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Fourier-transform infrared (FTIR) spectroscopy is a powerful high-throughput phenotyping tool for predicting traits that are expensive and difficult to measure in dairy cattle. Calibration equations are often developed using standard methods, such as partial least squares (PLS) regression. Methods that employ penalization, rank-reduction, and variable selection, as well as being able to model the nonlinear relations between phenotype and FTIR, might offer improvements in predictive ability and model robustness. This study aimed to compare the predictive ability of 2 machine learning methods, namely random forest (RF) and gradient boosting machine (GBM), and penalized regression against PLS regression for predicting 3 phenotypes differing in terms of biological meaning and relationships with milk composition (i.e., phenotypes measurable directly and not directly in milk, reflecting different biological processes which can be captured using milk spectra) in Holstein-Friesian cattle under 2 cross-validation scenarios. The data set comprised phenotypic information from 471 Holstein-Friesian cows, and 3 target phenotypes were evaluated: (1) body condition score (BCS), (2) blood β-hydroxybutyrate (BHB, mmol/L), and (3) κ-casein expressed as a percentage of nitrogen (κ-CN, % N). The data set was split considering 2 cross-validation scenarios: samples-out random in which the population was randomly split into 10-folds (8-folds for training and 1-fold for validation and testing); and herd/date-out in which the population was randomly assigned to training (70% herd), validation (10%), and testing (20% herd) based on the herd and date in which the samples were collected. The random grid search was performed using the training subset for the hyperparameter optimization and the validation set was used for the generalization of prediction error. The trained model was then used to assess the final prediction in the testing subset. The grid search for penalized regression evidenced that the elastic net (EN) was the best regularization with increase in predictive ability of 5%. The performance of PLS (standard model) was compared against 2 machine learning techniques and penalized regression using 2 cross-validation scenarios. Machine learning methods showed a greater predictive ability for BCS (0.63 for GBM and 0.61 for RF), BHB (0.80 for GBM and 0.79 for RF), and κ-CN (0.81 for GBM and 0.80 for RF) in samples-out cross-validation. Considering a herd/date-out cross-validation these values were 0.58 (GBM and RF) for BCS, 0.73 (GBM and RF) for BHB, and 0.77 (GBM and RF) for κ-CN. The GBM model tended to outperform other methods in predictive ability around 4%, 1%, and 7% for EN, RF, and PLS, respectively. The prediction accuracies of the GBM and RF models were similar, and differed statistically from the PLS model in samples-out random cross-validation. Although, machine learning techniques outperformed PLS in herd/date-out cross-validation, no significant differences were observed in terms of predictive ability due to the large standard deviation observed for predictions. Overall, GBM achieved the highest accuracy of FTIR-based prediction of the different phenotypic traits across the cross-validation scenarios. These results indicate that GBM is a promising method for obtaining more accurate FTIR-based predictions for different phenotypes in dairy cattle.

BackgroundOver the past decade, Fourier transform infrared (FTIR) spectroscopy has been used to predict novel milk protein phenotypes. Genomic data might help predict these phenotypes when integrated with milk FTIR spectra. The objective of this study was to investigate prediction accuracy for milk protein phenotypes when heterogeneous on-farm, genomic, and pedigree data were integrated with the spectra. To this end, we used the records of 966 Italian Brown Swiss cows with milk FTIR spectra, on-farm information, medium-density genetic markers, and pedigree data. True and total whey protein, and five casein, and two whey protein traits were analyzed. Multiple kernel learning constructed from spectral and genomic (pedigree) relationship matrices and multilayer BayesB assigning separate priors for FTIR and markers were benchmarked against a baseline partial least squares (PLS) regression. Seven combinations of covariates were considered, and their predictive abilities were evaluated by repeated random sub-sampling and herd cross-validations (CV).ResultsAddition of the on-farm effects such as herd, days in milk, and parity to spectral data improved predictions as compared to those obtained using the spectra alone. Integrating genomics and/or the top three markers with a large effect further enhanced the predictions. Pedigree data also improved prediction, but to a lesser extent than genomic data. Multiple kernel learning and multilayer BayesB increased predictive performance, whereas PLS did not. Overall, multilayer BayesB provided better predictions than multiple kernel learning, and lower prediction performance was observed in herd CV compared to repeated random sub-sampling CV.ConclusionsIntegration of genomic information with milk FTIR spectral can enhance milk protein trait predictions by 25% and 7% on average for repeated random sub-sampling and herd CV, respectively. Multiple kernel learning and multilayer BayesB outperformed PLS when used to integrate heterogeneous data for phenotypic predictions.

