluções dos SNPs foram estimadas por meio da metodologia ssGBLUP considerando janelas de 10 SNPs adjacentes. Regiões que representaram mais de 1.0% da variância genética aditiva foram utilizadas. A análise de enriquecimento funcional revelou processos biológicos que podem influenciar diretamente o crescimento e desenvolvimento animal. No Capítulo 3, objetivou-se com este estudo comparar a habilidade de predição genômica de características indicadoras de composição de carcaça em bovinos Nelore usando os métodos BLUP, GBLUP, ssGBLUP, métodos Bayesianos (BayesA, BayesB, BayesC e BayesianLASSO) e uma metodologia combinando a matriz de parentesco dos animais genotipados com a matriz genômica e métodos Bayesianos. Foram obtidas informações fenotípicas e genotípicas de aproximadamente 66.000 e 21.000 animais, respectivamente, avaliados pela ANCP para BF, RF, LMA, BS, FP e MS. Para obter a habilidade de predição, o conjunto de dados foi dividido em subconjuntos de treinamento (touros genotipados e mães com progênies) e validação (animais jovens genotipados sem registros de progênies e sem fenótipos). Em relação a habilidade de predição e o viés, os métodos bayesianos foram superiores para as características de escores visuais e o ssGBLUP para as características de carcaça obtidas por ultrassonografia, entretanto, resultados mais tendenciosos foram obtidos para BF e RF quando utilizado o ssGBLUP. O modelo ssGBLUP apresentou predição menos viesada para as características de baixa herdabilidade, como LMA, e também apresentou menor demanda computacional, caracterizado por ser um método que não necesita de cálculo de pseudofenótipos para a implementação da seleção genômica em bovinos de corte. No Capítulo 4, o objetivo deste estudo foi estimar parâmetros genéticos e identificar regiões genômicas associadas à facilidade de parto (CE) em novilhas Nelore precoces. Um total de 1.277 fenótipos para CE foram coletados e classificados em duas categorias: i- parto não assistido, categorizado como sucesso (1) e ii- parto assistido, no qual as novilhas necessitaram de qualquer forma de assistência ou intervenção para parir, categorizado como falha (2). As estimativas de herdabilidade direta e materna para CE foram baixas (0,18) e moderadas (0,39), respectivamente, indicando que o progresso genético para essa característica é viável e, portanto, responderia favoravelmente à seleção direta. A análise de enriquecimento funcional revelou processos que podem influenciar diretamente os processos fetais envolvidos na gestação e na resposta ao estresse.

This study aimed to identify genomic regions influencing growth traits in Nellore cattle and evaluate the predictive ability of each trait based on results obtained from single-step Genome-Wide Association Studies (ssGWAS) considering different SNP markesr densities. The National Association of Breeders and Researchers provided the dataset from eighteen Nellore herds participating of the Nellore Brazil breeding program. The traits birth weight (BW), adjusted weight at 210 (W210) and at 450 (W450) days of age and adult cow weight (ACW) were considered. A total of 963 animals, genotyped using the Illumina BovineHD BeadChip, were used as a reference population to impute genotypes of 7,689 animals, genotyped in low-density panel. Genotype imputation was performed using the FImpute 2.2 software. Several genes in enrichment analysis were related to muscle and adipose tissue development and metabolism, feed efficiency, milk composition and maternal behavior. The predictive ability varied from low (0.10) to moderate (0.68). The predictive ability and bias for both panels were similar for all traits. The results found in this study should improve the understanding of genetic and physiologic mechanism associated with growth traits. However, the association of these results with other approaches, like system biologic and other omics information should improve the identification of causative genetic variants in growth traits in indicine cattle. Este estudo teve como objetivo identificar regiões genômicas que influenciam características de crescimento em bovinos da raça Nelore e avaliar a capacidade preditiva de cada característica com base nos resultados obtidos a partir da metodologia single-step Genome-Wide Association Studies (ssGWAS) considerando diferentes densidades de marcadores do tipo SNP. A Associação Nacional de Criadores e Pesquisadores disponibilizou o conjunto de dados de dezoito rebanhos bovinos participantes do programa de melhoramento brasileiro da raça Nelore (Nelore Brasil). Foram consideradas as características peso ao nascer (PN), peso ajustado aos 210 (W210) e aos 450 (W450) dias de idade e peso adulto da vaca (PCA). Um total de 963 animais, genotipados utilizando o Illumina BovineHD BeadChip, foram utilizados como população de referência para imputar genótipos de 7.689 animais, genotipados em painel de baixa densidade. A imputação dos genótipos foi realizada utilizando o software FImpute 2.2.. Na análise de enriquecimento funcional, vários genes foram relacionados ao desenvolvimento e metabolismo de músculo e tecido adiposo, eficiência alimentar, composição do leite e comportamento materno. A habilidade de predição (HP)variou de baixa (0,10) a moderada (0,68). Os valores de viés e HP para ambos os painéis foram semelhantes para todas as características. Os resultados encontrados neste estudo devem melhorar a compreensão do mecanismo genético e fisiológico associado às características de crescimento. No entanto, associação desses resultados com outras abordagens, como informações biológicas do sistema e outras informações ômicas, devem melhorar a identificação de variantes genéticas causadoras de características de crescimento em bovinos zebuínos.