In general, Fourier-transform infrared (FTIR) predictions are developed using a single-breed population split into a training and a validation set. However, using populations formed of different breeds is an attractive way to design cross-validation scenarios aimed at increasing prediction for difficult-to-measure traits in the dairy industry. This study aimed to evaluate the potential of FTIR prediction using training set combining specialized and dual-purpose dairy breeds to predict different phenotypes divergent in terms of biological meaning, variability, and heritability, such as body condition score (BCS), serum β-hydroxybutyrate (BHB), and kappa casein (k-CN) in the major cattle breed, i.e., Holstein-Friesian. Data were obtained from specialized dairy breeds: Holstein (468 cows) and Brown Swiss (657 cows), and dual-purpose breeds: Simmental (157 cows), Alpine Grey (75 cows), and Rendena (104 cows), giving a total of 1461 cows from 41 multi-breed dairy herds. The FTIR prediction model was developed using a gradient boosting machine (GBM), and predictive ability for the target phenotype in Holstein cows was assessed using different cross-validation (CV) strategies: a within-breed scenario using 10-fold cross-validation, for which the Holstein population was randomly split into 10 folds, one for validation and the remaining nine for training (10-fold_HO), an across-breed scenario (BS_HO) where the Brown Swiss cows were used as the training set and the Holstein cows as the validation set, a specialized multi-breed scenario (BS+HO_10-fold), where the entire Brown Swiss and Holstein populations were combined then split into 10 folds, and a multi-breed scenario (Multi-breed), where the training set comprised specialized (Holstein and Brown Swiss) and dual-purpose (Simmental, Alpine Grey, and Rendena) dairy cows, combined with nine folds of the Holstein cows. Lastly a Multi-breed CV2 scenario was implemented, assuming the same number of records as the reference scenario and using the same proportions as the multi-breed. Within-Holstein, FTIR predictions had a predictive ability of 0.63 for BCS, 0.81 for BHB, and 0.80 for k-CN. Using a specific breed (Brown Swiss) as the training set for prediction in the Holstein population reduced the prediction accuracy by 10% for BCS, 7% for BHB, and 11% for κ-CN. Notably, the combination of Holstein and Brown Swiss cows in the training set increased the predictive ability of the model by 6%, which was 0.66 for BCS, 0.85 for BHB, and 0.87 for k-CN. Using multiple specialized and dual-purpose animals in the training set outperforms the 10-fold_HO (standard) approach, with an increase in predictive ability of 8% for BCS, 7% for BHB, and 10% for k-CN. When the Multi-breed CV2 was implemented, no improvement was observed. Our findings suggest that FTIR prediction of different phenotypes in the Holstein breed can be improved by including different specialized and dual-purpose breeds in the training population. Our study also shows that predictive ability is enhanced when the size of the training population and the phenotypic variability are increased

Made available in DSpace on 2019-10-04T19:13:02Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-04-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The objectives were to obtain estimates of genetic parameters and the genetic trends and to evaluate the direct responses and those correlated to the selection for scrotal circumference (SC) measured at different ages through random regression models (RRM) and multi-trait models (MM). A total of 14,200 information of SC from 4065 Guzerat individuals, with age ranging from 200 to 550 days, were used in the analyses. Both RRM and MM were utilized considering contemporary groups, as the fixed effect, and age of the mother at calving, as the covariate. For RRM, the direct additive genetic and the permanent environment effect of the animals were modeled by Legendre polynomials, with an order of fit ranging from 2 to 5. The residual variances were modeled considering variance homogeneity, and heterogeneity assuming 2, 3, and 4 classes. The results obtained by the RRM fitted better when compared with those obtained by the MM. The model that considered two classes of residual variances and polynomials of third order for the additive genetic and the permanent environment effects was the one that best fitted the scrotal circumference data according to the age based on the Bayesian and the Akaike Information criteria. Scrotal circumference heritability using RRM ranged from 0.42 (200 days of age) to 0.60 (364 days of age) and presented a low reduction from 365 until 550 (0.55) days of age. Correlation estimates for SC at the distinct ages were high (ranging from 0.66 to 0.98) and presented a reduction as the age intervals increased (0.66 +/- 0.05 for SC measured at 205 days of age vs. SC measured at 550 days of age). Genetic trends of scrotal circumference were positive (ranging from 0.048 [SC measured at 205 days of age] to 0.101 [SC measured at 550 days of age]) and significant (P < 0.0001). Using the RRM, an increase in selection response were obtained compared to MM. Based on the results, we conclude that genetic evaluation of scrotal circumference can be performed at 365 days of age utilizing the RRM. State Univ Sao Paulo, Fac Agr & Vet Sci, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil Fed Univ Jequitinhonha & Mucuri Valleys, Dept Anim Sci, BR-39100000 Diamantina, MG, Brazil Univ Fed Minas Gerais, Sch Vet, BR-30123970 Belo Horizonte, MG, Brazil Brazilian Assoc Zebu Breeders, BR-38022330 Uberaba, MG, Brazil Fed Inst Northern Minas Gerais, BR-39900000 Almenara, MG, Brazil State Univ Sao Paulo, Fac Agr & Vet Sci, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil CAPES: 23038.008980/2013-90

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k20), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCTeq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CFmax), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CFmax (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCTeq (0.53 and 0.41), tmax (0.38 and 0.48). Log MAC count was correlated with k20 (+0.34), and log PMN-LYM count was correlated with CFmax (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

Made available in DSpace on 2020-12-12T02:39:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-12-01 Age at first calving (AFC) plays an important role in the economic efficiency of beef cattle production. This trait can be affected by a combination of genetic and environmental factors, leading to physiological changes in response to heifers’ adaptation to a wide range of environments. Genome-wide association studies through the reaction norm model were carried out to identify genomic regions associated with AFC in Nellore heifers, raised under different environmental conditions (EC). The SNP effects for AFC were estimated in three EC levels (Low, Medium, and High, corresponding to average contemporary group effects on yearling body weight equal to 159.40, 228.6 and 297.6 kg, respectively), which unraveled shared and unique genomic regions for AFC in Low, Medium, and High EC levels, that varied according to the genetic correlation between AFC in different EC levels. The significant genomic regions harbored key genes that might play an important biological role in controlling hormone signaling and metabolism. Shared genomic regions among EC levels were identified on BTA 2 and 14, harboring candidate genes associated with energy metabolism (IGFBP2, IGFBP5, SHOX, SMARCAL1, LYN, RPS20, MOS, PLAG1, CHCD7, and SDR16C6). Gene set enrichment analyses identified important biological functions related to growth, hormone levels affecting female fertility, physiological processes involved in female pregnancy, gamete generation, ovulation cycle, and age at puberty. The genomic regions highlighted differences in the physiological processes linked to AFC in different EC levels and metabolic processes that support complex interactions between the gonadotropic axes and sexual precocity in Nellore heifers. São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences Via de Acesso Prof. Paulo Donato Castelane Geneticist Cobb-Vantress, 305 E Main St Department of Animal Sciences University of Wisconsin-Madison 1675 Observatory Dr. National Council for Science and Technological Development São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences Via de Acesso Prof. Paulo Donato Castelane

Two assays were performed to estimate digestible threonine-lysine (Threo-Lys) ratio for female meat-type quails between 21 and 28 days old and between 28 and 35 days old. Experimental design was totally randomized. The first assay comprised 440 quails distributed into 5 treatments, 8 replications and 11 fowls per cage. The second assay comprised 280 quails distributed into 5 treatments, 8 replications and 7 fowls per cage. Five digestible Threo: Lys ratios were evaluated (0.66, 0.71, 0.76, 0.81 and 0.86). Performance, carcass and cut yield, chemical composition of carcass and nitrogen balance were evaluated. There was an improvement (P

Depending on whether milk protein fractions are evaluated qualitatively or quantitatively, different genetic outcomes may emerge. In this study, we compared the genetic parameters for the major milk protein fractions&mdash, caseins (&alpha, S1-, &alpha, S2-, &beta, and к-CN), and whey proteins (&beta, lactoglobulin, &beta, LG, &alpha, lactalbumin, &alpha, LA)&mdash, estimated using the multi-trait genomic best linear unbiased prediction method and expressed variously as milk content (g/100g milk), percentage of milk nitrogen (%N) and daily yield per cow (g/d). The results showed that the genetic parameter estimates varied according to how the milk protein fractions were expressed. Heritability estimates for the caseins and whey protein fractions expressed as daily yields were lower than when they were expressed as proportions and contents, revealing important differences in genetic outcomes. The proportion and the content of &beta, CN were negatively correlated with the proportions and contents of &alpha, S1-CN, &alpha, S2-CN, and к-CN, while the daily yield of &beta, &ndash, CN was negatively correlated with the daily yields of &alpha, S1-CN and &alpha, S2-CN. The Spearman&rsquo, s rank correlations and the coincidence rates between the various predicted genomic breeding values (GEBV) for the milk protein fractions expressed in different ways indicated that these differences had a significant effect on the ranking of the animals. The results suggest that the way milk protein fractions are expressed has implications for breeding programs aimed at improving milk nutritional and technological characteristics.

Made available in DSpace on 2020-12-12T02:33:29Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates. School of Agricultural and Veterinarian Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane National Council for Science and Technological Development School of Agricultural and Veterinarian Sciences São Paulo State University (UNESP), Via de Acesso Prof. Paulo Donato Castelane FAPESP: 2009/16118-5 FAPESP: 2015/25356-8 FAPESP: 2017/02291-3 CNPq: 559631/2009-0

Made available in DSpace on 2020-12-12T00:54:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-11-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The Body structure (BS) is a trait to be considered in the genetic evaluation of beef cattle because it is associated with economically important traits, maintenance requirement, and physiological maturity. Therefore, the objective of this study was to determine the effect of genotype-environment (GxE) interaction considering contemporary group solutions for BW and BS as an environmental gradient (EG) to assess the changes in the body weight (BW). For this BW was measured at 120, 205, 365, 450 and 550 days of age in Guzerat cattle. Phenotypic data from 21,973 Guzerat animals were used to explore the GxE effect among BW, obtained from 150 farms distributed in five Brazilian States provided by the Brazilian Association of Zebu Breeders. A reaction norm model in two-steps was used to estimate the animals’ response to environmental changes. As evidence of GxE, heterogeneity of genetic variance across environments was observed for BW at different ages. Changes in heritability estimates ranged from 0.29 to 0.44 for BW and provided differences in the selection response across different EG levels. The genetic correlations between extreme EG levels indicated a strong effect of GxE interactions. Breeding value for BW at 120 and 205 days of age showed less plasticity than BW at 365, 450, and 550 days of age due to changes in EG. Nevertheless, these results indicate that the BS is an important factor to be considered in genetic evaluations for BW according to the growth phase. Department of Animal Science São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences Department of Animal Science Universidade Federal dos Vales do Jequitinhonha e Mucuri Department of Animal Science University of Wisconsin School of Veterinary Federal University of Minas Gerais Brazilian Association of Zebu Breeders (ABCZ) Department of Animal Science São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences

Multitrait meta-analyses are a strategy to produce more accurate genome-wide association studies, especially for complex phenotypes. We carried out a meta-analysis study for traits related to sexual precocity in tropical beef cattle (Nellore and Brahman) aiming to identify important genomic regions affecting these traits. The traits included in the analyses were age at first calving (AFC), early pregnancy (EP), age at first corpus luteum (AGECL), first postpartum anoestrus interval (PPAI), and scrotal circumference (SC). The traits AFC, EP, and SCN were measured in Nellore cattle, while AGECL, PPAI, and SCB were measured in Brahman cattle. Meta-analysis resulted in 108 significant single-nucleotide polymorphisms (SNPs), at an empirical threshold P-value of 1.39 × 10-5 (false discovery rate [FDR] < 0.05). Within 0.5 Mb of the significant SNP, candidate genes were annotated and analyzed for functional enrichment. Most of the closest genes to the SNP with higher significance in each chromosome have been associated with important roles in reproductive function. They are TSC22D2, KLF7, ARHGAP29, 7SK, MAP3K5, TLE3, WDR5, TAF3, TMEM68, PPP1R15B, NR2F2, GALR1, SUFU, and KCNU1. We did not observe any significant SNP in BTA5, BTA12, BTA17, BTA18, BTA19, BTA20, BTA22, BTA23, BTA25, and BTA28. Although the majority of significant SNPs are in BTA14, it was identified significant associations in multiple chromosomes (19 out of 29 autosomes), which is consistent with the postulation that reproductive traits are complex polygenic phenotypes. Five proposed association regions harbor the majority of the significant SNP (76%) and were distributed over four chromosomes (P < 1.39 × 10-5, FDR < 0.05): BTA2 (5.55%) from 95 to 96 Mb, BTA4 (5.55%) from 94.1 to 94.8 Mb, BTA14 (59.26%) from 24 to 25 Mb and 29 to 30 Mb, and BTA21 (5.55%) from 6.7 Mb to 11.4 Mb. These regions harbored key genes related to reproductive function. Moreover, these genes were enriched for functional groups associated with immune response, maternal-fetal tolerance, pregnancy maintenance, embryo development, fertility, and response to stress. Further studies including other breeds and precocity traits could confirm the importance of these regions and identify new candidate regions for sexual precocity in beef cattle.

The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R2C), and prediction (R2P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R2P = 0.40) and b* color (RMSEP = 1.21, R2P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R2P = 0.16) and a* (RMSEP = 1.42, R2P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

Made available in DSpace on 2018-11-26T15:47:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-04-01 Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs. State Univ Sao Paulo, Fac Agr & Vet Sci, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil Fed Inst Northern Minas Gerais, BR-39900000 Almenara, MG, Brazil Fed Univ Jequitinhonha & Mucuri Valleys, Dept Anim Sci, BR-39100000 Diamantina, MG, Brazil Univ Fed Minas Gerais, Sch Vet, BR-30123970 Belo Horizonte, MG, Brazil State Univ Sao Paulo, Fac Agr & Vet Sci, Dept Anim Sci, BR-14884900 Jaboticabal, SP, Brazil FAPEMIG: BPD 00292-14 - CVZ-PPM 00913-15 CNPq: 474149/2013-7 CAPES: 23038.008980/2013-90

The aim of this study was to identify functional variants within runs of homozygosity (ROH) islands present in the genome of Nellore cattle. Genotypic information of 3,492 animals and 755,319 single nucleotide polymorphism (SNPs), were used. ROH segments were detected using PLINK software. Only ROH segments shared by more than 50% of the population individuals were used for identifying homozygosity islands. The islands functional variants were classified using the VEP tool (predictor of variant effect) from ENSEMBL software. If the variant SIFT score was less than 0.05 it was considered to be “deleterious,” otherwise it was “tolerant.” We found five islands of homozygosity, located in chromosome 5, 7, 12, 21 and 26. Within the islands, a total of 1,181 variants were processed by VEP and all of them were recognized as existing variants. In total, 51 overlapped genes and 69 overlapped transcripts were found. Most of the variants were SNPs located in the intronic regions (55%), followed by intergenic spaces (14%), upstream (13%) and downstream gene variants (12%). The intronic variants can be related to specific QTLs, either because they are associated with regions affecting gene expression or in linkage disequilibrium with the causative mutation or even because they have an unknown function. Only a small portion of the variants is in synonymous regions (4%), splice regions (1%), untranslated regions (UTRs) (1%) or are missense variants (1%). We have found 11 missense variants, being three considered deleterious and eight tolerant. The deleterious variants were annotated: INHBC, SMIM33 e FBXW4 genes. The knowledge of functional variants distribution is important for improving annotation of the bovine genome. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and by São Paulo Research Foundation FAPESP (grants 2018/04313-7 and 2017/10630–2).

RESUMOObjetivou-se com o presente trabalho ajustar modelos não lineares para descrever o padrão de crescimento de genótipos de codornas de corte e de postura do nascimento aos 35 dias de idade. Foram utilizados dados de 1280 codornas machos e fêmeas, provenientes de sete genótipos de codornas de corte (EV1, EV2, UFV1, UFV2, UFV3, LF1, LF2) e um de postura. Todas as codornas foram pesadas a cada sete dias, do nascimento aos 35 dias de idade. Foram ajustados os modelos Brody, Gompertz, Logístico, Richards e von Bertalanffy aos dados de peso corporal de todos os genótipos. As análises estatísticas foram realizadas utilizando-se o PROC NLIN do SAS (Statistical Analysis System, versão 9.0). Os critérios empregados para a escolha do melhor modelo para descrever a curva de crescimento foram o coeficiente de determinação ajustado (R2), o desvio padrão assintótico (DPA), o desvio médio absoluto dos resíduos (DMA), o índice assintótico (IA), o critério de informação bayesiano (BIC), o critério de Akaike (AIC) e o quadrado médio do erro (QME). Todos os modelos não lineares testados convergiram, com exceção do modelo Brody, que não convergiu para nenhum genótipo avaliado. O modelo Richards não convergiu para o genótipo postura. Os parâmetros da curva de crescimento estimados pelos modelos indicaram maior precocidade, em geral, do genótipo postura comparado aos demais genótipos. O modelo Richards apresentou superestimação do ponto de inflexão para todos os genótipos, exceto para o genótipo postura. Os modelos Gompertz, Logístico e von Bertalanffy são recomendados para descrever o crescimento de codornas de corte dos grupos genéticos em estudo. O modelo Brody não convergiu, por isso não é recomendado para descrever o crescimento dos grupos genéticos de codornas em estudo. ABSTRACTThis work aimed to adjust nonlinear models to describe the growth pattern of meat type and posture quail genotypes from hatch to 35 days of age. A total of 1280 male and female quails from EV1, EV2, UFV1, UFV2, UFV3, LF1 and LF2 and Posture genotypes were weighed every seven days, from hatch to 35 days of age. Brody, Gompertz, Logistic, von Bertalanffy and Richards models were used to fit the growth of the genetic groups. Statistical analyses were performed using PROC NLIN of SAS (Statistical Analysis System, version 9.0). The criteria used to select the model showing the best goodness of fit to the growth of the genotypes were: Adjusted Coefficient of Determination (R2), Asymptotic Standard Deviation (DPA), Absolut Mean Deviation (DMA), Asymptotic Index (AI), Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC) and Errors Mean Square (MSE). All nonlinear models converged for the studied genotypes, except Richard the model for the Posture genotype. In general, the estimated parameters for the growth curve using nonlinear models suggested higher precocity for the Posture genotype in comparison to meat type genotypes. The Richard model overestimates the inflection point for all genotypes, except for the Posture genotype. The Gompertz, Logistic and von Bertalanffy are recommended to describe the growth patterns of the studied quail genetic groups. The Brody model did not converge and is not recommended to describe the genetic growth of the studied groups.

RESUMOObjetivou-se avaliar a sensibilidade dos valores genéticos para características de qualidade da carne em codornas de corte alimentadas com dietas contendo diferentes relações de (metionina + cistina): lisina, do nascimento aos 21 dias de idade, por meio de modelos de normas de reação. Utilizaram-se 9011 informações de qualidade de carne referentes a 1400 progênies de 80 reprodutores e 160 matrizes de duas linhas (LF1 e LF2). Para o ajuste dos modelos de regressão aleatória, foi usado o programa WOMBAT, considerando-se nas análises homogeneidade de variância residual. As codornas foram alimentadas do nascimento aos 21 dias de idade com dietas contendo as relações 0,61; 0,66; 0,71; 0,76 e 0,81 de (metionina + cistina): lisina, mantendo os níveis de proteína bruta de 26,12% e de energia em 2900 kcal EM/kg da dieta. Dos 22 aos 35 dias de idade, todas as codornas foram alimentadas com dieta contendo 22% de proteína bruta e 3050 kcal EM/kg da dieta. As estimativas da variância genética e da herdabilidade foram influenciadas pelo gradiente ambiental e pela linha, com mudanças nessas estimativas com o aumento do gradiente ambiental. Os valores genéticos das características de qualidade de carne referentes a cada uma das linhas se alteraram com o aumento das relações de aminoácidos das dietas em razão das mudanças no ordenamento dos valores genéticos, evidenciando a existência da interação genótipo x nível de relação dos aminoácidos da dieta para características de qualidade de carne. Predições de valores genéticos de características de qualidade de carne com base em determinada relação de (metionina + cistina): lisina da dieta não são válidas para outras relações desses aminoácidos. ABSTRACTThis study aimed to evaluate the sensitivity of breeding values for meat quality traits of European quails fed different (methionine + cystine): lysine ratio diets from hatch to 21 days of age, using reaction norm models. A total of 9011 meat quality records from 1400 progenies of 80 sires and 160 dams from two lines (LF1 and LF2) were used in the analyses considering homogeneity of residual variance. The quails from hatch to 21 days of age were fed diets containing 0.61, 0.66, 0.71, 0.76 and 0.81 (methionine + cystine): lysine ratios, 26.12% of crude protein and 2900 ME/kcal of diet. From 22 to 35 days of age all quail were fed a diet containing 22% of crude protein and 3050 kcal ME/kg of diet. The random regression model analyses was performed using the WOMBAT program considering homogeneity of residual variance. Genetic variance and heritability estimates were affected by the environment gradient of diet and line, increasing these estimates with the increase of the (methionine + cystine): lysine ratio of the diet. The breeding values changed with the increase of the environment gradient of the diet with changes in the rank of genetic breeding values characterizing the existence of genotype by environment interaction for meat quality traits. Predictions of meat quality trait breeding values based on a given (methionine + cystine): lysine ratio are not valid for other levels of the amino acid ratio.

Made available in DSpace on 2019-10-06T15:31:53Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 The aim of the present study was to estimate heritabilities and evaluate the existence of genotype-environment interactions for growth curve parameters in quail fed diets containing different threonine: Lysine ratios. A total of 4,441 body weight information from two genetic quail groups (LF1 and LF2) fed diets containing 0.66%, 0.71%, 0.76%, 0.81%, and 0.86% threonine:lysine ratios from hatching to 21 d of age were evaluated. From 22 to 35 d of age, quail received a single diet. The Gompertz model was used to estimate growth curve parameters. Genetic analyses were performed using random regression models, by Legendre polynomials of the second kind, considering homogeneity of residual variances. The following characteristics were evaluated: Asymptotic weight, asymptotic growth rate, and inflection point. Increases in threonine:lysine ratios promoted higher heritability estimates for these variables in the LF1 genetic group compared to LF2, which indicates that the additive genetic variation was modified due to the environmental variation influenced by the evaluated amino acid ratios, with differences between both genetic groups. Thus, it is recommended that quail be selected in the 0.86% ratio in genetic group LF1 and 0.66% in genetic group LF2, where greater heritabilities were observed. Dispersion of individual breeding values along the environmental gradient was observed for all evaluated characteristics, in both genetic groups, suggesting the existence of genotype-environment interactions for these variables. The evaluated amino acid ratios should be considered in quail breeding programs, since breeding value predictions for a determined threonine:lysine ratio are not valid for other ratios.;2018 Poultry Science Association Inc. Department of Animal Science Federal University of Jequitinhonha and Mucuri Valleys Department of Animal Science Federal University of Sao Jõao Del-Rei UFSJ School of Agricultural and Veterinary Sciences Sao Paulo State University (UNESP) Department of Animal Science Federal University of Mato Grosso School of Agricultural and Veterinary Sciences Sao Paulo State University (UNESP)

The main definition for meat quality should include factors that affect consumer appreciation of the product. Physical laboratory analyses are necessary to identify factors that affect meat quality and specific equipment is used for this purpose, which is expensive and destructive, and the analyses are usually time consuming. An alternative method to performing several beef analyses is near-infrared reflectance spectroscopy (NIRS), which permits to reduce costs and to obtain faster, simpler, and nondestructive measurements. The objective of this study was to evaluate the feasibility of NIRS to predict shear force [Warner-Bratzler shear force (WBSF)], marbling, and color (*a = redness; b* = yellowness; and L* = lightness) in meat samples of uncastrated male Nelore cattle, that were approximately 2-yr-old. Samples of longissimus thoracis (n = 644) were collected and spectra were obtained prior to meat quality analysis. Multivariate calibration was performed by partial least squares regression. Several preprocessing techniques were evaluated alone and in combination: raw data, reduction of spectral range, multiplicative scatter correction, and 1st derivative. Accuracies of the calibration models were evaluated using the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), coefficient of determination in the calibration (R(2)C), and prediction (R(2)P) groups. Among the different preprocessing techniques, the reduction of spectral range provided the best prediction accuracy for all traits. The NIRS showed a better performance to predict WBSF (RMSEP = 1.42 kg, R(2)P = 0.40) and b* color (RMSEP = 1.21, R(2)P = 0.44), while its ability to accurately predict L* (RMSEP = 1.98, R(2)P = 0.16) and a* (RMSEP = 1.42, R(2)P = 0.17) was limited. NIRS was unsuitable to predict subjective meat quality traits such as marbling in Nelore cattle.

The objective was to estimate genetic correlations between body weight (BW), scrotal circumference and visual evaluation scores of body conformation measured at standard ages in Guzerat cattle. All measurements were performed at 205 (weaning age), 365, 450 and 550 days of age; for BW, two additional measurements (at birth and 120 days of age) were realized. The data utilized in this study were retrieved from a database of the Brazilian Association of Zebu Breeders that contained information of registered Guzerat animals born between 1970 and 2013. Genetic parameters were estimated in bi-trait analyses by using Bayesian inference. Genetic correlations between BW at 205 and 450 days of age with other traits were high and positive, whereas the correlations between visual evaluation scores with other traits were moderate. Based on correlations herein obtained, we conclude that selection based on BW results in increased visual scores and scrotal circumference, leading to improvements in productive performance and animals with best body conformation.

Made available in DSpace on 2018-11-26T15:44:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-09-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Background: Leptin has a strong relation to important traits in animal production, such as carcass composition, feed intake, and reproduction. It is mainly produced by adipose cells and acts predominantly in the hypothalamus. In this study, circulating leptin and its gene expression in muscle were evaluated in two groups of young Nellore bulls with divergent feed efficiency. Individual dry matter intake (DMI) and average daily gain (ADG) of 98 Nellore bulls were evaluated in feedlot for 70 d to determinate the residual feed intake (RFI) and select 20 animals for the high feed efficient (LRFI) and 20 for the low feed efficient (HRFI) groups. Blood samples were collected on d 56 and at slaughter (80 d) to determine circulating plasma leptin. Samples of Longissimus dorsi were taken at slaughter for leptin gene expression levels. Results: DMI and RFI were different between groups and LRFI animals showed less back fat and rump fat thickness, as well as less pelvic and kidney fat weight. Circulating leptin increased over time in all animals. Plasma leptin was greater in LRFI on 56 d and at slaughter (P = 0.0049). Gene expression of leptin were greater in LRFI animals (P = 0. 0022) in accordance with the plasma levels. The animals of the LRFI group were leaner, ate less, and had more circulating leptin and its gene expression. Conclusion: These findings demonstrated that leptin plays its physiological role in young Nellore bulls, probably controlling food intake because feed efficient animals have more leptin and lower residual feed intake. Univ Fed Vales Jequitinhonha & Mucuri, Dept Zootecnia, BR-39100000 Diamantina, MG, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil Univ Sao Paulo, Dept Vet Med, Fac Zootecnia Engn Alimentos, Ave Duque Caxias Norte 225, BR-13635900 Pirassununga, SP, Brazil Univ Fed Fluminense, Fac Vet, Dept Zootecnia & Desenvolvimento Agrossocioambien, BR-24230340 Niteroi, RJ, Brazil Univ Sao Paulo, Dept Zootecnia, Fac Zootecnia & Engn Alimentos, BR-13635900 Pirassununga, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP, Brazil FAPESP: FAPESP 2010/05650-5 FAPESP: 2014/02493-7 FAPESP: 2014/07566-2

Several human health problems have been related to the allergenic constitution of bovine milk due to the body’s immune reaction to milk proteins. It is necessary find solutions to minimize the occurrence of such reactions, given the importance of milk as a source of animal protein. The aim of this study was to evaluate the allelic frequency of the CSN2 gene and to evaluate differences in the characteristics of Gir and Guzera bovine milk. One hundred and fifty-six cows were used (68 Gir and 88 Guzera) from the Felipe Camarao Experimental Station herd of the Agricultural Research Corporation of RN (EMPARN). DNA extractions were carried out from hair follicles of the animals; the gene was then amplified and sequenced in an ABI 3100 automatic sequencer. The obtained sequences were submitted to analysis using the Geneious 5.6.5® program. Data were submitted to analysis of variance and to the Tukey-Kramer test at 5% probability and cluster analyses by main components were performed. Allele frequencies were 98 and 97% for the A2 allele and 0.96 and 0.93% for the genotype A2A2 for Gir and Guzera, respectively. Gir and Guzera animals showed differences in protein, lactose, and non-fat dry extract levels. Although correlations between milk yield and the production and some milk components are moderate, increases in milk yield are always greater than the increase in constituent yield. In addition, even though Guzera animals have a higher percentage of protein, lactose, and non-fat dry extract, milk from Zebu breeds is an alternative for individuals sensitive to β-casein protein.

RESUMO Com o objetivo de estimar as melhores relações metionina + cistina: lisina digestíveis para codornas de corte machos durante os períodos de 22 a 28 e 29 a 35 dias de idade foram desenvolvidos dois experimentos. As aves foram submetidas a uma ração basal deficiente em metionina + cistina digestível, sendo esta suplementada com cinco níveis de DL-Metionina, em substituição ao ácido glutâmico e amido, resultando nas seguintes relações metionina + cistina: lisina digestíveis: 0,68; 0,73; 0,78; 0,83 e 0,88. Foram utilizadas 280 codornas distribuídas em delineamento inteiramente casualizado, com cinco tratamentos, oito repetições de sete aves por parcela. Avaliou-se o consumo de ração, ganho de peso, conversão alimentar, rendimento de carcaça, empenamento das aves, composição química da carcaça e balanço de nitrogênio. Durante o período de 22 a 28 dias de idade não houve efeito para as variáveis estudadas frente às relações + cistina: lisina digestíveis. Para o período de 29 a 35 dias de idade observou-se efeito para o consumo de ração, consumo de metionina + cistina e o ganho de peso. Aos 35 dias de idade observou-se efeito para o rendimento de coxa e sobrecoxa, extrato etéreo e proteína bruta da carcaça e para a retenção de nitrogênio. Recomendam-se as relações + metionina + cistina : lisina digestíveis de 0,68 e 0,88 durante os períodos de 22 a 28 e 29 a 35 dias de idade, respectivamente. SUMMARY In order of estimating the best relations methionine plus cystine: digestible lysine for quails males during the periods 22 to 28 and 29 to 35 days of age were developed two experiments. The quails received a basal diet deficient in methionine plus cystine, which were supplemented with five levels of DL-Methionine, replacing glutamic acid and starch, resulting in the following relations: 0.68, 0.73, 0.78, 0.83 and 0.88. A total of 280 quails distributed in a completely randomized design, with five treatments and eight replicates of seven quails per experimental unit. Feed intake, body weight gain, feed conversion, carcass yield and feathering of quails, composition of the carcass and nitrogen balance were evaluate. During the period from 22 to 28 days of age there was no effect for the variables studied front to relations methionine plus cystine : digestible lysine. During the period 29 to 35 days of age was observed effect on feed intake, methionine + cystine intake and weight gain. At 35 days old was observed effect on the yield of thigh and drumstick, ether extract and crude protein carcass and nitrogen retention. Are recommended that the relations methionine plus cystine : digestible lysine 0.68 and 0.88 over the period 22 to 28 and 29 to 35 days of age, respectively.

Objetivou-se avaliar tecnicas de avaliacao morfometrica por analise de imagem em equinos Quarto de Milha, a fim de estimar sua viabilidade na rotina da equinocultura brasileira. Foram avaliados 18 animais adultos de ambos os sexos da raca Quarto de Milha. Foram utilizadas tres tecnicas diferentes: avaliacao morfometrica tradicional, avaliacao morfometrica por analise de imagens atraves de software (ImageJ®) sem adesivos reflexivos e avaliacao morfometrica por analise de imagens atraves de software (ImageJ®) com adesivos reflexivos. As medidas corporais foram obtidas foram altura de cernelha (AC), altura de garupa (AG), comprimento corporal (CC), comprimento do pescoco ate a cernelha (CPC), comprimento do pescoco ate a escapula (CPE), comprimento dorso-lombar (CL), comprimento de garupa (CG), comprimento toracico (CT), comprimento de escapula (ESC), comprimento de umero (UME), comprimento de radio/ulna (R/U), comprimento de metacarpo (ME). Para comparacao das metodologias foi utilizado o teste de Dunnet a 5% de probabilidade GLM, a correlacao entre as metodologias foi avaliada pelo procedimento CORR (Statistical Analysis System, versao 9.3), bem como sua acuracia e precisao e analises por variaveis canonicas e de agrupamento pelos metodos de otimizacao de Tocher. Medidas morfometricas relacionadas com a altura do animal nao diferiram (P>0,05) entre as metodologias avaliadas. Os dados referentes a acuracia e precisao da avaliacao morfometrica por imagens apresentaram um elevado grau de proximidade com o observado pela tecnica tradicional. O software ImageJ® pode ser utilizado como tecnica alternativas de avaliacao morfometrica de equinos da raca Quarto de Milha.

Our objective was to estimate genetic parameters, and genetic and phenotypic trends for bodyweight (BW; measured at birth, 120, 205 (weaning age), 365, 450 and 550 days of age), scrotal circumference, and visual appraisal scores of body conformation in Guzerat cattle. Data regarding body structure, finishing precocity, muscling, sheath and navel, breed characteristics, limbs (soundness of feet and legs), and sexuality, which were visually appraised, were obtained from the Brazilian Association of Zebu Breeders, recorded between 1970 and 2013 in five Brazilian states. Variance components and heritability were estimated by using linear animal (for continuous variables) and threshold (for categorical variables) models using Bayesian inference. Genetic and phenotypic trends were obtained by regressing the average annual genetic value relative to animal’s birth year. The direct heritability values for BW were high, ranging from 0.38 to 0.45, whereas the maternal effect was responsible for 17–23% of the phenotypic variation. For scrotal circumference, the direct heritability values were median with values ranging from 0.08 and 0.15, whereas for visual appraisal scores, the values were median to high (0.07–0.18). Higher response to selection for BW traits is expected for those with moderate to high heritabilities. The estimated genetic trends indicated favourable changes for BW with average annual changes of 396, 2948, 3388, 5808, 8184, and 8096 g for BW at the respective ages. The genetic values were decreasing over the years for scrotal circumference, body structure, finishing precocity, muscling, and sheath and navel. Therefore, a longer evaluation period should be utilised to assess these traits as little time has elapsed from the beginning of the selection until the time of the present study.

The objective was to estimate the genetic parameters for the cow’s ability to stay in the herd (stayability) until 48 and 54 months of age (STAY48 and STAY54) and up to 36 and 48 months after the first calving (STAY36ac and STAY48ac), and their associations with 305-day milk production (MP305) in the first lactation, age at first calving and first calving interval, from the first three lactations of cows reared in Brazil and born between 1987 and 2006. The covariance components were estimated by bivariate analyses, using the Bayesian approach. The a posteriori distributions of the components of interest were obtained with the Gibbs sampler. Fixed effect of contemporary group, additive and residual random genetic effect, and age of dam as covariate (linear and quadratic) were included in the analyses. Low heritability values were obtained for most traits, except for STAY48ac and MP305. Genetic correlation estimates between age at first calving and stayability traits were high and positive, except for STAY48ac. In addition, we detected genetic correlations between MP305 and STAY36ac and STAY48ac. In conclusion, we can infer that genetic correlations between MP305, and STAY36ac and STAY48ac indicate that the current focus on selection of animals for improved milk production in the first lactation can lead to genetic gains on longevity, although not expressive.

Our objective was to evaluate the effect of genotype by environment (G×E) interaction for body weight (BW) of meat-type quails ( Coturnix coturnix ) during the growing period using two strains (LF1 and LF2) to changes in the dietary (methionine+cystine):lysine ([Met+Cys]:Lys) ratio. A total of 4512 records, collected during the initial phase (day 14 and 21), and final phase (day 28 and 35), was used for analyses. During the initial phase, quails were fed diets with increasing (Met+Cys):Lys ratios (0.61, 0.66, 0.71, 0.76, and 0.81), containing 26.1% crude protein (CP) and 2900 kcal ME/kg; and during the final phase, quails were fed a single diet containing 22% CP and 3050 kcal ME/kg. A single-trait animal model, including sex as the fixed effect, (Met+Cys):Lys ratio as the control variable, and breeding value as the random effect, was utilized for analyses. The Legendre polynomial of second order was utilized for the analysis of the G×E (nutritional levels) interaction using reaction norm. Genetic variance and heritability estimates varied according to the nutritional gradient. The LF2 strain had greater sensitivity to changes in the dietary (Met+Cys):Lys ratio compared with LF1, and greater residual effect of diets provided during the initial phase of the growing period. Genetic evaluations for quails fed different dietary (Met+Cys):Lys ratio provided changes in the predicted BW breeding values. We conclude that selection population must be fed with same dietary (Met+Cys):Lys ratio that commercial populations are fed.